Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

Abstract

BackgroundOver the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes.ResultsHere we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype).ConclusionThis study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data.

Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations

“…We first compared the biomass equations from genome-scale models of eight phylogenetically different yeast species: Candida glabrata (Xu et al, 2013), Candida tropicalis (Mishra et al, 2016), Kluveromyces lactis (Dias et al, 2014), Pichia pastoris (Chung et al, 2010), Saccharomyces cerevisiae (Mo et al, 2009), Schizosaccharomyces pombe (Sohn et al, 2012), Scheffersomyces stipitis (Balagurunathan et al, 2012) and Yarrowia lipolytica (Kavšcek et al, 2015) (see Supplementary Methods; Figure 1A ). Each biomass equation contains metabolites that can be classified into any of the six major categories: carbohydrate, protein, RNA, DNA, lipid and cofactors.…”

Metabolomic Analysis of Schizosaccharomyces pombe: Sample Preparation, Detection, and Data Interpretation

“…Alternative estimates of the extent of the yeast metabolome can be obtained from reconstructed genome-wide metabolic models. The latest version of the S. cerevisiae metabolic network model (v. 7.11; available at http://yeast.sf.net) contains 2386 compounds (Aung et al 2013), while the S. pombe genome-scale metabolic model SpoMBEL1693 contains 1744 (Sohn et al 2012). It should be noted, however, that because of the nature of these systems biology models, identical chemical compounds present in different cellular compartments (e.g., ATP in cytoplasm versus ATP in mitochondria) are counted as different metabolites.…”

Time‐Dependent Diaryl Ether Inhibitors of InhA: Structure–Activity Relationship Studies of Enzyme Inhibition, Antibacterial Activity, and in vivo Efficacy

“…The first genome‐scale metabolic model for a yeast was for S. cerevisiae [36], for which there are currently seven metabolic reconstructions available [36–42]. Several other yeasts also have reconstructions, namely several Pichia strains [43–45], Schizosaccharomyces pombe [46], among various other fungi. However, although K. lactis is, along with S. cerevisiae , considered a prototype for modeling two distinct types of yeast, as yet there is no model for K. lactis [47].…”