Literature DB >> 30657448

Essential metabolism for a minimal cell.

Marian Breuer1, Tyler M Earnest1, Chuck Merryman2, Kim S Wise2, Lijie Sun2, Michaela R Lynott2, Clyde A Hutchison2, Hamilton O Smith2, John D Lapek3, David J Gonzalez3, Valérie de Crécy-Lagard4, Drago Haas4, Andrew D Hanson5, Piyush Labhsetwar1, John I Glass2, Zaida Luthey-Schulten1.   

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, Mycoplasma mycoides capri, 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.
© 2019, Breuer et al.

Entities:  

Keywords:  JCVI-syn3A; computational biology; gene essentiality; metabolic reconstruction; mycoplasma; proteomics; systems biology; transposon mutagenesis

Mesh:

Substances:

Year:  2019        PMID: 30657448      PMCID: PMC6609329          DOI: 10.7554/eLife.36842

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  161 in total

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