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Baehr, S.

Publications and source records attributed to Baehr, S..

2 recordsLinked to original sources

Consideration of a liquid mutation accumulation experiment to measure mutation rates by successive serial dilution.

The mutation-accumulation (MA) experiment is a fixture of evolutionary biology, though it is laborious to perform. MA experiments typically take between months and years to acquire sufficient mutations to measure DNA mutation rates and mutation spectra. MA experiments for many organisms rely on colony formation on agar plates and repetitive streaking, an environment which at first glance appears somewhat contrived, a poor imitation of real environmental living conditions. We propose that a fully liquid-phase mutation-accumulation experiment may at times more accurately reflect the environment of an organism. We note also that whereas automation of streaking plates is a daunting prospect, automation of liquid handling and serial dilution is already commonplace. In principle, this type of MA experiment can be automated so as to reduce the human capital requirements of measuring mutation rates. We demonstrate that a liquid MA recapitulates the mutation rate estimated for MMR- E. coli in liquid LB culture vs. plate LB culture. We detect a modified mutation spectrum with a transition skew of 4:1 of A:T[->]G:C vs G:C[->]A:T mutations, highlighting the potential role of tautomerization as a DNA mutation mechanism. We also find that using a plate reader to measure OD600 as a proxy for cell growth to be incapable of measuring carrying capacity for MA lines burdened with many mutations.

microbiology↗

A Narrow Range of Transcript-error Rates Across the Tree of Life

The expression of genomically-encoded information is not error-free. Transcript-error rates are dramatically higher than DNA-level mutation rates, and despite their transient nature, the steady-state load of such errors must impose some burden on cellular performance. However, a broad perspective on the degree to which transcript-error rates are constrained by natural selection and diverge among lineages remains to be developed. Here, we present a genome-wide analysis of transcript-error rates across the Tree of Life using a modified rolling-circle sequencing method, revealing that the range in error rates is remarkably narrow across diverse species. Transcript errors tend to be randomly distributed, with little evidence supporting local control of error rates associated with gene-expression levels. A majority of transcript errors result in missense errors if translated, and as with a fraction of nonsense transcript errors, these are underrepresented relative to random expectations, suggesting the existence of mechanisms for purging some such errors. To quantitatively understand how natural selection and random genetic drift might shape transcript-error rates across species, we present a model based on cell biology and population genetics, incorporating information on cell volume, proteome size, average degree of exposure of individual errors, and effective population size. However, while this model provides a framework for understanding the evolution of this highly conserved trait, as currently structured it explains only 20% of the variation in the data, suggesting a need for further theoretical work in this area.

evolutionary biology↗