Inhaltspezifische Aktionen

Reconstruction of Genome-scale Model (GEM)

Reconstruction of Genome-scale Model (GEM)

Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. The metabolic reconstruction can help identify potential targets for novel antibiotics or alternative therapeutic approaches. This necessitates a focus on a GEM, which can efficiently identify and characterize the constructed based on genome sequence annotation and physiological data, encompassing all the metabolic reactions within an organism and the genes encoding each enzyme. High-quality GEMs provide deeper insights into the species itself, its interactions with other species, and offer more personalized treatment options for diseases caused by these species. High-quality reconstructions of GEMs require extensive manual curation, which is often time-consuming

Materials

Recommended Literature

A protocol for generating a high-quality genome-scale metabolic reconstruction, Thiele, Palsson (2010)

High-Quality Genome-Scale Reconstruction of Corynebacterium glutamicum ATCC 13032, Feierabend et al. (2021)

First Genome-Scale Metabolic Model of Dolosigranulum pigrum Confirms Multiple Auxotrophies, Renz et al. (2021)

Genome-scale metabolic models consistently predict in vitro characteristics of Corynebacterium striatum, Bäuerle et al. (2023)

Genome-scale metabolic model of Staphylococcus epidermidis ATCC 12228 matches in vitro conditions, Leonidou et al. (2023)

SBOannotator: a Python tool for the automated assignment of systems biology ontology terms, Leonidou et al. (2023)

MCC: Automated Mass and Charge Curation at Genome-Scale Applied to C. tuberculostearicum, Mostolizadeh et al. (2024)

Tools

COBRApy

COBRA Toolbox

CarveMe

refineGEMs

SPECIMEN

MassChargeCuration

SBOannotator

BOFdat

ModelPolisher 

Memote 

SBML validator 

Escher