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Rifkin, S. A.

Publications and source records attributed to Rifkin, S. A..

2 recordsLinked to original sources

Genome-wide fitness assessment during diurnal growth reveals an expanded role of the cyanobacterial circadian clock protein KaiA

The recurrent pattern of light and darkness generated by Earths axial rotation has profoundly influenced the evolution of organisms, selecting for both biological mechanisms that respond acutely to environmental changes and circadian clocks that program physiology in anticipation of daily variations. The necessity to integrate environmental responsiveness and circadian programming is exemplified in photosynthetic organisms such as cyanobacteria, which depend on light-driven photochemical processes. The cyanobacterium Synechococcus elongatus PCC 7942 is an excellent model system for dissecting these entwined mechanisms. Its core circadian oscillator, consisting of three proteins KaiA, KaiB, and KaiC, transmits time-of-day signals to clock-output proteins, which reciprocally regulate global transcription. Research performed under constant light facilitates analysis of intrinsic cycles separately from direct environmental responses, but does not provide insight into how these regulatory systems are integrated during light-dark cycles. Thus, we sought to identify genes that are specifically necessary in a day-night environment. We screened a dense bar-coded transposon library in both continuous light and daily cycling conditions and compared the fitness consequences of loss of each nonessential gene in the genome. Although the clock itself is not essential for viability in light-dark cycles, the most detrimental mutations revealed by the screen were those that disrupt KaiA. The screen broadened our understanding of light-dark survival in photosynthetic organisms, identified unforeseen clock-protein interaction dynamics, and reinforced the role of the clock as a negative regulator of a night-time metabolic program that is essential for S. elongatus to survive in the dark.\n\nSignificanceUnderstanding how photosynthetic bacteria respond to and anticipate natural light-dark cycles is necessary for predictive modeling, bioengineering, and elucidating metabolic strategies for diurnal growth. Here, we identify the genetic components that are important specifically under light-dark cycling conditions and determine how a properly functioning circadian clock prepares metabolism for darkness, a starvation period for photoautotrophs. This study establishes that the core circadian clock protein KaiA is necessary to enable rhythmic de-repression of a night-time circadian program.

microbiology

Natural Genetic Variation Modifies Gene Expression Dynamics at the Protein Level During Pheromone Response in Saccharomyces cerevisiae

Heritable variation in gene expression patterns plays a fundamental role in trait variation and evolution, making understanding the mechanisms by which genetic variation acts on gene expression patterns a major goal for biology. Both theoretical and empirical work have largely focused on variation in steady-state mRNA levels and mRNA synthesis rates, particularly of protein-coding genes. Yet in order for this variation to affect higher order traits it must lead to differences at the protein level. Variation in protein-specific processes including protein synthesis rates and protein decay rates could amplify, mask, or even reverse effects transmitted from the transcript level, but the extent to which this happens is unclear. Moreover, mechanisms that underlie protein expression variation under dynamic conditions have not been examined. To address this challenge, we analyzed how mRNA and protein expression dynamics covary between two strains of Saccharomyces cerevisiae during mating pheromone response. Although divergent steady-state mRNA expression levels explained divergent steady-state protein levels for four out of five genes in our study, the same was true for only one out of five genes for expression dynamics. By integrating decay rate and allele-specific protein expression analyses, we resolved that expression divergence for Fig1p was caused by genetic variation acting in trans on protein synthesis rate, expression divergence for Ina1p was caused by cis-by-trans epistatic effects on transcript level and protein synthesis rate, and expression divergence for Fus3p and Tos6p were caused by divergence in protein synthesis rates. Our study demonstrates that steady-state analysis of gene expression is insufficient to understand the impact of genetic variation on gene expression variation. An integrated and dynamic approach to gene expression analysis - comparing mRNA levels, protein levels, protein decay rates, and allele-specific protein expression - allows for a detailed analysis of the genetic mechanisms underlying protein expression divergences.

genetics