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朝向最小细菌蛋白质组的完全功能特征描述。

Toward the Complete Functional Characterization of a Minimal Bacterial Proteome.

机构信息

Department of Chemistry, University of Illinois Urbana-Champaign, 600 S Mathews Ave, Urbana, Illinois 61801, United States.

Centro Nacional de Biotecnologia, Calle Darwin no. 3, 28049 Madrid, Spain.

出版信息

J Phys Chem B. 2022 Sep 15;126(36):6820-6834. doi: 10.1021/acs.jpcb.2c04188. Epub 2022 Sep 1.

DOI:10.1021/acs.jpcb.2c04188
PMID:36048731
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9483919/
Abstract

Recently, we presented a whole-cell kinetic model of the genetically minimal bacterium JCVI-syn3A that described the coupled metabolic and genetic information processes and predicted behaviors emerging from the interactions among these networks. JCVI-syn3A is a genetically reduced bacterial cell that has the fewest number and smallest fraction of genes of unclear function, with approximately 90 of its 452 protein-coding genes (that is less than 20%) unannotated. Further characterization of unclear JCVI-syn3A genes strengthens the robustness and predictive power of cell modeling efforts and can lead to a deeper understanding of biophysical processes and pathways at the cell scale. Here, we apply computational analyses to elucidate the functions of the products of several essential but previously uncharacterized genes involved in integral cellular processes, particularly those directly affecting cell growth, division, and morphology. We also suggest directed wet-lab experiments informed by our analyses to further understand these "missing puzzle pieces" that are an essential part of the mosaic of biological interactions present in JCVI-syn3A. Our workflow leverages evolutionary sequence analysis, protein structure prediction, interactomics, and genome architecture to determine upgraded annotations. Additionally, we apply the structure prediction analysis component of our work to all 452 protein coding genes in JCVI-syn3A to expedite future functional annotation studies as well as the inverse mapping of the cell state to more physical models requiring all-atom or coarse-grained representations for all JCVI-syn3A proteins.

摘要

最近,我们提出了一个最小基因组细菌 JCVI-syn3A 的全细胞动力学模型,该模型描述了耦合的代谢和遗传信息过程,并预测了这些网络相互作用所产生的行为。JCVI-syn3A 是一种遗传上简化的细菌细胞,其具有功能不明的基因数量最少,比例最小,其 452 个蛋白编码基因中约有 90 个(不到 20%)未注释。进一步阐明 JCVI-syn3A 基因的功能可以增强细胞建模工作的稳健性和预测能力,并深入了解细胞尺度上的生物物理过程和途径。在这里,我们应用计算分析来阐明几个参与细胞内过程的必需但以前未被描述的基因产物的功能,特别是那些直接影响细胞生长、分裂和形态的基因产物。我们还根据我们的分析提出了有针对性的湿实验室实验,以进一步了解这些“缺失的拼图”,它们是 JCVI-syn3A 中存在的生物相互作用马赛克的重要组成部分。我们的工作流程利用进化序列分析、蛋白质结构预测、互作组学和基因组结构来确定升级的注释。此外,我们将我们工作的结构预测分析组件应用于 JCVI-syn3A 中的所有 452 个蛋白编码基因,以加速未来的功能注释研究以及将细胞状态反向映射到更需要所有原子或粗粒度表示的更物理模型的研究,这些模型都需要 JCVI-syn3A 中的所有蛋白质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31ec/9483919/4809cb54c3cb/jp2c04188_0008.jpg
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