Biology subjects

Olin K Silander

Publications and source records attributed to Olin K Silander.

2 recordsLinked to original sources

bioRxiv2016

Combining Shigella Tn-seq data with Gold-standard E. coli Gene Deletion Data Suggests Rare Transitions between Essential and Non-essential Gene Functionality

Gene essentiality - whether or not a gene is necessary for cell growth - is a fundamental component of gene function. It is not well established how quickly gene essentiality can change, as few studies have compared empirical measures of essentiality between closely related organisms. Here we present the results of a Tn-seq experiment designed to detect essential protein coding genes in the bacterial pathogen Shigella flexneri 2a 2457T on a genome-wide scale. Superficial analysis of this data suggested that 451 protein-coding genes in this Shigella strain are critical for robust cellular growth on rich media. Comparison of this set of genes with a gold-standard data set of essential genes in the closely related Escherichia coli K12 BW25113 suggested that an excessive number of genes appeared essential in Shigella but non-essential in E. coli. Importantly, and in converse to this comparison, we found no genes that were essential in E. coli and non-essential in Shigella, suggesting that many genes were artefactually inferred as essential in Shigella. Controlling for such artefacts resulted in a much smaller set of discrepant genes. Among these, we identified three sets of functionally related genes, two of which have previously been implicated as critical for Shigella growth, but which are dispensable for E. coli growth. The data presented here highlight the small number of protein coding genes for which we have strong evidence that their essentiality status differs between the closely related bacterial taxa E. coli and Shigella. A set of genes involved in acetate utilization provides a canonical example. These results leave open the possibility of developing strain-specific antibiotic treatments targeting such differentially essential genes, but suggest that such opportunities may be rare in closely related bacteria.

Evolutionary Biology↗

bioRxiv2014

Expression noise facilitates the evolution of gene regulation

In studies of gene regulation, it is often tacitly assumed that the interactions between transcriptional regulators and their target promoters are finely tuned to ensure condition-appropriate gene expression of the targets. However, how natural selection might evolve such precise regulation from an initial state without regulation, is rarely discussed. In addition, the accuracy of gene regulation is affected by noise in gene expression [1]. Expression noise varies greatly across genes [2-5], suggesting that natural selection has affected noise levels, but the role of expression noise in gene regulation is currently poorly understood [6]. Here we present a combination of experimental evidence and theoretical modeling showing that the transmission of expression noise from regulators to their targets can function as a rudimentary form of gene regulation that facilitates the evolution of more finely tuned gene regulation. To assess how natural selection has affected transcriptional noise in E. coli, we evolved a large set of synthetic promoters under carefully controlled selective conditions and found, surprisingly, that native E. coli promoters show no signs of having been selected for minimizing their noise. Instead, a subset of native promoters, which are characterized by high expression plasticity and high numbers of regulatory inputs, show elevated noise levels. A general theoretical model, which recognizes that target genes are not only affected by the condition-dependent activities of their regulators, but also by the regulators noise, explains these observations. Noise transmission from regulators to their targets is favored by selection whenever regulation is imprecise, and may even constitute the main function of coupling a promoter to a regulator. Our theory provides a novel framework for understanding the evolution of gene regulation, demonstrating that in many situations expression noise is not the mere unwanted side-effect of regulatory interactions, but a beneficial function that is key to the evolvability of regulatory interactions.

Systems Biology↗