Biology subjects

Gilchrist, M. A.

Publications and source records attributed to Gilchrist, M. A..

8 recordsLinked to original sources

bioRxiv2026

Three catalase-peroxidases promote extended stationary phase survival of Vibrio natriegens during ecologically relevant exposures to exogenous hydrogen peroxide

Vibrio natriegens is an emerging model organism in laboratory and biotechnology research that is known for its fast growth rate and diverse metabolic capabilities. However, little is known about its response to oxidative stress. Reactive oxygen species (ROS) are ubiquitous stressors for most aerobic life and without mitigation can lead to cellular damage and sometimes death. V. natriegens is unusual amongst the Vibrio genus and Proteobacterial phylum in having three copies of katG encoding the bifunctional ROS defense enzyme catalase-peroxidase. The biological significance of having three copies of this protective gene was investigated with phylogenetics and gene inactivation studies. We determined that two of the katG copies arose recently via duplication and subsequent divergence. Analysis of single, double, and triple {Delta}katG constructs revealed each katG gene product contributes to survival during exposure to ecologically relevant concentrations of exogenous hydrogen peroxide (HOOH) under stationary phase conditions but found the genes were dispensable for HOOH resistance during exponential growth. We also demonstrated the involvement of the RpoS regulon in V. natriegens oxidative stress response in stationary phase. As an outcome of this investigation, we identified and repaired several spontaneous loss-of-function mutations of rpoS in laboratory cultures of the V. natriegens type strain ATCC 14048. Together, these results provide physiological and evolutionary insights into V. natriegens ROS response.

microbiology↗

bioRxiv2024

The Importance of Nonsense Errors: Estimating the Rate and Implications of Drop-Off Errors during Protein Synthesis

The process of mRNA translation is both energetically costly and relatively error-prone compared to transcription and replication. Nonsense errors during mRNA translation occur when a ribosome drops off a transcript before reaching a stop codon, resulting in energetic investment in an incomplete and likely non-functional protein. Nonsense errors impose a potentially significant energy burden on the cell, making it critical to quantify their frequency and energetic cost. Here, we present a model of ribosome movement for estimating protein production, elongation, and nonsense error rates from high-throughput ribosome profiling data. Applying this model to an exemplary ribosome profiling dataset in S. cerevisiae, we find that nonsense error rates vary between codons, in conflict with the general assumption of uniform rates across sense codons. Using our parameter estimates, we find multiple lines of evidence that selection against nonsense errors is a prominent force shaping coding-sequence evolution, including that nonsense errors place an energetic burden on cells comparable to ribosome pausing. Our results indicate greater consideration should be given to the impact of nonsense errors in shaping coding-sequence evolution. Author SummaryThe process of mRNA translation is both energetically expensive and relatively error-prone. As such, natural selection is thought to shape the evolution of CDSs to reduce the cost of these errors when they occur. Nonsense errors (NSEs) occur when a ribosome stops translation prior to completing a functional protein, resulting in wasted energy on non-functional product. Despite their functional consequences, NSEs and their effects on sequence evolution are generally understudied compared to other types of translation errors. This is in part due to the challenge of quantifying these errors from omics-scale data. We present a model for quantifying codon-specific estimates of elongation and NSE rates from ribosome profiling data, which gives a snapshot of the actively translating ribosomes in a cell. Although it is well-established that sense codons vary in their elongation rates, we find evidence that codons also vary in their NSE rates. Using our parameter estimates, we find multiple lines of evidence for selection against NSEs shaping patterns of codon usage bias. Our results suggest the cost of NSEs are comparable to the cost of ribosome pausing, and thus may play a greater role in coding-sequence evolution than previously appreciated.

evolutionary biology↗

bioRxiv2023

Profiling Expression Strategies for a Type III Polyketide Synthase in a Lysate-Based, Cell-free System

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli frequently results in a myriad of unpredictable issues with protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts, such as BGC refactoring, can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as 1) a valuable expression platform for enzymes that are challenging to synthesize in vivo, and as 2) a testbed for rapid prototyping that can improve cellular expression. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We synergistically tune promoter and codon usage to improve flaviolin production from cell-free expressed RppA. We then assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs. By showing the coordinators between CFE versus in vivo expression, this work advances CFE as a tool for natural product research. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/569483v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1aebfceorg.highwire.dtl.DTLVardef@1b289f1org.highwire.dtl.DTLVardef@7e46b4org.highwire.dtl.DTLVardef@53f480_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2020

Quantifying shifts in natural selection on codon usagebetween protein regions: A population genetics approach

BackgroundCodon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. ResultsHere we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure. As a result, our approach avoids the problem of needing to choose a specific metric of codon usage, naturally takes amino acid usage of a region into account, and explicitly takes variation in gene expression into account. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection between structures are subtle and/or intermittent. While the magnitude of differences in selection are slight, our results indicate the relationship between codon usage and protein structure is more complex than previously believed. ConclusionsWhile our results clearly indicate that selection on codon usage shifts between secondary structure, the overall impact of these shifts on codon usage are small. Nevertheless, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach are discussed.

evolutionary biology↗

bioRxiv2019

Gene Expression of Functionally-Related Genes Coevolves Across Fungal Species: Detecting Coevolution of Gene Expression Using Phylogenetic Comparative Methods

BackgroundResearchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate. ResultsWe compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric. ConclusionsOur work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.

evolutionary biology↗

bioRxiv2019

The Implications of Over-Estimating Gene Tree Discordance on a Rapid-Radiation Species Tree (Blattodea: Blaberidae)

Patterns of discordance between gene trees and the species trees they reside in are crucial to the debate over the superiority of coalescent or concatenation approaches to tree inference. However, errors in estimating gene tree topologies obfuscate the issue by making gene trees appear erroneously discordant with the species tree. We thus test the prevalence of discordance between gene trees and their species tree using an empirical dataset for a clade with a rapid radiation (Blaberidae). We find that one model of codon evolution (FMutSel0) prefers gene trees that are less discordant, while another (SelAC) shows no such preference. We compare the species trees resulting from the selected sets of gene trees on the basis of internal consistency, predictive ability, and congruence with independent data. The species tree resulting from gene trees those chosen by FMutSel0, a set with low discordance, is the most robust and biologically plausible. Thus, we conclude that the results from FMutSel0 are better supported: simple models (i.e., GTR and ECM) infer trees with erroneously high levels of gene tree discordance. Furthermore, the amount of discordance in the set of gene trees has a large effect on the downstream phylogeny. Thus, decreasing gene tree error by lessening erroneous discordance can result in higher quality species trees. These results allow us to support relationships among blaberid cockroaches that were previously in flux as they now demonstrate molecular and morphological congruence.

evolutionary biology↗

bioRxiv2019

Decomposing Mutation and Selection to Identify Mismatched Codon Usage

For decades, codon usage has been used as a measure of adaptation for translational efficiency and translation accuracy of a genes coding sequence. These patterns of codon usage reflect both the selective and mutational environment in which the coding sequences evolved. Over this same period, gene transfer between lineages has become widely recognized as an important biological phenomenon. Nevertheless, most studies of codon usage implicitly assume that all genes within a genome evolved under the same selective and mutational environment, an assumption violated when introgression occurs. In order to better understand the effects of introgression on codon usage patterns and vice versa, we examine the patterns of codon usage in Lachancea kluyveri, a yeast which has experienced a large introgression. We quantify the effects of mutation bias and selection for translation efficiency on the codon usage pattern of the endogenous and introgressed exogenous genes using a Bayesian mixture model, ROC SEMPPR, which is built on mechanistic assumptions about protein synthesis and grounded in population genetics. We find substantial differences in codon usage between the endogenous and exogenous genes, and show that these differences can be largely attributed to differences in mutation bias favoring A/T ending codons in the endogenous genes while favoring C/G ending codons in the exogenous genes. Recognizing the two different signatures of mutation bias and selection improves our ability to predict protein synthesis rate by 42% and allowed us to accurately assess the decaying signal of endogenous codon mutation and preferences. In addition, using our estimates of mutation bias and selection, we identify Eremothecium gossypii as the closest relative to the exogenous genes, providing an alternative hypothesis about the origin of the exogenous genes, estimate that the introgression occurred [~] 6 x 108 generation ago, and estimate its historic and current selection against mismatched codon usage. Our work illustrates how mechanistic, population genetic models like ROC SEMPPR can separate the effects of mutation and selection on codon usage and provide quantitative estimates from sequence data.

evolutionary biology↗

bioRxiv2018

Quantifying Selection on Codon Usage in Signal Peptides: Gene Expression and Amino Acid Usage Explain Apparent Selection for Inefficient Codons

The Sec secretion pathway is found across all domains of life. A critical feature of Sec secreted proteins is the signal peptide, a short peptide with distinct physicochemical properties located at the N-terminus of the protein. Previous work indicates signal peptides are biased towards translationally inefficient codons, which is hypothesized to be an adaptation driven by selection to improve the efficacy and efficiency of the protein secretion mechanisms. We investigate codon usage in the signal peptides of E. coli using the Codon Adaptation Index (CAI), the tRNA Adaptation Index (tAI), and the ribosomal overhead cost formulation of the stochastic evolutionary model of protein production rates (ROC-SEMPPR). Comparisons between signal peptides and 5-end of cytoplasmic proteins using CAI and tAI are consistent with a preference for inefficient codons in signal peptides. Simulations reveal these differences are due to amino acid usage and gene expression - we find these differences disappear when accounting for both factors. In contrast, ROC-SEMPPR, a mechanistic population genetics model capable of separating the effects of selection and mutation bias, shows codon usage bias (CUB) of the signal peptides is indistinguishable from the 5-ends of cytoplasmic proteins. Additionally, we find CUB at the 5-ends is weaker than later segments of the gene. Results illustrate the value in using models grounded in population genetics to interpret genetic data. We show failure to account for mutation bias and the effects of gene expression on the efficacy of selection against translation inefficiency can lead to a misinterpretation of codon usage patterns.

evolutionary biology↗