Metabolic gene regulation in a dynamically changing environment.

Natural selection dictates that cells constantly adapt to dynamically changing environments in a context-dependent manner. Gene-regulatory networks often mediate the cellular response to perturbation, and an understanding of cellular adaptation will require experimental approaches aimed at subjecting cells to a dynamic environment that mimics their natural habitat. Here we monitor the response of Saccharomyces cerevisiae metabolic gene regulation to periodic changes in the external carbon source by using a microfluidic platform that allows precise, dynamic control over environmental conditions. We show that the metabolic system acts as a low-pass filter that reliably responds to a slowly changing environment, while effectively ignoring fast fluctuations. The sensitive low-frequency response was significantly faster than in predictions arising from our computational modelling, and this discrepancy was resolved by the discovery that two key galactose transcripts possess half-lives that depend on the carbon source. Finally, to explore how induction characteristics affect frequency response, we compare two S. cerevisiae strains and show that they have the same frequency response despite having markedly different induction properties. This suggests that although certain characteristics of the complex networks may differ when probed in a static environment, the system has been optimized for a robust response to a dynamically changing environment.

Antagonistic gene transcripts regulate adaptation to new growth environments.

Cells have evolved complex regulatory networks that reorganize gene expression patterns in response to changing environmental conditions. These changes often involve redundant mechanisms that affect various levels of gene expression. Here, we examine the consequences of enhanced mRNA degradation in the galactose utilization network of Saccharomyces cerevisiae. We observe that glucose-induced degradation of GAL1 transcripts provides a transient growth advantage to cells upon addition of glucose. We show that the advantage arises from relief of translational competition between GAL1 transcripts and those of cyclin CLN3, a translationally regulated initiator of cell division. This competition creates a translational bottleneck that balances the production of Gal1p and Cln3p and represents a posttranscriptional control mechanism that enhances the cell's ability to adapt to changes in carbon source. We present evidence that the spatial regulation of GAL1 and CLN3 transcripts is what allows growth to be maintained during fluctuations of glucose availability. Our results provide unique insights into how cells optimize energy use during growth in a dynamic environment.

Partner choice during meiosis is regulated by Hop1-promoted dimerization of Mek1.

Meiotic recombination differs from mitotic recombination in that DSBs are repaired using homologous chromosomes, rather than sister chromatids. This change in partner choice is due in part to a barrier to sister chromatid repair (BSCR) created by the meiosis-specific kinase, Mek1, in a complex with two other meiosis-specific proteins, Hop1 and Red1. HOP1 contains two functional domains, called the N and C domains. Analysis of a point mutation that specifically inactivates the C domain (hop1-K593A) reveals that the N domain is sufficient for Hop1 localization to chromosomes and for Red1 and Hop1 interactions. The C domain is needed for spore viability, for chromosome synapsis, and for preventing DMC1-independent DSB repair, indicating it plays a role in the BSCR. All of the hop1-K593A phenotypes can be bypassed by fusion of ectopic dimerization domains to Mek1, suggesting that the function of the C domain is to promote Mek1 dimerization. Hop1 is a DSB-dependent phosphoprotein, whose phosphorylation requires the presence of the C domain, but is independent of MEK1. These results suggest a model in which Hop1 phosphorylation in response to DSBs triggers dimerization of Mek1 via the Hop1 C domain, thereby enabling Mek1 to phosphorylate target proteins that prevent repair of DSBs by sister chromatids.

Flavin-based metabolic cycles are integral features of growth and division in single yeast cells.

The yeast metabolic cycle (YMC) is a fascinating example of biological organization, in which cells constrain the function of specific genetic, protein and metabolic networks to precise temporal windows as they grow and divide. However, understanding the intracellular origins of the YMC remains a challenging goal, as measuring the oxygen oscillations traditionally associated with it requires the use of synchronized cultures growing in nutrient-limited chemostat environments. To address these limitations, we used custom-built microfluidic devices and time-lapse fluorescence microscopy to search for metabolic cycling in the form of endogenous flavin fluorescence in unsynchronized single yeast cells. We uncovered robust and pervasive metabolic cycles that were synchronized with the cell division cycle (CDC) and oscillated across four different nutrient conditions. We then studied the response of these metabolic cycles to chemical and genetic perturbations, showing that their phase synchronization with the CDC can be altered through treatment with rapamycin, and that metabolic cycles continue even in respiratory deficient strains. These results provide a foundation for future studies of the physiological importance of metabolic cycles in processes such as CDC control, metabolic regulation and cell aging.

Measuring competitive fitness in dynamic environments.

Most yeast genes are dispensable for optimal growth in laboratory cultures. However, this apparent lack of fitness contribution is difficult to reconcile with the theory of natural selection. Here we use stochastic modeling to show that environmental fluctuations can select for a genetic mechanism that does not affect growth in static laboratory environments. We then present a novel experimental platform for measuring the fitness levels of specific genotypes in fluctuating environments. We test this platform by monitoring a mixed culture of two yeast strains that differ in their ability to respond to changes in carbon source yet exhibit the same fitness level in static conditions. When the sugar in the growth medium was switched between galactose and glucose, the wild-type strain gained a growth advantage over the mutant strain. Interestingly, both our computational and experimental results show that the strength of the adaptive advantage conveyed by the wild-type genotype depends on the total number of carbon source switches, not on the frequency of these fluctuations. Our results illustrate the selective power of environmental fluctuations on seemingly slight phenotypic differences in cellular response dynamics and underscore the importance of dynamic processes in the evolution of species.

A map of the interactome network of the metazoan C. elegans.

To initiate studies on how protein-protein interaction (or "interactome") networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together with already described Y2H interactions and interologs predicted in silico, the current version of the Worm Interactome (WI5) map contains approximately 5500 interactions. Topological and biological features of this interactome network, as well as its integration with phenome and transcriptome data sets, lead to numerous biological hypotheses.