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最小细胞的基本代谢。

Essential metabolism for a minimal cell.

机构信息

Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, United States.

J Craig Venter Institute, La Jolla, United States.

出版信息

Elife. 2019 Jan 18;8:e36842. doi: 10.7554/eLife.36842.

Abstract

JCVI-syn3A, a robust minimal cell with a 543 kbp genome and 493 genes, provides a versatile platform to study the basics of life. Using the vast amount of experimental information available on its precursor, , we assembled a near-complete metabolic network with 98% of enzymatic reactions supported by annotation or experiment. The model agrees well with genome-scale in vivo transposon mutagenesis experiments, showing a Matthews correlation coefficient of 0.59. The genes in the reconstruction have a high in vivo essentiality or quasi-essentiality of 92% (68% essential), compared to 79% in silico essentiality. This coherent model of the minimal metabolism in JCVI-syn3A at the same time also points toward specific open questions regarding the minimal genome of JCVI-syn3A, which still contains many genes of generic or completely unclear function. In particular, the model, its comparison to in vivo essentiality and proteomics data yield specific hypotheses on gene functions and metabolic capabilities; and provide suggestions for several further gene removals. In this way, the model and its accompanying data guide future investigations of the minimal cell. Finally, the identification of 30 essential genes with unclear function will motivate the search for new biological mechanisms beyond metabolism.

摘要

JCVI-syn3A 是一种强大的最小细胞,具有 543 kbp 的基因组和 493 个基因,为研究生命的基本原理提供了一个多功能平台。利用其前体 中可用的大量实验信息,我们组装了一个接近完整的代谢网络,其中 98%的酶促反应得到注释或实验的支持。该模型与基于基因组规模的体内转座子诱变实验吻合良好,表明 Matthews 相关系数为 0.59。与在计算机上预测的必需性(79%)相比,重建中基因的体内必需性或准必需性高达 92%(68%必需)。这个 JCVI-syn3A 最小代谢的连贯模型同时也指出了关于 JCVI-syn3A 最小基因组的具体开放性问题,该基因组仍然包含许多具有通用或完全不清楚功能的基因。特别是,该模型及其与体内必需性和蛋白质组学数据的比较,对基因功能和代谢能力提出了具体假设,并为进一步的基因去除提供了建议。通过这种方式,该模型及其附带的数据指导了对最小细胞的未来研究。最后,鉴定出 30 个功能不清楚的必需基因,将激发对代谢以外的新生物学机制的探索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/814a/6609329/ca18e222023e/elife-36842-fig1.jpg

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