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代谢基因最优密码子使用特征为 budding yeast 生态学提供信息。

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology.

机构信息

Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America.

Department of Biology, Villanova University, Villanova, Pennsylvania, United States of America.

出版信息

PLoS Biol. 2021 Apr 19;19(4):e3001185. doi: 10.1371/journal.pbio.3001185. eCollection 2021 Apr.

Abstract

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter-species that have yet to be cultured in the lab or have only been identified by genomic material.

摘要

反向生态学是从基因组变异模式推断生态信息。一个丰富的、迄今为止未被充分利用的具有生态相关性的基因组信息来源是密码子最优性或适应性。在不同的生物体中,偏向于与 tRNA 池匹配的密码子与高基因表达强烈相关,这表明密码子优化可以在反向生态学框架中用于识别高度表达的、具有生态相关性的基因。为了验证这一假设,我们研究了经典半乳糖代谢(GAL)途径中的最优密码子使用与 329 种 budding 酵母(真菌的一个多样化亚门)的已知生态位之间的关系。我们发现,GAL 途径中的最优密码子使用与半乳糖的定量生长呈正相关,这表明 GAL 密码子优化反映了在半乳糖上生长的能力增强。GAL 途径中的最优密码子使用也与 CUG-Ser1 分支中的酵母的人类相关生态位以及 Saccharomycetaceae 家族中的乳制品相关生态位呈正相关。例如,主要人类病原体白色念珠菌(CUG-Ser1 分支)的基因组中 GAL 基因的最优密码子使用大于基因组中所有基因的 85%,而乳制品酵母 Kluyveromyces lactis(Saccharomycetaceae 家族)的基因组中 GAL 基因的最优密码子使用大于 75%。我们进一步发现 GALactose 途径基因的优化与几个与营养感应和代谢相关的基因之间存在相关性。这项工作表明,密码子优化蕴藏着关于微生物真核生物代谢生态学的信息。这些信息对于研究真菌暗物质特别有用,真菌暗物质是指尚未在实验室中培养或仅通过基因组材料鉴定的物种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b68/8084343/64f27d8c9213/pbio.3001185.g001.jpg

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