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Oxidative stress from excess H 2 O 2 activates transcription factors that restore redox balance and repair oxidative damage. Although many transcription factors are activated by H 2 O 2 , it is unclear whether they are activated at the same H 2 O 2 concentration, or time. Dose-dependent activation is likely as oxidative stress is not a singular state and exhibits dose-dependent outcomes including cell-cycle arrest and cell death. Here, we show that transcription factor activation is both dose-dependent and coordinated over time. Low levels of H 2 O 2 activate p53, NRF2 and JUN. Yet under high H 2 O 2 , these transcription factors are repressed, and FOXO1, NF-κB, and NFAT1 are activated. Time-lapse imaging revealed that the order in which these two groups of transcription factors are activated depends on whether H 2 O 2 is administered acutely by bolus addition, or continuously through the glucose oxidase enzyme. Finally, we provide evidence that 2-Cys peroxiredoxins control which group of transcription factors are activated. H 2 O 2 stress is known to activate a slew of transcription factors that restore redox balance. Here, the authors use live-cell imaging and single-cell analysis to reveal that the transcription factors that are activated and their timing of activation is dose dependent.

The origin of lineage correlations among single cells and the extent of heterogeneity in their intermitotic times (IMT) and apoptosis times (AT) remain incompletely understood. Here we developed single cell lineage-tracking experiments and computational algorithms to uncover correlations and heterogeneity in the IMT and AT of a colon cancer cell line before and during cisplatin treatment. These correlations could not be explained using simple protein production/degradation models. Sister cell fates were similar regardless of whether they divided before or after cisplatin administration and did not arise from proximity-related factors, suggesting fate determination early in a cell’s lifetime. Based on these findings, we developed a theoretical model explaining how the observed correlation structure can arise from oscillatory mechanisms underlying cell fate control. Our model recapitulated the data only with very specific oscillation periods that fit measured circadian rhythms, thereby suggesting an important role of the circadian clock in controlling cellular fates. The origins of lineage correlations and heterogeneity in division and apoptosis times among single cells are incompletely understood. Here, a new lineage tracking data analysis approach reveals that circadian oscillations may underlie cell fate control and explain the observed correlation structures.

When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.

Chemotherapy resistance is a major challenge to the effective treatment of cancer. Thus, a systematic pipeline for the efficient identification of effective combination treatments could bring huge biomedical benefit. In order to facilitate rational design of combination therapies, we developed a comprehensive computational model that incorporates the available biological knowledge and relevant experimental data on the life-and-death response of individual cancer cells to cisplatin or cisplatin combined with the TNF-related apoptosis-inducing ligand (TRAIL). The model's predictions, that a combination treatment of cisplatin and TRAIL would enhance cancer cell death and exhibit a \"two-wave killing\" temporal pattern, was validated by measuring the dynamics of p53 accumulation, cell fate, and cell death in single cells. The validated model was then subjected to a systematic analysis with an ensemble of diverse machine learning methods. Though each method is characterized by a different algorithm, they collectively identified several molecular players that can sensitize tumor cells to cisplatin-induced apoptosis (sensitizers). The identified sensitizers are consistent with previous experimental observations. Overall, we have illustrated that machine learning analysis of an experimentally validated mechanistic model can convert our available knowledge into the identity of biologically meaningful sensitizers. This knowledge can then be leveraged to design treatment strategies that could improve the efficacy of chemotherapy.

The establishment and maintenance of different cellular compartments in tissues is a universal requirement across all metazoans. Maintaining the correct ratio of cell types in time and space allows tissues to form patterned compartments and perform complex functions. Patterning is especially evident in the human colon, where tissue homeostasis is maintained by stem cells in crypt structures that balance proliferation and differentiation. Here, we developed a human 2D patient derived organoid screening platform to study tissue patterning and kinase pathway dynamics in single cells. Using this system, we discovered that waves of ERK signaling induced by apoptotic cells play a critical role in maintaining tissue patterning and homeostasis. If ERK is activated acutely across all cells instead of in wave-like patterns, then tissue patterning and stem cells are lost. Conversely, if ERK activity is inhibited, then stem cells become unrestricted and expand dramatically. This work demonstrates that the colonic epithelium requires coordinated ERK signaling dynamics to maintain patterning and tissue homeostasis. Our work reveals how ERK can antagonize stem cells while supporting cell replacement and the function of the gut.

The sudden rise of the SARS-CoV-2 virus and the delay in development of effective therapeutics for mitigation made evident a need for ways to screen compounds that can block infection and prevent further pathogenesis and spread. However, identifying effective drugs that are efficacious against viral infection and replication with minimal toxicity for the patient can be difficult. Monoclonal antibodies were shown to be effective, but as the SARS-CoV-2 mutated, these antibodies became ineffective. Small-molecule antivirals were identified using pseudovirus constructs to recapitulate infection in nonhuman cells, such as Vero E6 cells. However, the impact was limited due to poor translation of these compounds in the clinical setting. This is partly due to the lack of similarity of screening platforms to the in vivo physiology of the patient and partly because drugs effective in vitro showed dose-limiting toxicities. In this study, we performed two high-throughput screens in human lung adenocarcinoma cells with authentic SARS-CoV-2 virus to identify both monoclonal antibodies that neutralize the virus and clinically useful kinase inhibitors to block the virus and prioritize minimal host toxicity. Using high-content imaging combined with single-cell and multidimensional analysis, we identified antibodies and kinase inhibitors that reduce viral infection without affecting the host. Our screening technique uncovered novel antibodies and overlooked kinase inhibitors (i.e., PIK3i, mTORi, and multiple RTKi) that could be effective against the SARS-CoV-2 virus. Further characterization of these molecules will streamline the repurposing of compounds for the treatment of future pandemics and uncover novel mechanisms viruses use to hijack and infect host cells.

Natural Killer (NK) cells can target and destroy cancer cells, yet tumor microenvironments typically suppress NK cell recruitment and cytotoxicity. The epidermal growth factor receptor (EGFR) is a potent oncogene that can activate survival, migration, and proliferation pathways, and clinical data suggests it may also play an immunomodulating role in cancers. Recent work has demonstrated a novel role for nuclear EGFR (nEGFR) in regulating transcriptional events unique from the kinase domain. Using a novel peptide therapeutic (cSNX1.3) that inhibits retrograde trafficking of EGFR and an EGFR nuclear localization mutant, we discovered that nEGFR suppresses NK cell recruitment and cytotoxicity. RNA-Seq analysis of breast cancer cells treated with cSNX1.3 or modified to lack a nuclear localization sequence (EGFR ΔNLS ) revealed the EGF-dependent induction of NK activating receptor ligands, while kinase inhibition by erlotinib did not impact these genes. NanoString analysis of tumor-bearing WAP-TGFα transgenic mice treated with cSNX1.3 demonstrated an increase in immune cell populations and activating genes. Additionally, immunohistochemistry confirmed an increase in NK cells upon cSNX1.3 treatment. Finally, cSNX1.3 treatment was found to enhance NK cell recruitment and cytotoxicity in vitro. Together, the data demonstrate a unique immunomodulatory role for nEGFR.

Wnt ligands are considered classical morphogens, for which the strength of the cellular response is proportional to the concentration of the ligand. Herein, we show an emergent property of bistability arising from feedback among the Wnt destruction complex proteins that target the key transcriptional co-activator β-catenin for degradation. Using biochemical reconstitution, we identified positive feedback between the scaffold protein Axin and the kinase glycogen synthase kinase 3 (GSK3). Theoretical modeling of this feedback between Axin and GSK3 suggested that the activity of the destruction complex exhibits bistable behavior. We experimentally confirmed these predictions by demonstrating that cellular cytoplasmic β-catenin concentrations exhibit an “all-ornone” response with sustained memory (hysteresis) of the signaling input. This bistable behavior was transformed into a graded response and memory was lost through inhibition of GSK3. These findings provide a mechanism for establishing decisive, switch-like cellular response and memory upon Wnt pathway stimulation.

Yeast offers insight into how lifting controls on DNA re-replication can cause cells to make extra copies of a gene. Cells have a seemingly endless array of regulators to provide for fast and accurate DNA replication. Most cells succeed in doing it right, each and every time they divide, which is testimony to the powers of evolution. Failure to limit DNA replication to just once every cell cycle can lead to genome rearrangements, in particular to “amplification,” or an increase in the number of copies of some genes. Amplification can drive abnormal cell growth, and cancer cells often have amplified oncogenes ( 1 ). How gene amplification occurs, however, is unclear. One mechanism involves the breaking and fusion of aberrant chromosomes, a process first discovered by Nobel Laureate Barbara McClintock in the 1950s ( 2 ), which leads to extra copies of genes that are joined together ( 3 ). Another proposed mechanism involves defects in the “re-replication” controls that shut down the DNA-copying process after a single duplication, but this idea had not been testable ( 4 ). On page 943 of this issue, Green et al. overcome that hurdle with an extravagant experimental system in budding yeast that demonstrates that re-replication is indeed a potent mechanism of gene amplification ( 5 ).

Gross chromosomal rearrangements (GCRs) are large scale changes to chromosome structure and can lead to human disease. We previously showed in Saccharomyces cerevisiae that nearby inverted repeat sequences (∼20–200 bp of homology, separated by ∼1–5 kb) frequently fuse to form unstable dicentric and acentric chromosomes. Here we analyzed inverted repeat fusion in mutants of three sets of genes. First, we show that genes in the error-free postreplication repair (PRR) pathway prevent fusion of inverted repeats, while genes in the translesion branch have no detectable role. Second, we found that siz1 mutants, which are defective for Srs2 recruitment to replication forks, and srs2 mutants had opposite effects on instability. This may reflect separate roles for Srs2 in different phases of the cell cycle. Third, we provide evidence for a faulty template switch model by studying mutants of DNA polymerases; defects in DNA pol delta (lagging strand polymerase) and Mgs1 (a pol delta interacting protein) lead to a defect in fusion events as well as allelic recombination. Pol delta and Mgs1 may collaborate either in strand annealing and/or DNA replication involved in fusion and allelic recombination events. Fourth, by studying genes implicated in suppression of GCRs in other studies, we found that inverted repeat fusion has a profile of genetic regulation distinct from these other major forms of GCR formation.