The yeastGemMap: A process diagram to assist yeast systems-metabolic studies
Artikel i vetenskaplig tidskrift, 2021

Visualization is a key aspect of the analysis of omics data. Although many tools can generate pathway maps for visualization of yeast metabolism, they fail in reconstructing genome-scale metabolic diagrams of compartmentalized metabolism. Here we report on the yeastGemMap, a process diagram of whole yeast metabolism created to assist data analysis in systems-metabolic studies. The map was manually reconstructed with reactions from a compartmentalized genome-scale metabolic model, based on biochemical process diagrams typically found in educational and specialized literature. The yeastGemMap consists of 3815 reactions representing 1150 genes, 2742 metabolites, and 14 compartments. Computational functions for adapting the graphical representation of the map are also reported. These functions modify the visual representation of the map to assist in three systems-metabolic tasks: illustrating reaction networks, interpreting metabolic flux data, and visualizing omics data. The versatility of the yeastGemMap and algorithms to assist visualization of systems-metabolic data was demonstrated in various tasks, including for single lethal reaction evaluation, flux balance analysis, and transcriptomic data analysis. For instance, visual interpretation of metabolic transcriptomes of thermally evolved and parental yeast strains allowed to demonstrate that evolved strains activate a preadaptation response at 30 degrees C, which enabled thermotolerance. A quick interpretation of systems-metabolic data is promoted with yeastGemMap visualizations.

genome scale metabolic map

systems metabolic engineering

Saccharomyces cerevisiae

genome scale metabolic model

Författare

Luis Caspeta-Guadarrama

Systembiologi

Eduard Kerkhoven

Chalmers, Biologi och bioteknik, Systembiologi

Alfredo Martinez

Universidad Nacional Autonoma de Mexico

Jens B Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

BioInnovation Institute

Biotechnology and Bioengineering

0006-3592 (ISSN) 1097-0290 (eISSN)

Vol. In Press

Ämneskategorier

Annan data- och informationsvetenskap

Mediateknik

Datorseende och robotik (autonoma system)

DOI

10.1002/bit.27943

PubMed

34569624

Mer information

Senast uppdaterat

2021-10-14