Cell Journal, 18 February, 2011 Volume 144, Issue 4 pp. 455-626

Volume 144 Number 4 February 18, 2011

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Leading Edge Cell Volume 144 Number 4, February 18, 2011 IN THIS ISSUE CELL CULTURE 459

Academy Awards

BOOK REVIEW 463

The Grand Finale

E.H. Baehrecke

PREVIEWS 465

Targeting Aneuploidy for Cancer Therapy

E. Manchado and M. Malumbres

467

IL-7 Knocks the Socs Off Chronic Viral Infection

I.A. Parish and S.M. Kaech

469

Microbial Communication Superhighways

J.W. Schertzer and M. Whiteley

PERSPECTIVE 471

Epigenetic Centromere Propagation and the Nature of CENP-A Nucleosomes

B.E. Black and D.W. Cleveland

REVIEW 480

Revisiting the Central Dogma One Molecule at a Time

C. Bustamante, W. Cheng, and Y.X. Meija

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Chromatin Remodeling: CHD

Jennifer K. Sims and Paul A. Wade

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Articles Cell Volume 144 Number 4, February 18, 2011 499

Identification of Aneuploidy-Selective Antiproliferation Compounds

Y.-C. Tang, B.R. Williams, J.J. Siegel, and A. Amon

513

Role for Dpy-30 in ES Cell-Fate Specification by Regulation of H3K4 Methylation within Bivalent Domains

H. Jiang, A. Shukla, X. Wang, W.-y. Chen, B.E. Bernstein, and R.G. Roeder

526

ATP Binds to Proteasomal ATPases in Pairs with Distinct Functional Effects, Implying an Ordered Reaction Cycle

D.M. Smith, H. Fraga, C. Reis, G. Kafri, and A.L. Goldberg

539

Phosphorylation of Nup98 by Multiple Kinases Is Crucial for NPC Disassembly during Mitotic Entry

E. Laurell, K. Beck, K. Krupina, G. Theerthagiri, B. Bodenmiller, P. Horvath, R. Aebersold, W. Antonin, and U. Kutay

551

Stable Kinesin and Dynein Assemblies Drive the Axonal Transport of Mammalian Prion Protein Vesicles

S.E. Encalada, L. Szpankowski, C.-h. Xia, and L.S.B. Goldstein

566

DNA Damage in Oocytes Induces a Switch of the Quality Control Factor TAp63a from Dimer to Tetramer

G.B. Deutsch, E.M. Zielonka, D. Coutandin, T.A. Weber, B. Scha€fer, J. Hannewald, L.M. Luh, F.G. Durst, M. Ibrahim, J. Hoffmann, F.H. Niesen, A. Sentu€rk, H. Kunkel, B. Brutschy, E. Schleiff, S. Knapp, A. Acker-Palmer, € M. Grez, F. McKeon, and V. Dotsch

577

The Basement Membrane of Hair Follicle Stem Cells Is a Muscle Cell Niche

H. Fujiwara, M. Ferreira, G. Donati, D.K. Marciano, J.M. Linton, Y. Sato, A. Hartner, K. Sekiguchi, L.F. Reichardt, and F.M. Watt

590

Intercellular Nanotubes Mediate Bacterial Communication

G.P. Dubey and S. Ben-Yehuda

(continued)

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IL-7 Engages Multiple Mechanisms to Overcome Chronic Viral Infection and Limit Organ Pathology

M. Pellegrini, T. Calzascia, J.G. Toe, S.P. Preston, A.E. Lin, A.R. Elford, A. Shahinian, P.A. Lang, K.S. Lang, M. Morre, B. Assouline, K. Lahl, T. Sparwasser, T.F. Tedder, J.-h. Paik, R.A. DePinho, S. Basta, P.S. Ohashi, and T.W. Mak

614

The Coding of Temperature in the Drosophila Brain

M. Gallio, T.A. Ofstad, L.J. Macpherson, J.W. Wang, and C.S. Zuker

ANNOUNCEMENTS POSITIONS AVAILABLE

On the cover: Bacteria communicate by sending and receiving signals in the form of small molecules and can share genetic information during conjugation. In this issue, Dubey and Ben-Yehuda (pp. 590–600) show that bacteria interface directly with their neighbors through nanotubes. The tubes allow passage of proteins and plasmids and may represent a significant avenue for sharing of molecules and genetic information between individual bacteria of the same and different species. The cover shows B. subtilis cells grown on solid LB medium and visualized by high-resolution scanning electron microscopy (HR-SEM). Nanotubes connecting bacterial cells are visible. Artificial colors were added.

Announcing an innovative new textbook from Academic Cell Primer to The Immune Response, Academic Cell Update Edition By Tak W. Mak and Mary Saunders

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Leading Edge

In This Issue The Pushmi-Pullyu of Prion Transport PAGE 551

The prion protein PrPC is involved in the initiation of neurodegenerative diseases such as scrapie. PrPC is transported within neuronal axons, but it is not clear how it moves. Encalada et al. find that PrPC transport vesicles associate simultaneously with kinesin-1 and dynein, motors with opposite directionalities. They show that, in vivo, both motors remain attached to vesicles regardless of transport activity or direction. Thus, modulation of kinesin-1 and dynein activity, rather than regulation of their association with vesicles, determines PrPC transport.

A One-Two Punch for Aneuploid Cells PAGE 499

Aneuploidy is a hallmark of cancer that may be exploited therapeutically. Tang et al. have now identified compounds that kill aneuploid cells, but not euploid cells. The energy stress-inducing agent AICAR and the protein folding inhibitor 17-AAG both selectively antagonize proliferation of aneuploid mouse cells and aneuploid human cancer cells and are particularly effective in combination. The results suggest a strategy for targeting a broad spectrum of cancers.

Marking the Path to Differentiation PAGE 513

Many key developmental genes in embryonic stem cells (ESCs) are bivalently marked by histone H3K4 and H3K27 methylation. The functional role of H3K4 methylation has been unclear. Jiang et al. report that mammalian Dpy-30, a core subunit of MLL methyltransferase complexes, is required for efficient H3K4 methylation throughout the ESC genome. ESCs lacking Dpy-30 can self-renew but show differentiation defects, particularly along the neural lineage. The results establish a role for Dpy-30 and H3K4 methylation in ESC differentiation.

QC for Oocytes PAGE 566

The genetic quality of female oocytes is under tight control by p63, a cousin of the tumor suppressor p53. Deutsch et al. reveal that a network of domain-domain interactions keeps p63 in an inactive and dimeric state. DNA damage triggers an irreversible switch of p63 from its inactive state to its active tetrameric form. This conformational transition leads to the elimination of damaged germ cells, offering insight into how females ensure genetic stability of their finite number of oocytes.

ATP Delivers Marching Orders to the Proteasome PAGE 526

Protein degradation by the 26S proteasome and its homologs relies on ATP binding and hydrolysis. Smith et al. find that, for PAN, a hexameric proteasomal ATPase, the number and position of bound ATPs governs the complex’s activity. ATP binding to one protomer reduces binding to the adjacent protomer, consistent with a model in which the PAN subunits use ordered ATP binding and hydrolysis to power proteolysis. These findings may help to explain the interactions between the hexameric ATPase and the core proteasome particle. Cell 144, February 18, 2011 ª2011 Elsevier Inc. 455

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The Stem Cell Niche Is Givin’ Me Goosebumps PAGE 577

When arrector pili muscles (APMs) in the skin contract, they raise hair follicles, causing goosebumps. Fujiwara and colleagues now reveal that stem cells in the hair follicle create a special niche in the underlying basement membrane that promotes the maturation of APMs and their attachment to hair follicles. Hair follicle stem cells deposit nephronectin, an extracellular matrix component, onto the basement membrane. Nephronectin binds to an integrin expressed by muscle precursors and induces their differentiation. The findings suggest that basement membrane specialization is a mechanism for developmental patterning.

A Breakdown of NPC Breakdown PAGE 539

At the beginning of mitosis, cells in higher eukaryotes dismantle their nuclear envelope (NE), which requires disassembly of nuclear pore complexes (NPCs). Laurell et al. demonstrate that timely NPC disassembly depends on hyperphosphorylation of the peripheral nucleoporin Nup98 by multiple kinases. Nuclei carrying a phosphorylation-deficient mutant of Nup98 disassemble slowly such that both permeabilization of the NE and NPC disassembly are delayed, implicating phosphorylation as an early rate-limiting step.

Instant Messaging for Bacteria PAGE 590

Bacteria communicate via extracellular signals and transfer of plasmids during conjugation. Dubey and Ben-Yehuda describe a potentially more direct avenue for information sharing. They identify intercellular nanotubes connecting neighboring bacteria. The tubes allow sharing of cytoplasmic components, and this type of molecular exchange is ubiquitous, occurring within and between species. Nanotube-mediated cytoplasmic sharing may therefore represent a key form of bacterial communication in natural multicellular communities.

What’s Hot and What’s Not in the Fly Brain PAGE 614

Animals sense temperature changes by using thermal receptor proteins, but how thermal information is encoded in the brain and how it affects behavior is less clear. Gallio et al. examine thermosensation in fruit flies and show that a group of cells in the antenna functions as the fly temperature sensor. They further demonstrate that the fly brain segregates hot and cold signals, creating a spatial temperature map in the brain. The authors’ results suggest that hot and cold stimuli may function independently to regulate the fly’s response to temperature.

Supercharged Cytokines Combat Chronic Infection PAGE 601

Augmenting host immunity is a potential avenue for clearing chronic viral infections that are refractory to antiretroviral therapies. Pellegrini et al. report that therapeutic administration of the immunostimulatory cytokine IL-7 promotes clearance of a chronic viral infection in mice without adverse side effects. These effects are mediated through downregulation of the cytokine signaling repressor, Socs3, which results in amplified cytokine production and increased T cell effector function. Translating these insights to human chronic infections holds promise for eradicating pathogens that abrogate host immune responses.

Cell 144, February 18, 2011 ª2011 Elsevier Inc. 457

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Leading Edge

Cell Culture: Academy Awards On February 27, 2011, Hollywood’s royalty will gather in Kodak Theater to honor the best films of 2010. To add a scientific twist on this year’s Academy Awards, Cell Culture dives beneath the skin of the top films’ protagonists, identifying a brain structure that impacts our ‘‘friend count,’’ genes that make a king stammer, a cellular fragmentation process that saves a solo hiker, and stem cells required for a ballerina to grow feathers. May I have the viral envelope, please?

You Don’t Get to 500 Million Friends with a Small Amygdala The Golden Globe winner for Best Picture, ‘‘The Social Network’’ loosely chronicles Mark Zuckerberg’s ascent from Harvard sophomore to Facebook CEO and a self-worth of >$6 billion. But the idea of a ‘‘social network’’ is not new; for more than a century, psychologists have analyzed people’s relationships in terms of network maps, with friends as nodes and relationships as edges. More recently, however, neuroscientists have started pinpointing brain structures and circuits that manage these networks. Now Bickart et al. (2011) find that the total volume of the amygdala—an almond-sized group of neurons adjacent to the hippocampus—positively correlates with both the size and complexity of an individual’s ‘‘social network.’’ Big amygdalas (red) correlate First, Bickart et al. ask 58 volunteers, from ages 19 to 78, to count the total number of people they with big social lives. Image contact biweekly (i.e., their network size). They then quantify network diversity by categorizing adapted from Anatomograthese relationships into 12 types, such as children, workmates, and schoolmates. Next Bickart phy, website maintained by Life Science Databases et al. use magnetic resonance imaging (MRI) to measure the volume of each brain region below (LSDB), under a Creative the cortex (e.g., brainstem, thalamus, caudate). Remarkably, only the volume of the amygdala Commons Attribution-Share significantly correlates with the social network variables (p 0.4). Alike 2.1 Japan. The amygdala helps people respond to emotional and social cues, such as the identification of fear on someone’s face or the trustworthiness of a new acquaintance. Moreover, the amygdala’s reaction appears to be rapid and automatic, and it probably occurs before thoughts reach consciousness. So why might a bigger amygdala be better? Bickart and colleagues speculate that a larger amygdala may equate to a ‘‘better-connected’’ amygdala. With more processing power, the amygdala would better equip a person to seek and thrive in larger, more complex social situations. For example, Kennedy et al. (2009) found that the amygdala is critical for measuring ‘‘personal space.’’ Such skills are obviously important for thriving at in-person social events, but whether the amygdala is critical for ‘‘virtual’’ social skills awaits future experimentation. Bickart, K.C., et al. (2010). Nat. Neurosci. 14, 163–164. Kennedy, D.P., et al. (2009). Nat. Neurosci. 12, 1226–1227.

The King’s Lysosome Like Zuckerberg, the protagonist of ‘‘The King’s Speech’’ also struggles with social graces, but for Prince Albert the problem is due, in large part, to a severe case of stuttering. The cause of stuttering is clearly complex and multifaceted. However, twin studies indicate that this common speech disorder is highly inheritable, with 60% of cases appearing within families. Now Kang et al. (2010) have tracked down the first genetic factors associated with stuttering and, in the process, uncovered a surprising link between Tagging hydrolases ensures smooth trafficking to speech fluency and protein trafficking to the lysosome. lysosomes and smooth speech. In a previous study, the authors genotyped 46 families and used classical mapping analysis to identify a 10 Mb interval on chromosome 12 as the likely location of a causative gene. Now Kang and colleagues sequenced 45 genes in this region and found that a mutation in GNPTAB, which encodes the GlcNAc-phosphotransferase, is most strongly linked to stuttering. Sequencing GNPTAB in additional families uncovered 3 more mutations, none of which appeared in controls. Lysosomes are packed with hydrolase enzymes that degrade lipids, proteins, and nucleic acids. These enzymes are tagged in the endoplasmic reticulum with mannose-6-phosphate, a ‘‘zip code’’ that ensures their proper sorting in the Golgi apparatus and trafficking to the lysosome. The GlcNAc-phosphotransferase catalyzes the first step of this pathway, and disrupting its activity causes a severe developmental disorder, called mucolipidosis type II. The second step of the pathway is catalyzed by the NAGPA enzyme, and indeed, sequencing the NAGPA gene revealed 3 more mutations in 6 patients that stutter but not in the >700 controls. Although the 7 mutations identified by Kang and colleagues were observed in only 5% of patients, the strong connection between speech fluency and lysomome function launches a new direction for speech disorder research and provides the first molecular hook for deciphering the mechanism of stuttering. Kang, C., et al. (2010). N. Engl. J. Med. 362, 677–685. Cell 144, February 18, 2011 ª2011 Elsevier Inc. 459

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‘‘127 Hours’’ to Shed off Proplatelets When Aron Ralston found himself trapped under an 800 lb boulder, it took him ‘‘127 Hours’’ to muster the courage to escape deadly dehydration by amputating his right arm. But as soon as he slices through the soft tissue, another race for survival begins: Ralston is bleeding to death, and he still must hike >7 miles to help. Luckily, while dangling in the canyon for 5 days, Ralston’s megakaryocytes were undeterred by his condition and continued to pump out new platelets in a unique process, called ‘‘thrombopoiesis.’’ The details of thrombopoiesis had been debated for decades until Junt et al. (2007) captured this process with live-imaging microscopy. These remarkable videos demonstrate that megakaryocytes extend finger-like projections into blood vessels, which are then sheared off by hydrodynamic James Franco reenacts Aron Ralston’s 5 days in forces of blood flow to generate new platelets. Blue John Canyon in the biographical adventure First, Junt et al. used microsurgery to expose bone marrow from a mouse film ‘‘127 Hours.’’ TM and ª Twentieth Century Fox expressing a fluorescent version of CD41, a receptor on both megakaryoFilm Corporation. All Rights Reserved. cytes and platelets. They then acquired three-dimensional images of megakaryocytes every 7–15 s using two-photon laser microscopy. In the reconstructed videos, the megakaryocytes were always in contact with small vessels, and they often exhibited pseudopodia-like structures (3300 mM3), called proplatelets, reaching through the endothelial tissue. The protrusions would break off from the megakaryocytes, and the resulting proplatelet masses moved in the direction of the blood flow. Collectively, the images indicated that this fragmentation event occurs approximately every 7 hr, a rate that would account for a bulk of the 1  109 platelets produced each day in a mouse. Therefore, assuming a similar mechanism occurs in humans (and a half-life of 5–9 days for human platelets), then a considerable proportion of the platelets that saved Ralston’s life probably derived from this megakaryocyte-shedding process during his ‘‘127 Hours’’ in the Utah canyon. Junt, T., et al. (2007). Science 317, 1767–1770.

The Black Swan’s Feather Follicles While Ralston hallucinates in ‘‘127 Hours’’ because of severe dehydration, the underlying cause of Nina’s hallucinations in the psychological thriller ‘‘The Black Swan’’ is unclear. Nevertheless, as the ballet star prepares for the lead role in Tchaikovsky’s Swan Lake, black feathers begin growing from her hair follicles. This is clearly impossible given that hair and feather follicles evolved independently from reptiles 225 and 175 million years ago, respectively. However, according to an elegant study by Yue et al. (2005), these skin organs share surprising similarities, including a population of multipotent stem cells sitting at the edge of the follicle that regenerate its filament during cycles of growth and molting. The hair follicle contains a pocket of stem cells along its sheath, called the ‘‘bulge cells,’’ which divide infrequently but are capable of regenerating the entire hair follicle. Anatomically, the feather follicle doesn’t have an equivalent to a ‘‘bulge.’’ Therefore, to identify the location of slowly dividing stem cells in the feather follicle, Yue et al. labeled the epithelia cells of young chickens with 5-bromodeoxyuridine (BrdU), A ring of stems cells in the ‘‘collar bulge’’ a thymidine analog that integrates into the DNA. Over time, essentially all cells in (orange) can regenerate two types of the bird’s feather follicles lost the BrdU label, except for a ring of cells on the inside feathers depending on its angle in the of the follicle, named the ‘‘collar bulge.’’ Indeed, lineage tracing demonstrated that feather follicle. Image courtesy of these slowly dividing cells are multipotent, capable of integrating into multiple regions C.-M. Chuong. of the feather filament when transplanted into host skin. Furthermore, when these cells divide, their progeny move upward in the follicle and then differentiate into the growing feather. Clearly, these collar cells in feather follicles are functional analogs to bulge stem cells in hair follicles. Interestingly, Yue et al. also found that the angle of this stem cell ring correlated with the symmetry of its feather. A horizontal collar generates downy feathers with radial symmetry, whereas a tilted collar generates flight feathers with bilateral symmetry—a clever mechanism that allows the generation of different feather structures from one growth cycle to the next. Yue, Z., et al. (2005). Nature 438, 1026–1029. Michaeleen Doucleff

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Leading Edge

Book Review The Grand Finale Means to an End: Apoptosis and Other Cell Death Mechanisms Author: Douglas R. Green Cold Spring Harbor, NY, USA: Cold Spring Harbor Laboratory Press (2011). 220 pp. $45 The formation of cells, tissues, and organisms is analogous to the construction of a building; it requires building blocks. Therefore, it is somewhat counterintuitive that the formation and maintenance of animals also requires massive demolition by cell death. Perhaps this is why the link between cell death and animal development lagged behind the appreciation of cell division’s impact by many years. A new book by Douglas R. Green, Means to an End: Apoptosis and Other Cell Death Mechanisms, highlights discoveries of the past 30 years on the mechanisms that control programmed cell death. Green states in the Preface that this book is neither a monograph, nor an historical account, nor an exhaustive description of a field. Rather, the author focuses on the mechanisms underlying mammalian apoptosis, a form of cell death. This book gracefully covers a wide variety of subjects and, in my opinion, distills our knowledge of cell death into an accessible text that is both enjoyable to read and appropriate for a broad audience. Do not misunderstand the Preface, as readers will experience much more than a description of mammalian apoptosis. Although this may have been the original motivation behind the book, Green integrates our knowledge of cell death in diverse biological contexts and periodically detours into ‘‘just so stories’’ that present the author’s entertaining thoughts about the evolution of apoptosis. The term programmed cell death is based on the observation that dying cells go through an ordered series of morphological changes. This, combined with a need for RNA and protein synthesis, suggested that cell death is controlled by a genetic program. Descriptive studies of normal and cancerous cells led to the definition of morphological forms of cell death. Apoptosis (type I cell death) requires two cells: the dying cell and the

phagocyte that digests the dead cell with the help of the phagocyte lysosome—the equivalent of the cell trash can. Autophagic (type II) cell death depends on the dying cells’ own lysosomes and a self-degradation process known as autophagy. Nonlysosomal (type III) cell death, also known as necrosis, is associated with membrane leakage and inflammation without any role for the lysosome.

The revolution in our understanding of cell death, which Martin Raff in the book’s Foreword accurately equates with the Big Bang, occurred when Robert Horvitz and colleagues performed screens to identify the genes that are required for programmed cell death in the worm Caenorhabditis elegans. These studies provided many important advances in our understanding of apoptosis, including a genetic parts list for cell death and an ordered pathway for how these parts interact and control distinct steps of these processes. Green confronts a description of the problem of how cells die by immediately

‘‘stepping into the deep end of the molecular pool of biochemical mechanisms that control cell death.’’ I had my doubts about this approach but confess that it works. A key advance that emerged directly from the pioneering studies of worms is that caspase proteases are key regulators of apoptosis in all organisms. These caspase enzymes cut cell proteins in a highly ordered manner resulting in the controlled disassembly of the cell. Work in many laboratories has led to an understanding of many of the proteins that are cut by caspases and of the biochemical mechanisms that control their activation. This subject occupies more than half the book, and this is appropriate given the importance of caspases and their regulation to cell death. The description of this complex subject is clear, comprehensive, and considers what is known about caspases in other organisms. This is an important side point, as it does not escape the author’s attention that much can be learned by studying cell death in different organisms, and during the development of these animals—the topic of an entire chapter. Although the focus of this book is on cell death in mammals, our knowledge of cell death in other organisms is integrated at appropriate points, and the author weaves a tight and entertaining story that all biologists with a basic understanding of the principles of biochemistry and molecular and cell biology will appreciate. If wood, mortar, and bricks are equivalent to the cell cytoskeleton frame, then mitochondria are the furnace that converts fuel to heat our home. In addition to being the center of cell bioenergetics, mitochondria are important regulators of cell death, and many proteins have been reported to influence mitochondria and cell death. Among them are the Bcl-2 family of proteins that alter mitochondria by poking holes in their membranes. This process, known as mitochondrial outer membrane permeabilization (MOMP), releases key activators of the death-activating caspases, including cytochrome c. MOMP is central to the intrinsic cell death pathway, but this is not the only way that cells activate caspases. Cells also have death receptors on their surface that control the extrinsic death pathway. As with MOMP, the author describes in

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considerable detail these proteins and how they contribute to cell death. The understanding of caspase activation is important for many reasons, including that this may be exploited for disease therapies, such as in cancer. No book on cell death is complete without a discussion of how dead cells are cleared. This is an important issue, as the failure to recognize and digest apoptotic cells may have a profound impact on our immune system. The author accurately describes how apoptotic cells are recognized by the phagocytes that eat them, as well as the complex communication between these two cell types that culminates in delivery of the dead cell into the phagocyte trash can for degradation and recycling. Apoptosis dominates this text, and this is appropriate for multiple reasons. Although our knowledge of the mechanisms that control apoptosis are quite sophisticated, the study of nonapoptotic forms of cell death is in its infancy. In fact, the first mechanisms for the regula-

tion of autophagic and programmed necrotic cell death have just been discovered. Although these forms of cell death must be important based on their presence in animals, we know little to nothing about their occurrence in mammals under physiological conditions. As a leader in the cell death field, Green recognizes that this is one of the up-and-coming areas of cell death research, and his inclusion of this topic is timely. Altered cell death has implications for numerous human disorders. Disease contexts for cell death are introduced throughout the text, including subjects such as autoimmune disorders. There is also a chapter dedicated to cell death and cancer, which seems appropriate given the intense research efforts at the intersection of these fields. The best example is work on the tumor suppressor p53. Although this could be the subject of an entire book, the author focuses on several important highlights that are appropriate to the broad target audience of this text.

The book ends with a vision for the future. Here the focus is on testing models of cell death and the development of ways to make cells live and die. These issues are critical to the development of disease therapies, and a reasonable way to end a book about this field. A major strength of the book, in addition to its writing style, is the breadth of coverage, which I think accurately reflects the current status of our understanding of cell death. It is worth noting that the illustrations and figures are appropriate and helpful, and the reading lists at the end of each chapter are useful additions for readers that want to learn more about specific topics. Green covers more territory than many specialized books and does this by elimination of detail. Because of this approach, the book is a must read for students, clinicians, and experts in other fields wanting to learn more about cell death. Although the content may be very familiar to experts in the field, my suspicion is that they too will enjoy and benefit from reading this entertaining book.

Eric H. Baehrecke1,* 1Department of Cancer Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA *Correspondence: eric.baehrecke@ umassmed.edu DOI 10.1016/j.cell.2011.01.036

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Leading Edge

Previews Targeting Aneuploidy for Cancer Therapy Eusebio Manchado1 and Marcos Malumbres1,* 1Cell Division and Cancer Group, Spanish National Cancer Research Centre (CNIO), E-28029 Madrid, Spain *Correspondence: [email protected] DOI 10.1016/j.cell.2011.01.037

Tumor cells frequently display an abnormal number of chromosomes, a phenomenon known as aneuploidy. Tang et al. (2011) now show that aneuploid cells are particularly sensitive to compounds that induce proteotoxic and energy stress. Could this vulnerability lead to new cancer therapies? More than a century ago, the German zoologist Theodor Boveri suggested that most chromosome combinations that deviate from the norm (aneuploidy) lead to cell death. But he also predicted that some abnormal chromosome distributions promote unrestrained proliferation and tumor formation (Holland and Cleveland, 2009). Although about 90% of all solid human tumors contain numerical chromosome aberrations (Weaver and Cleveland, 2006), the extent to which aneuploidy contributes to tumor development remains a matter of debate (Schvartzman et al., 2010; Weaver et al., 2007). This discussion has overshadowed efforts to address a related but no less important question—can aneuploidy be targeted for cancer therapy? In this issue, Tang et al. (2011) provide evidence that specific cellular stress resulting from chromosome imbalances can indeed be utilized for killing cancer cells. Earlier work in yeast or primary mouse embryonic fibroblasts (MEFs) indicates that just one extra chromosome results in important proliferative defects, as well as metabolic and energetic aberrations (Torres et al., 2007; Williams et al., 2008). These alterations are thought to result from the additional load of proteins encoded by the extra chromosomes. Based on these findings, it has been proposed that cells respond to the aneuploid state by engaging protein degradation and folding pathways to correct the protein overload caused by the chromosome imbalance. This cellular response is called proteotoxic stress, and it is accompanied by additional energetic requirements. Whether energy and pro-

teotoxic stress can be targeted as druggable, nononcogene addiction pathways represents the starting point of the investigation reported by Tang et al. By using euploid or aneuploid MEFs carrying Robertsonian fusion chromosomes, the authors investigate whether aneuploid cells are uniquely sensitive to a variety of compounds targeting different pathways. A few compounds are actually poorly tolerated by euploid cells, suggesting that extra copies of genes in aneuploid cells might be protective against a particular drug’s toxic effects. Interestingly, the autophagy inhibitor chloroquine, the heat shock protein 90 (Hsp90) inhibitor 17-AAG, and the inducer of the AMP-activated protein kinase (AMPK) AICAR displayed increased selectivity against trisomic MEFs. Two of these molecules, AICAR and 17-AAG, also display some selectivity against chromosomally unstable MEFs with specific alterations in BubR1 or Cdc20, two proteins whose precise regulation controls fidelity during chromosome segregation (Baker et al., 2005). In addition, AICAR and 17-AAG are more efficient at inhibiting the proliferation of human colorectal cancer cell lines with chromosomal instability when compared to similar tumor cells with microsatellite instability. Comparable results are also found in aneuploid lung tumor cells. Interestingly, all of these aneuploid tumor cells displayed marked sensitivity against the combination of these molecules at low doses (Tang et al., 2011). What do these inhibitors have in common, and why do they affect the proliferation of aneuploid cells? The answer is the selective triggering of apoptosis. In

primary aneuploid cells, the effect of AICAR is mediated through its target, AMPK. This kinase phosphorylates p53 on serine 15, and the subsequent stabilization of this tumor suppressor results in the induction of proapoptotic Bax. However, p53 is also activated by other compounds that do not show selectivity against aneuploid MEFs. In addition, AICAR and 17-AAG are similarly effective in p53 null human tumor cells. In search of an explanation for these results, Tang et al. analyze several markers of the cellular stress induced by aneuploidy. For instance, aneuploid cells express higher levels of two mediators of autophagy, LC3 and Bnip3, as well as increased levels of Hsp72, a chaperone involved in protein folding. Treatment with AICAR results in a further increase in the level of these markers in aneuploid cells compared to euploid cells. These results suggest that the selectivity of a given drug relies on its capacity to synergize with the basal stress levels existing in aneuploid cells. This suggestion is in agreement with the fact that the effect of AICAR, 17-AAG, or the combination of both directly correlates with the size of the additional chromosome and therefore depends on the protein overload in aneuploid cells. The results by Tang et al. support the argument that compounds that exacerbate the basal stress state exhibited by aneuploid cells could be effective against aneuploid tumors, irrespective of their origin or their p53 status. Both AICAR and 17-AAG display some toxicity against euploid cells. However, at low concentrations, they can synergize with basal proteotoxic and energy stress present in aneuploid cells, thus opening a window of opportunity for

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cells (Janssen et al., 2009). specific treatments against Whether AICAR and 17-AAG tumor cells (Figure 1). Given that the basal stress depends might synergize with microtuon the protein overload, these bule poisons or mitotic checkpoint abrogators remains to drugs are likely to be more effective in highly aneuploid be tested. It will be crucial in cells, a feature of many human future work to further explore cancers (Weaver and Clevethese or other therapeutic land, 2006). Yet, whether opportunities afforded by the energy and proteotoxic stress energy and proteotoxic stress are a general feature of aneupresent in aneuploid cells. ploid cells needs to be further REFERENCES tested in different human tumors. The recent finding Baker, D.J., Chen, J., and van that aneuploid yeast strains Deursen, J.M. (2005). Curr. Opin. Figure 1. Therapeutic Opportunities Arising from Aneuploidy proliferate better in some Cell Biol. 17, 583–589. The unbalanced protein load in aneuploid cells may result in energy and proculture conditions (Pavelka Holland, A.J., and Cleveland, D.W. teotoxic stress that increase the susceptibility of these cells to apoptotic (2009). Nat. Rev. Mol. Cell Biol. 10, et al., 2010) suggests that death. Due to this basal level of stress, these aneuploid cells are more sensitive to specific small molecule compounds that target these pathways, such as the 478–487. tumor cells could select aneustress-inducing agent AICAR or the protein folding inhibitor 17-AAG. The Janssen, A., Kops, G.J., and ploid compositions favorable sensitivity of cells to these drugs is likely to be proportional to the increased Medema, R.H. (2009). Proc. Natl. for their growth in vivo. Thus, protein load in highly aneuploid cells, a condition that is frequently present in Acad. Sci. USA 106, 19108–19113. human tumors or that may be forced with drugs that prevent fidelity during the effect of AICAR or Pavelka, N., Rancati, G., Zhu, J., chromosome segregation. The differential sensitivity of these cells to stress17-AAG, or of other small Bradford, W.D., Saraf, A., Florens, inducing compounds provides a new window of opportunity for specifically molecules targeting these L., Sanderson, B.W., Hattem, G.L., targeting cancer cells. pathways, needs to be tested and Li, R. (2010). Nature 468, 321–325. in each specific tumor type. For instance, both AICAR and 17-AAG results are confirmed, one could predict Schvartzman, J.M., Sotillo, R., and Benezra, R. were effective against aneuploid colorectal that treating cancer cells with drugs that (2010). Nat. Rev. Cancer 10, 102–115. tumor cells, whereas only a subset of lung increase aneuploidy by preventing chro- Tang, Y.-C., Williams, B.R., Siegel, J.J., and Amon, tumor cells were sensitive to AICAR (Tang mosome alignment or by abrogating the A. (2011). Cell 144, this issue, 499–512. et al., 2011), suggesting that not all aneu- mitotic checkpoint could synergize with Torres, E.M., Sokolsky, T., Tucker, C.M., Chan, ploidies are equal. A meta-analysis of drugs against the proteotoxic and energy L.Y., Boselli, M., Dunham, M.J., and Amon, A. gene expression profiles in aneuploid stress induced by aneuploidy (Figure 1). (2007). Science 317, 916–924. versus euploid tumor cells may help to The inhibition of chromosome alignment Weaver, B.A., and Cleveland, D.W. (2006). Does identify markers of the proteotoxic induced by microtubule poisons such as aneuploidy cause cancer? Curr. Opin. Cell Biol. response and perhaps predict the effect taxol may have such an effect. Also, abro- 18, 658–667. gation of the mitotic checkpoint by using Weaver, B.A., Silk, A.D., Montagna, C., Verdierof these drugs on different tumor types. In addition, the correlation between the BubR1 or Mps1 kinase inhibitors may Pinard, P., and Cleveland, D.W. (2007). Cancer efficacy of these drugs and protein over- represent an alternative mechanism. In Cell 11, 25–36. load should also be tested in vivo using fact, taxol and Mps1 downregulation Williams, B.R., Prabhu, V.R., Hunter, K.E., Glazier, cancer cells engineered to harbor different cooperate to elevate the frequency of mis- C.M., Whittaker, C.A., Housman, D.E., and Amon, chromosome compositions. If these segregation of chromosomes in tumor A. (2008). Science 322, 703–709.

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Leading Edge

Previews IL-7 Knocks the Socs Off Chronic Viral Infection Ian A. Parish1 and Susan M. Kaech1,2,* 1Department

of Immunobiology Hughes Medical Institute Yale University School of Medicine, New Haven, CT 06520, USA *Correspondence: [email protected] DOI 10.1016/j.cell.2011.01.038 2Howard

Chronic viral infections represent a major burden to human health, and modulation of the immune system is emerging as a novel approach to fighting such infections. Pellegrini et al. (2011) demonstrate that treatment with the cytokine IL-7 may reinvigorate the immune response to persistent infection by targeting immunosuppressive Socs3 proteins. Persistent infection with viruses such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV) causes debilitating illness associated with high rates of mortality and morbidity. While long-term viral persistence can often be attributed to viral evasion of the immune system, it is now evident that host-derived immunosuppressive processes also actively disrupt viral clearance. T cells represent a key effector arm of the immune system required for virus control. However, during certain chronic viral infections, some antiviral T cells fail to survive, leaving holes in the T cell repertoire, whereas others persist in a dysfunctional or ‘‘exhausted’’ state with impaired effector functions (Zajac et al., 1998). Strikingly, a host program of immunosuppression that involves immunological signaling molecules (cytokines) such as IL-10 and TGF-b, as well as inhibitory receptors like PD-1, directs such T cell dysfunction (Barber et al., 2006; Brooks et al., 2006; Ejrnaes et al., 2006; Tinoco et al., 2009). Though it may seem counterintuitive to dampen immune responsiveness to an ongoing infection, this process likely evolved to limit the tissue destruction that would result from an unregulated immune response against a widely disseminated virus. Nevertheless, transient interference with these inhibitory pathways has clear therapeutic benefits, given that it improves T cell function and lowers viral titers in animal models (Barber et al., 2006; Brooks et al., 2006; Ejrnaes et al., 2006; Tinoco et al., 2009). However,

lethal immunopathology can arise if the timing of treatment is wrong (Barber et al., 2006), demonstrating that boosting the immune response can come at a cost. Therefore, the ideal immunotherapy would act to boost the immune response while limiting any collateral damage to host tissues. In this issue, Pellegrini et al. (2011) demonstrate that administration of the cytokine IL-7 leads to viral control during chronic infection through its ability to simultaneously augment the T cell response and induce factors that limit tissue destruction. IL-7 treatment has the added benefit of boosting overall T cell numbers, a feature that could help to counter the low T cell numbers associated with HIV-induced acquired immunodeficiency syndrome (AIDS). Though IL-7 is known primarily for its role in promoting survival and homeostasis of naive and memory T cells, past work by the authors demonstrated that IL-7 also boosts effector functions within T cells. The authors speculated that IL-7 administration during chronic viral infection might similarly improve antiviral T cell function and facilitate viral clearance. To test this hypothesis, they administer IL-7 to mice infected with lymphocytic choriomeningitis virus (LCMV) clone 13, a powerful animal model of chronic viral infection that recapitulates many aspects of persistent virus infection in humans. The authors observe a dramatic effect, with accelerated virus clearance due to a large boost in both the numbers and functionality of antiviral T cells. Surprisingly, the animals survive this immune onslaught without

detectable organ damage, at least as assessed by examining liver damage. More impressively, the treatment is effective despite beginning at day 8 postinfection, when virus levels peak and antiviral T cell responses begin showing signs of exhaustion. The profound impact of IL-7 treatment on the immune response is likely multifactorial. Given the known role of IL-7 in T cell survival, the authors first examine the effect of IL-7 on overall T cell numbers and find that IL-7 drives an expansion of the entire pool of T cells, in part due to an increase in T cell production by the thymus. However, their work suggests that the increase in thymic output of T cells probably does not contribute to the elevation in virus-specific T cell numbers, but rather, this stems from other effects. Nevertheless, the effect of IL-7 was dependent on T cells, given that depletion of T cells (but not B cells) ablates the response induced by IL-7. The authors also examine changes in cytokine levels after IL-7 treatment and find a large shift in the cytokine profile, most notably an increase in the levels of IL-6 and IL-17, a decrease in immunosuppressive TGF-b, and an increase in the tissue-protective cytokine IL-22. IL-6 appears to be a key cytokine in this context, given that it is required for both the enhanced immune response and the cytoprotective effects of IL-7 treatment. Furthermore, the elevated IL-22 secretion is dependent on IL-6, and the authors subsequently find that IL-22 plays a key role in the prevention of liver destruction.

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These results thus explain Although Th17 cells have how IL-6 prevents tissue been previously associated destruction, but they don’t with better control of influexplain how IL-6 promotes enza infection (McKinstry the T cell response. et al., 2009), Th17 cells are Next, the authors investitypically linked to antifungal gate potential mechanisms and antibacterial immunity. by which IL-6 may boost the Further work will be required immune response. They first to determine the exact role show that the effects of IL-7 of these cells in antiviral do not depend on regulatory immunity. Ultimately, this T cells, a cell type known to study suggests that IL-7 suppress activated T cell treatment holds great Figure 1. Effects of IL-7 during Chronic Viral Infection function. Instead, they specpromise for controlling Pellegrini et al. (2011) demonstrate that chronic viral infection (left) promotes ulate that IL-7 may alter the chronic viral infections, such high expression of Socs3, a negative regulator of immune cytokine signaling, in responsiveness of T cells to as those caused by HIV and antiviral T cells. Socs3 impairs T cell function and promotes T cell ‘‘exhaustion,’’ leading to viral persistence. Treatment with the cytokine IL-7 (right) IL-6. They test this idea by hepatitis B and C viruses, blocks Socs3 induction in antiviral T cells, thereby promoting effector funcmeasuring the levels of which together infect and tions and viral clearance. IL-7 likely acts on CD4+ T cells to promote IL-17 suppressor of cytokine afflict more than 10% of the secretion, which in turn induces IL-6 production. IL-6 promotes survival and signaling 3 (Socs3), a protein world’s population. function of antiviral T cell by an unknown mechanism. IL-7 also promotes IL-22 secretion, which protects against tissue destruction by the elevated immune known to modulate IL-6 response. IL-7 may also act directly on the antiviral CD4 and CD8 T cells (not responsiveness. Indeed, shown). All of these factors lead to viral clearance without adverse immunothey find higher Socs3 levels pathology. In addition to its antiviral effect, IL-7 also boosts thymic production REFERENCES of naive T cells. The elevated thymic output could help to counter lower T cell in T cells derived from mice levels during chronic HIV infection. with chronic versus acute Barber, D.L., Wherry, E.J., MasoLCMV infection. Furtherpust, D., Zhu, B., Allison, J.P., more, IL-7 treatment lowers the amount (Ogura et al., 2008). Such a model Sharpe, A.H., Freeman, G.J., and Ahmed, R. of Socs3 within T cells, possibly via AKT predicts that IL-17 is required for the up- (2006). Nature 439, 682–687. and FOXO signaling. Perhaps most regulation of IL-6 upon IL-7 treatment, Brooks, D.G., Trifilo, M.J., Edelmann, K.H., Teyton, importantly, selective ablation of Socs3 an idea that needs testing. Furthermore, L., McGavern, D.B., and Oldstone, M.B. (2006). in T cells causes early virus clearance it will be important to determine whether Nat. Med. 12, 1301–1309. and recapitulates many of the effects of the Th17 cells are virus specific or derived Ejrnaes, M., Filippi, C.M., Martinic, M.M., Ling, IL-7 treatment. These data demonstrate from another source. E.M., Togher, L.M., Crotty, S., and von Herrath, Second, it is unclear how IL-6 M.G. (2006). J. Exp. Med. 203, 2461–2472. a role for Socs3 in limiting T cell responsiveness during chronic viral infection signaling and Socs3 deficiency conspire Johnston, J.A., and O’Shea, J.J. (2003). Nat. and implicate IL-7 treatment as a potential to elevate the antiviral T cell response. Immunol. 4, 507–509. therapeutic approach for interfering with Socs3 loss could cause altered IL-6 McKinstry, K.K., Strutt, T.M., Buck, A., Curtis, J.D., signaling in antiviral T cells (Johnston Dibble, J.P., Huston, G., Tighe, M., Hamada, H., this pathway (Figure 1). This study provides exciting clues as to and O’Shea, 2003), thereby boosting Sell, S., Dutton, R.W., and Swain, S.L. (2009). how the immune response is regulated their survival and function. However, it J. Immunol. 182, 7353–7363. during chronic infection and how we is unlikely that IL-7 and IL-6 signaling is Ogura, H., Murakami, M., Okuyama, Y., Tsuruoka, M., may manipulate regulatory pathways direct, given that IL-6 and IL-7 receptors Kitabayashi, C., Kanamoto, M., Nishihara, M., Iwatherapeutically. A number of questions are transcriptionally repressed in virus- kura, Y., and Hirano, T. (2008). Immunity 29, 628–636. remain, however. First, the exact mecha- specific T cells during clone 13 infection Pellegrini, M., Calzascia, T., Toe, J.G., Preston, nism by which IL-7 treatment causes (Wherry et al., 2007). The cause of S.P., Lin, A.E., Elford, A.R., Shahinian, A., Lang, IL-6 upregulation remains unclear. The elevated Socs3 expression in untreated P.A., Lang, K.L., Morre, M., et al. (2011). Cell 144, authors note an increase in both CD4+ mice during chronic infection is also of this issue, 601–613. T cells that produce IL-17 (Th17 cells) interest. The inhibitory cytokine IL-10 Tinoco, R., Alcalde, V., Yang, Y., Sauer, K., and and serum IL-17 after IL-7 treatment. is a likely candidate because IL-10 sig- Zuniga, E.I. (2009). Immunity 31, 145–157. Given that Socs3 is an inhibitor of Th17 naling induces Socs3 expression, and Wherry, E.J., Ha, S.J., Kaech, S.M., Haining, W.N., differentiation, they hypothesize that the IL-10 deficiency has effects on chronic Sarkar, S., Kalia, V., Subramaniam, S., Blattman, reduction in Socs3 levels caused by IL-7 viral infection similar to those caused J.N., Barber, D.L., and Ahmed, R. (2007). Immunity permits greater numbers of Th17 cells to by IL-7 treatment (Brooks et al., 2006; 27, 670–684. develop. An increase in Th17 cells, in Ejrnaes et al., 2006). Zajac, A.J., Blattman, J.N., Murali-Krishna, K., Finally, the study suggests that Th17 Sourdive, D.J., Suresh, M., Altman, J.D., and turn, likely induces IL-6 production, consistent with previous experiments cells may protect against virus infection. Ahmed, R. (1998). J. Exp. Med. 188, 2205–2213.

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Leading Edge

Previews Microbial Communication Superhighways Jeffrey W. Schertzer1 and Marvin Whiteley1,* 1Section of Molecular Genetics and Microbiology, Institute of Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, USA *Correspondence: [email protected] DOI 10.1016/j.cell.2011.02.001

Exchange of information is critical for bacterial social behaviors. Now Dubey and Ben-Yehuda (2011) provide evidence for bacterial ‘‘nanotube’’ conduits that allow microbes to directly exchange cytoplasmic factors. Protein and DNA transfer between distantly related species raises the prospect of a new, widely distributed mechanism of bacterial communication. Bacteria spare no expense when it comes to coordinating their social activities. They have elaborate mechanisms to exchange DNA, share proteins and small molecules, and communicate through diffusible signals. Collectively, communication among bacteria is called quorum sensing. Ever since the discovery that quorum sensing could involve sophisticated macromolecular packaging, such as lipid vesicles (Mashburn and Whiteley, 2005), researchers have been interested in identifying alternate delivery systems for quorum-sensing signals and effector molecules. In this issue of Cell, Dubey and Ben-Yehuda (2011) now propose that bacteria interact by directly sharing cytoplasmic components. In support of this proposal, they present evidence for ‘‘nanotube’’ connections between neighboring cells, including the passage of DNA and proteins through these channels. As we learn how bacteria interact with both prokaryotic and eukaryotic cells, we gain an appreciation for the myriad ways that information and effectors can move between cells. Complex machinery has evolved to facilitate such transfer, which often involves either the construction of massive multicomponent structures or remodeling of the cell surface. The classic example of bacterial intercellular interaction is ‘‘conjugation,’’ or the sharing of genetic material both within and between species. In conjugation, a ‘‘donor’’ cell extends a narrow hair-like appendage, or pilus, which attaches to a neighboring ‘‘recipient’’ cell. The pilus retracts, pulling the donor and recipient into close proximity, and then DNA is transferred between cells. However, whether this pilus acts directly as

a conduit for DNA transfer has never been clearly demonstrated. Aside from conjugal DNA transfer, bacteria have developed other complex secretion systems to move cargo between cells. Many of these systems involve trafficking of molecules through macromolecular tubes (Hayes et al., 2010). Type III secretion systems move cargo through an apparatus that is homologous to the flagellum, whereas type IV secretion systems transfer DNA and effectors through a pilin channel. In type VI secretion, the cell builds an apparatus that is homologous to the tail tube of the phage virus, and then cargo is transferred between cells. Importantly, each of these systems involves the construction of a large secretion machine composed of proteins that allows cargo delivery to neighboring cells through a tube-like structure. In addition to these molecular machines, bacteria can also exchange information using small, hormone-like signaling molecules. Originally thought to function exclusively through the diffusion of signaling molecules between cells, some quorum-sensing molecules are packaged in more sophisticated ways, including in outer membrane vesicles that bud from the surface of Gram-negative bacteria (Mashburn and Whiteley, 2005). Fittingly, these vesicles selectively traffic proteins and even DNA molecules for export out of the cell (Bomberger et al., 2009; Horstman and Kuehn, 2000; Renelli et al., 2004). More intimate methods of communication exist for eukaryotic cells. Plants share cytoplasmic material through intercellular channels called plasmodesmata,

whereas animal cells possess analogous gap junctions and recently identified tunneling nanotubes (Rustom et al., 2004). Now the study by Dubey and Ben-Yehuda proposes a similar method of communication between bacteria, involving the exchange of information or effectors through direct cytoplasmic sharing. This idea is not unprecedented, as direct cytoplasmic connections have been proposed to exist in cyanobacteria (Mullineaux et al., 2008). The authors begin by showing that Bacillus subtilis grown on solid medium can transfer green fluorescent protein (GFP) between neighboring cells in a manner dependent upon time and the distance between cells. Similarly, antibiotic-resistant microbes could confer transient, nonhereditary resistance to neighboring cells. To exclude genetic transfer as the mechanism mediating this resistance, the authors then add the small molecule calcein to their cultures. Calcein is a membrane-permeable molecule that becomes fluorescent and trapped within cells upon hydrolysis by endogenous esterases. When the authors preload a cell with calcein, indeed the fluorescent compound transfers to untreated cells. Together, these experiments suggest that cytoplasmic molecules move between cells by a contact-dependent mechanism. In support of this hypothesis, Dubey and Ben-Yehuda then identify tubular connections between cells grown on solid medium, which appear structurally distinct from conjugative pili. Images from highresolution scanning electron microscopy (HR-SEM) and the fact that nanotubes are disrupted in the presence of the detergent

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Figure 1. Intercellular Communication through Nanotubes High-resolution scanning electron microscopy has identified tube-like connections (‘‘nanotubes’’) between Bacillus subtilis cells, which appear distinct from known extracellular structures (Dubey and Ben-Yehuda 2011). The exchange of antibiotic resistance (e.g., CmR) and green fluorescent protein (GFP) between bacterial strains depends on the proximity of the donor and recipient cells. In addition, the transfer of traits remains either stable and heritable in the recipient or transient and nonheritable, depending on whether the transferred element is DNA or a protein, respectively. Transmission electron microscopy with GFP labeled with immunogold particles revealed GFP within the tubes, suggesting that molecules could transit through the structures. Interestingly, similar structures were observed with cultures of B. subtilis, Staphylococcus aureus, Escherichia coli, or binary mixtures of the species, giving rise to the proposition that bacterial nanotubes facilitate intra- and interspecies transfer of cytoplasmic components.

SDS lead the authors to conclude that the structures are composed of membranous layers. If true, this property would distinguish these nanotubes from other known secretion structures (except outer membrane vesicles). Characterizing the composition of the nanotube structures is an obvious direction for further study, particularly because SDS treatment has been shown to disrupt some proteinaceous pili (Achtman et al., 1978). Perhaps the most intriguing experiments reported by Dubey and Ben-Yehuda are those in which they visualize immunogold-labeled GFP by transmission electron microscopy. These images reveal the presence of GFP within the nanotubes, providing strong support for the conclusion that cytoplasmic molecules can be transported through the observed structures. Given the large dimensions of the nanotubes (i.e., 30–130 nm in diameter), the authors next test whether they could facilitate transfer of genes on plasmids. Indeed, plasmids conferring heritable antibiotic resistance move between cells under conditions in which nanotubes are present. However, the authors present only indirect evidence suggesting that

DNA passes directly through the tubes themselves. Finally, Dubey and Ben-Yehuda show that nanotube junctions are not restricted to interactions between the same species. GFP transfers between B. subtilis, Staphylococcus aureus, and Escherichia coli in various two-partner combinations (Figure 1). Accordingly, each transfer was coincident with the presence of nanotubes. It is exciting to speculate about the evolutionary advantages provided by such an intimate interaction, including the ability to communicate stably with a specific partner chosen by the microbe. In addition, direct cytoplasmic connections bypass any diffusion barriers or inhibitory systems that diffusible signals might encounter. However, the communication mechanisms proposed by Dubey and Ben-Yehuda also raise many questions. For example, one would like to know whether cargo is specifically selected, and whether traffic flow is bidirectional. Also, how does a microbe discriminate between friend and foe? Interestingly, another recent study suggested that the Gram-positive bacterium B. anthracis may also engage in vesicle-mediated

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transport (Rivera et al., 2010), a mode of sharing that could account for many of the observations described by Dubey and Ben-Yehuda. Nevertheless, the existence of bacterial nanotubes is an exciting new discovery that promises many new avenues of study. It will be important to characterize the properties of these nanotubes, including their distribution and relevance under different growth conditions. For example, are the nanotubes limited to growth on solid medium, and if not, how does the growth environment affect their construction and use? In addition, it is critical to determine whether the nanotubes are present in bacterial populations growing on surfaces in nature, as opposed to agar plates in the laboratory. Finally, if nanotubes are an extension of the cell surface, it will be interesting to determine how differences in cell-surface composition between two species are reconciled. Once these and many other questions are answered, we can then begin to assess the impact of the findings presented by Dubey and Ben-Yehuda, a discovery that has the potential to change the way we think about bacterial interactions and social behavior.

REFERENCES Achtman, M., Morelli, G., and Schwuchow, S. (1978). J. Bacteriol. 135, 1053–1061. Bomberger, J.M., Maceachran, D.P., Coutermarsh, B.A., Ye, S., O’Toole, G.A., and Stanton, B.A. (2009). PLoS Pathog. 5, e1000382. Dubey, G.P., and Ben-Yehuda, S. (2011). Cell 144, this issue, 590–600. Hayes, C.S., Aoki, S.K., and Low, D.A. (2010). Annu. Rev. Genet. 44, 71–90. Horstman, A.L., and Kuehn, M.J. (2000). J. Biol. Chem. 275, 12489–12496. Mashburn, L.M., and Whiteley, M. (2005). Nature 437, 422–425. Mullineaux, C.W., Mariscal, V., Nenninger, A., Khanum, H., Herrero, A., Flores, E., and Adams, D.G. (2008). EMBO J. 27, 1299–1308. Renelli, M., Matias, V., Lo, R.Y., and Beveridge, T.J. (2004). Microbiology 150, 2161–2169. Rivera, J., Cordero, R.J., Nakouzi, A.S., Frases, S., Nicola, A., and Casadevall, A. (2010). Proc. Natl. Acad. Sci. USA 107, 19002–19007. Rustom, A., Saffrich, R., Markovic, I., Walther, P., and Gerdes, H.H. (2004). Science 303, 1007–1010.

Leading Edge

Perspective Epigenetic Centromere Propagation and the Nature of CENP-A Nucleosomes Ben E. Black1,* and Don W. Cleveland2,* 1Department

of Biochemistry and Biophysics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA Institute for Cancer Research, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA *Correspondence: [email protected] (B.E.B.), [email protected] (D.W.C.) DOI 10.1016/j.cell.2011.02.002 2Ludwig

Centromeres direct chromosome inheritance, but in multicellular organisms their positions on chromosomes are primarily specified epigenetically rather than by a DNA sequence. The major candidate for the epigenetic mark is chromatin assembled with the histone H3 variant CENP-A. Recent studies offer conflicting evidence for the structure of CENP-A-containing chromatin, including the histone composition and handedness of the DNA wrapped around the histones. We present a model for the assembly and deposition of centromeric nucleosomes that couples these processes to the cell cycle. This model reconciles divergent data for CENP-A-containing nucleosomes and provides a basis for how centromere identity is stably inherited. The centromere is a specialized region on each chromosome that ensures the faithful inheritance of the chromosome during cell division. Specifically, the centromere mediates the chromosome’s attachment to the mitotic spindle, and it also serves as the location of final cohesion between the duplicated copies of a chromosome (i.e., chromatids) prior to their complete separation and movement to opposite spindle poles near the end of mitosis. Centromeric DNA usually contains a repetitive sequence with a repeating unit, typically 160–180 bp, that is slightly smaller than the average spacing between nucleosomes on chromosomal arms (i.e., 200 bp). The repeating sequences found in centromeric DNA evolve rapidly relative to the rest of the chromosome (Figure 1), and they are likely to have a role in maintaining the large heterochromatin domains typically found at centromeres. In the budding yeast Saccharomyces cerevisiae, centromeric DNA is a single domain of 125 bp (bottom, Figure 1), and its position is specified by sequence-specific recruitment of a centromere binding complex, which contains four proteins (Ndc10, Cep3, Ctf13, and Skp1) (Lechner and Carbon, 1991). In all other species studied, centromeric DNA spans thousands to millions of base pairs and contains repetitive DNA motifs that sharply diverge between species, making these repeats sequence unique for each species. Surprisingly, however, the presence of these repeats does not specify centromere location, and they are not required for the general function of centromeres. Rather, the epigenetic information that specifies centromeres tracks with the chromatin underlying the mitotic kinetochore, the protein complex that physically connects each chromosome to the microtubule-based spindle apparatus. In all eukaryotes, a key component of the chromatin that specifies centromeres is the incorporation of a variant of histone H3, named CENP-A in mammals, CID in flies, and Cse4 in budding yeast. In all likely models of centromere inheritance, CENP-A

or its homolog is what physically distinguishes centromeric chromatin from the rest of the chromosome. In addition, after DNA replication in S phase, the presence of CENP-A is also probably responsible for directing the deposition of newly expressed CENP-A and other centromere components, which in mammals include CENP-C, M, N, U, and T (Foltz et al., 2006). A consistent observation is that centromere-specifying chromatin vacates ‘‘silenced’’ centromeres that no longer function (Earnshaw and Migeon, 1985; Warburton et al., 1997). The best examples of these ‘‘silenced’’ centromeres are produced by rare chromosomal translocations in which both initial centromeres end up on one chromosome (which has been called a ‘‘pseudodicentric’’ chromosome). Invariably, one of the centromeres is silenced and loses all centromere proteins, including CENP-A. In other examples in humans, centromere silencing (or loss through germline chromosomal rearrangement) at a normal chromosomal location has been accompanied by activation of a new centromere at a different position on the same chromosome, creating what is referred to as a neocentromere. Neocentromeres form at sites without the typical repetitive DNA found at the original centromeres and without any DNA sequence changes (Lo et al., 2001). Even more remarkably, the locations of such neocentromeres are faithfully maintained through the human germline (Amor et al., 2004; Depinet et al., 1997; du Sart et al., 1997; Warburton et al., 1997). Furthermore, centromeric chromatin can spread linearly along DNA (Maggert and Karpen, 2001). It is poorly understood how epigenetic information encoded by chromatin at specific sites is retained during major chromosomal events, including DNA replication and transcription. Of these epigenetic marks, the centromere mark is the longest lived (i.e., through evolutionary timescales). Nevertheless, there is no consensus on what are the most crucial questions to address concerning the epigenetic basis of centromere identity: What is Cell 144, February 18, 2011 ª2011 Elsevier Inc. 471

Figure 1. Epigenetic Centromere Specification Rapid evolution of centromeric DNA sequence length, composition, and organization is in contrast to the ubiquitous presence of nucleosomes containing CENP-A.

the structure of centromeric chromatin? What is the likely epigenetic mark? Or, how is that mark replicated and maintained through centromere DNA duplication? Instead, a set of seemingly inconsistent models for the structure of CENP-A-containing chromatin have been proposed (Camahort et al., 2009; Furuyama and Henikoff, 2009; Lavelle et al., 2009; Mizuguchi et al., 2007; Sekulic et al., 2010; Williams et al., 2009). Reconciling the disparate data on the structure of centromeric chromatin and generating testable models—two primary goals of this essay—are critical for understanding the molecular mechanisms that drive the self-propagation of the epigenetic mark underling centromere inheritance. Here we consider the merits (and weaknesses) of each model. Building on the discovery that in metazoans, the assembly of centromeric chromatin occurs only after exit from mitosis (i.e., half a cell cycle after centromeric DNA replication) (Jansen et al., 2007; Schuh et al., 2007), we propose a model for cell-cycle-dependent maturation of centromeric nucleosomes. Propagating Centromeric Chromatin Perhaps the most central, unresolved question regarding replication of centromere identity is how CENP-A already assembled into centromeric chromatin is retained at centromeres as nucleosomes are disrupted by DNA polymerase and then reassembled onto each daughter centromere after replication. A second, related question is when during the cell cycle is CENP-A deposited at centromeres. Surprisingly, this deposition is not contemporaneous with DNA replication. Evidence in human cells (Jansen et al., 2007) and fly embryos (Schuh et al., 2007) indicates that deposition of newly synthesized CENP-A onto centromeric DNA starts late in mitosis and extends through the G1 phase of the following cycle. Temporal separation of the assembly of new CENP-A chromatin from the replication of centromeric DNA raises the likelihood that distinct forms of centromeric chromatin exist during different portions of the cell cycle. In particular, the current evidence suggests that restoration of complete loading of CENP-A occurs in G1. However, after DNA replication in S phase, despite complete reloading of previously centromere-bound CENP-A, there are twice as many centromeres, resulting in half as many CENP-A at each centromere (Jansen et al., 2007; Schuh et al., 2007). This CENP-A loading at half the maximal level persists through the G2 and mitosis phases. Such distinct forms of centro472 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

meric chromatin could include variations in the histone (or nonhistone) composition of nucleosomes or even alterations in higher-order chromatin structure. Regardless of the answers to these crucial questions, two steps must occur to separate the deposition of CENP-A at centromeres from pathways depositing bulk histones at noncentromeric chromatin: the sorting of newly synthesized CENP-A away from bulk H3 and the selective recognition of centromeric chromatin for assembling new CENP-A protein into it. Newly synthesized histones are thought to rapidly bind to their partners: H3 binds to H4 and H2A to H2B. In addition, prior to assembly, the histone complexes are bound by ‘‘chaperones’’ that prevent promiscuous association of the highly basic proteins with highly acidic nucleic acids (Ransom et al., 2010). The chaperone that sorts the (CENP-A:H4)2 heterotetramer away from bulk histone is called HJURP in humans (Dunleavy et al., 2009; Foltz et al., 2009) and Scm3 in budding (Camahort et al., 2007; Mizuguchi et al., 2007; Stoler et al., 2007) and fission (Pidoux et al., 2009; Williams et al., 2009) yeasts. This chaperone is part of the pathway that couples CENP-A deposition to the cell cycle and targets CENP-A to centromeres. Human HJURP forms a complex with newly synthesized CENP-A protein (i.e., before it integrates into a nucleosome) by recognizing the CENP-A Targeting Domain (CATD) on the CENP-A:H4 tetramer (Foltz et al., 2009). The CATD consists of 22 amino acid substitutions within the classic histone fold domain (Black et al., 2004). When it is substituted into histone H3, it not only is sufficient to confer centromere targeting capabilities to H3 (Black et al., 2004), but it also enables the hybrid H3-CATD to maintain centromere function when CENPA is reduced (Black et al., 2007b). Substantial structural differences distinguish CENP-A:H4 from its histone counterpart, H3:H4. These include several alterations in surface-exposed side chains; a bulged loop (loop L1) that generates a different shape and oppositely charged surface as found on H3; a rigid interface with H4; and a rotated CENP-A:CENP-A interface that compacts the overall size of the (CENP-A:H4)2 heterotetramers (Sekulic et al., 2010). Following incorporation into chromosomes, CENP-A must mark the chromatin as centromeric, thus distinguishing the centromere from the rest of the chromosome. One or a few nucleosomes with CENP-A substituting for the conventional H3 histone is apparently insufficient to generate a functional centromere, except in budding yeast in which a DNA sequence element is used for identifying centromeres (Figure 1). This view is built upon several observations. First, CENP-A accumulation at noncentromeric sites of DNA damage is transient (Zeitlin et al., 2009). Second, when CENP-A is massively overproduced,

Figure 2. Models for the CENP-A Nucleosome Conflicting evidence for the structure of centromeric DNA containing CENP-A has led to the proposal of six chromatin configurations, which vary in histone composition and the handedness in which the DNA wraps around the protein core.

it deposits onto chromosomal arms, but these sites only occasionally recruit one or more kinetochore components even when incorporated into expansive ectopic loci (Heun et al., 2006). Mechanisms that reinforce centromere identity probably rely on recognizing the foundational mark that CENP-A confers to nucleosomes. This could occur either by CENP-A nucleosomes recognizing other CENP-A nucleosomes in higher-order chromatin folding (Blower et al., 2002; Ribeiro et al., 2010) or direct recognition of CENP-A-containing nucleosomes by other centromere components (Carroll et al., 2009, 2010). Recent studies have uncovered additional mechanisms that prevent CENP-A from stably incorporating into chromosome arms. For example, in the budding yeast, ubiquitination by the E3 ligase Psh1, which specifically recognizes CENP-A through the CATD (Ranjitkar et al., 2010), triggers subsequent degradation of CENP-A at noncentromeric locations (Hewawasam et al., 2010; Ranjitkar et al., 2010). Competing Proposals for Centromeric Chromatin Throughout the genome, epigenetic marks encoded by nucleosomes are generally thought to exist as posttranslational modifications of conventional histones, the incorporation of histone variants, or a combination of both. A major challenge has been to define how the variant CENP-A physically alters chromatin to specify and maintain centromere location on the chromosome. In fact, several recent studies have provided evidence that support seemingly contradictory models for the structure of chromatin containing CENP-A (Figure 2): (1) The most conventional view is of an octameric nucleosome with two copies of each histone, H2A, H2B, H4, and CENP-A (in place of H3) (Camahort et al., 2009; Conde e Silva et al., 2007; Foltz et al., 2006; Palmer and Margolis, 1985; Sekulic et al., 2010; Shelby et al., 1997). As with conventional nucleosomes

in noncentromeric chromatin, the DNA wraps around the histones with a lefthand twist (Sekulic et al., 2010). (2) A tetrasome with two copies of CENP-A and H4 but lacking H2A:H2B dimers (Williams et al., 2009). (3) A hemisome, or other non-nucleosomal complex assembled onto DNA, with one copy of each histone instead of the two copies found in conventional nucleosomes (Dalal et al., 2007; Williams et al., 2009). In addition, the DNA wraps around the histones with a right-hand twist instead of the traditional left-hand twist (Furuyama and Henikoff, 2009). (4) An octameric ‘‘reversome’’ with the same stoichiometry as in a conventional nucleosome but with right-handed wrapping of DNA (Lavelle et al., 2009). (5) A hexameric complex that resembles a nucleosome but in which H2A:H2B dimers are replaced by recruitment of two molecules of Scm3 (as proposed for the centromere of budding yeast) (Mizuguchi et al., 2007). (6) A trisome of Cse4, H4, and Scm3 (again proposed in budding yeast) with right-handed wrapping of DNA (Furuyama and Henikoff, 2009). Centromeric Chromatin as an Octameric Nucleosome Several lines of evidence in diverse species support the conventional view that centromeric nucleosomes consist of the octameric configuration found elsewhere in the genome but with CENP-A replacing H3 (Figure 2A) (Camahort et al., 2009; Erhardt et al., 2008; Sekulic et al., 2010; Shelby et al., 1997). In humans, for instance, CENP-A-containing chromatin isolated from cultured cells contains stoichiometric amounts of CENP-A, H4, H2A, and H2B, including two CENP-A molecules (Foltz et al., 2006; Shelby et al., 1997). Octameric nucleosomes are also readily reconstituted from purified components (Black et al., 2007a; Yoda et al., 2000). In these nucleosomes, the DNA wraps around the histones with a conventional left-handed twist (Sekulic et al., 2010), albeit slightly less negatively than in conventional H3 nucleosomes and with loss of conventional strand crossing at the DNA entry-exit site (Conde e Silva et al., 2007). The prominent form of CENP-A-containing nucleosomes contains two copies of CENP-A (i.e., homotypic) instead of one copy each of CENP-A and H3 (i.e., heterotypic) (Foltz et al., 2006; Shelby et al., 1997). This is likely because CENP-A has a higher affinity for itself than for histone H3 (Kingston et al., 2011). In addition, the CATD domain of CENP-A imparts unique structural properties to (CENP-A:H4)2 heterotetramers and to Cell 144, February 18, 2011 ª2011 Elsevier Inc. 473

octameric CENP-A-containing nucleosomes. Specifically, these complexes with CENP-A are more compact in size and less flexible than their conventional counterparts (Black et al., 2004, 2007a; Sekulic et al., 2010). These unique structural features are attractive candidates for how CENP-A octameric nucleosomes may be readily differentiated from bulk H3-containing nucleosomes. Therefore, the simplest model is that CENP-A restructures chromatin by replacing histone H3 in nucleosomes of otherwise conventional histone stoichiometry while still maintaining the directionality of DNA wrapping. The Hemisome Model and Positive Supercoiling Findings in Drosophila cells (Dalal et al., 2007) and, more recently, in mammalian cells (Dimitriadis et al., 2010) have led to the hypothesis that a hemisome (Figure 2C) is a key component of centromeric chromatin. Using atomic force microscopy (AFM) to measure the size of chromatin, these studies found that isolated chromatin containing CENP-A is half the height of conventional chromatin (Dalal et al., 2007; Dimitriadis et al., 2010). Further, the Drosophila CID-containing structures fail to crosslink into an octameric form under conditions in which conventional H3-containing octamers crosslink (Dalal et al., 2007). Nevertheless, large centromeric components (e.g., CENP-B and CENP-C) that copurify with CENP-A chromatin at near stoichiometric levels (Dimitriadis et al., 2010; Foltz et al., 2006) are apparently not represented in the height of the CENP-A particles (Dalal et al., 2007; Dimitriadis et al., 2010). Therefore, DNA dimensions and topology probably dominate the AFM measurements, rather than protein content within each particle. In addition, the reduced crosslinking observed for CENP-A chromatin in Drosophila might be expected because CID is missing the key crosslinkable lysine residues present in H3-containing nucleosomes (Black and Bassett, 2008). The hemisome model was recently extended to budding yeast and to include right-handed wrapping of DNA as a major component of the epigenetic mark generated by CENP-A/Cse4 (Furuyama and Henikoff, 2009). The key evidence supporting this model emerged from examining how the incorporation of a functional centromeric DNA sequence into a ‘‘minichromosome’’ alters the supercoiling of the DNA. On a DNA template that typically accommodates 9 conventional nucleosomes, adding the centromeric DNA reduced the negative supercoiling by two supercoils. Although the loss of negative supercoils could result from centromeric Cse4 adding a right-handed, positive supercoil to the nucleosomal DNA, as was proposed (Furuyama and Henikoff, 2009), a simpler possibility is that the centromere and the proteins recruited to the centromere may sterically block assembly of more than one nucleosome on adjacent DNA, reducing the total number of negative supercoils present. Reconstitution experiments with Drosophila CID have provided the most direct evidence for positive DNA supercoiling of centromeric chromatin (Furuyama and Henikoff, 2009). Nevertheless, these findings may perhaps be more easily explained by unconventional interactions between histones and DNA both within and across histone particles of a single type or a mixture of tetrasomes (CENP-A:H4)2, hexasomes (CENP-A:H4)2(H2A: H2B), or octameric nucleosomes (CENP-A:H4:H2A:H2B)2 (Lavelle et al., 2009). 474 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

The High-Energy Reversome Model As an alternative explanation for the apparent positive supercoiling seen by Furuyama and Henikoff (2009), Lavelle et al. (2009) proposed the ‘‘reversome’’ model (Figure 2D) for nucleosomes at functional yeast centromeres upon incorporation of Cse4. Reversomes are high-energy states (Bancaud et al., 2007) that are not significantly populated by reconstituted nucleosomes containing either H3 (Simpson et al., 1985) or CENP-A (Sekulic et al., 2010). Therefore, this model is plausible only if the structure is stabilized by additional, but still unknown, components of the centromere, which overcome the initially highly unfavorable energetics. The Tetrasome Model Evidence for a centromeric tetrasome (Figure 2B) initially emerged from the findings that functional centromeres in fungi can be deficient in H2A and H2B (Mizuguchi et al., 2007; Williams et al., 2009). In budding yeast, H2B, H2A, and Htz1 (i.e., an H2A variant) interact only weakly with centromeric DNA sequences, at least as judged after chromatin immunoprecipitation (Mizuguchi et al., 2007). In fission yeast, H2B interacts weakly with Cnt1 and Imr1 (Figure 1) sequences (Williams et al., 2009). However, depleting cells of Scm3 and CENP-A fails to restore H2A/H2B to levels comparable to those observed at other genomic loci in either type of yeast (Mizuguchi et al., 2007; Williams et al., 2009). This result suggests the existence of an unexplained anomaly in the methods for assessing stoichiometry of bound proteins, at least for this locus. In principle, the unusual structural properties of CENP-A could stabilize tetrasomes (Figure 2B). These structural changes would be similar to the ones proposed for the octameric nucleosomes with CENP-A, and as for the octameric model, they would also distinguish CENP-A-containing tetrasomes from conventional prenucleosomal intermediates, such as [H3:H4]2 heterotetramers assembled onto DNA without H2A:H2B dimers (Sekulic et al., 2010). Trisome and Hexasome Models with HJURP/Scm3 Lastly, evidence in budding yeast has suggested that centromeric nucleosomes consist of a hexasome and/or trisome. Both models propose the existence of CENP-A (Cse4)-containing complexes on DNA with the H2A:H2B dimer replaced by Scm3. The hexomeric complex contains two copies for each molecule, CENP-A/Cse4, H4, and Scm3 (Figure 2E) (Mizuguchi et al., 2007), whereas the trisome model contains only one copy of each molecule (Figure 2F) (Furuyama and Henikoff, 2009). The main support for the hexasome model derives from experiments in which H2A:H2B dimers are replaced with Scm3 in recombinant hexameric histone complexes assembled in vitro and without DNA. In addition, H2A:H2B was markedly diminished or absent from centromeric DNA in chromatin immunoprecipitation (ChIP) experiments in yeast (Mizuguchi et al., 2007). The trisomal model (Figure 2F) was proposed based on the discovery that functional centromeres in budding yeast appear to confer less negative supercoiling to minichromosomal templates than the same DNA template without a functional centromeric DNA sequence. The trisome is the second of two possible models that explain the reduced negative supercoiling

observed for the assembly of CENP-A/Cse4 onto DNA, the alternative model being the hemisome model (Figure 2C) (Furuyama and Henikoff, 2009). It should be noted that both models involving the incorporation of Scm3 have been sharply challenged by the observation from other investigators that mononucleosomes containing Cse4 copurify with H2A, H2B, and H4. Indeed, this observation is consistent with a conventional, octameric histone composition ([Cse4:H4:H2A:H2B]2) as the major form of Cse4-containing chromatin (Camahort et al., 2009). A Model for Replication and Maintenance of Centromere Chromatin To reconcile the data supporting each of the six proposals for centromeric chromatin (Figures 2A–2F), we suggest a working model (Figure 3A) that couples the steps required to assemble nucleosomes specifying centromeric location to the cell cycle. These processes include the maturation of nucleosomes with CENP-A, broad conservation of soluble prenucleosomal complexes across eukaryotic species (which include the appropriate histone chaperones prior to CENP-A deposition on DNA), conserved nucleosome assembly intermediates on DNA, and immature and mature assembly products of CENP-A on DNA that maintain centromere identity over long durations. Although the particular details of cell-cycle timing and assembly intermediates on DNA differ among diverse eukaryotic species, centromere identity is a fundamentally important biological process, and thus, the underlying properties of centromerespecifying nucleosomes are likely to be common to diverse species. Indeed, among the many models proposed for the various intermediates and forms of centromere-specifying histone complexes that contain CENP-A orthologs, it is remarkable how the major components are conserved even in the most divergent examples. Despite only minor sequence homology, fungal Scm3 and its mammalian ortholog HJURP appear to play similar roles as chaperones for newly expressed prenucleosomal CENP-A:H4 complexes (Dunleavy et al., 2009; Foltz et al., 2009; Pidoux et al., 2009). HJURP/Scm3 is clearly present at the centromere for a substantial duration of time in both human and yeast. In human cultured cells, HJURP is present at centromeres for 2–3 hr (about 1/10th of the cell cycle time) following mitotic exit (Dunleavy et al., 2009; Foltz et al., 2009). In fission yeast, Scm3 is present at centromeres for the majority of the cell cycle (Pidoux et al., 2009; Williams et al., 2009). In budding yeast, one group reported Scm3 bound to Cse4-containing chromatin (Mizuguchi et al., 2007), but another group found conventional nucleosomes with H2A:H2B (Camahort et al., 2009). One possibility for reconciling this disparity is that Scm3 loading at budding yeast centromeres may depend on cell-cycle position, and the two groups analyzed cell populations with different distributions in the cell cycle. In our proposal, what seems most likely is that intermediate forms of CENP-A-containing histone complexes exist on centromeric DNA prior to the assembly of a final nucleosomal form (bottom right, Figure 3A). Further, prenucleosomal forms, nucleosomal forms (potentially including trisome/hexasome or tetrasome intermediates; top right, Figure 3A), and nucleosomes

(lower right, Figure 3A) are all stable structures, with the intrinsic properties of CENP-A dictating this stability. Under such a model, the inheritance of mammalian centromeres is achieved by HJURP performing two major tasks. First, it acts as a chaperone for prenucleosomal CENP-A synthesized in S and G2. Then following mitotic exit, HJURP functions as a loading factor and a transient component of the centromere during maturation of centromeric chromatin in the next G1 phase (top, Figure 3A). What remains still unresolved is whether centromeric intermediates are a hexameric complex with two copies each of HJURP/ Scm3, CENP-A, and H4, or a trimeric complex containing a single copy of each protein. The dimerization of HJURP (Shuaib et al., 2010), however, supports a hexamer similar to the structure proposed for centromeric chromatin in budding yeast (i.e., the [Scm3:CENP-A/Cse4:H4]2 hexamer) (Mizuguchi et al., 2007). In the metazoan context, HJURP is present at the centromere beginning at mitotic exit, and its presence at the centromere is coincident with the transient targeting of the Mis18 complex to centromeres (i.e., the complex required for licensing centromeric chromatin for subsequent CENP-A deposition) (Hayashi et al., 2004; Maddox et al., 2007). HJURP at the centromere is presumably bound to CENP-A, which is then assembled onto centromeric DNA in a non-nucleosomal form, which could be either the proposed hexasome (Mizuguchi et al., 2007) or trisome (Furuyama and Henikoff, 2009) (top right, Figure 3A). When HJURP vacates the centromere later in G1, a CENP-A-containing complex may transiently exist in a tetrasomal form prior to H2A:H2B dimer addition, which then completes formation of the mature octameric nucleosome. Other factors involved in depositing centromeric nucleosomes onto DNA also may function at particular points of the cell cycle. The generic chromatin remodeler, RSF, has been proposed to facilitate maturation of CENP-A nucleosomes in the G1 phase of the cell cycle (Perpelescu et al., 2009). The small GTPases Cdc42 and Rac, in combination with their GTPase-activating protein, MgcRacGAP, and guanine exchange factor, Ect2, are also each required for maturation, apparently at an even later step that is closer to the G1/S boundary (Lagana et al., 2010). The nature of how Rsf1 and these small GTPases affect the maturation of centromeric chromatin awaits further investigation. Interestingly, bulk deposition of H3:H4 by the histone chaperone Asf1 provides a precedent for an obligate, stepwise assembly pathway for nucleosomes, similar to the one that we are proposing for the maturation of CENP-A nucleosomes (Figure 3C). Binding of Asf1 to H3:H4 completely occludes H3:H3 interactions in the Asf1:H3:H4 trimer (Ransom et al., 2010). The trimeric Asf1 complex exists in solution prior to chromatin assembly. The assembly intermediates on DNA remain undefined for this deposition pathway, but the final product appears to be an octameric nucleosome. At the centromere, two copies of CENP-A are likewise predicted by our model (bottom right, Figure 3A) to exist in the ‘‘final’’ product (i.e., tetrasomes or octameric nucleosomes) of the HJURP/Scm3-mediated chromatin assembly pathway (top right, Figure 3A), even if the binding of HJURP/Scm3 initially occludes oligomerization of CENP-A:CENP-A as an intermediate step. Given the stability that the intrinsic properties of CENP-A confer to octameric nucleosomes with left-handed DNA Cell 144, February 18, 2011 ª2011 Elsevier Inc. 475

Figure 3. Coupling the Assembly of CENP-A Chromatin to the Cell Cycle (A) Cell-cycle-coupled maturation of CENP-A-containing nucleosomes in mammals. (B) Possibilities for generating a substantial pool of hemisomes. If the initial deposition of CENP-A is as a trisome that contains Scm3, the large intrinsic stability of nucleosomal CENP-A predicts that the trisome will rapidly convert to the octameric form, following the addition of H2A:H2B. Other mechanisms may exist to stabilize a hemisomal form, such as the association of an uncharacterized (or unknown) factor that specifically binds to CENP-A nucleosomes. (C) Octamer formation of canonical nucleosomes following the initial deposition by the trimeric assembly complex, Asf1:H3:H4.

wrapping (Black et al., 2007a; Sekulic et al., 2010), this conformation is likely the form that maintains centromere identity, as opposed to the right-handed wrapping in the ‘‘reversome.’’ 476 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

Reversomes are energetically disfavored for H3-containing nucleosomes. Furthermore, in assays with single nucleosomal minicircles, CENP-A-containing nucleosomes populate the

high-energy reversome to an even lesser degree than conventional nucleosomes (Conde e Silva et al., 2007). Although the application of a large, positive torsional stress could force both canonical and centromere-specifying nucleosomes to populate the reversome conformations at significant levels (Bancaud et al., 2007; Lavelle et al., 2009), preserving this conformation would require sustained centromeric stress as a means to mark centromere location. Centromeric Chromatin after DNA Replication As cells enter S phase, DNA replication must disrupt the mature CENP-A-containing nucleosomes (Figure 3A). Experiments using an in vivo fluorescence pulse-chase approach (SNAPtagging) have distinguished preexisting and newly assembled CENP-A. These experiments have clearly shown that CENP-A molecules bound at centromeres prior to DNA replication are quantitatively reassembled onto each daughter DNA strand after replication (Jansen et al., 2007), thereby replicating the CENP-A centromeric mark. One major untested question is whether CENP-A chaperones and chromatin remodelers directly associate with the replication machinery to mediate this critical step. These chaperones and remodelers are needed to accept the CENP-A-containing histone complexes as they are stripped from the DNA by the replication machinery and then to facilitate their replacement onto both daughter strands immediately after replication. The identities of these proposed chaperones are still unknown, as well as whether their association with centromeres is more than a transient encounter during S phase. CENP-A’s reloading onto the daughter strands after DNA replication may also involve more passive mechanisms in which a high local concentration of subnucleosomal histone complexes produced by passage of the replication fork contributes strongly to the redistribution of CENP-A nucleosomes behind the fork. If no new CENP-A is added during the quantitative reloading of previously bound CENP-A during, or just after, centromeric DNA replication, then there are three possibilities for the chromatin state of centromeric DNA on the two daughter strands (bottom left, Figure 3A): d

d

d

The most conventional hypothesis is that two molecules of ‘‘old’’ (or previously bound) CENP-A/H4 are used for reassembly with H4, H2A, and H2B of a centromeric nucleosome. However, twice as many DNA strands are present after replication but no new CENP-A is added. Therefore, adjacent DNA positions would either be left bare (which is an unattractive hypothesis, given that long stretches [171–200 bp] of DNA are likely to remain naked only transiently) or loaded with the replication-dependent H3.1-containing nucleosomes. A second possibility is that the remaining CENP-A is assembled into octameric nucleosomes with one molecule each of CENP-A and H3. This model could account for the small amount of H3 copurifying with CENP-A-containing nucleosomes isolated from asynchronous cells (Foltz et al., 2006). A third possibility is that after DNA replication, centromeric DNA containing CENP-A is maintained in a non-nucleosomal form. One such form would be a hemisome (Fig-

ure 2C), a model which would account for the following: the general stoichiometry of histones found in CENP-A chromatin (from human cells) (Foltz et al., 2006); the reduced height of centromeric chromatin (from Drosophila) seen by ATM (Dalal et al., 2007); and the reduced negative supercoiling seen on a multinucleosomal plasmid upon the incorporation of an active centromere (in budding yeast) (Furuyama and Henikoff, 2009). In considering the possible models, CENP-A/H4 heterotetramers are likely to be the prenucleosomal form. In support of this view, CENP-A and H4 spontaneously form soluble (CENPA:H4)2 heterotetramers upon coexpression in bacteria (Black et al., 2004). In addition, the atomic resolution structure of (CENP-A:H4)2 heterotetramers revealed conserved salt-bridges and strengthened hydrophobic interactions in the CENPA:CENP-A interface compared to the H3:H3 interface in (H3:H4)2 heterotetramers (Sekulic et al., 2010). There is currently no indication of any intrinsic property of CENP-A that would disfavor the CENP-A:CENP-A interaction and lead to the formation of structures on DNA containing only a single copy of CENPA, as proposed by the hemisome and trisome models (Figures 2C and 2F, respectively). Indeed, these two models remain the most difficult for us to reconcile completely with the available data from many independent groups. Moreover, we believe that the evidence supporting the hemisome and right-handed DNA wrapping models can be accommodated almost equally well by other models. On the other hand, an unidentified means of trapping or stabilizing hemisomes or other forms of CENP-A-containing complexes may exist (Figure 3B). Other centromere proteins, or even histone chaperones involved in redistributing CENP-A onto newly replicated centromeric DNA during S phase (chaperones that likely exist but have not yet been identified), could stabilize high-energy or non-nucleosomal centromeric chromatin prior to reassembly of bona fide nucleosomes at exit from mitosis. Conclusions The epigenetic mark that specifies centromere location on chromosomes is stably inherited over many generations and typically changes position only over evolutionary timescales (Amor et al., 2004; Murphy et al., 2005). The assembly of centromeric chromatin with CENP-A is the best candidate for this epigenetic mark. CENP-A is an extremely long-lived protein in cells, and there is no (or almost no) turnover of it at centromeres throughout most of the cell cycle (Hemmerich et al., 2008; Jansen et al., 2007; Shelby et al., 2000). Such stability disfavors models in which short-lived high-energy states would play an important role in marking centromere location. Centromere identity is maintained in cells that exit the cell cycle for long periods of time (e.g., decades, in the case of mammalian oocytes). Amid divergent evidence for the structure of centromeric chromatin, a critical future challenge is to define the stable chromatin complexes formed by CENP-A on centromeric DNA across the various stages of the cell cycle. These complexes represent the strongest candidates for the epigenetic mark that maintains centromere inheritance and underlies the mechanisms that Cell 144, February 18, 2011 ª2011 Elsevier Inc. 477

stabilize chromosomes in yeast to humans. An important future step will be to test the hypothesis of cell-cycle-coupled maturation of CENP-A-containing nucleosomes. ACKNOWLEDGMENTS The authors thank members of their laboratories for many discussions of centromere inheritance and anonymous reviewers for helpful comments. This work was supported by grants from the National Institutes of Health to B.E.B. (GM82989) and D.W.C. (GM74150). B.E.B. is also supported by a Career Award in the Biomedical Sciences from the Burroughs Wellcome Fund and a Rita Allen Foundation Scholar Award. D.W.C. receives salary support from the Ludwig Institute for Cancer Research. REFERENCES

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Leading Edge

Review Revisiting the Central Dogma One Molecule at a Time Carlos Bustamante,1,2,3,4,5,* Wei Cheng,6,8 and Yara X. Meija7,8 1Jason

L. Choy Laboratory of Single-Molecule Biophysics Institute 3Physics Department 4Howard Hughes Medical Institute University of California, Berkeley, CA 94720, USA 5Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA 6Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109, USA 7Biological Micro and Nanotechnology, Max Planck Institute for Biophysical Chemistry, Am Faßberg 11, D-37077 Go ¨ ttingen, Germany 8These authors contributed equally to this work *Correspondence: [email protected] DOI 10.1016/j.cell.2011.01.033 2QB3

The faithful relay and timely expression of genetic information depend on specialized molecular machines, many of which function as nucleic acid translocases. The emergence over the last decade of single-molecule fluorescence detection and manipulation techniques with nm and A˚ resolution and their application to the study of nucleic acid translocases are painting an increasingly sharp picture of the inner workings of these machines, the dynamics and coordination of their moving parts, their thermodynamic efficiency, and the nature of their transient intermediates. Here we present an overview of the main results arrived at by the application of single-molecule methods to the study of the main machines of the central dogma. Introduction ‘‘The operative industry of Nature is so prolific that machines will be eventually found not only unknown to us but also unimaginable by our mind.’’ So wrote in De Viscerum Structura Marcello Malpighi (Malpighi, 1666), the founder of microscopic anatomy. Malpighi (1628–1694), a Professor at the University of Bologna, was the leader of the revolution that swept through the biological sciences in the 17th century and that mirrored the parallel revolution that was occurring in physics. Coincidentally, during the latter, Galileo and Newton refined the concepts of inertia, force, and acceleration that establish the foundations of kinematics and dynamics and that became the language to describe the operation of machines. Coincidentally again, in both revolutions, the invention of instruments that made it possible to observe and measure what was not directly visible to the human eye, the microscope and the telescope, became the catalyst that unleashed, in both sciences, the modern scientific imagination. Since the era of Malpighi, the mechanical paradigm has been a recurrent idea in biology. In recent decades, the molecular biology revolution has revealed that much of the inner workings of the cell are the result of specialized units or assembly lines that function as molecular machines (Alberts, 1998). Many of these entities operate as molecular motors, converting chemical energy into mechanical work, and their description must be done in the language of mechanics: ‘‘moving parts,’’ forces, torques, displacements, thermodynamic efficiencies, and time. And once again, the recent advent of single-molecule methods, which permit to follow in real-time the individual molecular trajec480 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

tories without having to synchronize a population of molecules, and specifically the development of single-molecule manipulation, whose direct observables are precisely displacements, forces, and torques, is making it possible to formulate an accurate description of molecular machines and to uncover the physical principles and diverse biological designs that underlie their operation. Most of these machines are enzymes that couple a thermodynamically spontaneous chemical reaction (typically nucleotide hydrolysis) to a mechanical task. Because of their microscopic dimensions, the many small parts that make up these machine-like devices operate at energies only marginally higher than that of the thermal bath and, hence, their operation is subjected to large fluctuations. The fluctuations revealed by single-molecule analyses are not just a nuance or an artifact of studying them in singulo. In fact, many of them are present and need only be present in very small numbers to carry their physiological role in the cell, a role, therefore, subjected to large fluctuations. Behaving as true thermodynamic open systems, these devices can exchange energy and matter with the bath and take advantage of fluctuations to operate, sometimes, as energy rectifiers. Like ‘‘honest’’ Maxwell Demons that sit astride the line that separates stochastic from deterministic phenomena, the function of these molecular machines is to tame the randomness of molecular events and generate directional processes in the cell. How does this taming take place? How does this noise affect the coordinated operation required to maintain cellular homeostasis? How should we modify our concepts from macroscopic

chemistry and biochemistry to obtain a more faithful description of these stochastic devices? These and other questions are becoming the common thread that ties the ever-increasing number of single-molecule studies of cellular machines, some of which are the subjects of this Review. Here we will restrict our review to single-molecule studies of the machinery involved in the metabolism and transactions of nucleic acids, primary protagonists of the central dogma of molecular biology, the operating system of the cell. Processes such as replication, transcription, and translation require the information encoded in the sequence of nucleic acids to be read and copied in a directional manner. Therefore, these machines are all, necessarily, translocases. We have accordingly organized this article following the cell’s operational logic. First we will review single-molecule studies of machines involved in the packaging and storage of the genome. This section will be followed by a review of helicases, followed in turn by a review of single-molecule studies of genome replication and DNA transcription, and will end with translation studies. Translocases in Chromosomal Partitioning and Segregation Newly replicated DNA molecules must be properly partitioned and segregated into daughter cells, spores, or viral capsids. In many cases, these processes utilize an active mechanism that involves an ATP-dependent translocase. Generally the viral packaging and prokaryotic segregation ATPases belong to the P loop NTPase fold and appear to have an ancient common origin (Catalano, 2005; Iyer et al., 2004b; Koonin et al., 1993). Members of the P loop NTPase fold possess a conserved nucleotide-binding and Mg2+-binding motif (Walker A) and a wateractivating motif (Walker B) and belong to one of two major divisions: the KG division, which includes P loop kinases and GTPases, and the ASCE (additional strand conserved E [glutamate]) division. Due to space limitations, we will only review here the main single-molecule results obtained on viral packaging systems. Viral Packaging Systems The machinery involved in the packaging of viral DNA has two components, the portal-connector and the ATPase (Catalano, 2005; C.L. Hetherington, J.R. Moffitt, P.J. Jardine, and C.B., unpublished data; Jardine and Anderson, 2006). The phylogenetic origin of these components and their spatial and functional relationships define four different types of viral genome packaging systems: (1) terminase-portal systems, (2) the packaging systems of lipid inner membrane-containing viruses, (3) the 429-like packaging system, and (4) the adenovirus packaging apparatus (Burroughs et al., 2007). (See Supplemental Information). Viral DNA packaging has been divided into initiation, elongation, and termination. So far, single-molecule studies have been restricted to bacteriophages T4, lambda, and 429. The DNA packaging motor of bacteriophage 429, the best studied so far, is made up of three concentric rings (Grimes et al., 2002) (Figure 1A): (1) the head–tail connector, a dodecamer that fits in the pentameric opening at one of the ends of the

Figure 1. f29 Packaging Motor (A) Cryo-electron microscopy of the packaging motor. Left: Packaging motor with capsid and DNA modeled in for scale. Right: Close-up on packaging motor. Modified from Morais et al. (2008). (B) Optical tweezers packaging assay. Left: An optical trap exerts a force, F, on a single packaging bacteriophage while monitoring the length, L, of the unpackaged DNA. Right: DNA length versus time. Different colors correspond to different concentrations of [ATP]. (C) High-resolution packaging reveals a burst-dwell packaging mechanism. Left: Cartoon layout of high-resolution packaging assay. Right: Schematic diagram of the kinetic events that occur during the dwell and burst phases overlaid on packaging data.

capsid; (2) a ring of five molecules of RNA, each 174 nucleotides (nt) long of unknown function; and (3) a pentameric ring (Morais et al., 2008) of gp16, an ATPase that belongs to the FtsK/HerA family of the ASCE superfamily of P loop NTPases. Packaging Initiation Initiation of viral DNA packaging requires recognition of the viral genome by the packaging machinery. This process is done either through binding of a specific DNA sequence (reviewed in Catalano, 2005; Jardine and Anderson, 2006) or through a terminal protein bound to the ends of the viral DNA. Only the latter form of initiation has been studied by single-molecule methods. In bacteriophage 429, a terminal protein, gp3, is bound to both 50 ends of the viral genome, and at least one of them is required for robust packaging in vitro. In EM studies, the terminal protein is seen to induce a loop or lariat on the Cell 144, February 18, 2011 ª2011 Elsevier Inc. 481

Box 1. Basics of Optical Tweezers Optical tweezers are a means of exerting forces on objects and to measure those forces. Optical tweezers can be built by focusing a laser beam through a positive lens to form a ‘‘trap.’’ The interaction of small dielectric objects with a focused Gaussian beam generates a force in the direction of the field gradient that draws it toward the center of the beam and traps it there. A restoring force arises whenever the object is displaced away from the center of the beam (left inset). When the size of the object is greater than the wavelength of the light (a cell, a plastic bead), this restoring or trapping force can be seen to arise from the exchange of linear momentum of the light with the object in its path and can be understood from geometric ray tracing optics (left inset). Photons carry momentum; when the object is removed from the center of the beam it deflects the beam producing a rate of change of momentum in the light, i.e., a force. Because of the conservation of momentum, the object must experience also a rate of change of momentum, or a force of equal but opposite magnitude that tends to restore the object back to the center of the beam. This restoring force can be measured directly by projecting the beam onto a position-sensitive photo-detector and measuring both its intensity and its deflection. It is typically in the range of 1 to 200 piconewton (pN) depending on the intensity of the beam, a force range sufficient to break the majority of noncovalent interactions involved in most macromolecular interactions and sufficient to stall most molecular motors. For example, the stall force of myosin is between 3–5 pN (Finer et al., 1994), whereas that of kinesin is 7 pN under saturating [ATP] (Visscher et al., 1999). Because this restoring force is proportional to the stiffness of the trap and to the displacement Dx of the object from the center of the trap, the force can also be determined from this displacement using Hooke’s law: F = kDx (right inset). Forces can be applied to molecules by attaching them to the surface of a micron-size optically trapped polystyrene bead through complementary biochemistry.

DNA that appears to be supercoiled by the packaging machinery (Grimes and Anderson, 1997b) and that is thought to be necessary for initiation (Grimes and Anderson, 1997a; Koti et al., 2008; Turnquist et al., 1992). Optical tweezers experiments (Box 1) in which DNA packaging is initiated in situ suggest that DNA recognition by the packaging machinery leads to the formation of some kind of loop structure that can be packaged (Rickgauer et al., 2006). Packaging initiation of DNA without the terminally bound gp3 has been observed in optical tweezers experiments, albeit with low efficiency and without 482 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

affecting translocation (Rickgauer et al., 2006), suggesting that the protein role is circumscribed to assist the search phase of initiation. Packaging Elongation Viral DNA packaging involves translocation of DNA by the multimeric ring ATPases through the portal-connector structure into the capsid. Single-molecule studies of viral DNA packaging have used an experimental design as shown in Figure 1B. Here a tether is formed between a packaging viral capsid bound to the surface of a bead and the distal end of the DNA bound to another bead and usually held in an optical trap (Chemla et al., 2005; Fuller et al., 2007a, 2007b; Smith et al., 2001). These types of studies revealed that the 429 motor is capable of producing forces as high as 60 piconewton (pN), corresponding to an internal pressure of DNA inside the capsid at the end of packaging of 6 MPa or 60 atm (Smith et al., 2001). Similar forces have been reported for T4 (Fuller et al., 2007a) and for lambda (Fuller et al., 2007b). It is likely, however, that the motor is capable of generating higher forces and that those measured are operational stall forces at which the motor is forced to enter an off-pathway inactive state through structural deformation or unfolding, for example. In a molecular motor, force is itself a product of the reaction. Moreover, the step in which the conversion from chemical to mechanical energy occurs is the one where movement is generated and must be sensitive to external force. External force can thus be used as an inhibitor of the reaction: by varying its magnitude as a function of ATP concentration, above and below its Michaelis-Menten constant (KM), we can determine in what step of the hydrolysis cycle the mechanochemical conversion occurs (Keller and Bustamante, 2000). In 429 the power stroke of the ATPases coincides with the release of the inorganic phosphate from ATP hydrolysis (Chemla et al., 2005). The rate of viral DNA packaging varies among different systems. For 429 under saturating ATP concentrations, it has a narrow distribution around 120 bp/s (Chemla et al., 2005), whereas it is highly variable for T4 reaching values as high as 2000 bp/s, with an average of 700 bp/s. Interestingly, this variation is observed among viral particles (static dispersion) and at different times for the same particle (dynamic dispersion) (Fuller et al., 2007a). The latter observations suggest that the motor can interconvert between alternative different functional states within the duration of the single-molecule assay (Fuller et al., 2007a). Resolving the Individual Steps of a Packaging Motor For 429, it was found that the activities of the ATPases around the ring are strictly coordinated into an overall motor’s cycle, as addition of small amounts of nonhydrolyzable ATP analogs pauses the motor for variable periods that, presumably, correspond to the times required by the ATPases to exchange their nonhydrolyzable substrate for ATP. The pause density (number of pauses per unit length of DNA packaged) increases linearly with the concentration of analog, indicating that a single bound analog is sufficient to stop the motor (Chemla et al., 2005). The first direct characterization of the intersubunit coordination and the step size of a ring ATPase were reported recently for 429. Using ultra-high-resolution optical tweezers (Moffitt et al.,

2006), it was found that this motor packages the DNA in increments of 10 bp separated by stochastically varying dwell times (Moffitt et al., 2009). Statistical analysis of the dwell times revealed that multiple ATPs bind during each dwell; application of high force showed that these 10 bp increments are composed of four 2.5 bp steps. Further analysis demonstrated that the hydrolysis cycles of the individual subunits are highly coordinated: the ATP binding to all subunits occurs during the ‘‘dwell’’ phase that is completely segregated from and followed by the translocation or ‘‘burst’’ phase (Figure 1C). Interestingly, the strong coordination among the ATPase activities in the ring is not consistent with the Hill coefficient of 1 measured experimentally. It turns out that if the binding of the individual ATPs to the various subunits is separated by an irreversible step, the Hill analysis will yield n = 1 despite the strong coordination and cooperativity among these subunits (Moffitt et al., 2009). The Nature of the DNA-Motor Interaction Little is known about the interactions responsible for the large forces displayed by these motors and the noninteger base pair steps observed for 429. The role played by the phosphate backbone charge in the motor-DNA interaction was investigated recently in single-molecule packaging experiments by challenging the motor with DNA constructs bearing inserted regions of neutral DNA segments containing methylphosphonate (MeP) modifications (Aathavan et al., 2009). Remarkably, the motor actively traverses these inserts, though with reduced probability compared to regular DNA, indicating that phosphate charges are important but not essential for translocation. By changing the length of the MeP inserts and selectively restoring the charge to one or the other DNA strand, it was found that important contacts are made with phosphate charges every 10 bp on the 50 /30 strand only. High-resolution measurements of the dynamics through the insert reveal that, in addition to providing a load-bearing contact, these phosphate contacts also play a role regulating the timing of the mechanochemical cycle (Aathavan et al., 2009). A step size that is a noninteger number of base pairs requires motor-DNA interactions that do not depend on any given periodic structure in the DNA molecule, and that are of steric nature. Thus, the motor was challenged with a series of additional inserts: DNA lacking bases and sugars, single-stranded gaps, unpaired bulges, and a nonbiological linker (Aathavan et al., 2009). Surprisingly, none of the modifications abolish packaging, indicating that the motor makes promiscuous, steric contacts with a wide variety of chemical moieties over a range of geometries, helping to rationalize the observed 2.5 A˚ steps. These results suggest that the 2.5 bp step is determined by the magnitude of the conformational change that the individual ATPases undergo during their power stroke. The Structural Basis of Force Generation Several sequence motifs define the members of the ASCE family of P loop NTPases (Erzberger and Berger, 2006; Iyer et al., 2004a; Thomsen and Berger, 2008), including the Walker A and Walker B motifs—known to coordinate binding of the nucleotides and to catalyze hydrolysis (Dhar and Feiss, 2005) —and the arginine finger. In addition, the Q-motif and the C-motif are present in some of the packaging ATPases (Mitchell et al.,

2002; Rao and Feiss, 2008). These conserved sequence elements are likely to be involved in the mechanochemical energy transduction of viral packaging machines and are, therefore, prime targets for combined mutational and single-molecule studies. Tsay et al. (2009) used optical tweezers to investigate the effect of mutations in the large terminase subunit of bacteriophage l on the dynamics of packaging. One of the mutations, K84A, near the Walker A motif reduced packaging velocity by 40% but did not affect the processivity of the motor nor its force sensitivity (i.e., the distance to the transition state) (see Supplemental Information). The other mutant, Y46F, was found to reduce the rate of the motor by 40% but to decrease also its processivity 10-fold. This same mutant greatly weakened the motor mechanically (Tsay et al., 2009). These findings indicate that viral motors contain an adenine-binding motif that regulates ATP hydrolysis and substrate affinity analogous to the Q-motif recently identified in DEAD-box RNA helicases. Furthermore, the Q-motif appears to be involved in coupling the conformational changes in the ATP-binding pocket to substrate translocation (Worrall et al., 2008). In a separate study, Tsay et al. (2010) found that mutation T194M downstream of the Walker B motif slows the motor 8-fold without modifying its processivity or force generation. In contrast, mutation G212S in the C-motif causes a 3-fold reduction in velocity but also a 6-fold reduction in processivity. Future studies using A˚-resolution optical tweezers should help establish which phase of the dynamic cycle of the motor, relative to nucleotide binding and hydrolysis, is directly affected by these modifications. Helicases: Keys to the Sequence Vault Helicases constitute a large class of motor proteins that play indispensible roles in almost every aspect of nucleic acid metabolism (Matson et al., 1994; Rocak and Linder, 2004). Most organisms encode multiple helicases, and genes encoding proteins with helicase/translocase activities comprise close to 2% of the eukaryotic genome (Shiratori et al., 1999). Conventionally, helicases are defined as enzymes that utilize ATP to break the complementary hydrogen bonds in double-stranded nucleic acids (dsNA), a process essential for DNA or RNA replication (Lohman and Bjornson, 1996). Biochemical functions of helicases go beyond the mere catalytic opening of doublestranded DNA (dsDNA) or RNA (dsRNA), however. Many helicases not only perform canonical functions but also catalyze disassembly of protein-nucleic acid complexes (PNAC), an important activity required in many essential cellular processes (Jankowsky and Bowers, 2006; Krejci et al., 2003). In addition, some helicase proteins may not function to unwind dsNA but rather serve other biological functions inside the cell, like chromatin remodeling (Saha et al., 2006). This multifunctional facet begs important questions about helicases: How do helicases use ATP to catalyze the opening of dsDNA or the disassembly of PNAC? How are these activities integrated in a given molecule? How is ATP hydrolysis coordinated with the mechanical tasks of the enzyme? Research over the last 10 years, often using single-molecule techniques, has yielded a tremendous amount of information at a mechanistic level on how these proteins catalyze the opening of dsNA and the disassembly of PNAC. These advances will be reviewed here. Cell 144, February 18, 2011 ª2011 Elsevier Inc. 483

Figure 2. Single-Molecule Studies of Helicases and Mechanistic Insights (A) Single-molecule hairpin assay for NS3 helicase: cartoon representation of the experimental setup using optical tweezers to study translocation and unwinding of double-stranded RNA by individual NS3 helicase. (B) Representative real-time unwinding trajectory of NS3 helicase on the hairpin substrate collected at 1 mM ATP; the burst of NS3 activity is noted by arrows and has an average size of 11 ± 3 bp. (C) Possible mode of binding in NS3 helicase. The binding of 30 single strand is observed in cocrystal structures between NS3 and single-stranded nucleic acids. However, the binding of 50 single strand has not been observed in any crystal structures but is suggested from single-molecule studies. (D) Hexameric helicase, for example, T7 gp4 DNA helicase, extrudes one strand of the DNA through the center hole of the helicase while displacing the other strand.

Common Structural Features of Helicase Proteins Although helicases are functionally diverse, their protein sequences and three-dimensional (3D) structures have several common features (Supplemental Information). All helicases appear to have common structural building blocks (Bird et al., 1998; Story et al., 1992; Waksman et al., 2000). However, despite this similarity, two classes of helicases have been long recognized, based on their oligomeric structures. One class forms characteristic rings, typically hexameric, and helicase activity appears to require formation of the hexamer (Patel and Picha, 2000). The second class comprises a large number of helicases, mainly grouped in the SF1 and SF2 superfamilies (Gorbalenya and Koonin, 1993), that do not form hexameric structures, although many of them still undergo oligomerization reactions (Lohman and Bjornson, 1996) (Supplemental Information). Helicase-Catalyzed dsNA Unwinding How do these motor proteins couple ATP binding and hydrolysis to the mechanical function of strand separation in dsNA? Extensive biochemical and biophysical studies have been carried out on several model helicases in order to answer this question (Lohman et al., 2008; Mackintosh and Raney, 2006; Myong and Ha, 2010; Patel and Picha, 2000; Pyle, 2008). One of the best characterized nonhexameric helicases is the NS3 protein from hepatitis C virus (HCV) (Kolykhalov et al., 2000), a representative member of Superfamily 2 (Gorbalenya and Koonin, 1993), possessing structural resemblance to other helicase proteins despite an overall low sequence identity beyond the helicase motifs (Korolev et al., 1998) (Figure S1). Although its exact biological function is still not clear (Lindenbach and Rice, 2005; Moradpour et al., 2007), this helicase is essential for viral RNA replication and virion assembly (Lam and Frick, 2006; Ma et al., 2008), and as such, it is a potentially important drug target (Frick, 2003; Raney et al., 2010). It displays both DNA (Pang et al., 2002) and RNA helicase activities in vitro. Although dimerization enhances its RNA helicase processivity in vitro (Serebrov and Pyle, 2004), the NS3 protein monomer possesses helicase activity by itself (Cheng et al., 2007; Jennings et al., 2009; Serebrov et al., 2009). 484 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

Single-molecule experiments have been particularly useful for revealing molecular mechanisms underlying the operation of helicases (Bianco et al., 2001; Bustamante et al., 2000; Dohoney and Gelles, 2001; Ha et al., 2002). In particular, optical tweezers have been used to follow for the first time the individual trajectories of single NS3 molecules powered by ATP (Dumont et al., 2006). Shown in Figure 2A is a schematic representation of the experimental set up used to monitor the unwinding activity of individual molecules of NS3 on dsRNA (Cheng et al., 2007; Dumont et al., 2006). A single RNA hairpin molecule was attached between a microsphere in an optical trap and a microsphere placed atop a micropipette via hybrid RNA-DNA ‘‘molecular handles’’ to separate the hairpin from the surfaces. The RNA substrate contains a 30 single-stranded RNA (ssRNA) ‘‘launching pad’’ 10 nt long that facilitates loading and initiation of NS3 helicase activity (see Supplemental Information for polarity of helicase unwinding). NS3 and ATP are next added together into the chamber, while the tethered RNA substrate is held at a constant tension at a preset value, below the mechanical unfolding force of the hairpin. As NS3 unwinds the hairpin, the molecule lengthens, requiring the beads to be separated to maintain the force constant. The end-to-end distance of the molecule can be converted to the number of RNA bp unwound by using the worm-like chain model of ssRNA elasticity (Bustamante et al., 1994) (Box 2), yielding traces with 2 bp spatial resolution and 20 ms time resolution. Several lines of evidence suggest that the functional form of NS3, observed in this single-molecule experiment, is a monomer (Dumont et al., 2006). Typical unwinding trajectories consist of cycles of bursts of base pair-opening activity followed by pauses (Figure 2B). The average size of these bursts is 11 ± 3 bp, or about the pitch of dsRNA. The length of the pauses between these 11 bp steps, like the velocity within the 11 bp steps, is [ATP] dependent. These 11 bp steps further decompose into smaller ‘‘substeps’’ at low [ATP], with an average substep size of 3.6 ± 1.3 bp at 50 mM ATP. Dwell time analysis further implies that one ATP is bound during the pause, and one ATP is bound before every substep. However, the 3.6 bp may not represent the minimal

Box 2. Worm-like Chain Model of Polymer Elasticity

Box 3. Basics of Magnetic Tweezers

Although the rates of nucleic acid translocases are expressed in base pairs per second (bp/s) or nucleotides per second, in many singlemolecule manipulation experiments of translocases, the quantity measured is change in time of the end-to-end distance of the nucleic acid at some force. It is thus necessary to convert this distance into molecular contour length, and this, in turn, into numbers of base pairs or nucleotides. The worm-like chain model of DNA elasticity (Bustamante et al., 1994) describes correctly the elastic response of single DNA molecules (Smith et al., 1992, 1996). The expression derived from this model (see Equation 1) relates the end-to-end distance extension (x) of a polymer molecule to its contour length (L) at a given external force (F) applied at its ends. For double-stranded DNA, the contour length of the DNA is the unit length of a single base pair (0.34 nm for standard B-form DNA) times the number of base pairs (kB, Boltzmann constant; T, absolute temperature; and P, the persistence length of the polymer).

Magnetic tweezers use an external magnetic field to exert forces on macromolecules attached to micron-size paramagnetic beads via complementary biochemistry. Limited by the magnetic field strength, the range of force that can be applied by magnetic tweezers is typically one order of magnitude lower than that in optical tweezers (1 to 10 pN). However, magnetic tweezers can hold this force constant with sub-piconewton precision for a remarkable length of time. In addition, because the magnetic field is not localized to a single spot in space, as is the case with most optical tweezers, magnetic tweezers can be used to manipulate simultaneously many molecules in parallel, thus increasing the throughput of experiments. Moreover, because most magnetic beads have a small permanent magnetization, an external rotating magnetic field can be used to introduce torsion and supercoil DNA (Strick et al., 1996; Bryant et al., 2003).

FP 1 x 1 +  = kB T 4ð1  x=LÞ2 L 4

force. A subsequent study in which RNA hairpins harboring different sequences were used (Cheng et al., 2007) favors the second explanation. This study revealed that pause duration and stepping rate are strongly influenced by the base pair sequence, i.e., by the magnitude of the barrier at the fork, and indicates that the force insensitivity of the stepping velocity is more likely due to junction protection by the enzyme. Surprisingly, this study found that regions of high duplex stability ahead of the junction lead to increased NS3 dissociation and reduced processivity. These authors proposed a mechanism in which the enzyme contacts the duplex as far as 6 bp ahead of the junction and destabilizes it to start a new inchworm cycle. A stable duplex ahead of the junction can induce enzyme dissociation (Cheng et al., 2007). The independence of unwinding rate and the increase of processivity with the external force applied to the hairpin were similarly observed in a single-molecule magnetic tweezers (Box 3) study of E. coli DNA helicase UvrD, a 30 to 50 nonhexameric DNA helicase with structural resemblance to NS3 (Dessinges et al., 2004). Recent pre-steady-state bulk kinetic studies have confirmed the 11 bp step size for NS3 monomer (Serebrov et al., 2009). Interestingly, a single-molecule fluorescence (Box 4) study on NS3 catalyzing the opening of dsDNA did not reveal the 11 bp stepping seen both in optical tweezers and in pre-steady-state bulk experiments. This study found instead a periodic 3 bp step size for the helicase (Myong et al., 2007). Analysis of the pauses separating the 3 bp steps suggests that there are three rate-limiting events within each 3 bp step, although whether the rate-limiting events correspond to single bp steps remains to be addressed. A similar single-molecule optical tweezers assay was developed for bacteriophage T7 hexameric helicase (Johnson et al., 2007). Both the processivity and unwinding rate of the helicase increase with the application of mechanical force at hairpin ends; the ring in hexameric helicases can open (Ahnert et al., 2000), which may allow them to detach from the nucleic acids. The unwinding rate of the helicase also varies with the DNA sequence. Theoretical analysis of the unwinding rates from this study supports an active mechanism in which the helicase preferentially stabilizes the open over the closed form of the

(1)

step of the enzyme due to limitations in spatial and temporal resolution of the experiment. The 11 bp steps separated by pauses, and their decomposition into smaller substeps, were rationalized through an inchworm mechanism that requires at least two separate RNA-binding sites in NS3 (Dumont et al., 2006). The force on the hairpin was found to strongly enhance NS3 processivity but did not affect pause duration or stepping velocity. The processivity of a helicase (Lohman et al., 1998) measures the relative probability that the enzyme remains bound to the nucleic acid instead of detaching: p = kforward/(kforward + koff), where kforward is the rate constant of forward movement and koff is the rate of helicase dissociation. Because kforward does not change with force, the increase of helicase processivity must be due to a decrease of its koff. This explanation is consistent with crystal structures of NS3 in complex with ssRNA, in which the flexible ssRNA adopts an extended form in the NS3binding site (Appleby et al., 2010). Presumably, force helps overcome the configurational entropy loss associated with chain stretching, decreasing the off rate. The invariance of kforward with force also suggests that either strand separation by NS3 is not rate limiting in the reaction or that the dsRNA at the junction is protected by NS3 from being directly acted on by mechanical

Cell 144, February 18, 2011 ª2011 Elsevier Inc. 485

Box 4. Basics of Single-Molecule Fluorescence The ability to detect the fluorescence emitted by certain dyes at the single-molecule level has furnished another way to follow the dynamics of complex biochemical processes in real-time. Singlemolecule fluorescence methods make it possible, for example, to localize the emitter with nanometer precision (Yildiz et al., 2003). In particular, single-molecule fluorescence resonance energy transfer, FRET, takes advantage of the fact that the fluorescence emission of a molecule (called a donor) is influenced by a neighboring molecule (the acceptor) through dipolar coupling. The efficiency of this coupling is determined by the spectral overlap between the emission of the donor and the absorbance of the acceptor, the distance, and the orientation between these two molecules. Because this efficiency decreases with the sixth power of the distance between the donor and the acceptor, this method can be used to monitor conformational changes of macromolecules or changes in the relative orientation between macromolecules. In practice, FRET is better used to monitor relative changes in distance and/or orientation because the absolute distance measurements require information about the orientation of the fluorophores, which is not always available (Muschielok et al., 2008). The application of single-molecule fluorescence techniques to nucleic acid translocases has revealed many novel insights and mechanistic details of these motors (Ha et al., 2002). These experiments are mostly carried out using evanescent field excitation to reduce fluorescence background and achieve single-molecule sensitivity. This particular experimental design also permits to monitor many individual molecules simultaneously.

junction (Betterton and Julicher, 2005) (see Supplemental Information for passive versus active unwinding). Although not directly observed in this study, the analysis of unwinding rates indicates a step size of 2 bp. Using a magnetic tweezers assay, Lionnet et al. studied the DNA-unwinding mechanism catalyzed by bacteriophage T4 helicase gp41, a hexameric helicase involved in phage DNA replication (Lionnet et al., 2007). The difference between the rate of unwinding in these experiments (30 bp/s) and the expected rate in vivo (400 bp/s) suggests that gp41 must interact with other components of the replisome to achieve rapid and processive unwinding of the T4 genome. Interestingly, this study showed a clear dependence of DNAunwinding rate on the tension applied to the hairpin. Hexameric versus Nonhexameric Helicases A comparison of the behavior of hexameric and nonhexameric helicases reveals that for both groups processivity increases with applied force and the rate of dsNA unwinding depends on the thermodynamic stability of the base pair at the junction. However, the unwinding rate of nonhexameric helicases is insensitive to mechanical force on the hairpin (Dessinges et al., 2004; Dumont et al., 2006), whereas that of hexameric helicases studied so far increases with force (Johnson et al., 2007; Lionnet et al., 2007). The speeding up of hexameric helicases with force indicates that strand separation constitutes the rate-limiting step of their mechanochemical cycle. It also suggests that these two classes of helicases may interact with their dsNA substrates in different ways: whereas nonhexameric helicases may protect the junction and hold onto the single-stranded nucleic acids (ssNA) chains immediately after separation, preventing the force to reach the junction (Figure 2C), hexameric helicases do not 486 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

protect the junction (Figure 2D). Structural (Enemark and Joshua-Tor, 2008) and biochemical studies (Patel and Picha, 2000) have shown that ring-shaped helicases pass one strand of the dsDNA through the center channel of the ring while excluding the other strand, consistent with a simple picture of a ‘‘wire stripper’’ (Figure 2D). In contrast, single-molecule fluorescence studies on NS3 suggest that the helicase maintains contact with the 50 displaced single strand during unwinding (Myong et al., 2007). This notion is supported by the observation that domain II of the protein contains a positive patch that may form part of the exit path for the displaced 50 single strand (Serebrov et al., 2009). Protein-Displacement Activity of Helicases Although genetic studies have long implied the role of helicases in DNA recombination and repair (Aboussekhra et al., 1992; Palladino and Klein, 1992), it was not until recently that biochemical studies demonstrated unambiguously their requirement for disassembly of the DNA-Rad51 complex, the recombination intermediate in eukaryotes (Krejci et al., 2003; Veaute et al., 2003). Helicase malfunction in this case leads to hyperrecombination and cell death (Gangloff et al., 2000). There are also numerous examples of the involvement of RNA helicases in disassembly of RNA-protein complexes (Jankowsky and Bowers, 2006). The mechanisms by which helicases catalyze protein displacement are just beginning to be explored (Antony et al., 2009). In particular, single-molecule fluorescence studies in vitro showed that the repetitive movement of the E. coli Rep translocase monomer on single-stranded DNA (ssDNA) can delay the formation of recombination intermediates (Myong et al., 2005), and in the case of PcrA helicase, this activity can lead to catalytic disruption of the recA-DNA filament (Park et al., 2010). Direct observation of repetitive helicase translocation on ssNA is a capability unique to single-molecule methods and highlights their power in mechanistic studies of nucleic acid translocases. DNA Replication In the decade that followed the now famous paper by Watson and Crick on the structure of DNA, Arthur Kornberg and his group, working with E. coli cell extracts, showed that the building blocks of the reaction were deoxynucleoside tri-phosphates (Bessman et al., 1958; Lehman et al., 1958), that these building blocks could yield a copy of the DNA molecule in a thermodynamically spontaneous reaction with a DNA template, and that this reaction, however energetically possible, required a catalyst to proceed at biologically compatible rates; they called the enzyme that they isolated ‘‘DNA polymerase’’ (Lehman et al., 1958) (now called DNA polymerase I). These enzymes are universally present across species (see Supplemental Information). Many of these enzymes contain two active sites, a polymerization (pol) site that catalyzes the synthesis of dsDNA from an ssDNA template and an exonucleolysis (exo) site, capable of hydrolyzing and excising bases incorporated erroneously, greatly increasing the fidelity of the enzyme. DNA polymerases are distributive enzymes that require processivity factors to remain bound to the DNA template during replication. Thus, instead of tethering the enzyme and one end of the template,

as in transcription assays (see below), in single-molecule manipulation experiments one must tether both ends of the template. In the first study of this type, a single molecule of ssDNA was spanned between one bead held atop a micropipette by suction and another kept in an optical trap (Wuite et al., 2000). To follow the activity of T7 DNA polymerase, these authors took advantage of the difference in extension between ssDNA and dsDNA under all tensions (Box 2). As the enzyme converted ssDNA into dsDNA, the tweezers instrument, to keep the tension on the DNA constant at a preset value, changed the separation between the beads in an amount proportional to the progress of the enzyme. The authors observed bursts of polymerization activity, whose lengths were enzyme concentration and force independent, followed by gaps of constant extension whose lengths depended on enzyme concentration. These data indicated that each burst of activity corresponded to a different DNA polymerase binding, polymerizing, and falling off the template. It was estimated that the processivity of this polymerase is only around 420 bases (at 15 pN of tension). The rate of DNA polymerization decreased with increasing template tension until a (reversible) stall was reached at tensions around 34 pN. Surprisingly, the application of tension around and above this value induced exonucleolysis at rates 100 times faster than in solution. Based on these observations and analysis of the crystal structure of the ternary elongation complex (polymerase, incoming nucleotide, and DNA) (Doublie et al., 1998), the authors proposed a model in which two bases of ssDNA are organized within the enzyme during polymerization. Application of high forces deforms the DNA at the active site triggering the transfer of the 30 end to the exonucleolysis site. Lowering the force below this threshold value allows the enzyme to resume polymerization. Experiments with T7 DNA polymerase were complicated by the enzyme’s low processivity: the observed kinetics of polymerization and exonucleolysis were convolved with the enzyme’s on and off rates. Ibarra et al. (2009) studied the effect of force on the transfer dynamics between the pol and exo sites of 429 DNA polymerase, an enzyme with a processivity greater than 70 kb. Again, this assay monitored the single-molecule conversion of ssDNA into dsDNA and vice versa by individual polymerases. Two mutants were studied besides the wild-type enzyme, an exo-deficient variant that lacks exo activity and a transfer-deficient mutant that cannot transfer the DNA between the pol and exo domains. Polymerization rate was found to be independent of force for a wide range of forces. However, above this range, polymerization speed decreased rapidly until all activity ceased at a force of 37 pN for the wild-type enzyme. Upon lowering the tension, activity resumed, indicating that the stalling was reversible. Tensions above 46 pN or as low as 30 pN induced exonucleolysis activity in the presence (saturating conditions) or absence of dNTPs, respectively. Analysis of the enzyme’s pausing and elongating behavior as a function of tension suggests that the tension mimics the presence of a nucleotide mismatch that distorts the DNA primer-template interactions triggering the exo editing response. This study revealed two intermediate states of the replication complex in the pol-exo transfer reaction. One of them appears to be a fidelity checkpoint before the pol-exo transfer.

Still, DNA replication in vivo is a more complex process because it involves both leading- and lagging-strand synthesis, as well as additional proteins that together form the replisome. Furthermore, due to the antiparallel nature of DNA strands and the 50 -30 polarity of DNA polymerases, discontinuous pieces of DNA, known as Okazaki fragments, must be synthesized on the lagging strand (Ogawa and Okazaki, 1980). In order to coordinate the synthesis of the Okazaki fragments with the leadingstrand polymerase, a DNA loop is thought to be formed between the leading polymerase at the replication fork and the polymerization site on the lagging strand (Alberts et al., 1983). Hamdan et al. (2009) have used a single-molecule technique to monitor the formation and release of these loops for single bacteriophage T7 replisomes. Four proteins form the T7 replisome, one of the simplest known: the polymerase, the helicase-primase protein gp4, the gp5-thioredoxin protein clamp, and the gp2.5 singlestranded binding protein. In this single-molecule experiment, the lagging strand of a DNA replication fork was attached to a glass slide while the downstream DNA was attached to a bead and kept under force (see Figure S2). In the presence of all four proteins as well as a full set of deoxynucleotides and the ribonucleotides required for primer synthesis, a shortening followed by a lengthening of the DNA was observed, presumably corresponding to the formation and release of the loop. Two models have been proposed for the triggering of loop release: the signaling and collision models. In the signaling model, primase activity is responsible for the timing of loop release, independently of the completion of the Okazaki fragment. In contrast, the collision model proposes that the arrival of DNA polymerase to the end of the previous Okazaki fragment causes loop release. For this model, however, leading-strand polymerization must continue even after loop release to allow the primase to find its next starting sequence. This additional polymerization length would then increase the size of the next loop formed, a directly testable prediction. Indeed, analyses of the data show a positive correlation of the lag time between the formation of two loops and the loop length, consistent with the collision model. However, by changing the concentration of the available ribonucleotides for primer synthesis or by substituting them with dinucleotides, a change in both the length of the loop and the lag time between loops was observed. These data then indicated that the first step in RNA primer synthesis—the formation of the first two RNA bases—triggered loop release and argued instead for the signaling model. The authors concluded that not being mutually exclusive, both mechanisms operate during DNA replication. Additionally, using single-molecule fluorescence resonance energy transfer (FRET), researchers have begun to understand other specialized types of DNA polymerases, such as the HIV reverse transcriptase (Liu et al., 2008) and telomerase (Wu et al., 2010) (see Supplemental Information). Even though some progress has been made, there is still a long way before the complex dynamics of these enzymes are fully revealed. DNA Transcription RNA polymerase is the enzyme responsible for the first step of gene expression: copying the information stored in DNA into the messenger RNA (mRNA). The prokaryotic RNA polymerase, Cell 144, February 18, 2011 ª2011 Elsevier Inc. 487

RNAP, is a 450 kDa protein with five core subunits and one initiation factor. Of the various RNA polymerases that exist in eukaryotes, RNA polymerase II (Pol II)—the one responsible for the synthesis of mRNA, some small nuclear RNAs (sNRNA), and most microRNAs—is the most studied. Pol II has a molecular weight close to that of its prokaryotic counterpart (550 kDa), it is composed of 12 subunits, and it requires a rather large number of factors to initiate transcription. For both enzymes, the transcription cycle consists of three stages: initiation, elongation, and termination. During initiation, the polymerase, with the help of initiation factors, binds to the promoter sequence in the template DNA and unwinds the duplex, forming a transcription bubble in an open promoter complex (OPC). The polymerase then undergoes a series of attempts known as abortive initiation in which short pieces of RNA are formed but detach from the complex. It is not until the growing RNA reaches a length of around 9–11 bases that the complex makes the transition into the elongation stage. As part of elongation and as it reads the template DNA in the 30 to 50 direction, RNAP displaces the transcription bubble base by base, opening the next base pair in front and closing a base pair at its back. At each DNA base, RNAP binds the next correct ribonucleoside tri-phosphate (NTP), hydrolyzes it, incorporates it into the 30 end of the RNA growing chain, and releases pyrophosphate (PPi). During termination, the enzyme reads the terminator sequence and detaches from the DNA, releasing the transcript. Termination can occur either in a Rho-independent or in a Rho-dependent manner. In the former, a very stable RNA hairpin and a U-rich track are required to destabilize the complex. In the latter, Rho, an RNA helicase, moves along the transcript until it reaches the enzyme and releases the transcript. RNA polymerase has been studied by means of an evergrowing array of techniques. Traditional biochemical bulk methods, together with recent structural breakthroughs, have set the stage for much of what is known about this molecular motor. However, these approaches cannot provide a detailed picture of the dynamics of transcription, as much of the details of the individual molecular trajectories are lost in the asynchronous average of the signals. In contrast, single-molecule methods have made it possible to follow the individual transcription traces, characterize their heterogeneity, and reveal their stochastic alternation in periods of continuous translocation and pauses. Initiation Studies Initiation is the process by which RNA polymerase binds to a promoter sequence and locally unwinds the DNA template to form the OPC. Atomic force microscopy (AFM) studies have revealed that lPR promoter wraps around the polymerase over 270 in OPCs and that 2/3 of this wrapping involves extensive contacts of the enzyme with the upstream DNA (Rivetti et al., 1999). At this point, the catalytic center of the polymerase will be located at the +1 site of the template from which RNA synthesis will start. Most single-molecule studies of initiation have been performed on prokaryotic RNA polymerase due to the vast complexity of eukaryotic initiation. In bacteria, only one transcription factor is required for initiation, the sigma factor. In E. coli sigma-70 is the housekeeping factor, but other factors, like sigma-32, the heat shock sigma factor, also exist. 488 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

In recent years, single-molecule fluorescence has risen as a powerful tool for analyzing the dynamics of initiation. Kapanidis et al. (2005) used FRET to render the first quantitative study of the extent of sigma-70 retention during the transition from initiation to elongation. The authors placed a donor-acceptor pair on the sigma subunit of the polymerase and on either the downstream or upstream template DNA. By measuring changes in FRET efficiency they were able to assess both the translocation state of the polymerase and the presence or absence of the sigma factor as a function of transcript length. Contrary to previous biochemical results that argued sigma-70 detachment upon the transition from initiation to elongation, this single-molecule experiment proved that, for the lacUV5 promoter, the sigma factor is retained for approximately half of the transcription elongation complexes, even for mature elongation complexes with 50 bp transcripts. Margeat et al. (2006) performed a similar experiment but with surface-immobilized complexes and not only again confirmed sigma-70 retention by elongation complexes but, more importantly, conclusively eliminated the possibility of sigma factor rebinding, a plausible concern for solution experiments. Together, these experiments convincingly demonstrate that sigma release is not required for promoter escape and challenge the conventional belief of sigma disengagement as part of the transition between initiation and elongation. However, as Kapanidis et al. point out, sigma retention in vivo could be different due to the presence of other transcription factors that might facilitate sigma release. Three different movement mechanisms involved in the early dynamics of transcription initiation have been proposed: inchworming, scrunching, and transient excursions (Kapanidis et al., 2006; Revyakin et al., 2006; and references therein). In the inchworming model, a portion of the polymerase containing its catalytic center and the complete transcription bubble moves forward on the DNA, while its trailing edge remains static. This mechanism requires that the polymerase be somewhat elastic, extending and contracting as it moves along DNA. The scrunching hypothesis postulates that the polymerase remains static with respect to the DNA, but that it reels in the template keeping the extra DNA inside. Finally, the transient excursion model proposes that the entire polymerase moves rapidly forward and backward along the DNA as it creates abortive products. Two separate studies, using two distinct single-molecule methods, have evaluated the predictions of these three models. Revyakin et al. (2006) used a magnetic tweezers assay in which changes in extension of supercoiled DNA are observed upon unwinding due to initiation. Their results show an initial unwinding due to DNA bubble opening as expected but, surprisingly, also an additional unwinding whose extent depends on the length of the abortive RNA product. Only the scrunching model predicts increased unwinding during abortive initiation because the reeled-in DNA bases are unwound and kept as single-stranded bulges inside the polymerase. The two other mechanisms should only advance the transcription bubble but not change the unwound state of the DNA. Based on these results the authors conclude that all transcription complexes undergo scrunching during initiation for transcripts longer than 2 bp and propose that it is precisely the creation of this stressed intermediate that facilitates promoter escape. Along the same lines, Kapanidis et al. (2006) have used

a single-molecule FRET experiment to test these three models. Donor-acceptor pairs in specific locations on the initiation complex are used as reporters of changes in distance. With this method the authors find that during abortive initiation, there is a change in extension between the leading edge of the polymerase and the downstream end of the DNA, as expected, but not a measurable distance change between the trailing edge of the polymerase and the upstream DNA (eliminating the transient excursion model) or between two positions on the enzyme (invalidating the inchworming model). These results, again, independently support the DNA scrunching mechanism. The observation of partial loss of upstream contacts during abortive transcription of a 6-mer and 8-mer (Straney and Crothers, 1987) suggests that abortive initiation may result from the failure of the enzyme to fully break these contacts. The energy required to break the association of the enzyme to the promoter has been estimated in roughly 10–15 kcal/mol (Murakami et al., 2002). On the other hand, the maximum work that the prokaryotic enzyme can generate is roughly 0.8–1 kcal/mol using one-half of 0.34 nm per base pair for the distance to the transition state and between 20–25 pN for the stall force of the motor (see below). Therefore, the motor cannot climb the required energetic hill in a single step. More likely, the enzyme ‘‘peels’’ itself off from the promoter through successive catalytic cycles during abortive initiation, breaking partial interactions with the promoter one step at a time. It was early suggested that some kind of stress intermediate could be responsible for the escape and clearance of the promoter (Straney and Crothers, 1987). The finding of DNA scrunching provides a candidate for that intermediate and a mechanism for the storage and accumulation of at least part of the work done by the enzyme during its separation from the promoter. This stored energy should increase as the DNA is compressed inside the enzyme until the scrunched DNA is released either at the front of the polymerase (abortion followed by release of the short transcript) or at its back (formation of stable elongation complex). Elongation and Pausing The first study of RNAP’s ability to move against an external opposing force and generate work was done by Yin et al. (Yin et al., 1995) using optical tweezers. By immobilizing an E. coli RNA polymerase molecule on a glass slide and attaching a polystyrene bead to the downstream end of the DNA, they observed individual transcription events under force. These authors determined that E. coli’s enzyme generates average forces as high as 14 pN before stalling. Later experiments (Wang et al., 1998) yielded mean stall forces of 25 pN, a value more than five times those of myosin and kinesin but small compared to forces exerted by other DNA translocases (Chemla et al., 2005), as described before. Analysis of the RNAP’s force-velocity behavior (Wang et al., 1998) revealed that the translocation velocity of the enzyme is largely unaffected by the force until the maximum force is reached, and that, at the single-molecule level, transcription was made up of alternating continuous translocation and stochastic pausing events. A more systematic study of the kinetics of the enzyme’s pausing behavior (Davenport et al., 2000) demonstrated that translocation and pausing compete kinetically, suggesting that pauses states are off the main

elongation pathway. This study also revealed that the paused state is an intermediary to irreversible motor arrest. Forde et al. (2002) studied the effect of opposing and assisting force and of nucleotide concentration on elongation velocity and pause entry. Their data show that lower nucleotide concentrations lead to decreased velocity and increased pausing, again confirming the kinetic competition between the main elongation pathway and the off-pathway paused state. As the resolution and precision of optical tweezers experiments improved, more detailed studies of RNAP pausing became possible. Shaevitz et al. (2003) observed backward movements along the DNA and identified them with the backtracking events described by bulk studies when the polymerase was shown to move backward displacing the 30 end of the transcript from its catalytic center (Nudler et al., 1997). In parallel, Neuman et al. described short polymerase pauses that could be well fit by a double exponential and were force independent, arguing against a backtracking mechanism (Neuman et al., 2003). Therefore, these two studies claimed the existence of two distinct types of pauses: ‘‘ubiquitous’’ pausing in which backtracking does not occur, and backtracked pauses. Another study (Dalal et al., 2006) analyzed the effect of RNA secondary structure on ubiquitous pauses by pulling on the 50 end of the nascent RNA during transcription. They did not observe a significant effect on the enzyme’s processivity, elongation rate, pause frequency, or pause lifetimes, thereby concluding that ubiquitous pauses are not related to the formation of RNA hairpins. In addition, Herbert et al. (2006) studied the sequence dependence of pausing and proposed that ubiquitous pauses are associated with DNA sequences similar to known regulatory pause sequences. This conclusion was challenged when Galburt et al. (2007) demonstrated that pause durations for the yeast polymerase (Pol II) follow a power-law distribution of t3/2. These authors proposed that such dependence arises naturally if, during backtracking, the transcription bubble moves backward and forward executing an isoenergetic one-dimensional diffusion along the DNA. A pause ends when the 30 end of the RNA realigns at the active site so that elongation can resume. These distributions suggested that most if not all pauses observed are backtracking pauses. This same mechanism for pausing was later verified for the E. coli polymerase as well (Mejia et al., 2008). The earlier observation that some pauses do not appear to involve backtracks was recently addressed by Depken et al. (2009). In this work, backtracking was modeled as a discrete one-dimensional random walk, with an absorbing boundary, along the periodic potential of the DNA. The distribution derived from their model predicts three regimes as a function of pause duration. Short pauses have a probability density that falls off exponentially, whereas intermediate pause durations follow a t3/2 decay that is then cut off by an exponential behavior for even longer pause durations. Furthermore, they also showed that the pauses within the short time limit would display apparent force insensitivity, and very brief and shallow backward excursions, both characteristics observed for the ubiquitous pauses. Therefore, these authors conclude that a single mechanism, backtracking, can account for the behavior of most if not all pauses observed. Cell 144, February 18, 2011 ª2011 Elsevier Inc. 489

Figure 3. Transcription through the Nucleosome (A) Hodges and Bintu (Hodges et al., 2009) follow Pol II transcription through the nucleosome in real-time. They observe an increase in the probability of nucleosome passage with ionic strength, as well as an increase in pause density and pause duration in the vicinity of the nucleosome. Their model supports a passive mechanism of motion that depends on thermal fluctuations of the DNA-nucleosome interactions. (B) Jin et al. (2010) use an unzipping technique to infer the position of the polymerase after transcription has occurred. They also observe increased pausing within the nucleosomal sequence and verify nucleosome-induced polymerase backtracking of 10–15 bp. The inclusion of RNase or a trailing polymerase limits backtracking and increases the passage probability (adapted from Hodges and Bintu et al. [Hodges et al., 2009] and Jin et al. [2010]).

Surprisingly, the first studies of Pol II revealed that it stalls at an opposing force two to three times smaller (7 pN) than its prokaryotic counterpart due to its greater tendency to enter a backtrack (Galburt et al., 2007). This was a surprising finding, given that the natural substrate for this enzyme is not bare but nucleosomal DNA. These authors also found that addition in trans of TFIIS, a transcription factor known to activate cleavage of the 30 end of the transcript by backtracked Pol II complexes, increases the stall force of the enzyme by 3-fold. They proposed that the weaker mechanical performance of RNAP is part of a regulatory mechanism of transcription elongation in eukaryotes. Transcription through the Nucleosome How does RNA polymerase overcome hurdles along the transcriptional path? What is the physical basis underlying the regulation of eukaryotic gene expression by nucleosomal DNA? 490 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

Hodges and Bintu (Hodges et al., 2009) used an optical tweezers instrument to observe Pol II transcription of a template containing a single nucleosomal particle. Their data show that the probability of transcribing over the nucleosomal barrier increases sharply with the ionic strength of the environment (Figure 3), presumably due to the decreased stability of the nucleosomeDNA interactions under high screening conditions. The presence of the nucleosome increased the local pause density (as compared to that of bare DNA), slowed pause recovery (increased pause duration), and slightly reduced elongation speed. Interestingly, their data indicate that during transcription the polymerase does not actively separate the DNA from the nucleosome. Instead, it waits for thermal fluctuations that cause local unwrapping of the nucleosomal DNA in order to advance. Thus, the polymerase acts as a rectifier of nucleosome fluctuations, consistent with the ratchet mechanism of motion

proposed for the operation of RNAP (Bar-Nahum et al., 2005). Based on these results, they developed a quantitative model in which the nucleosome behaves as a fluctuating mechanical barrier that slows forward translocation and causes the polymerase to enter backtracked/paused states and, as a result, increases the probability of enzyme arrest. Furthermore, during backtracks the nucleosome can rewrap the newly exposed DNA, a process that slows down the recovery from a pause. As a way to better understand the interactions between the DNA and the nucleosome, Jin et al. (2010) developed a DNA unzipping technique that monitors the position of RNA polymerase from E. coli on the DNA template after transcription (Figure 3B). In this experiment, a nucleosome is placed downstream of a polymerase and, after transcription is allowed to take place for varying periods of time, the two strands of the transcribed molecule are pulled apart. The bacterial polymerase does not encounter nucleosomes in vivo, however it is used as a model system warranted by the high level of functional homology with Pol II (Walter et al., 2003). The resulting force extension curves show characteristic transitions that indicate the position of the polymerase on the DNA (to avoid additional transitions due to nucleosome unwrapping, the nucleosome was removed from the template using heparin). The authors observed nucleosome-induced polymerase pausing with a 10 bp periodicity that was sequence independent and correlated with the periodicity of the interactions between the nucleosome and the DNA. Moreover, by comparing the size of the RNA formed (using a transcription gel) with the position of the polymerase on the template (using the unzipping assay), they estimated that the polymerase backtracks between 10–15 bases when it encounters the nucleosome. They further reasoned that, if backtracking and arrest occur upon transcription through the nucleosome, conditions under which backtracking is limited should facilitate passage. As predicted, the use of RNase, as a way to reduce the number of RNA bases the polymerase could backtrack on, decreased the number of backtracked bases and increased the number of complexes that passed the nucleosome. Similarly, the addition of a second trailing polymerase that physically limited the number of bases the leading polymerase could move back enhanced passage by a factor of 5, an amount similar to experiments using RNase. From these experiments the authors speculate that the presence of multiple polymerases in vivo will further facilitate transcription through the nucleosome by preventing or reducing backtracking. Also, transcription factors like TFIIS could rescue backtracked polymerases, expediting nucleosome passage. It would be interesting to repeat these experiments with the eukaryotic enzyme. RNA polymerase pausing and backtracking are intrinsic and complex properties of RNA polymerase important for transcription regulation and control of transcription fidelity. Future use of mutant polymerases with altered pausing behavior and the reconstitution in vitro of ever more complex single-molecule transcription reactions should provide a more complete picture of the mechanisms that control gene expression during transcription elongation. Transcription Termination To investigate the importance of mechanical force on termination, forces up to 30 pN were applied to the nascent RNA tran-

script (Dalal et al., 2006). No significant effect was found on enzyme processivity, elongation rates, pause frequencies, and lifetimes. It is unlikely that the termination hairpin or Rho could exert larger forces; thus if force plays any role in termination, it must be aided by an allosteric effect wherein the binding energy of the hairpin and/or Rho to the complex pay in part the energetic price of disrupting the DNA-RNA hybrid. Larson et al. (2008) found that pulling between RNAP and upstream DNA does not affect termination efficiency on two out of three terminators studied, indicating that hypertranslocation (forward movement of the bubble with respect to RNA’s 30 end) either cannot be effected mechanically or is not the only mechanism of termination. In fact, the authors propose that depending on the identity of the terminator, shearing of the RNA-DNA hybrid or hypertranslocation, or both, can occur during transcript release. Prokaryotic Translation Ribosomes are the cellular machines that hydrolyze GTP to ‘‘read’’ and translate the information encoded in mRNA into protein (Moore and Steitz, 2003). Single-molecule studies of translation are quite recent and restricted to prokaryotic ribosomes. Translation is an extremely complex process also conveniently divided in three phases: initiation, elongation, and termination (Ramakrishnan, 2002). In prokaryotes, initiation begins with the binding of the ribosome to the methionine-encoding mRNA translation start codon, AUG, whose placing at the P site of the ribosome is directed by an upstream Shine-Dalgarno (SD) sequence complementary to a segment of the 16S ribosomal RNA. Initiation requires initiation factors IF1, IF2,GTP, and IF3. In elongation, ternary complexes of tRNAs charged with the correct amino acids, elongation factor EF-Tu, and GTP bind to ribosome. The correct amino acid-carrying tRNA is selected by its complementarity to the codon on the mRNA and interactions with the small and large subunits at the A site of the ribosome. Upon GTP hydrolysis and release of EF-Tu, the tRNA is bound in the ‘‘classical’’ position at the A site, adjacent to the peptide-containing tRNA bound in the classical position at the P site. Subsequently, a new peptide bond is formed as the polypeptide in the P site is transferred to the A site tRNA, a reaction catalyzed by the peptidyl transferase active site in the 23S rRNA of the 50S subunit. This event allows the tRNAs to access intermediate binding conformations called ‘‘hybrid’’ states, in which the anticodon ends of the tRNAs remain in their classical A and P sites in the 30S subunit but their acceptor stems make contacts in the P and E sites of the 50S subunit, respectively (Moore and Steitz, 2003). The elongation cycle is completed with the translocation of the ribosome relative to the mRNA upon binding of another elongation factor, EF-G,GTP, and the subsequent hydrolysis of GTP. In this process, the tRNA at the A site moves to the P site and the tRNA at the P site moves to the exit or E site. Termination occurs when the ribosome encounters a stop codon (either UAA, UAG, or UGA). Protein release factors are bound that cleave the peptide from the tRNA at the P site; release factor 1 (RF1) recognizes UAA and UAG; release factor 2 (RF2) recognizes UAA and UGA. The ribosome then remains attached to the mRNA. Dissociation of the ribosome into its Cell 144, February 18, 2011 ª2011 Elsevier Inc. 491

Figure 4. Single-Molecule Studies of Ribosomes (A) Experimental design for monitoring single ribosome translation in real-time. The ribosome was stalled at the 50 side of the mRNA hairpin construct, which was then held between two polystyrene beads. Drawings are schematic and not to scale. (B) Single ribosome trajectory through an mRNA hairpin as in (A). Data obtained at constant force (lower panel). The arrows represent individual codon steps (Wen et al., 2008).

component subunits requires ribosome-recycling factor, RRF (Liljas, 2004), and EF-G. Optical tweezers have been used to pull the mRNA from the ribosome in various conditions (Uemura et al., 2007). The strength of the ribosome-mRNA interactions increased by 5 pN when deacylated tRNAfMet was bound to the P site. A PhetRNAPhe at the A site stabilized the P-site-bound ribosome by 10 pN. A SD sequence further strengthened the interaction by 10 pN. A peptidyl-tRNA analog N-acetyl-Phe-tRNAPhe bound to the A site weakened the rupture force in an SD-independent manner relative to the complex carrying a Phe-tRNAPhe, indicating that following peptide bond formation, the ribosome looses grip of the mRNA to complete translocation. Recently, optical tweezers were used (Wen et al., 2008) to monitor translation of an RNA hairpin by single E. coli ribosomes using a helicase-based assay (see Figure 4A) similar to the one used previously for the studies of NS3 helicase (see above). Ribosomes load at a start side on the 50 side of the hairpin. At the beginning of the experiment, a preset force is applied to the ends of the hairpin and held constant via a feedback circuit in the instrument. As the ribosome translates each codon in the hairpin, six bases are converted into ssRNA, making the molecule longer and requiring the beads to be moved apart to keep the force constant. At 20 pN, each codon corresponds to a bead displacement of 2.7 nm. These studies have revealed that translation occurs through successive translocation-and-pause cycles (see Figure 4B). The distribution of pause lengths, with a median of 2.8 s, reveals that at least two rate-determining processes control each pause. Each translocation step occurs in less than 0.1 s and measures three bases—one codon—indicating that translocation and RNA unwinding (helicase activity) are strictly coupled ribosomal functions. Pause lengths, and therefore the overall translation rate, depend on the secondary structure of the mRNA. Unlike in the case of the NS3 helicase (see above), the external force applied to the hairpin reduces the magnitude of the kinetic barrier at the junction and decreases pause durations. It does not, however, affect the actual translocation times. 492 Cell 144, February 18, 2011 ª2011 Elsevier Inc.

Although single-molecule manipulation studies of translating ribosomes have just started, these codon-resolution experiments should provide answers to questions such as: Does the codon sequence affect the dwell time of the ribosome at a pause? Is the ribosome a passive or an active helicase? How are the single ribosome helicase trajectories affected by the concentration of EF-G and EF-Tu? How does the ribosome respond in real-time to barriers such as hairpins, pseudo-knots, and other structures? How powerful is the ribosome as a motor? That is, what kind of forces can it develop? How does the ribosome translation rate respond to direct mechanical load, or in other words, what is the ribosome velocity versus force curve? What is the distance to the transition state for translocation? How do frameshifts occur and what are their microscopic dynamics? Finally, by directly grabbing the nascent polypeptide, it will be possible to follow in real-time its folding dynamics on the surface of the ribosome. Single-molecule FRET has been used also to explore translation. Fluorescently labeled phe-tRNAs have been used to reveal tRNA dynamics during elongation (Blanchard et al., 2004a, 2004b; Lee et al., 2007; Marshall et al., 2008). Cy5-labeled Phe-tRNAPhe ternary complexes delivered to 70S elongation complexes bound to Cy3-labeled fMet-tRNAfMet. tRNAs were seen to attain a high-FRET state from low- and middle-FRET states in about 100 ms. The low-FRET state was shown to correspond to the initial selection of the tRNA at the A site, the middleFRET state to correspond to the GTPase activation ensuing the binding of the cognate tRNA, and the high-FRET state to correspond to the full tRNA accommodation. These single-molecule experiments revealed that binding of the ternary complex to the ribosome is made up of two components: a codon-independent binding of the complex to L7/L12 proteins with zero FRET and a codon-dependent, reversible, rapid (50 ms) sampling of the A-site codon leading to the low-FRET state. Following accommodation and formation of the high-FRET state, a reversible transition to a second mid-FRET state was observed (Blanchard et al., 2004b), which was identified as the signature of the hybrid state. Single-molecule FRET has also been used to investigate the dynamics of the internal degrees of freedom of the ribosome. During translocation, the large and the small subunits are known to rotate by 10 relative to each other (Frank et al., 2007).

This ‘‘ratchet’’ motion is thought to accompany the formation of the hybrid states (Ermolenko et al., 2007). Fluctuations in the spatial orientations of the large and small subunits were followed in real-time by FRET changes between Cy3-labeled protein L9 and Cy5-labeled protein S6 (Cornish et al., 2008). Ribosomes fluorescently labeled at L1 and L33 were also used to monitor the movement of the L1 stalk of the E site (Cornish et al., 2009). A correlation between the L1 stalk position and the binding, movement, and release of the deacylated tRNA at the E site was found, suggesting that conformational changes of the stalk are responsible for the tRNA transitions. Consistent with these observations, fluctuating FRET signals between the L1 stalk and the incoming tRNA were also detected (Fei et al., 2008). These signals were thought to represent the stochastic movements of the L1 stalk between open and closed conformations in the pretranslocation elongation complex, coupled to the fluctuations of the P-site tRNA between its classical and its hybrid configurations. Taken all together, these observations suggest that the deacylation of the peptidyl-tRNA during elongation triggers the fluctuation of the entire pretranslocation complex between two major conformational states, global state 1 (GS1) and global state 2 (GS2) (Fei et al., 2008). Evidence for these two global states has been recently found by two CryoEM studies (Agirrezabala et al., 2008; Julian et al., 2008). Single-molecule FRET has been used to investigate the dynamics of the ribosome and tRNAs during translation termination and ribosome recycling (Sternberg et al., 2009). These authors used fluorescently labeled RF1, tRNAs, and ribosomes to show that when RF1 binds at a stop codon and promotes the hydrolysis of the peptide, the ribosome is locked in the GS1 state. Subsequent binding of RF3 and GTP induce the ribosome to transition into GS2 and RF1 to release. GTP hydrolysis then ensues and primes the ribosome for recycling. The authors showed that the effect of RRF is to bias the state of the ribosome to GS2, the recycling-competent state. The implementation of single-molecule approaches together with new technical developments such as zero-mode waveguides (ZMWs) allowed Uemura et al. (2010) to follow in realtime the binding of tRNA during processive translation at physiologically relevant micromolar ligand concentrations. By labeling the tRNAs with distinct fluorophores, these authors were able to determine the identity of the tRNA and the mRNA codon involved. This study found that ribosomes are only briefly occupied by two tRNA molecules and that release of deacylated tRNA from the exit (E) site is uncoupled from binding of aminoacyltRNA site (A site) tRNA, occurring rapidly after translocation. Perspective The minimal unit of living matter, the cell, is a complex microscopic factory whose integrity and homeostasis depend on the operation of an interconnected network of highly specialized tiny processing units or molecular machines. Some of these machines, like the ones that are the subject of this Review, must function as nucleic acid translocases. They must move along their nucleic acid templates to read, copy, and translate the linear information encoded in their sequences and ensure the flow, control, and expression of genetic information. Until recently, the detailed study of their function had lagged behind

that of their structures, mainly because of the difficulty of synchronizing a population of molecules to follow their dynamics. This situation is now changing rapidly. The emergence over the last two decades of single-molecule techniques has begun to yield impressive details on how these macromolecular machines work. By following the actual molecular trajectories of these translocases, and not just the mean or average behavior of a population of molecules, we are beginning to learn unprecedented details of their complex dynamics, the manner by which they move on nucleic acids, the mechanical nature of their moving parts, the presence of transient intermediates, their mechanisms of fidelity, and the manner in which they use the spontaneous fluctuations of the bath to accomplish their mechanical tasks. We have many reasons to believe that these developments are just the beginning of growing insight into the operation of these machines: with the advent of high-resolution, single-molecule optical tweezers (Abbondanzieri et al., 2005; Moffitt et al., 2006) and the combination of optical tweezers with single-molecule fluorescence capability (Hohng et al., 2007; Lang et al., 2004), it should be possible now to monitor directly the movement of motors at angstrom-level resolution (Moffitt et al., 2009) and to uncover the coordination of their various parts during their mechanochemical conversion (Ishijima et al., 1998). Future efforts, through the study of ever more complex assemblies, will also likely try to fill the gap between the controlled experimental conditions of in vitro studies and the need to understand at a quantitative level how the performance of these machines is influenced by their physiological partners (Stano et al., 2005). Finally, recent advances in super-resolution optical imaging (Betzig et al., 2006; Hell, 2007; Huang et al., 2008) may also make it possible to fulfill the ultimate hope of directly observing the activity of these machines in living cells. Ultimately, a comparison of the diverse molecular designs utilized by evolution to accomplish these directional and energy-driven tasks, the unraveling of the physical principles that lie behind their function, and the emerging understanding of the importance of fluctuations in their operation and thermodynamic efficiency should provide, in the not-too-distant future, the basis for the development of a comprehensive theory of molecular motors. At the very least, we hope that these efforts will fulfill the goal of endowing the detailed structures of these molecular entities, with an equally detailed description of the molecular choreography that underlies their operation in the cell. SUPPLEMENTAL INFORMATION Supplemental Information includes an Extended Discussion, two figures, and Supplemental References and can be found with this article online at doi: 10.1016/j.cell.2011.01.033. ACKNOWLEDGMENTS We thank Timothy M. Lohman at Washington University School of Medicine for a critical reading of the draft on helicases and many colleagues for stimulating discussions. The literature on nucleic acid translocases, in particular their single-molecule studies, is ever increasing. Due to space limitations and our coverage of selected topics, we would like to apologize to our colleagues who actively work on nucleic acid translocases yet whose work has not been cited here. C.B. was supported by NIH, DOE, and HHMI. W.C. was supported by Ara Paul Professorship fund at the University of Michigan Ann Arbor.

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Identification of Aneuploidy-Selective Antiproliferation Compounds Yun-Chi Tang,1 Bret R. Williams,1 Jake J. Siegel,1 and Angelika Amon1,* 1David H. Koch Institute for Integrative Cancer Research and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA *Correspondence: [email protected] DOI 10.1016/j.cell.2011.01.017

SUMMARY

Aneuploidy, an incorrect chromosome number, is a hallmark of cancer. Compounds that cause lethality in aneuploid, but not euploid, cells could therefore provide new cancer therapies. We have identified the energy stress-inducing agent AICAR, the protein folding inhibitor 17-AAG, and the autophagy inhibitor chloroquine as exhibiting this property. AICAR induces p53-mediated apoptosis in primary mouse embryonic fibroblasts (MEFs) trisomic for chromosome 1, 13, 16, or 19. AICAR and 17-AAG, especially when combined, also show efficacy against aneuploid human cancer cell lines. Our results suggest that compounds that interfere with pathways that are essential for the survival of aneuploid cells could serve as a new treatment strategy against a broad spectrum of human tumors. INTRODUCTION Aneuploidy, a condition in which the chromosome number is not a multiple of the haploid complement, is associated with death and disease in all organisms in which this has been studied. In budding and fission yeast, aneuploidy inhibits proliferation (Niwa et al., 2006; Torres et al., 2007). In flies and worms, most or all whole-chromosome trisomies and monosomies are lethal, respectively (Hodgkin, 2005; Lindsley et al., 1972). In the mouse, all monosomies and all trisomies but trisomy 19 result in embryonic lethality. In humans, all whole-chromosome aneuploidies except trisomy 13, 18, or 21 lead to death during embryogenesis. The viable trisomies display severe abnormalities (Lin et al., 2006; Moerman et al., 1988; Antonarakis et al., 2004). Aneuploidy is also detrimental at the cellular level. Budding and fission yeast cells carrying an additional chromosome display cell proliferation defects (Niwa et al., 2006; Pavelka et al., 2010; Torres et al., 2007). Primary aneuploid mouse embryonic fibroblasts (MEFs) trisomic for any of four chromosomes, chromosome 1, 13, 16, or 19, primary foreskin fibroblast cells derived from Down’s syndrome individuals (trisomy 21), and human cell lines with decreased chromosome segregation fidelity exhibit cell proliferation defects (Segal and McCoy, 1974; Thompson and Compton, 2008; Williams et al., 2008).

Two systematic studies in disomic budding yeasts and trisomic MEFs furthermore showed that the presence of an additional chromosome elicits a set of phenotypes that is shared between different aneuploidies in both yeast and mouse. Yeast cells carrying an additional chromosome display metabolic alterations and increased sensitivity to compounds that interfere with protein folding and turnover (Torres et al., 2007). These shared traits are due to the additional proteins produced from the additional chromosomes (Torres et al., 2007). Similar phenotypes are seen in trisomic MEFs. Trisomic cells show increased sensitivity to proteotoxic compounds, higher basal levels of autophagy, elevated amounts of the active form of the molecular chaperone Hsp72 (see below), and increased uptake of glutamine, a major carbon source for the TCA cycle (DeBerardinis et al., 2007; Williams et al., 2008). Based on these findings, it was proposed that aneuploidy leads to a cellular response (Torres et al., 2010; Torres et al., 2007). Cells engage protein degradation and folding pathways in an attempt to correct protein stoichiometry imbalances caused by aneuploidy. This increases the load on the cell’s protein quality control pathways and results in heightened sensitivity to proteotoxic compounds and an increased need for energy. Whether the cell proliferation defects that are observed in aneuploid cells are also a part of the response to the aneuploid state, as is seen in many other stress responses, or are caused by the misregulation of individual cell cycle proteins is not yet known. Although aneuploidy adversely affects cell proliferation, the condition is associated with a disease characterized by unabated growth, cancer (reviewed in Luo et al. [2009]). More than 90% of all solid human tumors carry numerical karyotype abnormalities (Albertson et al., 2003). Studies in mouse models of chromosome instability indicate that aneuploidy is not simply a by-product of the disease but is directly responsible for tumor formation. Impairing spindle assembly checkpoint activity or halving the gene dosage of the motor protein CENP-E causes chromosome missegregation. Remarkably, it also causes increased tumor formation in mice (Li et al., 2010; Sotillo et al., 2007; Weaver et al., 2007). How aneuploidy promotes tumorigenesis despite its antiproliferative effects is an important question that remains to be answered. Irrespective of how aneuploidy promotes tumorigenesis, the stresses caused by the aneuploid state could still exist in aneuploid cancer cells, a condition termed ‘‘nononcogene addiction’’ (Luo et al., 2009). Compounds that exhibit lethality with the aneuploid state either by exaggerating the adverse effects of Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc. 499

aneuploidy and/or by interfering with pathways that are essential for the survival of aneuploid cells could represent new tumor treatments. We have identified the energy and proteotoxic stress-inducing compounds AICAR, 17-AAG, and chloroquine as exhibiting this selectivity. They induce p53-mediated apoptosis in primary mouse embryonic fibroblasts trisomic for chromosome 1, 13, 16, or 19. AICAR and 17-AAG also show efficacy against aneuploid human cancer cell lines. When combined, the two compounds are more effective in inhibiting the proliferation of human colorectal cancer cells that exhibit high-grade aneuploidy (chromosome instability lines, CIN) compared to lines that show low-grade aneuploidy (microsatellite instability lines, MIN). Our results raise the interesting possibility that the aneuploid state of a cancer cell can be exploited in cancer therapy. RESULTS Identification of Compounds that Preferentially Antagonize the Proliferation of Aneuploid Cells To identify compounds that exhibit adverse synthetic interactions with the aneuploid state, we employed MEFs trisomic for chromosome 1, 13, 16, or 19. We generated these cells using mice that carry Robertsonian fusion chromosomes (Williams et al., 2008) and compared their drug response to that of littermate control cells that carry a Robertsonian chromosome but are euploid (note that these controls were included in all experiments described here). Chromosomes 1, 13, 16, and 19 were chosen because they cover a large portion of the size and coding spectrum of mouse chromosomes (Chr1, 197 Mbp and 1228 genes; Chr13, 120 Mbp and 843 genes; Chr16, 98 Mbp and 678 genes; and Chr19, 61 Mbp and 734 genes) (Williams et al., 2008). Because aneuploidy leads to cell proliferation defects as well as proteotoxic and energy stress (Torres et al., 2007; Williams et al., 2008; reviewed in Luo et al., 2009), we selected compounds with similar effects, with the rationale that further interference with pathways that are already impaired in aneuploids or are essential for their viability may lead to lethality. We tested compounds that cause genotoxic stress (aphidocolin, camptothecin, cisplatin, doxorubicin, and hydroxyurea; see Supplemental Information available online for effects of these compounds), proteotoxic stress (17-allylamino-17-demethoxygeldanamycin [17-AAG], cycloheximide, chloroquine, lactacystin, MG132, puromycin, and tunicamycin), and energy stress (5-aminoimidazole-4-carboxamide riboside [AICAR], compound C, 2-deoxyglucose, metformin, rapamycin, and torin1). Approximately 2 3 105 MEFs were plated into 6-well plates and, after 24 hr, were exposed to compound or vehicle alone. The effects on cell number were determined for 3 days. Because cell accumulation is impaired in trisomic cells even in the absence of treatment (Williams et al., 2008) (Figure 1A), cell number is presented as a percentage of cells observed in the absence of treatment. For a few compounds (e.g., aphidicolin), this percentage is greater in some trisomic cells than in euploid controls (Table S1). Though this indicates that trisomic cells tolerate the compound better than euploid cells, it is important to note that trisomic cells still grow significantly worse than euploid cells. 500 Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc.

The majority of compounds did not exhibit selectivity toward trisomic MEFs or did so for only a subset of the trisomies tested (Table S1). However three compounds—the energy stress inducer AICAR, the Hsp90 inhibitor 17-AAG, and the autophagy inhibitor chloroquine—impaired the accumulation of all four trisomic MEFs to a higher degree than that of euploid control cells (Table S1). AICAR is a cell-permeable precursor of ZMP (an AMP analog), which allosterically activates AMP-activated protein kinase (AMPK), thereby mimicking energy stress (Corton et al., 1995). AMPK is sensitive to the intracellular AMP:ATP ratio and upregulates catabolic pathways to produce more ATP and downregulates anabolic pathways to conserve energy charge (Hardie, 2007). AICAR significantly inhibited the accumulation of cells trisomic for the large chromosomes 1 and 13. Accumulation of cells carrying the gene-poorer chromosome 16 was less affected (Figure 1). Proliferation of cells trisomic for the smallest chromosome, chromosome 19, was only subtly inhibited by AICAR (Figure 1). Importantly, whereas euploid cells continued to proliferate in the presence of high concentration of AICAR (0.5 mM), cell numbers declined in all trisomic cultures (Figure 1A), indicating that AICAR in fact kills trisomic MEFs. Treatment of cells with metformin, a type 2 diabetes drug that also induces energy stress and activates AMPK (Canto´ et al., 2009), also impaired the accumulation of trisomy 13 and 16 cells in culture, although the effects were not as dramatic (Table S1 and Figure S1A). However, 2-deoxyglucose, which also causes AMPK activation (Figures S1B and S1C), did not show selectivity for trisomic cells (Figure S1D). In fact, 2-deoxyglucose was highly toxic even in euploid cells (Figure S1D). Why AICAR, metformin, and 2-deoxyglucose show different efficacy in trisomic MEFs, despite both causing AMPK activation, is at present unclear (see Discussion). 17-AAG inhibits the chaperone Hsp90. This chaperone together with others is needed for the folding, activation, and assembly of a specific set of client proteins (Young et al., 2001). 17-AAG inhibited proliferation of all aneuploid cells at a concentration of 100 nM (Figure 2A and Table S1). Furthermore, cells trisomic for the largest chromosome, Chr1, exhibited higher sensitivity to the compound than cells harboring an additional copy of the smaller chromosomes, Chr16 or 19. This finding suggests that aneuploid cells rely on protein quality control pathways for their survival, which is consistent with the finding that levels of the chaperone Hsp72 are increased in trisomic MEFs (Figure 5D). Chloroquine also induces proteotoxic stress because it inhibits late stages of autophagy, a homeostatic mechanism that is critical for the elimination of damaged proteins and organelles (Levine and Kroemer, 2008; Mizushima et al., 2008). Chloroquine preferentially inhibited the proliferation of trisomic MEFs, although the antiproliferative effects were not as dramatic as those caused by AICAR or 17-AAG. Similar results were obtained when autophagy was impaired by the knockdown of the autophagy factor Beclin 1 in trisomy 13 cells (Figure S1E). As observed for AICAR and 17-AAG, the increased sensitivity of trisomic cells correlated with the size of the additional chromosome (Figure 2B and Table S1). We conclude that interference with autophagy is detrimental in aneuploid MEFs, perhaps because aneuploid cells rely on autophagy to produce energy

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and/or reduce proteotoxic stress. Indeed, autophagy is increased in trisomic MEFs (Figures 5A–5C). Interestingly, the combined treatment of trisomic cells with AICAR and 17-AAG significantly impaired the proliferative abilities of trisomic MEFs but had little effect on euploid control cultures (Figure 2C). Similar results were obtained when cells were treated with a combination of AICAR and chloroquine (Figure 2D). We conclude that compounds exist that selectively inhibit the proliferation of trisomic MEFs. Their combined

AICAR, 17-AAG, and Chloroquine Induce Apoptosis in Trisomic MEFs To examine how AICAR, 17-AAG, and 0 0.2 0.5 chloroquine preferentially antagonize AICAR (mM) the proliferation of trisomic MEFs, we asked whether the compounds induce WT apoptosis in trisomic, but not euploid, Ts16 ** cells. At high dose, AICAR inhibits the ** proliferation of wild-type MEFs by inducing cell-cycle arrest and apoptosis (Jones et al., 2005) (Figure 3). At a concentration of 0.2 mM, AICAR did not induce apoptosis in wild-type cells, but 0.5 mM AICAR led to a 66% increase in early 0 0.2 0.5 apoptotic cells (Figures 3A and 3B). The AICAR (mM) effects of AICAR on trisomic cells were more dramatic. Apoptosis was not increased in untreated trisomic MEFs, WT Ts19 * but addition of 0.2 or 0.5 mM AICAR led * to a 2-fold increase in early apoptotic cells (Figures 3A and 3B). 17-AAG and chloroquine also induced apoptosis in trisomy 13 MEFs (Figure 3C). Is apoptosis the only antiproliferative effect of the identified compounds? We addressed this question for AICAR. We 0 0.2 0.5 did not detect substantial cell cycle AICAR (mM) delays in AICAR-treated trisomic MEFs (Figure S2A), although subtle cell cycle alterations cannot be excluded when examining unsynchronized cells. AICAR did not appear to induce premature senescence in trisomic MEFs either, as judged by the production of senescence-associated b-galactosidase (Figure S2B). Treatment of cells with necrostatin-1 (Nec-1), an inhibitor for necroptosis (Degterev et al., 2005), did not suppress the antiproliferative effects of AICAR either (Figure S2C). AICAR is known to inhibit the mTOR pathway (Sarbassov et al., 2005). Inhibition of the mTOR pathway either through treatment of cells with the mTOR kinase inhibitors rapamycin or torin1 or Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc. 501

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Figure 2. The Proteotoxic Compounds 17-AAG and Chloroquine Exaggerate the Antiproliferative Effects of AICAR (A and B) Wild-type (filled bars) and trisomic cells (open bars) were treated with the indicated concentrations of 17-AAG (A) or chloroquine (B), and cell number was determined after 3 days. (C and D) Cells were treated with 0.2 mM AICAR and the indicated concentrations of 17-AAG (C) or chloroquine (D). Cell number was determined after 3 days. The data are the mean of three independent experiments ± standard deviation. *p < 0.05; **p < 0.005; t test. See also Table S1 and Figure S1E.

through knockdown of mTOR neither inhibited the proliferation of trisomic MEFs nor enhanced the antiproliferative effects of AICAR (Figure S3). We conclude that AICAR treatment inhibits proliferation by increasing apoptosis in trisomic MEFs. 17-AAG and chloroquine have a similar effect, at least, in trisomy 13 cells. 502 Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc.

The Antiproliferative Effects of AICAR Are Mediated by AMPK and p53 How do AICAR, 17-AAG, and chloroquine induce apoptosis in trisomic MEFs? We addressed this question for AICAR. First, we tested whether AICAR antagonizes the proliferation of trisomic

MEFs by affecting AMPK. Knockdown of AMPK using short hairpins not only effectively lowered AMPK protein levels (Figure 4A), but also ameliorated the cell accumulation defect brought about by AICAR treatment (Figure 4B; note that the effects of AICAR treatment were assessed after only 24 hr in this experiment). Thus, its effects on control trisomic cells were not as dramatic as after 3 days, as is shown in Figure 1B). Inhibition of AMPK by other means had similar effects. Compound C is a pyrazolopyrimidine compound that functions as an ATP-competitive inhibitor of AMPK and other protein kinases (Bain et al., 2007). Treatment with compound C increased the proliferative abilities of trisomic cells (Figure 4C) and suppressed the adverse effects of AICAR (Figure 4D). AICAR thus inhibits the accumulation of trisomic MEFs, at least in part, by activating AMPK. The sensitivity of trisomic cells to AICAR could be due to hyperactivation of AMPK in trisomic, but not euploid, cells. To test this possibility, we measured AMPK activity in euploid and aneuploid MEFs in the presence or absence of AICAR. The basal activity of AMPK was not increased in untreated trisomic MEFs, as judged by in vitro AMPK kinase assays and phosphorylation of Threonine 172 on AMPK, a modification that is indicative of active AMPK (Lamia et al., 2009) (Figures 4E and 4F). AMPK activation occurred faster in aneuploid MEFs upon AICAR treatment (Figure 4G), but the degree of activation was similar in euploid and aneuploid MEFs 24 hr after AICAR addition (Figures 4E and 4F). We conclude that hyperactivation of AMPK is not responsible for the adverse effects of AICAR on trisomic MEFs. However, our results suggest that AMPK is activated more readily by AICAR in trisomic cells. Having established that the effects of AICAR on trisomic cells are, at least in part, mediated by AMPK activation, we next determined how this could lead to apoptosis. AMPK activates p53 through phosphorylation of Serine15 (Jones et al., 2005). We find that AICAR treatment subtly induced S15 phosphorylation and p53 stabilization in both wild-type and trisomy 13 MEFs (Figure 3D), but both events occurred significantly faster in trisomy 13 cells (Figure 3D). We also examined two p53 targets, the CDK inhibitor p21 and the proapoptotic protein Bax. p21 protein levels were not increased in response to AICAR treatment. In contrast, Bax activity was (Figures 3D and 3E). Bax integrates into the outer membrane of mitochondria, causing the activation of the apoptotic program (Vander Heiden and Thompson, 1999). AICAR treatment led to an increase in mitochondrially associated Bax in both wild-type and trisomy 13 cells, but the amount of Bax associated with this organelle fraction was higher in trisomy 13 cells (Figure 3E). These results suggest that p53 induces apoptosis in trisomic MEFs. Consistent with this idea, we find that p53 knockdown suppressed the antiproliferative effects of AICAR in trisomy 13 and 16 MEFs (Figures 3F and 3G). We conclude that the antiproliferative effects of AICAR in trisomic cells are, at least in part, mediated by p53-mediated apoptosis. 17-AAG and chloroquine-induced apoptosis also depend on this transcription factor, at least in trisomy 13 cells (Figure S4). AICAR Exaggerates the Cellular Stresses Caused by Aneuploidy AICAR treatment leads to increased p53-dependent apoptosis in trisomic, but not euploid, MEFs. However, other compounds

that induce p53-mediated apoptosis, i.e., genotoxic compounds, do not show this selectivity. This indicates that, in addition to inducing p53, AICAR must have other adverse effects on trisomic MEFs. The increased sensitivity of aneuploid cells to AICAR could be due to aneuploidy and AICAR affecting parallel pathways and/or due to AICAR exaggerating defects that are already present in trisomic MEFs. To test the latter possibility, we analyzed proteotoxic stress indicators in trisomic cells in the presence and absence of AICAR. In both aneuploid budding yeasts and MEFs, the majority of genes located on an additional chromosome are expressed (Pavelka et al., 2010; Torres et al., 2007, 2010; Williams et al., 2008). This observation, together with the finding that aneuploid yeast cells are sensitive to conditions that interfere with protein folding and turnover, led to the proposal that, in yeast, excess proteins that are produced by the additional chromosomes place stress on the cell’s protein quality control systems (Torres et al., 2007, 2010). To determine whether trisomic MEFs are under proteotoxic stress, we examined basal levels of autophagy and the Hsp72 chaperone in trisomic MEFs and their behavior in response to AICAR treatment. During autophagy, the autophagosomal membrane component LC3 is lipidated and incorporated into autophagosomal structures (Mizushima et al., 2008). In the absence of AICAR, trisomy 13 and 16 cells contained increased levels of LC3 mRNA and lipidated LC3 that was incorporated into autophagosomes (Figures 5A and 5C). Expression of Bnip3, a component of the autophagy machinery that is induced by many different stresses (Mizushima and Klionsky, 2007), was also increased in trisomy 13 and 16 MEFs (Figure 5B). AICAR treatment further induced Bnip3 expression as well as LC3 expression and LC3 incorporation into autophagosomes (Figures 5A–5C). Trisomic MEFs also harbor elevated levels of the inducible form of the chaperone Hsp72 (Figure 5D). AICAR treatment led to a further increase in Hsp72 levels in all but trisomy 16 cells in which Hsp72 levels were already very high (Figure 5D). Our results indicate that the activities of protein quality control pathways are elevated in aneuploid MEFs. They further show that AICAR enhances the proteotoxic stress present in aneuploid cells. We propose that this enhancement of the proteotoxic stress in trisomic cells contributes to the aneuploidy-selective antiproliferative effects of AICAR. AICAR and 17-AAG Inhibit the Proliferation of Primary MEFs with Decreased Chromosome Segregation Fidelity Having characterized the effects of AICAR, 17-AAG, and chloroquine on defined aneuploidies, the trisomic MEFs, we next wanted to determine whether the compounds also inhibit proliferation of MEFs in which aneuploidies are spontaneously generated due to increased chromosome missegregation. To this end, we tested the effects of AICAR and 17-AAG on primary MEFs with a compromised spindle assembly checkpoint (SAC). Partial inactivation of the SAC by impairing BUBR1 function using the hypomorphic Bub1bH/H allele or by expressing a checkpointresistant CDC20 allele (Cdc20AAA) causes chromosome missegregation and the accumulation of aneuploid cells in culture over time (Baker et al., 2004; Li et al., 2009). Primary MEFs Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc. 503

Control

A

104

AICAR 0.5mM

AICAR 0.2 mM

2.65

15.7

3.11

15.5

0.84

13.4

103

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102 67.8

67.3

62.7

101 13.9

Propidium iodide intensity

100

Ts1

104 10

1.61

14.1

19.7

2.29

23.1

16

1.67

21.3

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102 63.1

43.9

28

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15.6 101

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103

37.8

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49

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Annexin-V FITC intensity

% of apoptotic cells

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P-p53 * P-p53/actin

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Figure 3. AICAR, 17-AAG, and Chloroquine Induce Apoptosis in Trisomic MEFs (A) Wild-type (top) and trisomy 1 cells (bottom) were treated with AICAR for 24 hr, and apoptosis was measured using annexin V-FITC/ PI staining. Early apoptotic cells are found in the bottom-right quadrant. (B and C) Quantification of the percentage of annexin V-FITC-positive, PI-negative cells in wild-type, trisomy 1, and trisomy 13 cultures 24 hr after AICAR treatment (B) and in wild-type and trisomy 13 cultures 24 hr after 17-AAG or chloroquine treatment (C). (D) Wild-type and trisomy 13 cells were treated with 0.2 mM AICAR and p53 Serine 15 phosphorylation and p53 and p21 protein levels were analyzed. Quantifications of the ratio of phosphorylated p53/actin protein are shown under the P-p53 blot. The ratios were normalized to untreated wild-type cells. Asterisk denotes S15 phosphorylated p53.

504 Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc.

carrying these mutations were sensitive to 17-AAG and AICAR (Figures 6A and 6B). The effects were not as dramatic as in the trisomic MEFs, presumably because only 36% and 52% of the Bub1bH/H and Cdc20AAA MEFs are aneuploid after several passages, respectively (Baker et al., 2004; Li et al., 2009). Our results indicate that AICAR and 17-AAG also antagonize the proliferation of MEFs with decreased chromosome segregation fidelity. AICAR and 17-AAG Inhibit Proliferation of Aneuploid Human Cancer Cells A key question that arises from our findings is whether AICAR, 17-AAG, and chloroquine also show efficacy against aneuploid cancer cell lines. To address this question, we analyzed the effects of these compounds on the proliferative abilities of colorectal cancer cell lines with high-grade aneuploid karyotypes (CIN lines) and of colorectal cell lines with near-euploid karyotypes (MIN lines) (Cunningham et al., 2010). MIN (microsatellite instability) colorectal cancer lines (HCT-116, HCT-15, DLD-1, SW48, and LoVo) maintain a near-euploid karyotype (Bhattacharyya et al., 1994) (Figure 6C); CIN (chromosome instability) colorectal cell lines (Caco2, HT-29, SW403, SW480, and SW620) harbor between 50 and 100 chromosomes (Rajagopalan et al., 2003) (Figure 6C). Chloroquine did not affect CIN or MIN tumor cell line growth (Figure S5A), which is perhaps not surprising given the compound’s modest antiproliferative effects in trisomic MEFs. AICAR and 17-AAG showed greater growth inhibitory effects in CIN cell lines than in MIN cell lines or in euploid cell lines (CCD112 CoN and CCD841 CoN) (Figure 6C). Treating cells with both AICAR and 17-AAG had an even more significant differential effect (Figure 6C). We also examined the effects of AICAR, 17-AAG, and chloroquine on aneuploid lung cancer cell lines. As in colorectal cancer cell lines, chloroquine did not show a differential effect in lung cancer cell lines (Figure S5B). The effects of AICAR on lung cancer cell lines were modest. Of the eight aneuploid lung cancer lines examined (A549, NCI-H520, NCI-H838, NCI-H1563, NCI-H1792, NCI-H2122, NCI-H2170, and NCI-H2347), only a subset of cell lines exhibited sensitivity to AICAR (Figure 6D). However, all eight cell lines showed significant sensitivity toward 17-AAG. Furthermore, a slight additive effect between AICAR and 17-AAG at high concentrations of compound (0.2 mM AICAR + 200 nM 17-AAG) was observed (Figure 6D; p = 0.03). Interestingly, all aneuploid cancer cell lines exhibited increased sensitivity to AICAR and/or 17-AAG, irrespective of whether p53 was functional or not (Figures 6C and 6D; see Discussion). AICAR and 17-AAG also inhibited tumor cell growth in xenograft models. Two MIN (HCT15 and LoVo) and two CIN (HT29 and SW620) cell lines were injected into the flanks of immunocompromised mice and were then treated with AICAR,

17-AAG, or both compounds. Consistent with the cell culture analyses, the combination treatment was more effective in inhibiting CIN tumor growth than in preventing MIN tumor growth (Figures 7A and 7B). The reduced ability of CIN lines to form tumors could, in part, be due to increased apoptosis. The two CIN lines, but not the MIN lines, exhibited high levels of apoptosis when treated with AICAR or AICAR+17-AAG in culture (Figure 7C). Furthermore, as in trisomic MEFs, AICAR treatment induced the transcription of a number of autophagy genes in the two CIN (HT29 and SW620) cell lines, but not the two MIN (HCT15 and LoVo) cell lines, and increased the levels of the lipidated form of LC3 (Figure S6). Hsp72 levels were also higher in CIN lines, but AICAR did not cause a further increase in Hsp72 levels (Figure S6B). AICAR and 17-AAG most likely inhibit tumor cell growth in multiple ways. Our results raise the interesting possibility that one reason for their growth inhibitory effect is the aneuploid state of these cancer cells. DISCUSSION A Response to the Aneuploid State In yeast, aneuploidy causes cell proliferation defects and increased sensitivity to proteotoxic stress (Torres et al., 2007). The data presented here together with our previous analyses of trisomic MEFs (Williams et al., 2008) indicate that the consequences of aneuploidy in mouse cells are remarkably similar to those in yeast. Cell proliferation is impaired (Williams et al., 2008), and cells show signs of energy and proteotoxic stress (Williams et al., 2008 and this study). Cells take up more glutamine and are sensitive to the energy stress-causing compound AICAR. Autophagy and active Hsp72 are elevated in trisomic MEFs, and cells are sensitive to compounds that induce proteotoxic stress. It thus appears that the effects of aneuploidy on cell physiology are conserved across species. The findings described here also lend further support to our previous proposal (Torres et al., 2007; Williams et al., 2008) that cells respond to the aneuploid state by engaging protein quality control pathways in an attempt to correct protein stoichiometry imbalances caused by aneuploidy. Two recent studies showed that p53 is also part of this response (Li et al., 2010; Thompson and Compton, 2010). We did not detect elevated levels of active p53 in trisomic MEFs. We speculate that aneuploidy of a single chromosome is not sufficient to induce a p53 response. Single-Chromosome Gains as a Model for Aneuploidy in Cancer We have used single chromosome gains to study the effects of aneuploidy on cell physiology. But can this type of aneuploidy also shed light on the role of aneuploidy in tumorigenesis? Single chromosomal gains rarely occur in cancer. Instead, severe

(E) Wild-type and trisomy 13 cells were treated with 0.2 or 0.5 mM AICAR for 24 hr. Equal amounts of cytoplasmic or mitochondrial protein extracts were probed for the presence of Bax by immunoblotting. Mitochondrial Hsp60 served as loading control in mitochondrial extracts. Quantifications of the ratio of mitochondrial Bax/total Bax protein normalized to untreated wild-type cells are shown under the mitochondrial Bax blot. (F) p53 knockdown efficiency revealed by immunoblotting using an anti-p53 antibody. Actin serves as a loading control in western blots. (G) Cells were transfected with a p53 knockdown shRNA and treated with AICAR for 24 hr at the indicated doses. The data are the mean of three independent experiments ± standard deviation. *p < 0.05; **p < 0.005; t test. See also Figure S2, Figure S3, and Figure S4.

Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc. 505

AMPK

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PK PK c AM c AM Ve sh Ve sh

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Figure 4. AICAR Antagonizes Proliferation of Trisomic MEFs in an AMPK-Dependent Manner (A) AMPKa knockdown efficiency revealed by immunoblotting using an anti-AMPK antibody. (B) Cells infected with either empty vector or an AMPKa knockdown construct were counted 24 hr after AICAR treatment. (C) Wild-type (filled bars) and trisomic (open bars) cells were treated with the indicated concentrations of compound C for 3 days. Even though the effects of compound C were less severe in trisomic cells than in euploid controls, it is important to note that the treated trisomic cells grew poorly compared to euploid control cells. (D) Wild-type (filled bars) and trisomic cells (open bars) were treated with 0.5 mM AICAR and compound C at the indicated doses for 3 days, and cell number was counted. (E and F) AMPK activity was analyzed by determining the extent of threonine172 phosphorylation on AMPK (E) or by in vitro kinase assays using the substrate peptide IRS-1 S789 (F) in wild-type and trisomic cells after 24 hr of AICAR treatment. Quantifications of the ratio of phosphorylated AMPK/total AMPK protein normalized to untreated wild-type cells are shown under the P-AMPK blot. (G) AMPK activity was measured by in vitro kinase assays at the indicated time point following addition of 0.2 mM AICAR. The data are the mean of three independent experiments ± standard deviation. *p < 0.05; **p < 0.005; t test.

karyotypic abnormalities involving many chromosomes and often multiple copies of individual chromosomes are the norm. Despite this difference in degree of aneuploidy, we believe that 506 Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc.

single chromosome gains can speak to the role of aneuploidy in cancer for the following reasons. First, important features and traits of the aneuploid state can be deduced from the

AICAR (mM)

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inducible Hsp72 Hsp72/Hsp90 1 Hsp90 Figure 5. AICAR Exaggerates the Stressed State of Trisomic MEFs (A) Lipidated LC3-II was analyzed by immunoblotting in wild-type and trisomy 13 and 16 cells after 24 hr of AICAR treatment. Quantifications of the ratio of lipidated LC3II /actin protein normalized to untreated wild-type cells are shown under the LC3-II blot. (B) Quantitative RT-PCR analysis of mRNA abundance of the autophagy genes ATG1, ATG4, Beclin1, LC3, BNIP3, and GAPRAPL1. mRNA levels were quantified in untreated wild-type (black bars) and trisomic (white bars) cells as well as wild-type (gray bars) and trisomic (blue bars) cells treated with 0.5 mM AICAR for 24 hr. RNA levels were normalized to those of the ribosomal RPL19 gene. (C) The extent of autophagy was quantified by determining the number of LC3-GFP puncta in cells. Typical images are shown as examples for LC3-GFP puncta formation in trisomy 13 and 16 and wild-type cells after AICAR treatment (left). Incubation in HBSS induces acute starvation and served as a positive control. At 24 hr after AICAR treatment, the number of cells that harbor more than 4 LC3-GFP puncta was determined (right). The data are the mean of three independent experiments ± standard deviation. *p < 0.05; **p < 0.005; t test. (D) Wild-type and trisomic MEFs were treated with AICAR at the indicated doses, and levels of inducible Hsp72 were determined by immunoblotting. Quantifications of the ratio of inducible Hsp72/Hsp90 protein normalized to untreated wild-type cells are shown underneath the Hsp72 blot.

analysis of multiple single chromosomal abnormalities because phenotypes shared by cells carrying different single additional chromosomes will also exist in cells with multiple chromosomal abnormalities. In fact, the protein stoichiometry imbalances caused by aneuploidy and the proteotoxic and energy stresses that these imbalances elicit will, if anything, be more pronounced in cells with multiple numeric chromosomal abnormalities. Second, in some cancers, premalignant lesions or low-grade tumors show limited chromosomal gains or losses. For example,

small adenomas and atypical ductal hyperplastic lesions show a low degree of loss of heterozygosity (Larson et al., 2006; Shih et al., 2001). The study of single chromosomal abnormalities could therefore provide important insights into the early stages of tumorigenesis. Finally, the compounds that we discovered to inhibit the proliferation of trisomic MEFs also showed efficacy against aneuploid human cancer cell lines, suggesting that the trisomy system can be employed to reveal features of aneuploid tumor cells. Cell 144, 499–512, February 18, 2011 ª2011 Elsevier Inc. 507

A Relative cell number

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0.5

NS A change at position 754 from the START codon, resulting in the early termination generate a temperature reading and trigger the appropriate W205 > STOP. The temperature preference phenotype of each mutant was behavioral responses. Alternatively, the ‘‘preferred temperature’’ also tested in trans to a deletion uncovering the region (Df(3L)Exel9007 for might be a default state, in essence a point (or temperature brv1 and Df(3L)Exel6131 for brv2) and was indistinguishable from that of range) defined by the independent activity of two labeled lines homozygous mutants (Figure S1 and data not shown): we conclude that these each mediating behavioral aversion to temperatures above or alleles are likely null or strong loss of function mutations. The brv2 rescue below this point (in this case temperatures below 21 C and construct was produced by cloning a 4 Kb genomic fragment including the brv2 coding region into a modified pCasper vector. The hot-cell Gal4 driver above 28 C). This push-push mechanism would de-mark the line was identified from a collection covering a wide range of candidates with boundaries of the non-aversive (i.e., preferred) temperature expression in the antennae (Hayashi et al., 2002); flybase.org; pubmed.org). range, and thus provide a very robust mechanism for transform- To restrict expression of CD8:GFP and TeNT to antennal neurons ing temperature signals into a simple behavioral choice. This expressing NP4486, we used the following intersectional strategy: eyFLP is Cell 144, 614–624, February 18, 2011 ª2011 Elsevier Inc. 621

active in the antenna (and in the retina), but not in the brain. tubP-FRT > Gal80 > FRT drives expression of the Gal4 inhibitor Gal80 ubiquitously, effectively silencing NP4486-Gal4 mediated expression of the transgenes. Only in the antenna, where eyFLP is active, the FRT > Gal80 > FRT cassette is excised and lost, allowing Gal4-mediated expression. This effectively limits transgene expression to the cells in which both eyFLP and NP4486 are active. Behavioral Assays All assays were carried out in a room kept at 24 C, 40% RH. The temperature gradient arena has been previously described (Sayeed and Benzer, 1996) (Figure S1). For two choice assays (Figure 1 and Figure 6) 15 flies are placed on an arena consisting of four 1’’ square, individually addressable Peltier tiles (Oven Industries Inc.). In each trial, flies are presented for 30 with a choice between 25 C and a test temperature between 11 and 39 C at 2 C intervals (15 trials total). The position of flies is monitored during each trial to calculate an avoidance index for each test temperature. The avoidance index is defined as (AI = #flies at 25 C - #flies at test temp) / total # flies. AI values were compared using t tests (Figures S1A and S1B) or by 2-way ANOVA followed by Bonferroni post-tests when comparing more than 2 groups (Figure 1, Figure S1, and Figure 6). Kolmogorov-Smirnov tests where used to confirm a normally distributed sample. Threshold p = 0.05. Constant variance of the datasets was also confirmed by computing the Spearman rank correlation between the absolute values of the residuals and the observed value of the dependent variable, by SigmaPlot). In Situ Hybridization and Immunohistochemistry Fluorescent in situ hybridization was carried out as in (Benton et al., 2006) with a brv1 digoxigenin-labeled RNA probe visualized with sheep anti-digoxigenin (Boehringer), followed by donkey anti-sheep Cy3 (Jackson). We were unable to detect brv2 or brv3 expression by ISH. Immunohistochemistry was performed using standard protocols. Real-Time PCR Quantitative PCR was carried out in quintuplicates using Brilliant SYBR Green PCR Master Mix (Stratagene) on a StepOnePlus real-time PCR system (Applied Biosystems) using brv3 specific primers. Beta-actin served as the endogenous normalization control. Live Imaging and Two-Photon Microscopy Confocal Images were obtained using a Zeiss LSM510 confocal microscope with an argon-krypton laser. For live imaging through the cuticle, intact heads or whole flies where mounted within a custom-built perfusion chamber covered with a coverslip and imaged through a water-immersion 40X Zeiss objective and a EM-CCD camera (Photonmax, Princeton Instruments). Image series were acquired at 10 frames per second and analyzed using ImageJ and a custom macro written in Igor Pro (Wavemetrics). To image the responses of cold receptor neurons in brv1 and -2 mutant backgrounds (Figure 2), G-CaMP was expressed in all aristal neurons (under elav-Gal4) in controls (backgroundmatched) and mutant animals. At the beginning of each experiment, a set of defined hot and cold stimuli (Dt3 C) was delivered while imaging on different focal planes to identify the 3 hot and 3 cold cells in each arista (note that the G-CaMP responses of hot cells -including inhibition to cold stimuli- remain normal in brv1 and -2 backgrounds). The most optically accessible cold receptor cell in each arista was then imaged responding to various cold stimuli. A maximum of 5 stimuli of different intensities was recorded for each preparation. For two-photon microscopy, we built a customized system based on a Movable Objective Microscope (MOM) from Sutter (Sutter Inc.) in combination with a ultrafast Ti:Sapphire laser from Coherent (Chameleon). Live imaging experiments were captured at four frames per second with a resolution of 128 3 128 pixels. Analysis of imaging data and DF/F calculations were performed using Igor Pro and a custom macro as in (Wang et al., 2003). For live imaging of PAP projections, fly heads where immobilized in a custom built perfusion chamber. Sufficient head cuticle and connective tissue was removed to allow optical access to the PAP. Temperature stimulation was achieved by controlling the temperature of the medium, constantly flowing

622 Cell 144, 614–624, February 18, 2011 ª2011 Elsevier Inc.

over the preparation at 5ml/min, by a custom-built system of 3 way valves (Lee Instruments, response time 2ms). In all experiments, heating or cooling was at 1 C/sec. Temperature was recorded using a BAT-12 electronic thermometer equipped with a custom microprobe (time constant .004 s, accuracy 0.01 C, Physitemp).

SUPPLEMENTAL INFORMATION Supplemental Information includes Extended Experimental Procedures and five figures and can be found with this article online at doi:10.1016/j.cell. 2011.01.028. ACKNOWLEDGMENTS We thank Cahir O’Kane for UAS-TeNT flies; Paul Garrity for dTRPA1KO flies; and especially Michael Reiser for invaluable help with designing and implementing the behavioral arenas and assays. We also thank David Julius and Avi Priel for their help and kindness hosting us (M.G.) in our efforts to express Brv channels in Xenopus oocytes. Wilson Kwan, George Gallardo, and Lisa Ha provided expert help with fly husbandry. We are grateful to Hojoon Lee, Dimitri Trankner, and Robert Barretto for help with experiments and data analysis; and Nick Ryba, Michael Reiser, and members of the Zuker lab for critical comments on the manuscript. We also thank Kevin Moses, Gerry Rubin, and the Janelia Farm Visitor Program. M.G. was supported by a Wenner-Grens Stiftelse and a Human Frontiers Science Program long term fellowship. L.J.M. is a fellow of the Jane Coffin Childs Foundation. C.S.Z. is an investigator of the Howard Hughes Medical Institute and a Senior Fellow at Janelia Farm Research Campus. Author contributions: M.G. and C.S.Z. conceived all the experiments and wrote the paper. M.G. performed all the experiments presented in this paper, except the in situ hybridizations (T.A.O.). T.A.O. also helped with the set up for 2-choice behavioral assays, and J.W.W. helped design and setup the custom imaging system. L.J.M., M.G., and T.A.O. carried out extensive efforts to heterologously express Brv channels (data not shown). Received: February 17, 2010 Revised: November 3, 2010 Accepted: January 24, 2011 Published: February 17, 2011 REFERENCES Altner, H., and Loftus, R. (1985). Ultrastructure and Function of Insect Thermo- And Hygroreceptors doi:10.1146/annurev.en.30.010185.001421. Annual Review of Entomology 30, 273-295. Basbaum, A.I., Bautista, D.M., Scherrer, G., and Julius, D. (2009). Cellular and molecular mechanisms of pain. Cell 139, 267–284. Bateman, A., Birney, E., Durbin, R., Eddy, S.R., Howe, K.L., and Sonnhammer, E.L. (2000). The Pfam protein families database. Nucleic Acids Res. 28, 263–266. Bautista, D.M., Siemens, J., Glazer, J.M., Tsuruda, P.R., Basbaum, A.I., Stucky, C.L., Jordt, S.E., and Julius, D. (2007). The menthol receptor TRPM8 is the principal detector of environmental cold. Nature 448, 204–208. Benton, R., Sachse, S., Michnick, S.W., and Vosshall, L.B. (2006). Atypical membrane topology and heteromeric function of Drosophila odorant receptors in vivo. PLoS Biol. 4, e20. Buchner, E., Bader, R., Buchner, S., Cox, J., Emson, P.C., Flory, E., Heizmann, C.W., Hemm, S., Hofbauer, A., and Oertel, W.H. (1988). Cell-specific immunoprobes for the brain of normal and mutant Drosophila melanogaster. I. Wildtype visual system. Cell Tissue Res. 253, 357–370. Caterina, M.J., Leffler, A., Malmberg, A.B., Martin, W.J., Trafton, J., PetersenZeitz, K.R., Koltzenburg, M., Basbaum, A.I., and Julius, D. (2000). Impaired nociception and pain sensation in mice lacking the capsaicin receptor. Science 288, 306–313.

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ATPase

DNA binding

PHD

ATPase

ATPase BRK

SANT

Subfamily III: CHD6-9

PHD domain 2 modeled with H3 peptide

Chromo

Subfamily II: CHD3-5/Mi-2

Chromo domain cocrystalized with H3K4me3 peptide

Chromo

Subfamily I: CHD1/CHD2

General structure of CHD family

CHD9

CHD6/7/8

CHD5

dMec

NuRD

CHD2

CHD1

CHD6/7/8

KIS-L

HUMAN

WDR5

Unknown

Ash2L

RbBp5 CHD8

PBAF CHD7 complex

PARP1

CHD6-2-3MDa complex

F LY

RbAp46/48

p66
/ CHD3/4 HDAC1/2 MBD2/3

MTA1/2/3

HUMAN

Monomer

Monomer

HUMAN

Unknown

dMep1

dMBD2/3

dMTA

Monomer

Monomer

F LY

Unknown

dMi2

p55 dMi2

dRPD3

p66/68

F LY

CHD1

SAGA/SLIK complex

YEAST

Complex members

Jennifer K. Sims and Paul A. Wade Laboratory of Molecular Carcinogenesis, NIEHS, Research Triangle Park, NC 27709, USA

CHD1

ATP ADP+P i

NAP1 Core histones

Chromatin assembly

CHD1

ATP ADP+P i

Nucleosome spacing

Remodeling mechanisms/biological functions

CHD9: Regulates gene expression in osteoblasts

CHD8: Implicated in expression of small RNAs and of genes regulated by -catenin; represses p53 functions

CHD7: Mutated in CHARGE syndrome; preferentially binds to distal regulatory elements

CHD6: Localizes to sites of transcription and is induced by DNA damage

Mechanism unknown

CHD5: Potential tumor suppressor in breast, colon, and neuroectodermal cancers

CHD3/4

ATP ADP+P i

Nucleosome sliding

CHD2: Roles in mammalian development, DNA damage responses, and tumor suppression

CHD1: Maintenance of mouse embryonic stem cells

SnapShot: Chromatin Remodeling: CHD

PHD

Chromo

Chromo

DOI 10.1016/j.cell.2011.02.019

Chromo

Cell 144, February 18, 2011 ©2011 Elsevier Inc.

Chromo

626

See online version for legend and references.

Metabolism & Aging March 27-29, 2011 Cape Cod, Massachusetts, USA

Conference Organizers Prof. David A. Sinclair, Harvard Medical School, Boston, USA Dr. Nir Barzilai, M.D., Albert Einstein College of Medicine, New York, USA Dr. C. Ronald Kahn, Joslin Diabetes Center at Harvard Medical School, Boston, USA Speakers Domenico Accilli, Columbia University, NY, USA Adam Antebi, Max Planck Institute for Biology of Ageing, Germany Dongsheng Cai, Albert Einstein College of Medicine, NY, USA Hassy Cohen, UC Los Angeles, CA, USA Jill Crandall, Albert Einstein College of Medicine, NY, USA Rafael de Cabo, National Institute of Health, MD, USA Andy Dillin, Salk Institute For Biological Studies, CA, USA David J. Glass, Novartis Institutes for BioMedical Research, MA, USA Leonard Guarente, Massachusetts Institute of Technology, MA, USA Pankaj Kapahi, The Buck Institute for Age Research, CA, USA Brian Kennedy, University of Washington, WA, USA James Kirkland, Mayo Clinic, MN, USA Valter D. Longo, UC San Francisco, CA, USA Jim Nelson, UT Health Science Center, TX, USA Eric Ravussin, Pennington Biomedical Research Center, LA, USA Arlan Richardson, UT Health Science Center, TX, USA Randy Strong, UT Health Science Center, TX, USA Marc Tatar, Brown University, RI, USA Heidi Tissenbaum, University of Massachusetts Medical School, MA, USA Eric Verdin, UC San Francisco, CA, USA

The first Cell Symposia meeting of 2011, Metabolism & Aging takes place on March 27 – 29 in the beautiful Cape Cod peninsula at the southern tip of Massachusetts, USA. This meeting aims to bring together scientists with interests in aging and metabolism to further explore how these fields intersect and to identify the most promising future directions. We will hear the latest data from leaders in the field about the key pathways at the level of the cell and the organ, across a range of contexts including model organisms, mammalian systems, and translational studies in primates and humans. Topics will also include how the signalling networks of metabolism and aging connect and communicate and how we can best make use of these connections to improve medicine and society.

Visit the Metabolism & Aging website to: REGISTER

Supporting publications

Submit your poster abstract Study the final programme View our speakers biographies

www.cell-symposia-metabolism-aging.com

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