Author Correction: Cooperative nutrient accumulation sustains growth of mammalian cells.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Dual inhibition of DNA-PK and DNA polymerase theta overcomes radiation resistance induced by p53 deficiency.

TP53 deficiency in cancer is associated with poor patient outcomes and resistance to DNA damaging therapies. However, the mechanisms underlying treatment resistance in p53-deficient cells remain poorly characterized. Using live cell imaging of DNA double-strand breaks (DSBs) and cell cycle state transitions, we show that p53-deficient cells exhibit accelerated repair of radiomimetic-induced DSBs arising in S phase. Low-dose DNA-dependent protein kinase (DNA-PK) inhibition increases the S-phase DSB burden in p53-deficient cells, resulting in elevated rates of mitotic catastrophe. However, a subset of p53-deficient cells exhibits intrinsic resistance to radiomimetic-induced DSBs despite DNA-PK inhibition. We show that p53-deficient cells under DNA-PK inhibition utilize DNA polymerase theta (Pol θ)-mediated end joining repair to promote their viability in response to therapy-induced DSBs. Pol θ inhibition selectively increases S-phase DSB burden after radiomimetic therapy and promotes prolonged G2 arrest. Dual inhibition of DNA-PK and Pol θ restores radiation sensitivity in p53-deficient cells as well as in p53-mutant breast cancer cell lines. Thus, combination targeting of DNA-PK- and Pol θ-dependent end joining repair represents a promising strategy for overcoming resistance to DNA damaging therapies in p53-deficient cancers.

Bistable switches as integrators and actuators during cell cycle progression.

Progression through the cell cycle is driven by bistable switches-specialized molecular circuits that govern transitions from one cellular state to another. Although the mechanics of bistable switches are relatively well understood, it is less clear how cells integrate multiple sources of molecular information to engage these switches. Here, we describe how bistable switches act as hubs of information processing and examine how variability, competition, and inheritance of molecular signals determine the timing of the Rb-E2F bistable switch that controls cell cycle entry. Bistable switches confer both robustness and plasticity to cell cycle progression, ensuring that cell cycle events are performed completely and in the correct order, while still allowing flexibility to cope with ongoing stress and changing environmental conditions.

Evidence that the human cell cycle is a series of uncoupled, memoryless phases.

The cell cycle is canonically described as a series of four consecutive phases: G1, S, G2, and M. In single cells, the duration of each phase varies, but the quantitative laws that govern phase durations are not well understood. Using time-lapse microscopy, we found that each phase duration follows an Erlang distribution and is statistically independent from other phases. We challenged this observation by perturbing phase durations through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Despite large changes in durations in cell populations, phase durations remained uncoupled in individual cells. These results suggested that the independence of phase durations may arise from a large number of molecular factors that each exerts a minor influence on the rate of cell cycle progression. We tested this model by experimentally forcing phase coupling through inhibition of cyclin-dependent kinase 2 (CDK2) or overexpression of cyclin D. Our work provides an explanation for the historical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states.

The Cell Cycle Browser: An Interactive Tool for Visualizing, Simulating, and Perturbing Cell-Cycle Progression.

The cell cycle is driven by precise temporal coordination among many molecular activities. To understand and explore this process, we developed the Cell Cycle Browser (CCB), an interactive web interface based on real-time reporter data collected in proliferating human cells. This tool facilitates visualizing, organizing, simulating, and predicting the outcomes of perturbing cell-cycle parameters. Time-series traces from individual cells can be combined to build a multi-layered timeline of molecular activities. Users can simulate the cell cycle using computational models that capture the dynamics of molecular activities and phase transitions. By adjusting individual expression levels and strengths of molecular relationships, users can predict effects on the cell cycle. Virtual assays, such as growth curves and flow cytometry, provide familiar outputs to compare cell-cycle behaviors for data and simulations. The CCB serves to unify our understanding of cell-cycle dynamics and provides a platform for generating hypotheses through virtual experiments.

Orchestration of DNA Damage Checkpoint Dynamics across the Human Cell Cycle.

Although molecular mechanisms that prompt cell-cycle arrest in response to DNA damage have been elucidated, the systems-level properties of DNA damage checkpoints are not understood. Here, using time-lapse microscopy and simulations that model the cell cycle as a series of Poisson processes, we characterize DNA damage checkpoints in individual, asynchronously proliferating cells. We demonstrate that, within early G1 and G2, checkpoints are stringent: DNA damage triggers an abrupt, all-or-none cell-cycle arrest. The duration of this arrest correlates with the severity of DNA damage. After the cell passes commitment points within G1 and G2, checkpoint stringency is relaxed. By contrast, all of S phase is comparatively insensitive to DNA damage. This checkpoint is graded: instead of halting the cell cycle, increasing DNA damage leads to slower S phase progression. In sum, we show that a cell's response to DNA damage depends on its exact cell-cycle position and that checkpoints are phase-dependent, stringent or relaxed, and graded or all-or-none.

Expression and Prognostic Value of Indoleamine 2,3-dioxygenase in Pancreatic Cancer / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Indoleamine 2,3-dioxygenase (IDO), an enzyme for tryptophan metabolism through the kynurenine pathway, exhibits an immunosuppressive effect and induces immune tolerance in tumor cells. The effects of IDO on pancreatic cancer are poorly understood. This study aimed to investigate the expression and prognostic significance of IDO in pancreatic cancer.</p><p><b>METHODS</b>We evaluated the protein expression of IDO in PANC-1, CFPAC-1, and BxPC-3 cell lines with or without 48 h treatment by 500 U/ml interferon-γ (IFN-γ). We performed immunohistochemical staining and Western blot analysis for IDO expression in both pancreatic cancer and normal pancreas tissues obtained from Chinese PLA General Hospital from July 2012 to December 2013. Survival analysis was performed to correlate IDO expression and histopathologic parameters with overall survival. The Kaplan-Meier method and Cox proportional hazards regression model were conducted.</p><p><b>RESULTS</b>PANC-1, CFPAC-1, and BxPC-3 cell lines expressed IDO at the protein level, and the relative expression amount increased after stimulation with 500 U/ml IFN-γ. Immunohistochemical analysis results revealed that high IDO expression was observed in 59% of pancreatic adenocarcinoma tissues. Compared with normal pancreatic tissues, pancreatic adenocarcinoma showed significantly higher IDO expression levels, especially among patients with high tumor node metastasis (TNM) stages (χ2 = 4.550, P = 0.030), poor histological differentiation (χ2 = 5.690, P = 0.017), and lymph node metastasis (χ2 = 4.340 P = 0.037). Kaplan-Meier survival curves showed that high IDO expression was correlated with low survival rates (hazard ratio [HR] = 0.49 P = 0.009). Multivariate analysis using Cox proportional hazards model indicated that lymph node metastasis (HR = 0.35 P = 0.010) and IDO expression (HR = 0.42 P = 0.020) were two independent prognostic predictors of pancreatic adenocarcinoma.</p><p><b>CONCLUSIONS</b>The study confirmed that high IDO expression in pancreatic adenocarcinoma was related to poor prognosis of patients. These findings provided evidence that IDO was involved in pancreatic adenocarcinoma progression and might serve as a relevant therapeutic target.</p>

Cooperative nutrient accumulation sustains growth of mammalian cells.

The coordination of metabolic processes to allow increased nutrient uptake and utilization for macromolecular synthesis is central for cell growth. Although studies of bulk cell populations have revealed important metabolic and signaling requirements that impact cell growth on long time scales, whether the same regulation influences short-term cell growth remains an open question. Here we investigate cell growth by monitoring mass accumulation of mammalian cells while rapidly depleting particular nutrients. Within minutes following the depletion of glucose or glutamine, we observe a growth reduction that is larger than the mass accumulation rate of the nutrient. This indicates that if one particular nutrient is depleted, the cell rapidly adjusts the amount that other nutrients are accumulated, which is consistent with cooperative nutrient accumulation. Population measurements of nutrient sensing pathways involving mTOR, AKT, ERK, PKA, MST1, or AMPK, or pro-survival pathways involving autophagy suggest that they do not mediate this growth reduction. Furthermore, the protein synthesis rate does not change proportionally to the mass accumulation rate over these time scales, suggesting that intracellular metabolic pools buffer the growth response. Our findings demonstrate that cell growth can be regulated over much shorter time scales than previously appreciated.

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids.

Inactivation of ß-lactam antibiotics by resistant bacteria is a 'cooperative' behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a ß-lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used ß-lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.

Hidden randomness between fitness landscapes limits reverse evolution.

In biological evolution, adaptations to one environment can in some cases reverse adaptations to another environment. To study this "reverse evolution" on a genotypic level, we measured the fitness of E. coli strains with each possible combination of five mutations in an antibiotic-resistance gene in two distinct antibiotic environments. While adaptations to one environment generally lower fitness in the other, we find that reverse evolution is rarely possible and falls as the complexity of adaptations increases, suggesting a probabilistic, molecular form of Dollo's law.