Dual feedback loops in the GAL regulon suppress cellular heterogeneity in yeast

Abstract

Transcriptional noise is known to be an important cause of cellular heterogeneity and phenotypic variation. The extent to which molecular interaction networks may have evolved to either filter or exploit transcriptional noise is a much debated question. The yeast genetic network regulating galactose metabolism involves two proteins, Gal3p and Gal80p, that feed back positively and negatively, respectively, on GAL gene expression. Using kinetic modeling and experimental validation, we demonstrate that these feedback interactions together are important for (i) controlling the cell-to-cell variability of GAL gene expression and (ii) ensuring that cells rapidly switch to an induced state for galactose uptake.

Negative feedback confers mutational robustness in yeast transcription factor regulation

“…Characteristics of regulatory networks that confer robustness include pathway redundancy and master regulatory organization (5), phenotypic capacitors (6-8), paired activating and inhibiting inputs (9), and cooperative and feed-forward regulation (10). Additionally, negative regulatory feedback, in which a biomolecule represses its own abundance, can buffer variation in gene expression (11,12), and negative feedback loops have been shown to underlie robustness to variable environmental conditions and stochastic intracellular change (13)(14)(15). Negative feedback may also confer network stability against the effects of mutations (3,16), but evidence for negative feedback as a driver of mutational robustness in vivo has been at a premium (17); the relevance of this principle to natural genetic variation remains largely unknown.…”

Single yeast cells vary in transcription activity not in delay time after a metabolic shift

“…These findings are in agreement with earlier findings on sulphur-source shifts with yeast [48][49][50] . Earlier studies on different nutrient shifts have reported the existence of a subpopulation of cells that does not respond at all 2,3,5,6 or the occurrence of very dispersed response times 4,7,8 across a range of microbial species. In these cases, stochasticity in the cell population is large, mostly due to stochasticity in response times, leading either to a bimodal or very broad distribution of cell responses.…”

“…Then they have to rely on stochasticity-induced adaptation mechanisms. This applies for instance to E. coli with respect to lactose and for S. cerevisiae in the case of galactose 4,[7][8][9] . In such a case, the organism has to rely on leaky gene expression of dedicated permeases.…”

“…In both these cases, the lag phases of individual cells vary greatly. The fact that many different adaptation mechanisms can occur may explain the great variation in lag phase durations that have been experimentally observed, which range from minutes to days [2][3][4]7,8 .…”

“…The general interpretation is that a lag phase results from the time that it takes for the microorganism to adapt its metabolism. Several single-cell studies indicate that the cause for the lag phase can also involve stochasticity: either only a small fraction of the population grows under the new condition [2][3][4][5][6] , and the lag phase derives from the time that it takes until those cells reach a significant fraction of the total population; or cells start to grow only after a fluctuation in gene-expression activity has occurred that is large enough to kick-start the induction of the nutrient uptake pathway [7][8][9] . In both these cases, the lag phases of individual cells vary greatly.…”