Essential metabolism for a minimal cell

Marian Breuer, Tyler M. Earnest, Chuck Merryman, Kim S. Wise, Lijie Sun, Michaels R. Lynott, Clyde A. Hutchison, Hamilton O. Smith, John D. Lapek, David J. Gonzalez, Valerie De Crecy-Lagard, Drago Haas, Andrew D. Hanson, Piyush Labhsetwar, John Glass, Zaida Luthey-Schulten*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

71 Citations (Web of Science)


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.
Original languageEnglish
Article numbere36842
Pages (from-to)1-75
Number of pages77
Publication statusPublished - 18 Jan 2019
Externally publishedYes


  • JCVI-syn3A
  • Metabolic reconstruction
  • Transposon mutagenesis
  • Mycoplasma
  • Proteomics
  • Gene essentiality

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