Quantitative analysis of biological decision switches

Biological organisms from multicellular eukaryotes to bacteria and even viruses often exhibit multiple alternative phenotypes or behaviors to adapt to various environmental stimuli. Therefore, an organism chooses one phenotype among multiple alternatives, and we call this process a decision switch. Here we focus on decision switches at the cellular level, and investigate decision switches mediated by gene regulation. Even if environmental stimuli provide inputs for gene regulation, it is intrinsically stochastic, and an isogenic population may exhibit different phenotypes even under almost identical conditions. We focus on two particular aspects of biological decision switches at the cellular level: (1) how changes in copy numbers of genetic components affect gene expression and facilitate multiple alternative phenotypes and (2) how temporal dynamics of gene regulation mediate alternative cell fates and lead to future cell fates.;To study the effect of copy number of genetic components on gene expression, we present a quantitative model of the phage lambda decision switch based on models of gene regulatory dynamics. By treating copy numbers of viral genes as variables, we show that the decision between lysis and lysogeny can sensitively depend on the number of coinfecting phages. Therefore, our results suggest that even viruses can adapt their behaviors collectively by sharing their gene products within a host cell. We also show that strong nonlinearity within the gene regulatory networks can lead to bistability, hence facilitate alternative phenotypes. Then we also model other commonly observed genetic circuits while systematically varying copy numbers of genetic circuits. Analyses of these genetic circuits demonstrate that the gene copy number is an omnipresent parameter that can facilitate alternative phenotypes, and small changes in copy number may lead to drastic changes in gene expression. Further, changes in the copy number of a three-gene motif with successive inhibition can switch between oscillatory and stationary dynamics. In all cases, the qualitative change in gene expression is due to the nonlinear nature of transcriptional feedback.;To investigate how alternative cell fates are mediated by temporal dynamics of gene regulation, we revisit the lysis-lysogeny decision switch of bacteriophages in which cell fates are determined by temporal dynamics of gene regulation unlike the earlier model. We find that increasing the number of coinfecting phages increases the chance of quiescent viral growth, in agreement with prior experimental studies. Predicted heterogeneity in cell fates is shown to agree with experimental data when including a previously unidentified gene dosage compensation mechanism, which represents an alternative hypothesis to explain how multiple phages interact in influencing cell fate. Next we study how cell fates can be predicted given temporal dynamics of gene expression. To do so, we present a quantitative measure of cell fate predictability. Our analyses of simple model systems suggest temporal dynamics of gene expression can be highly correlated with eventual cell fates. Thus, our study quantifies when and how the current state of a cell may serve as an indicator of its future. xiii.