Cells growing in a constant environment, such as a laboratory culture, are free to dedicate all of their resources to growth and division and often reach their maximal growth rate. However, in the natural world, cells rarely if ever experience static conditions. Whether they exist as a single cell or as part of a large multicellular organism, natural-living cells must cope with frequent changes to their surroundings. To survive in a dynamic environment, cells are equipped with gene networks that allow growth to continue in spite of changing conditions. This exibility comes at a price, and cells experiencing environmental uctuations usually do not attain their fastest growth rate. To fully understand the interface between cell growth and dynamic metabolism, we must study cells as they grow in a changing environment. In the proposed project, we will use the yeast galactose network as a paradigm of environment-sensitive gene regulation to ask how cells balance the need to respond to changes in the growth medium against the pressure to maintain growth. Throughout this study, we will rely on innovative microuidic tools to grow and observe single cells in precisely controlled dynamic environments. The dynamic data we collect will inform a set of mathematical models that will be used to identify key points of regulation in the galactose network, which will then be rigorously, tested using previously established molecular biology techniques. This multi-disciplinary approach will bolster our ability to identify new mechanisms of gene regulation that specially inuence the way cells perceive the growth environment, which are diffcult to observe in standard laboratory cultures. Our rst aim will be to study the eects of regulatory loops inherent to the galactose network on the sensitivity of cells to available carbon sources, and to determine how they contribute to the metabolic cost of growth on galactose. In previous work, we observed that the transcripts of several galactose network genes are spatially regulated. In the second aim, we will focus on the localization of these transcripts to test the hypothesis that the spatial regulation of gene expression can lead to ne temporal control in the cellular response to environmental signals. Our preliminary data show that the synthesis of galactose proteins is negatively eected by the mRNA of a specic cell cycle regulator. In the third aim, we will use queuing theory to explain how a competition for translation between specic transcripts can lead to a coupling of cell division and galactose metabolism and result in slower growth rates when glucose is unavailable. Finally, in the fourth aim, we will study the function of the regulatory loops of the galactose pathway by determining the robustness of the network in the context of varying degrees of competitive protein synthesis. The successful completion of this project will lead to advances in our understanding of how cells solve the universal biological problem of survival in an unpredictable environment. This work will be particularly relevant to understanding the mechanisms involved in balancing growth rate according to environmental cues, as is important in cancer biology, tissue patterning, and embryonic development. 1
Cells rarely experience a constant environment. However, much of what we know of cellular function is derived from static experimental conditions. This project uses computational modeling and microu- idic technology to explore the interface between cell growth and metabolism in a dynamically changing environment.
| Hossain, Munshi Azad; Claggett, Julia M; Edwards, Samantha R et al. (2016) Posttranscriptional Regulation of Gcr1 Expression and Activity Is Crucial for Metabolic Adjustment in Response to Glucose Availability. Mol Cell 62:346-358 |
| Mather, William H; Hasty, Jeff; Tsimring, Lev S et al. (2013) Translational cross talk in gene networks. Biophys J 104:2564-72 |
| Selimkhanov, Jangir; Hasty, Jeff; Tsimring, Lev S (2012) Recent advances in single-cell studies of gene regulation. Curr Opin Biotechnol 23:34-40 |
| Mather, William H; Hasty, Jeff; Tsimring, Lev S (2012) Fast stochastic algorithm for simulating evolutionary population dynamics. Bioinformatics 28:1230-8 |
| Jin, Meng; Errede, Beverly; Behar, Marcelo et al. (2011) Yeast dynamically modify their environment to achieve better mating efficiency. Sci Signal 4:ra54 |
| Mather, W H; Hasty, J; Tsimring, L S et al. (2011) Factorized time-dependent distributions for certain multiclass queueing networks and an application to enzymatic processing networks. Queueing Syst 69:313-328 |
| Cookson, Natalie A; Mather, William H; Danino, Tal et al. (2011) Queueing up for enzymatic processing: correlated signaling through coupled degradation. Mol Syst Biol 7:561 |
| Baumgartner, Bridget L; Bennett, Matthew R; Ferry, Michael et al. (2011) Antagonistic gene transcripts regulate adaptation to new growth environments. Proc Natl Acad Sci U S A 108:21087-92 |
| Castro-Longoria, Ernestina; Ferry, Michael; Bartnicki-Garcia, Salomon et al. (2010) Circadian rhythms in Neurospora crassa: dynamics of the clock component frequency visualized using a fluorescent reporter. Fungal Genet Biol 47:332-41 |
| Prindle, Arthur; Hasty, Jeff (2010) Biochemistry. Stochastic emergence of groupthink. Science 328:987-8 |
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