Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human

Methods Mol Biol. 2019:2049:347-363. doi: 10.1007/978-1-4939-9736-7_20.

Abstract

Genome-scale modelling in eukaryotes has been pioneered by the yeast Saccharomyces cerevisiae. Early metabolic networks have been reconstructed based on genome sequence and information accumulated in the literature on biochemical reactions. Protein-protein interaction networks have been constructed based on experimental observations such as yeast-2-hybrid method. Gene regulatory networks were based on a variety of data types, including information on TF-promoter binding and gene coexpression. The aforementioned networks have been improved gradually, and methods for their integration were developed. Incorporation of omics data including genomics, metabolomics, transcriptomics, fluxome, and phosphoproteome led to next-generation genome-scale models. The methods tested on yeast have later been implemented in human, further, cellular components found to be important in yeast physiology under (ab)normal conditions, and (dis)regulation mechanisms in yeast shed light to the healthy and disease states in human. This chapter provides a historical perspective on next-generation genome-scale models incorporating multilevel 'omics data, from yeast to human.

Keywords: Data integration; Metabolic networks; Metabolomics; Protein–protein interaction networks; Proteomics; Transcriptional regulatory networks; Transcriptomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Gene Regulatory Networks
  • Humans
  • Metabolic Networks and Pathways / physiology*
  • Metabolomics
  • Protein Binding
  • Saccharomyces cerevisiae / metabolism*
  • Systems Biology