A simplified Bcl-2 network model reveals quantitative determinants of cell-to-cell variation in sensitivity to anti-mitotic chemotherapeutics

Anti-mitotic drugs constitute a major class of cytotoxic chemotherapeutics used in the clinic, killing cancer cells by inducing prolonged mitotic arrest that activates intrinsic apoptosis. Anti-mitotics-induced apoptosis is known to involve degradation of anti-apoptotic Bcl-2 proteins during mitotic arrest; however, it remains unclear how this mechanism accounts for significant heterogeneity observed in the cell death responses both within and between cancer cell types. To unravel quantitative determinants underlying variability in anti-mitotic drug response, we constructed a single-cell dynamical Bcl-2 network model describing cell death control during mitotic arrest, and constrained the model using experimental data from four representative cancer cell lines. The modeling analysis revealed that, given a variable, slowly accumulating pro-apoptotic signal arising from anti-apoptotic protein degradation, generation of a switch-like apoptotic response requires formation of pro-apoptotic Bak complexes with hundreds of subunits, suggesting a crucial role for high-order cooperativity. Moreover, we found that cell-type variation in susceptibility to drug-induced mitotic death arises primarily from differential expression of the anti-apoptotic proteins Bcl-xL and Mcl-1 relative to Bak. The dependence of anti-mitotic drug response on Bcl-xL and Mcl-1 that we derived from the modeling analysis provides a quantitative measure to predict sensitivity of distinct cancer cells to anti-mitotic drug treatment

Maintenance of Mitochondrial Oxygen Homeostasis by Cosubstrate Compensation

Mitochondria maintain a constant rate of aerobic respiration over a wide range of oxygen levels. However, the control strategies underlying oxygen homeostasis are still unclear. Using mathematical modeling, we found that the mitochondrial electron transport chain (ETC) responds to oxygen level changes by undergoing compensatory changes in reduced electron carrier levels. This emergent behavior, which we named cosubstrate compensation (CSC), enables the ETC to maintain homeostasis over a wide of oxygen levels. When performing CSC, our ETC models recapitulated a classic scaling relationship discovered by Chance [Chance B (1965) J. Gen. Physiol. 49:163-165] relating the extent of oxygen homeostasis to the kinetics of mitochondrial electron transport. Analysis of an in silico mitochondrial respiratory system further showed evidence that CSC constitutes the dominant control strategy for mitochondrial oxygen homeostasis during active respiration. Our findings indicate that CSC constitutes a robust control strategy for homeostasis and adaptation in cellular biochemical networks

Regulatory gene network circuits underlying T cell development from multipotent progenitors

Regulatory gene circuits enable stem and progenitor cells to detect and process developmental signals and make irreversible fate commitment decisions. To gain insight into the gene circuits underlying T cell fate decision making in progenitor cells, we generated an updated T-lymphocyte developmental gene regulatory network from genes and connections found in the literature. This reconstruction allowed us to identify candidate regulatory gene circuit elements underlying T cell fate decision making. Here, we examine the roles of these circuits in facilitating different aspects of the decision making process, and discuss experiments to further probe their structure and functio

A simplified Bcl-2 network model reveals quantitative determinants of cell-to-cell variation in sensitivity to anti-mitotic chemotherapeutics

Anti-mitotic drugs constitute a major class of cytotoxic chemotherapeutics used in the clinic, killing cancer cells by inducing prolonged mitotic arrest that activates intrinsic apoptosis. Anti-mitotics-induced apoptosis is known to involve degradation of anti-apoptotic Bcl-2 proteins during mitotic arrest; however, it remains unclear how this mechanism accounts for significant heterogeneity observed in the cell death responses both within and between cancer cell types. To unravel quantitative determinants underlying variability in anti-mitotic drug response, we constructed a single-cell dynamical Bcl-2 network model describing cell death control during mitotic arrest, and constrained the model using experimental data from four representative cancer cell lines. The modeling analysis revealed that, given a variable, slowly accumulating pro-apoptotic signal arising from anti-apoptotic protein degradation, generation of a switch-like apoptotic response requires formation of pro-apoptotic Bak complexes with hundreds of subunits, suggesting a crucial role for high-order cooperativity. Moreover, we found that cell-type variation in susceptibility to drug-induced mitotic death arises primarily from differential expression of the anti-apoptotic proteins Bcl-xL and Mcl-1 relative to Bak. The dependence of anti-mitotic drug response on Bcl-xL and Mcl-1 that we derived from the modeling analysis provides a quantitative measure to predict sensitivity of distinct cancer cells to anti-mitotic drug treatment

Hematopoiesis and T-cell specification as a model developmental system

The pathway to generate T cells from hematopoietic stem cells guides progenitors through a succession of fate choices while balancing differentiation progression against proliferation, stage to stage. Many elements of the regulatory system that controls this process are known, but the requirement for multiple, functionally distinct transcription factors needs clarification in terms of gene network architecture. Here, we compare the features of the T-cell specification system with the rule sets underlying two other influential types of gene network models: first, the combinatorial, hierarchical regulatory systems that generate the orderly, synchronized increases in complexity in most invertebrate embryos; second, the dueling ‘master regulator’ systems that are commonly used to explain bistability in microbial systems and in many fate choices in terminal differentiation. The T-cell specification process shares certain features with each of these prevalent models but differs from both of them in central respects. The T-cell system is highly combinatorial but also highly dose-sensitive in its use of crucial regulatory factors. The roles of these factors are not always T-lineage-specific, but they balance and modulate each other's activities long before any mutually exclusive silencing occurs. T-cell specification may provide a new hybrid model for gene networks in vertebrate developmental systems

Actin disassembly by cofilin, coronin, and Aip1 occurs in bursts and is inhibited by barbed-end cappers

Turnover of actin filaments in cells requires rapid actin disassembly in a cytoplasmic environment that thermodynamically favors assembly because of high concentrations of polymerizable monomers. We here image the disassembly of single actin filaments by cofilin, coronin, and actin-interacting protein 1, a purified protein system that reconstitutes rapid, monomer-insensitive disassembly (Brieher, W.M., H.Y. Kueh, B.A. Ballif, and T.J. Mitchison. 2006. J. Cell Biol. 175:315–324). In this three-component system, filaments disassemble in abrupt bursts that initiate preferentially, but not exclusively, from both filament ends. Bursting disassembly generates unstable reaction intermediates with lowered affinity for CapZ at barbed ends. CapZ and cytochalasin D (CytoD), a barbed-end capping drug, strongly inhibit bursting disassembly. CytoD also inhibits actin disassembly in mammalian cells, whereas latrunculin B, a monomer sequestering drug, does not. We propose that bursts of disassembly arise from cooperative separation of the two filament strands near an end. The differential effects of drugs in cells argue for physiological relevance of this new disassembly pathway and potentially explain discordant results previously found with these drugs

Positive Feedback Between PU.1 and the Cell Cycle Controls Myeloid Differentiation

Regulatory gene circuits with positive-feedback loops control stem cell differentiation, but several mechanisms can contribute to positive feedback. Here, we dissect feedback mechanisms through which the transcription factor PU.1 controls lymphoid and myeloid differentiation. Quantitative live-cell imaging revealed that developing B cells decrease PU.1 levels by reducing PU.1 transcription, whereas developing macrophages increase PU.1 levels by lengthening their cell cycles, which causes stable PU.1 accumulation. Exogenous PU.1 expression in progenitors increases endogenous PU.1 levels by inducing cell cycle lengthening, implying positive feedback between a regulatory factor and the cell cycle. Mathematical modeling showed that this cell cycle–coupled feedback architecture effectively stabilizes a slow-dividing differentiated state. These results show that cell cycle duration functions as an integral part of a positive autoregulatory circuit to control cell fate

Rapid actin monomer–insensitive depolymerization of Listeria actin comet tails by cofilin, coronin, and Aip1

Actin filaments in cells depolymerize rapidly despite the presence of high concentrations of polymerizable G actin. Cofilin is recognized as a key regulator that promotes actin depolymerization. In this study, we show that although pure cofilin can disassemble Listeria monocytogenes actin comet tails, it cannot efficiently disassemble comet tails in the presence of polymerizable actin. Thymus extracts also rapidly disassemble comet tails, and this reaction is more efficient than pure cofilin when normalized to cofilin concentration. By biochemical fractionation, we identify Aip1 and coronin as two proteins present in thymus extract that facilitate the cofilin-mediated disassembly of Listeria comet tails. Together, coronin and Aip1 lower the amount of cofilin required to disassemble the comet tail and permit even low concentrations of cofilin to depolymerize actin in the presence of polymerizable G actin. The cooperative activities of cofilin, coronin, and Aip1 should provide a biochemical basis for understanding how actin filaments can grow in some places in the cell while shrinking in others

Computational modelling of T-cell formation kinetics: output regulated by initial proliferation-linked deferral of developmental competence

Bone-marrow-derived progenitors must continually enter the thymus of an adult mouse to sustain T-cell homeostasis, yet only a few input cells per day are sufficient to support a yield of 5 × 10^7 immature T-cells per day and an eventual output of 1–2 × 10^6 mature cells per day. While substantial progress has been made to delineate the developmental pathway of T-cell lineage commitment, still little is known about the relationship between differentiation competence and the remarkable expansion of the earliest (DN1 stage) T-cell progenitors. To address this question, we developed computational models where the probability to progress to the next stage (DN2) is related to division number. To satisfy differentiation kinetics and overall cell yield data, our models require that adult DN1 cells divide multiple times before becoming competent to progress into DN2 stage. Our findings were subsequently tested by in vitro experiments, where putative early and later-stage DN1 progenitors from the thymus were purified and their progression into DN2 was measured. These experiments showed that the two DN1 sub-populations divided with similar rates, but progressed to the DN2 stage with different rates, thus providing experimental evidence that DN1 cells increase their commitment probability in a cell-intrinsic manner as they undergo cell division. Proliferation-linked shifts in eligibility of DN1 cells to undergo specification thus control kinetics of T-cell generation