The mutual repression between Pax2 and Snail factors regulates the epithelial/mesenchymal state during intermediate mesoderm differentiation

The pronephros is the first renal structure in the embryo, arising after mesenchymal to epithelial transition (MET) of the intermediate mesoderm, where Pax2 induces epithelialization of the mesenchyme. Here we show that, in the early embryo, Snail1 directly represses Pax2 transcription maintaining the intermediate mesoderm in an undifferentiated state. Reciprocally, Pax2 directly represses Snail1 expression to induce MET upon receiving differentiation signals. We also show that BMP7 acts as one such signal by downregulating Snail1 and upregulating Pax2 expression. This, together with the Snail1/Pax2 reciprocal repression, establish a regulatory loop in a defined region along the anteroposterior axis, the bi-stability domain within the transition zone, where differentiation of the neural tube and the somites is known to occur. Thus, we show that the antagonism between Snail1 and Pax2 determines the epithelial/mesenchymal state during the differentiation of the intermediate mesoderm and propose that the bi-stability zone extends to the intermediate mesoderm, synchronizing the differentiation of tissues aligned along the mediolateral embryonic axis.

Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation

Background Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network. Results We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory. Conclusions Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity when designing synthetic circuits with memory function.

Altering the temporal regulation of one transcription factor drives sensory trade-offs

SUMMARYSize trade-offs of visual versus olfactory organs is a pervasive feature of animal evolution. Comparing Drosophila species, we find that larger eyes correlate with smaller antennae, where olfactory organs reside, and narrower faces. We demonstrate that this tradeoff arises through differential subdivision of the head primordium into visual versus non-visual fields. Specification of the visual field requires a highly-conserved eye development gene called eyeless in flies and Pax6 in humans. We discover that changes in the temporal regulation of eyeless expression during development is a conserved mechanism for sensory trade-offs within and between Drosophila species. We identify a natural single nucleotide polymorphism in the cis-regulatory region of eyeless that is sufficient to alter its temporal regulation and eye size. Because Pax6 is a conserved regulator of sensory placode subdivision, we propose that alterations in the mutual repression between sensory territories is a conserved mechanism for sensory trade-offs in animals.

Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation

BackgroundCellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network.ResultsWe find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory.ConclusionsOur work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity to designing synthetic circuits with memory function.

Design Principles of Lambda’s Lysis/Lysogeny Decision vis-a-vis Multiplicity of Infection

Bacteriophage lambda makes a decision between lysis and lysogeny based on the number of coinfecting phages, namely the multiplicity of infection (MoI): lysis at low MoIs; lysogeny at high MoIs. Here, by evaluating various rationally designed models on their ability a) to make the lytic decision at MoI of 1 and the lysogeny decision at MoI of 2, b) to exhibit bistability at both MoIs, and c) to perform accurately in the presence of noise, it is demonstrated that lambda’s lysis/lysogeny decision is based on three features, namely a) mutual repression, b) cooperative positive autoregulation of CI, and c) cooperative binding of the activator protein, not basal expression, triggering positive autoregulatory loop of CI. Cro and CI are sufficient to acquire the first two features. CII is required to acquire the third feature. The quasi-minimal two-protein model for the switch is justified by showing its qualitative equivalence, except for Cro repression of pRM, to the lambda’s gene regulatory network responsible for the decision. A three-protein simplified version of the lambda’s switch is shown to possess all the three design features. Bistability at MoI of 1 is responsible for lysogen stability, whereas bistability at MoI of 2 imparts stability to lytic development post-infection and especially during prophage induction.

Dynamic regulation of Nanog and stem cell-signaling pathways by Hoxa1 during early neuro-ectodermal differentiation of ES cells

Homeobox a1 (Hoxa1) is one of the most rapidly induced genes in ES cell differentiation and it is the earliest expressed Hox gene in the mouse embryo. In this study, we used genomic approaches to identify Hoxa1-bound regions during early stages of ES cell differentiation into the neuro-ectoderm. Within 2 h of retinoic acid treatment, Hoxa1 is rapidly recruited to target sites that are associated with genes involved in regulation of pluripotency, and these genes display early changes in expression. The pattern of occupancy of Hoxa1 is dynamic and changes over time. At 12 h of differentiation, many sites bound at 2 h are lost and a new cohort of bound regions appears. At both time points the genome-wide mapping reveals that there is significant co-occupancy of Nanog (Nanog homeobox) and Hoxa1 on many common target sites, and these are linked to genes in the pluripotential regulatory network. In addition to shared target genes, Hoxa1 binds to regulatory regions of Nanog, and conversely Nanog binds to a 3′ enhancer of Hoxa1. This finding provides evidence for direct cross-regulatory feedback between Hoxa1 and Nanog through a mechanism of mutual repression. Hoxa1 also binds to regulatory regions of Sox2 (sex-determining region Y box 2), Esrrb (estrogen-related receptor beta), and Myc, which underscores its key input into core components of the pluripotential regulatory network. We propose a model whereby direct inputs of Nanog and Hoxa1 on shared targets and mutual repression between Hoxa1 and the core pluripotency network provides a molecular mechanism that modulates the fine balance between the alternate states of pluripotency and differentiation.