Gylcolytic oscillations in yeast are a by-product of a trade-off between robustness and efficiency.

Summary Mammalian T lymphocytes are a prototype for development from adult pluripotent stem cells. While T-cell specification is driven by Notch signaling, T-lineage commitment is only finalized after prolonged Notch activation. However, no T-lineage specific regulatory factor has been reported that mediates commitment. We used a gene-discovery approach to identify additional candidate T-lineage transcription factors and characterized expression of >100 regulatory genes in early T-cell precursors using realtime RT-PCR. These regulatory genes were also monitored in multilineage precursors as they entered T-cell or non-T-cell pathways in vitro; in non-T cells ex vivo; and in later T-cell developmental stages after lineage commitment. At least three major expression patterns were observed. Transcription factors in the largest group are expressed at relatively stable levels throughout T-lineage specification as a legacy from prethymic precursors, with some continuing while others are downregulated after commitment. Another group is highly expressed in the earliest stages only, and is downregulated before or during commitment. Genes in a third group undergo upregulation at one of three distinct transitions, suggesting a positive regulatory cascade. However, the transcription factors induced during commitment are not T-lineage specific. Different members of the same transcription factor family can follow opposite trajectories during specification and commitment, while factors co-expressed early can be expressed in divergent patterns in later T-cell development. Some factors reveal new regulatory distinctions between αβ and γδ T-lineage differentiation. These results show that T-cell identity has an essentially complex regulatory basis and provide a detailed framework for regulatory network modeling of T-cell specification.

BackgroundHow tissue and organ sizes are specified is one of the great unsolved mysteries in biology. Experiments and mathematical modeling implicate feedback control of cell lineage progression, but a broad understanding of what lineage feedback accomplishes is lacking.ResultsBy exploring the possible effects of various biologically relevant disturbances on the dynamic and steady state behaviors of stem cell lineages, we find that the simplest and most frequently studied form of lineage feedback - which we term renewal control - suffers from several serious drawbacks. These reflect fundamental performance limits dictated by universal conservation-type laws, and are independent of parameter choice. Here we show that introducing lineage branches can circumvent all such limitations, permitting effective attenuation of a wide range of perturbations. The type of feedback that achieves such performance - which we term fate control - involves promotion of lineage branching at the expense of both renewal and (primary) differentiation. We discuss the evidence that feedback of just this type occurs in vivo, and plays a role in tissue growth control.ConclusionsRegulated lineage branching is an effective strategy for dealing with disturbances in stem cell systems. The existence of this strategy provides a dynamics-based justification for feedback control of cell fate in vivo.See commentary article: http://dx.doi.org/10.1186/s12915-015-0123-7.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-015-0122-8) contains supplementary material, which is available to authorized users.

Abstract-Autocatalysis is necessary and ubiquitous in both engineered and biological systems but can aggravate control performance and cause instability. We analyze the properties of autocatalysis in the universal and well studied glycolytic pathway. A simple two-state model incorporating ATP autocatalysis and inhibitory feedback control captures the essential dynamics, including limit cycle oscillations, observed experimentally. System performance is limited by the inherent autocatalytic stoichiometry and higher levels of autocatalysis exacerbate stability and performance. We show that glycolytic oscillations are not merely a "frozen accident" but a result of the intrinsic stability tradeoffs emerging from the autocatalytic mechanism. This model has pedagogical value as well as appearing to be the simplest and most complete illustration yet of Bode's integral formula.

Autocatalytic pathways are frequently encountered in biological networks. One such pathway, the glycolytic pathway, is of special importance and has been studied extensively. Using tools from linear systems theory, our previous work on a simple two dimensional model of glycolysis demonstrated that autocatalysis can aggravate control performance and contribute to instability. Here, we expand this work and study properties of nonlinear autocatalytic pathway models (of which glycolysis is an example). Changes in the concentration of metabolites and catalyzing enzymes during the lifetime of the cell can perturb the system from the nominal operating point of the pathway. We investigate effects of such perturbations through the estimation of invariant subsets of the region of attraction around nominal operating conditions (i.e., a measure of the set of perturbations from which the cell recovers). Numerical experiments demonstrate that systems that are robust with respect to perturbations in parameter space have easily "verifiable" region of attraction properties in terms of proof complexity.