Biology subjects

Novak, B.

Publications and source records attributed to Novak, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Lipoproteins modulate the uptake and biological functionof cationic cell-penetrating peptides across the animal lineage.

Cationic cell-penetrating peptides (+CPPs) are pervasive killer peptides produced by all animals and found in innate immune systems, venoms and neurodegenerative diseases. Despite their ubiquity, the mechanisms underlying their uptake remain opaque and intensely debated. Here, we interrogate +CPPs spanning 600 million years of animal evolution and identify endocytosis as a conserved/convergent uptake mechanism across cell types and organisms, at physiological concentrations. By combining multiplex imaging, genetic screening, cryo-electron tomography, and biophysical methods, we uncover that +CPPs seemingly universally enter eukaryote cells via 'hitchhiking' on lipoproteins. We further show that the interaction of +CPPs with lipoproteins modulates their antimicrobial function. Combined, our findings establish a unified molecular framework describing a pan-eukaryote cell penetrance mechanism. As hyperlipidemia is a common comorbidity, our findings have direct implications for human health. Lastly, the insights gleaned from this work highlight design principles that may inform the future engineering of peptide-based therapeutics and delivery vehicles.

cell biology↗

bioRxiv2025

Wee1 opposes APC/C(Cdh1) activity to promote S-phase entry

Wee1 phosphorylates and inhibits CDK activity to inhibit mitotic entry and establish a G2 DNA damage checkpoint. Consequently, Wee1 inhibitors are in clinical trials, developed to be synthetically lethal in TP53 mutant tumours that become reliant on a Wee1-mediated DNA damage checkpoint. However, Wee1 inhibitors have efficacy in TP53 wild-type tumours and many trials have been terminated due to high levels of toxic side-effects, suggesting that Wee1 has unknown functions. Here, we show that Wee1 promotes cell cycle re-entry from quiescence (G0) by opposing the activity of the E3 ubiquitin ligase, APC/CCdh1. Wee1 phosphorylates Cdh1 (FZR1) at key residues that mediate the interaction between Cdh1 and APC/C. Cells with loss-of-function of Wee1 during G0/G1 have delayed S-phase entry, an impaired G1/S transition, abnormal S-phase accumulation of the CDK inhibitor p21 and enter a p21-dependent G2 arrest. Reduced expression of APC/CCdh1 or p21 renders cells more sensitive to acute Wee1 inhibition and both pathways are downregulated in acquired Wee1 inhibitor resistance. Our study reveals a new cell cycle control mechanism that has implications for how Wee1 inhibitors should be used in the clinic.

cell biology↗

bioRxiv2025

Regulation of cell proliferation by a novel feedback system on Cdk function

The proliferation of eukaryotic cells is regulated by a complex network of regulatory systems that promotes efficient cell cycle progression and ensures proper responses to the environment. Despite this complexity, the core inputs that are necessary and sufficient for robust alternation of DNA replication and mitosis are surprisingly simpler than anticipated. Indeed, fission yeast cells operating with an engineered minimal cell cycle network that lacks the highly conserved Wee1+Cdc25 feedback loops on Cdk1 function are viable, although slow growing. This provides a unique entry for evaluating how such simplified cells can evolve and improve their proliferation potential while exploring unknown mechanisms modulating cell cycle progression. Taking advantage of this model, we applied laboratory evolution assays to minimal fission yeast backgrounds and selected for the emergence of faster growing populations. We found that loss of the small disordered protein Spo12 brings about enhanced population growth in cells lacking the Wee1+Cdc25 mitotic switch. Importantly, we demonstrate that Spo12 defines a new and conserved family of inhibitors of the Cdk-counteracting phosphatase PP2A that are directly regulated by Cdk-dependent phosphorylation. Our results also reveal a trade-off associated with Spo12-dependent regulation, which may have implications for our understanding of the principles underlying the evolution of cell cycle control. Finally, our study highlights how combining simplified circuits with experimental evolution allows for uncovering regulatory elements that may be obscured by network complexity.

cell biology↗

bioRxiv2025

Accurate predictions of conformational ensembles of disordered proteins with STARLING

Intrinsically disordered proteins and regions (collectively IDRs) are found across all kingdoms of life and play critical roles in virtually every eukaryotic cellular process. In contrast to folded proteins, IDRs lack a stable 3D structure and are instead described in terms of a conformational ensemble, a collection of energetically accessible interconverting structures. This unique structural plasticity facilitates diverse molecular recognition and function; thus, a convenient way to view IDRs is through their ensembles. Here, we combine advances in physics-based force fields for IDPs with the power of modern multi-scale generative modeling to develop STARLING, an approach for the rapid and accurate prediction of IDR ensembles directly from sequence. STARLING enables ensembles of hundreds of conformers to be generated in seconds and works on GPUs and CPUs. This, in turn, dramatically lowers the barrier to the computational interrogation of IDR function through the lens of emergent biophysical properties complementing bioinformatic protein sequence analysis. We evaluate STARLINGs accuracy against extant experimental data and offer a series of vignettes illustrating how STARLING can enable rapid hypothesis generation for IDR function and aid the interpretation of experimental data.

biophysics↗

bioRxiv2024

High-throughput affinity measurements of direct interactions between activation domains and co-activators

Sequence-specific activation by transcription factors is essential for gene regulation1,2. Key to this are activation domains, which often fall within disordered regions of transcription factors3,4 and recruit co-activators to initiate transcription5. These interactions are difficult to characterize via most experimental techniques because they are typically weak and transient6,7. Consequently, we know very little about whether these interactions are promiscuous or specific, the mechanisms of binding, and how these interactions tune the strength of gene activation. To address these questions, we developed a microfluidic platform for expression and purification of hundreds of activation domains in parallel followed by direct measurement of co-activator binding affinities (STAMMPPING, for Simultaneous Trapping of Affinity Measurements via a Microfluidic Protein-Protein INteraction Generator). By applying STAMMPPING to quantify direct interactions between eight co-activators and 204 human activation domains (>1,500 Kds), we provide the first quantitative map of these interactions and reveal 334 novel binding pairs. We find that the metazoan-specific co-activator P300 directly binds >100 activation domains, potentially explaining its widespread recruitment across the genome to influence transcriptional activation. Despite sharing similar molecular properties (e.g. enrichment of negative and hydrophobic residues), activation domains utilize distinct biophysical properties to recruit certain co-activator domains. Co-activator domain affinity and occupancy are well-predicted by analytical models that account for multivalency, and in vitro affinities quantitatively predict activation in cells with an ultrasensitive response. Not only do our results demonstrate the ability to measure affinities between even weak protein-protein interactions in high throughput, but they also provide a necessary resource of over 1,500 activation domain/co-activator affinities which lays the foundation for understanding the molecular basis of transcriptional activation.

biophysics↗

bioRxiv2024

Newton's Cradle: Cell Cycle Regulation by Two Mutually Inhibitory Oscillators

The cell division cycle is a fundamental physiological process displaying a great degree of plasticity during the course of multicellular development. This plasticity is evident in the transition from rapid and stringently-timed divisions of the early embryo to subsequent size-controlled mitotic cycles. Later in development, cells may pause and restart cell proliferation in response to myriads of internal or external signals, or permanently exit the cell cycle following terminal differentiation or senescence. Beyond this, cells can undergo modified cell division variants, such as endoreplication, which increases their ploidy, or meiosis, which reduces their ploidy. This wealth of behaviours has led to numerous conceptual analogies intended as frameworks for understanding the proliferative program. Here, we aim to unify these mechanisms under one dynamical paradigm. To this end, we take a control theoretical approach to frame the cell cycle as a pair of arrestable and mutually-inhibiting, doubly amplified, negative feedback oscillators controlling chromosome replication and segregation events, respectively. Under appropriate conditions, this framework can reproduce fixed-period oscillations, checkpoint arrests of variable duration, and endocycles. Subsequently, we use phase plane and bifurcation analysis to explain the dynamical basis of these properties. Then, using a physiologically realistic, biochemical model, we show that the very same regulatory structure underpins the diverse functions of the cell cycle control network. We conclude that Newtons cradle may be a suitable mechanical analogy of how the cell cycle is regulated. Declaration of interestThe authors declare no competing or financial interests.

systems biology↗

bioRxiv2024

The bistable mitotic switch in fission yeast

In most situations, eukaryotic cells proceed irreversibly through the cell division cycle (G1-S-G2-M) in order to produce two daughter cells with the same number and identity of chromosomes of their progenitor. The integrity of this process is maintained by checkpoints that hold a cell at particular transition points of the cycle until all requisite events are completed. The crucial functions of these checkpoints seem to depend on irreversible bistability of the underlying checkpoint control systems. Bistability of cell cycle transitions has been confirmed experimentally in frog egg extracts, in budding yeast cells and in mammalian cells. For fission yeast cells, a recent paper by Patterson et al. (1) provides experimental evidence for an abrupt transition from G2 phase into mitosis, and we show that these data are consistent with a stochastic model of a bistable switch governing the G2/M checkpoint. Interestingly, our model suggests that their experimental data could also be explained by a reversible/sigmoidal switch, and stochastic simulations confirm this supposition. We propose a simple modification of their experimental protocol that could provide convincing evidence for (or against) bistability of the G2/M transition in fission yeast.

systems biology↗

bioRxiv2023

POPSHIFT: A THERMODYNAMICALLY SOUND APPROACH TO ESTIMATE BINDING FREE ENERGIES BY ACCOUNTING FOR LIGAND-INDUCED POPULATION SHIFTS FROM A LIGAND-FREE MSM

Obtaining accurate binding free energies from in silico screens has been a longstanding goal for the computational chemistry community. However, accuracy and computational cost are at odds with one another, limiting the utility of methods that perform this type of calculation. Many methods achieve massive scale by explicitly or implicitly assuming that the target protein adopts a single structure, or undergoes limited fluctuations around that structure, to minimize computational cost. Others simulate each protein-ligand complex of interest, accepting lower throughput in exchange for better predictions of binding affinities. Here, we present the PopShift framework for accounting for the ensemble of structures a protein adopts and their relative probabilities. Protein degrees of freedom are enumerated once, and then arbitrarily many molecules can be screened against this ensemble. Specifically, we use Markov state models (MSMs) as a compressed representation of a proteins thermodynamic ensemble. We start with a ligand-free MSM and then calculate how addition of a ligand shifts the populations of each protein conformational state based on the strength of the interaction between that protein conformation and the ligand. In this work we use docking to estimate the affinity between a given protein structure and ligand, but any estimator of binding affinities could be used in the PopShift framework. We test PopShift on the classic benchmark pocket T4 Lysozyme L99A. We find that PopShift is more accurate than common strategies, such as docking to a single structure and traditional ensemble docking--producing results that compare favorably with alchemical binding free energy calculations in terms of RMSE but not correlation--and may have a more favorable computational cost profile in some applications. In addition to predicting binding free energies and ligand poses, PopShift also provides insight into how the probability of different protein structures is shifted upon addition of various concentrations of ligand, providing a platform for predicting affinities and allosteric effects of ligand binding. Therefore, we expect PopShift will be valuable for hit finding and for providing insight into phenomena like allostery.

biophysics↗

bioRxiv2023

The oscillation of mitotic kinase governs cell cycle latches in mammalian cells

The mammalian cell cycle alternates between two phases: S-G2-M with high levels of A- and B-type cyclin-dependent kinases (CycA,B:CDK); and G1 with persistent degradation of CycA,B by Cdh1-activated APC/C (anaphase promoting complex/cyclosome). Because CDKs phosphorylate and inactivate Cdh1, these two phases are mutually exclusive. This toggle switch is flipped from G1 to S by cyclin-E (CycE:CDK), which is not degraded by Cdh1:APC/C; and from M to G1 by Cdc20:APC/C, which is not inactivated by CycA,B:CDK. After flipping the switch, cyclin E is degraded and Cdc20:APC/C is inactivated. Combining mathematical modelling with single-cell timelapse imaging, we show that dysregulation of CycB:CDK disrupts strict alternation of the G1-S and M-G1 switches. Inhibition of CycB:CDK results in Cdc20-independent Cdh1 endocycles, and sustained activity of CycB:CDK drives Cdh1-independent Cdc20 endocycles. Our model provides one mechanistic explanation for how whole genome doubling can arise, a common event in tumorigenesis that can drive tumour evolution.

systems biology↗

bioRxiv2023

Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells

The mammalian cell cycle is regulated by a well-studied but complex biochemical reaction system. Computational models provide a particularly systematic and systemic description of the mechanisms governing mammalian cell cycle control. By combining both state-of-the-art multiplexed experimental methods and powerful computational tools, this work aims at improving on these models along four dimensions: model structure, validation data, validation methodology and model reusability. We developed a comprehensive model structure of the full cell cycle that qualitatively explains the behaviour of human retinal pigment epithelial-1 cells. To estimate the model parameters, time courses of eight cell cycle regulators in two compartments were reconstructed from single cell snapshot measurements. After optimisation with a parallel global optimisation metaheuristic we obtained excellent agreements between simulations and measurements. The PEtab specification of the optimisation problem facilitates reuse of model, data and/or optimisation results. Future perturbation experiments will improve parameter identifiability and allow for testing model predictive power. Such a predictive model may aid in drug discovery for cell cycle-related disorders. Author SummaryWhile there are numerous cell cycle models in the literature, mammalian cell cycle models typically suffer from four limitations. Firstly, the descriptions of biological mechanisms are often overly complicated yet insufficiently comprehensive and detailed. Secondly, there is a lack of experimental data to validate the model. Thirdly, inadequate parameter estimation procedures are used. Lastly, there is no standardized description of the model and/or optimization problem. To overcome these limitations, we combine best-in-class technology to address all four simultaneously. We use a rule-based model description to provide a concise and less error-prone representation of complex biology. By applying trajectory reconstruction algorithms to existing data from highly multiplexed immunofluorescence measurements, we obtained a rich dataset for model validation. Using a parallel global metaheuristic for parameter estimation allowed us to bring simulations and data in very good agreement. To maximize reproducibility and reusability of our work, the results are available in three popular formats: BioNetGen, SBML, and PEtab. Our model is generalizable to many healthy and transformed cell types. The PEtab specification of the optimization problem makes it straightforward to re-optimize the parameters for other cell lines. This may guide hypotheses on cell type-specific regulation of the cell cycle, potentially with clinical relevance.

systems biology↗

bioRxiv2022

Drug specificity and affinity are encoded in the probability of cryptic pocket opening in myosin motor domains

The design of compounds that can discriminate between closely related target proteins remains a central challenge in drug discovery. Specific therapeutics targeting the highly conserved myosin motor family are urgently needed as mutations in at least 6 of its members cause numerous diseases. Allosteric modulators, like the myosin-II inhibitor blebbistatin, are a promising means to achieve specificity. However, it remains unclear why blebbistatin inhibits myosin-II motors with different potencies given that it binds at a highly conserved pocket that is always closed in blebbistatin-free experimental structures. We hypothesized that the probability of pocket opening is an important determinant of the potency of compounds like blebbistatin. To test this hypothesis, we used Markov state models (MSMs) built from over 2 milliseconds of aggregate molecular dynamics simulations with explicit solvent. We find that blebbistatins binding pocket readily opens in simulations of blebbistatin-sensitive myosin isoforms. Comparing these conformational ensembles reveals that the probability of pocket opening correctly identifies which isoforms are most sensitive to blebbistatin inhibition and that docking against MSMs quantitatively predicts blebbistatin binding affinities (R2=0.82). To test our ability to make blind predictions, we predicted blebbistatins binding affinity for an isoform (Myh7b) whose blebbistatin sensitivity was unknown. Encouragingly, we find good agreement between the predicted and measured IC50 (0.67 {micro}M vs. 0.36 {micro}M). Therefore, we expect this framework to be useful for the development of novel specific drugs across numerous protein targets. SignificanceDrug development requires the discovery of compounds which specifically target one member of a protein family without triggering side effects that arise from interactions with other related proteins. Myosins are a family of motor proteins that are drug targets for heart diseases, cancer, and parasitic infections. Here, we investigate why the compound blebbistatin specifically inhibits some myosins more potently than others, even though its binding site is closed in all known experimental structures. We find that the blebbistatin binding pocket opens in molecular dynamics simulations of certain myosin motors, and that the probability of opening predicts how potently blebbistatin inhibits a particular motor. Our work suggests that differences in cryptic pocket formation can be exploited to develop specific therapeutics.

biophysics↗

bioRxiv2021

The oscillation of mitotic kinase governs cell cycle latches

In order to transmit a eukaryotic cells genome accurately from mother cell to daughter cells, it is essential that the basic events of the cell division cycle (DNA synthesis and mitosis) occur once and only once per cycle, i.e., that a cell progresses irreversibly from G1 to S to G2 to M and back to G1. Irreversible progression through the cell cycle is assured by a sequence of latching molecular switches, based on molecular interactions among cyclin-dependent kinases and their auxiliary partners. Positive feedback loops (++ or --) create bistable switches with latching properties, and negative feedback loops drive progression from one stage to the next. In budding yeast (Saccharomyces cerevisiae) these events are coordinated by double-negative feedback loops between Clb-dependent kinases (Clb1-6) and their antagonists (APC:Cdh1 and Sic1). If the coordinating signal is compromised, either by deletion of Clb1-5 proteins or expression of non-degradable Clb2, then irreversibility is lost and yeast cells exhibit multiple rounds of DNA replication or mitotic exit events (Cdc14 endocycles). Using mathematical modelling of a stripped-down control network, we show how endocycles arise because the switches fail to latch, and the gates swing back and forth by the action of the negative feedback loops.

systems biology↗

bioRxiv2020

SARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential

Coronaviruses have caused multiple epidemics in the past two decades, in addition to the current COVID-19 pandemic that is severely damaging global health and the economy. Coronaviruses employ between twenty and thirty proteins to carry out their viral replication cycle including infection, immune evasion, and replication. Among these, nonstructural protein 16 (Nsp16), a 2-O-methyltransferase, plays an essential role in immune evasion. Nsp16 achieves this by mimicking its human homolog, CMTr1, which methylates mRNA to enhance translation efficiency and distinguish self from other. Unlike human CMTr1, Nsp16 requires a binding partner, Nsp10, to activate its enzymatic activity. The requirement of this binding partner presents two questions that we investigate in this manuscript. First, how does Nsp10 activate Nsp16? While experimentally-derived structures of the active Nsp16/Nsp10 complex exist, structures of inactive, monomeric Nsp16 have yet to be solved. Therefore, it is unclear how Nsp10 activates Nsp16. Using over one millisecond of molecular dynamics simulations of both Nsp16 and its complex with Nsp10, we investigate how the presence of Nsp10 shifts Nsp16s conformational ensemble in order to activate it. Second, guided by this activation mechanism and Markov state models (MSMs), we investigate if Nsp16 adopts inactive structures with cryptic pockets that, if targeted with a small molecule, could inhibit Nsp16 by stabilizing its inactive state. After identifying such a pocket in SARS-CoV-2 Nsp16, we show that this cryptic pocket also opens in SARS-CoV-1 and MERS, but not in human CMTr1. Therefore, it may be possible to develop pan-coronavirus antivirals that target this cryptic pocket. Statement of SignificanceCoronaviruses are a major threat to human health. These viruses employ molecular machines, called proteins, to infect host cells and replicate. Characterizing the structure and dynamics of these proteins could provide a basis for designing small molecule antivirals. In this work, we use computer simulations to understand the moving parts of an essential SARS-CoV-2 protein, understand how a binding partner turns it on and off, and identify a novel pocket that antivirals could target to shut this protein off. The pocket is also present in other coronaviruses but not in the related human protein, so it could be a valuable target for pan-coronavirus antivirals.

biophysics↗

bioRxiv2020

Computational modelling of chromosome re-replication in mutant strains of fission yeast

Typically cells replicate their genome only once per division cycle, but under some circumstances, both natural and unnatural, cells synthesize an overabundance of DNA, either in a disorganized fashion ( over-replication) or by a systematic doubling of chromosome number ( endoreplication). These variations on the theme of DNA replication and division have been studied in strains of fission yeast, Schizosaccharomyces pombe, carrying mutations that interfere with the function of mitotic cyclin-dependent kinase (Cdk1:Cdc13) without impeding the roles of DNA-replication licensing factor (Cdc18) and S-phase cyclin-dependent kinase (Cdk1:Cig2). Some of these mutations support endoreplication, and some over-replication. In this paper, we propose a dynamical model of the interactions among the proteins governing DNA replication and cell division in fission yeast. By computational simulations of the mathematical model, we account for the observed phenotypes of these re-replicating mutants, and by theoretical analysis of the dynamical system, we provide insight into the molecular distinctions between over-replicating and endoreplicating cells. In case of induced over-production of regulatory proteins, our model predicts that cells first switch from normal mitotic cell cycles to growth-controlled endoreplication, and ultimately to disorganized over-replication, parallel to the slow increase of protein to very high levels.

systems biology↗

bioRxiv2020

Mechanisms of signalling-memory governing progression through the eukaryotic cell cycle

As cells pass through each replication-division cycle, they must be able to postpone further progression if they detect any threats to genome integrity, such as DNA damage or misaligned chromosomes. Once a decision is made to proceed, the cell unequivocally enters into a qualitatively different biochemical state, which makes the transitions from one cell cycle phase to the next switch-like and irreversible. Each transition is governed by a unique signalling network; nonetheless, they share a common characteristic of bistable behaviour, a hallmark of molecular memory devices. Comparing the cell cycle signalling mechanisms acting at the Restriction Point, G1/S, G2/M and meta-to-anaphase transitions, we deduce a generic network motif of coupled positive and negative feedback loops underlying each transition.

systems biology↗

bioRxiv2019

A single light-responsive sizer can control multiple-fission cycles in Chlamydomonas

Proliferating cells need to coordinate cell division and growth to maintain size homeostasis. Any systematic deviation from a balance between growth and division results in progressive changes of cell size over subsequent generations. While most eukaryotic cells execute binary division after a mass doubling, the photosynthetic green alga Chlamydomonas can grow more than eight-fold during daytime before undergoing rapid cycles of DNA replication, mitosis and cell division at night, which produce up to 16 daughter cells. Here, we propose a mechanistic model for multiple fission and size control in Chlamydomonas. The model comprises a light-sensitive and size-dependent biochemical toggle switch that acts as a sizer and guards transitions into and exit from a phase of cell-division cycle oscillations. We show that this simple sizer-oscillator arrangement reproduces the experimentally observed features of multiple-fission cycles and the response of Chlamydomonas cells to different light-dark regimes. Our model also makes testable predictions about the dynamical properties of the biochemical network that controls these features and about the networks makeup. Collectively, these results provide a new perspective on the concept of a commitment point during the growth of Chlamydomonas cells and hint at an intriguing continuity of cell-size control in different eukaryotic lineages.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC=\"FIGDIR/small/648436v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (35K):\norg.highwire.dtl.DTLVardef@48f9corg.highwire.dtl.DTLVardef@170625eorg.highwire.dtl.DTLVardef@14a20a0org.highwire.dtl.DTLVardef@1a3ff9a_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIG1-sizer and S/M-oscillator can give rise to multiple-fission cycles in Chlamydomonas\nC_LIO_LILight-responsive bistable switch may guard transition between G1 and S/M-cycles\nC_LIO_LIIllumination increases S/M-entry threshold, causing multiple-fission cycles\nC_LIO_LIDark shift lowers S/M-entry threshold, allowing small cells to commit to fewer divisions\nC_LI

cell biology↗

bioRxiv2019

Absolute quantification of cohesin, CTCF and their regulators in human cells

The organisation of mammalian genomes into loops and topologically associating domains (TADs) contributes to chromatin structure, gene expression and recombination. Loops and TADs are formed by cohesin and positioned by CTCF. In proliferating cells, cohesin also mediates sister chromatid cohesion, which is essential for chromosome segregation. Current models of chromatin folding and cohesion are based on assumptions of how many cohesin and CTCF molecules organise the genome. Here we have measured absolute copy numbers and dynamics of cohesin, CTCF, NIPBL, WAPL and sororin by mass spectrometry, fluorescence-correlation spectroscopy and fluorescence recovery after photobleaching in HeLa cells. In G1-phase there are ~245,000 cohesin complexes, of which ~139,000 are on chromatin. Comparison with chromatin immunoprecipitation-sequencing data implies that some genomic cohesin and CTCF enrichment sites are unoccupied in single cells at any one time. We discuss the implications of these findings for how cohesin can contribute to genome organisation and cohesion.

cell biology↗

bioRxiv2018

Cyclin A triggers Mitosis either via Greatwall or Cyclin B

Two mitotic Cyclins, A and B, exist in higher eukaryotes, but their specialised functions in mitosis are poorly understood. Using degron tags we analyse how acute depletion of these proteins affects mitosis. Loss of Cyclin A in G2-phase prevents the initial activation of Cdk1. Cells lacking Cyclin B can enter mitosis and phosphorylate most mitotic proteins, because of parallel PP2A:B55 phos-phatase inactivation by Greatwall kinase. The final barrier to mitotic establishment corresponds to nuclear envelope breakdown that requires a decisive shift in the balance of Cdk1 and PP2A:B55 activity. Beyond this point Cyclin B/Cdk1 is essential to phosphorylate a distinct subset mitotic Cdk1 substrates that are essential to complete cell division. Our results identify how Cyclin A, B and Greatwall coordinate mitotic progression by increasing levels of Cdk1-dependent substrate phos-phorylation.

cell biology↗