The multiple mechanisms that regulate p53 activity and cell fate.

The tumour suppressor p53 has a central role in the response to cellular stress. Activated p53 transcriptionally regulates hundreds of genes that are involved in multiple biological processes, including in DNA damage repair, cell cycle arrest, apoptosis and senescence. In the context of DNA damage, p53 is thought to be a decision-making transcription factor that selectively activates genes as part of specific gene expression programmes to determine cellular outcomes. In this Review, we discuss the multiple molecular mechanisms of p53 regulation and how they modulate the induction of apoptosis or cell cycle arrest following DNA damage. Specifically, we discuss how the interaction of p53 with DNA and chromatin affects gene expression, and how p53 post-translational modifications, its temporal expression dynamics and its interactions with chromatin regulators and transcription factors influence cell fate. These multiple layers of regulation enable p53 to execute cellular responses that are appropriate for specific cellular states and environmental conditions.

Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing.

Many chemotherapeutic drugs kill only a fraction of cancer cells, limiting their efficacy. We used live-cell imaging to investigate the role of p53 dynamics in fractional killing of colon cancer cells in response to chemotherapy. We found that both surviving and dying cells reach similar levels of p53, indicating that cell death is not determined by a fixed p53 threshold. Instead, a cell's probability of death depends on the time and levels of p53. Cells must reach a threshold level of p53 to execute apoptosis, and this threshold increases with time. The increase in p53 apoptotic threshold is due to drug-dependent induction of anti-apoptotic genes, predominantly in the inhibitors of apoptosis (IAP) family. Our study underlines the importance of measuring the dynamics of key players in response to chemotherapy to determine mechanisms of resistance and optimize the timing of combination therapy.

Encoding and decoding cellular information through signaling dynamics.

A growing number of studies are revealing that cells can send and receive information by controlling the temporal behavior (dynamics) of their signaling molecules. In this Review, we discuss what is known about the dynamics of various signaling networks and their role in controlling cellular responses. We identify general principles that are emerging in the field, focusing specifically on how the identity and quantity of a stimulus is encoded in temporal patterns, how signaling dynamics influence cellular outcomes, and how specific dynamical patterns are both shaped and interpreted by the structure of molecular networks. We conclude by discussing potential functional roles for transmitting cellular information through the dynamics of signaling molecules and possible applications for the treatment of disease.

Cycling cancer persister cells arise from lineages with distinct programs.

Non-genetic mechanisms have recently emerged as important drivers of cancer therapy failure1, where some cancer cells can enter a reversible drug-tolerant persister state in response to treatment2. Although most cancer persisters remain arrested in the presence of the drug, a rare subset can re-enter the cell cycle under constitutive drug treatment. Little is known about the non-genetic mechanisms that enable cancer persisters to maintain proliferative capacity in the presence of drugs. To study this rare, transiently resistant, proliferative persister population, we developed Watermelon, a high-complexity expressed barcode lentiviral library for simultaneous tracing of each cell's clonal origin and proliferative and transcriptional states. Here we show that cycling and non-cycling persisters arise from different cell lineages with distinct transcriptional and metabolic programs. Upregulation of antioxidant gene programs and a metabolic shift to fatty acid oxidation are associated with persister proliferative capacity across multiple cancer types. Impeding oxidative stress or metabolic reprogramming alters the fraction of cycling persisters. In human tumours, programs associated with cycling persisters are induced in minimal residual disease in response to multiple targeted therapies. The Watermelon system enabled the identification of rare persister lineages that are preferentially poised to proliferate under drug pressure, thus exposing new vulnerabilities that can be targeted to delay or even prevent disease recurrence.

Fluctuations in p53 Signaling Allow Escape from Cell-Cycle Arrest.

Biological signals need to be robust and filter small fluctuations yet maintain sensitivity to signals across a wide range of magnitudes. Here, we studied how fluctuations in DNA damage signaling relate to maintenance of long-term cell-cycle arrest. Using live-cell imaging, we quantified division profiles of individual human cells in the course of 1 week after irradiation. We found a subset of cells that initially establish cell-cycle arrest and then sporadically escape and divide. Using fluorescent reporters and mathematical modeling, we determined that fluctuations in the oscillatory pattern of the tumor suppressor p53 trigger a sharp switch between p21 and CDK2, leading to escape from arrest. Transient perturbation of p53 stability mimicked the noise in individual cells and was sufficient to trigger escape from arrest. Our results show that the self-reinforcing circuitry that mediates cell-cycle transitions can translate small fluctuations in p53 signaling into large phenotypic changes.

MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data.

MOTIVATION: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. RESULTS: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/marjanfaizi/MSModDetector.

Basal dynamics of p53 reveal transcriptionally attenuated pulses in cycling cells.

The tumor suppressor p53 is activated by stress and leads to cellular outcomes such as apoptosis and cell-cycle arrest. Its activation must be highly sensitive to ensure that cells react appropriately to damage. However, proliferating cells often encounter transient damage during normal growth, where cell-cycle arrest or apoptosis may be unfavorable. How does the p53 pathway achieve the right balance between high sensitivity and tolerance to intrinsic damage? Using quantitative time-lapse microscopy of individual human cells, we found that proliferating cells show spontaneous pulses of p53, which are triggered by an excitable mechanism during cell-cycle phases associated with intrinsic DNA damage. However, in the absence of sustained damage, posttranslational modifications keep p53 inactive, preventing it from inducing p21 expression and cell-cycle arrest. Our approach of quantifying basal dynamics in individual cells can now be used to study how other pathways in human cells achieve sensitivity in noisy environments.

Single-cell biology: what does the future hold?

In this Editorial, our Chief Editor and members of our Advisory Editorial Board discuss recent breakthroughs, current challenges, and emerging opportunities in single-cell biology and share their vision of "where the field is headed."

Time-series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations.

The cell stress-responsive transcription factor p53 influences the expression of its target genes and subsequent cellular responses based in part on its dynamics (changes in level over time). The mechanisms decoding p53 dynamics into subsequent target mRNA and protein dynamics remain unclear. We systematically quantified p53 target mRNA and protein expression over time under two p53 dynamical regimes, oscillatory and rising, using RNA-sequencing and TMT mass spectrometry. Oscillatory dynamics allowed for a greater variety of dynamical patterns for both mRNAs and proteins. Mathematical modeling of empirical data revealed three distinct mechanisms that decode p53 dynamics. Specific combinations of these mechanisms at the transcriptional and post-transcriptional levels enabled exclusive induction of proteins under particular dynamics. In addition, rising induction of p53 led to higher induction of proteins regardless of their functional class, including proteins promoting arrest of proliferation, the primary cellular outcome under rising p53. Our results highlight the diverse mechanisms cells employ to distinguish complex transcription factor dynamics to regulate gene expression.

Fully unsupervised symmetry-based mitosis detection in time-lapse cell microscopy.

MOTIVATION: Cell microscopy datasets have great diversity due to variability in cell types, imaging techniques and protocols. Existing methods are either tailored to specific datasets or are based on supervised learning, which requires comprehensive manual annotations. Using the latter approach, however, poses a significant difficulty due to the imbalance between the number of mitotic cells with respect to the entire cell population in a time-lapse microscopy sequence. RESULTS: We present a fully unsupervised framework for both mitosis detection and mother-daughters association in fluorescence microscopy data. The proposed method accommodates the difficulty of the different cell appearances and dynamics. Addressing symmetric cell divisions, a key concept is utilizing daughters' similarity. Association is accomplished by defining cell neighborhood via a stochastic version of the Delaunay triangulation and optimization by dynamic programing. Our framework presents promising detection results for a variety of fluorescence microscopy datasets of different sources, including 2D and 3D sequences from the Cell Tracking Challenge. AVAILABILITY AND IMPLEMENTATION: Code is available in github (github.com/topazgl/mitodix). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The effect of dust storm particles on single human lung cancer cells.

Exposure to dust particles during dust storms can lead to respiratory problems, diseases, and even death. The effect of dust particles at the cellular level is poorly understood. In this study, we investigated the impact that dust storm particles (Montmorillonite) have on human lung epithelial cells (A549) at the single cell level. Using live-cell imaging, we continuously followed individual cells after exposure to a wide range of concentrations of dust particles. We monitored the growth trajectory of each cell including number and timing of divisions, interaction with the dust particles, as well as time and mechanism of cell death. We found that individual cells show different cellular fates (survival or death) even in response to the same dust concentration. Cells that died interacted with dust particles for longer times, and engulfed more dust particles, compared with surviving cells. While higher dust concentrations reduced viability in a dose-dependent manner, the effect on cell death was non-monotonic, with intermediate dust concentration leading to a larger fraction of dying cells compared to lower and higher concentrations. This non-monotonic relationship was explained by our findings that high dust concentrations inhibit cell proliferation. Using cellular morphological features, supported by immunoblots and proinflammatory cytokines, we determined that apoptosis is the dominant death mechanism at low dust concentrations, while higher dust concentrations activate necrosis. Similar single cell approaches can serve as a baseline for evaluating other aerosol types that will improve our understanding of the health-related consequences of exposure to dust storms.

Decoding the insulin signal.

In this issue of Molecular Cell, Kubota et al. (2012) show how different temporal patterns of insulin are decoded by the AKT signaling network, providing both new mechanistic insights and physiological relevance.

Quantitative live cell imaging reveals a gradual shift between DNA repair mechanisms and a maximal use of HR in mid S phase.

DNA double-strand breaks are repaired by two main pathways: nonhomologous end joining (NHEJ) and homologous recombination (HR). The choice between these pathways depends on cell-cycle phase; however the continuous effect of cell cycle on the balance between them is still unclear. We used live cell imaging and fluorescent reporters for 53BP1, Rad52, and cell cycle to quantify the relative contribution of NHEJ and HR at different points of the cell cycle in single cells. We found that NHEJ is the dominant repair pathway in G1 and G2 even when both repair pathways are functional. The shift from NHEJ to HR is gradual, with the highest proportion of breaks repaired by HR in mid S, where the amount of DNA replication is highest. Higher proportions of HR also strongly correlate with slower rates of repair. Our study shows that the choice of repair mechanism is continuously adjusted throughout the cell cycle and suggests that the extent of active replication, rather than the presence of a sister chromatid influences the balance between the two repair pathways in human cells.

Dynamics extracted from fixed cells reveal feedback linking cell growth to cell cycle.

Biologists have long been concerned about what constrains variation in cell size, but progress in this field has been slow and stymied by experimental limitations. Here we describe a new method, ergodic rate analysis (ERA), that uses single-cell measurements of fixed steady-state populations to accurately infer the rates of molecular events, including rates of cell growth. ERA exploits the fact that the number of cells in a particular state is related to the average transit time through that state. With this method, it is possible to calculate full time trajectories of any feature that can be labelled in fixed cells, for example levels of phosphoproteins or total cellular mass. Using ERA we find evidence for a size-discriminatory process at the G1/S transition that acts to decrease cell-to-cell size variation.

How to survive and thrive in the mother-mentor marathon.

This article is for women who ask whether it is possible to combine motherhood with academia and still be successful and happy. It is also for those working with, bosses of, or married to such women, giving them a better feel for the challenges mothers in academia face, and the strategies that can be used to survive and thrive in both of these worlds.

Recurrent initiation: a mechanism for triggering p53 pulses in response to DNA damage.

DNA damage initiates a series of p53 pulses. Although much is known about the interactions surrounding p53, little is known about which interactions contribute to p53's dynamical behavior. The simplest explanation is that these pulses are oscillations intrinsic to the p53/Mdm2 negative feedback loop. Here we present evidence that this simple mechanism is insufficient to explain p53 pulses; we show that p53 pulses are externally driven by pulses in the upstream signaling kinases, ATM and Chk2, and that the negative feedback between p53 and ATM, via Wip1, is essential for maintaining the uniform shape of p53 pulses. We propose that p53 pulses result from repeated initiation by ATM, which is reactivated by persistent DNA damage. Our study emphasizes the importance of collecting quantitative dynamic information at high temporal resolution for understanding the regulation of signaling pathways and opens new ways to manipulate p53 pulses to ask questions about their function in response to DNA damage.

Activation and control of p53 tetramerization in individual living cells.

Homo-oligomerization is found in many biological systems and has been extensively studied in vitro. However, our ability to quantify and understand oligomerization processes in cells is still limited. We used fluorescence correlation spectroscopy and mathematical modeling to measure the dynamics of the tetramers formed by the tumor suppressor protein p53 in single living cells. Previous in vitro studies suggested that in basal conditions all p53 molecules are bound in dimers. We found that in resting cells p53 is present in a mix of oligomeric states with a large cell-to-cell variation. After DNA damage, p53 molecules in all cells rapidly assemble into tetramers before p53 protein levels increase. We developed a model to understand the connection between p53 accumulation and tetramerization. We found that the rapid increase in p53 tetramers requires a combination of active tetramerization and protein stabilization, however tetramerization alone is sufficient to activate p53 transcriptional targets. This suggests triggering tetramerization as a mechanism for activating the p53 pathway in cancer cells. Many other transcription factors homo-oligomerize, and our approach provides a unique way for probing the dynamics and functional consequences of oligomerization.

Constant rate of p53 tetramerization in response to DNA damage controls the p53 response.

The dynamics of the tumor suppressor protein p53 have been previously investigated in single cells using fluorescently tagged p53. Such approach reports on the total abundance of p53 but does not provide a measure for functional p53. We used fluorescent protein-fragment complementation assay (PCA) to quantify in single cells the dynamics of p53 tetramers, the functional units of p53. We found that while total p53 increases proportionally to the input strength, p53 tetramers are formed in cells at a constant rate. This breaks the linear input-output relation and dampens the p53 response. Disruption of the p53-binding protein ARC led to a dose-dependent rate of tetramers formation, resulting in enhanced tetramerization and induction of p53 target genes. Our work suggests that constraining the p53 response in face of variable inputs may protect cells from committing to terminal outcomes and highlights the importance of quantifying the active form of signaling molecules in single cells.

The p53 response in single cells is linearly correlated to the number of DNA breaks without a distinct threshold.

BACKGROUND: The tumor suppressor protein p53 is activated by cellular stress. DNA double strand breaks (DSBs) induce the activation of the kinase ATM, which stabilizes p53 and activates its transcriptional activity. Single cell analysis revealed that DSBs induced by gamma irradiation trigger p53 accumulation in a series of pulses that vary in number from cell to cell. Higher levels of irradiation increase the number of p53 pulses suggesting that they arise from periodic examination of the damage by ATM. If damage persists, additional pulses of p53 are triggered. The threshold of damage required for activating a p53 pulse is unclear. Previous studies that averaged the response across cell populations suggested that one or two DNA breaks are sufficient for activating ATM and p53. However, it is possible that by averaging over a population of cells important features of the dependency between DNA breaks and p53 dynamics are missed. RESULTS: Using fluorescent reporters we developed a system for following in individual cells the number of DSBs, the kinetics of repair and the p53 response. We found a large variation in the initial number of DSBs and the rate of repair between individual cells. Cells with higher number of DSBs had higher probability of showing a p53 pulse. However, there was no distinct threshold number of breaks for inducing a p53 pulse. We present evidence that the decision to activate p53 given a specific number of breaks is not entirely stochastic, but instead is influenced by both cell-intrinsic factors and previous exposure to DNA damage. We also show that the natural variations in the initial amount of p53, rate of DSB repair and cell cycle phase do not affect the probability of activating p53 in response to DNA damage. CONCLUSIONS: The use of fluorescent reporters to quantify DNA damage and p53 levels in live cells provided a quantitative analysis of the complex interrelationships between both processes. Our study shows that p53 activation differs even between cells that have a similar number of DNA breaks. Understanding the origin and consequences of such variability in normal and cancerous cells is crucial for developing efficient and selective therapeutic interventions.