Reconstruction and inference of the Lactococcus lactis MG1363 gene co-expression network.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2019
2019
Historique:
received:
15
11
2018
accepted:
21
03
2019
entrez:
23
5
2019
pubmed:
23
5
2019
medline:
14
1
2020
Statut:
epublish
Résumé
Lactic acid bacteria are Gram-positive bacteria used throughout the world in many industrial applications for their acidification, flavor and texture formation attributes. One of the species, Lactococcus lactis, is employed for the production of fermented milk products like cheese, buttermilk and quark. It ferments lactose to lactic acid and, thus, helps improve the shelf life of the products. Many physiological and transcriptome studies have been performed in L. lactis in order to comprehend and improve its biotechnological assets. Using large amounts of transcriptome data to understand and predict the behavior of biological processes in bacterial or other cell types is a complex task. Gene networks enable predicting gene behavior and function in the context of transcriptionally linked processes. We reconstruct and present the gene co-expression network (GCN) for the most widely studied L. lactis strain, MG1363, using publicly available transcriptome data. Several methods exist to generate and judge the quality of GCNs. Different reconstruction methods lead to networks with varying structural properties, consequently altering gene clusters. We compared the structural properties of the MG1363 GCNs generated by five methods, namely Pearson correlation, Spearman correlation, GeneNet, Weighted Gene Co-expression Network Analysis (WGCNA), and Sparse PArtial Correlation Estimation (SPACE). Using SPACE, we generated an L. lactis MG1363 GCN and assessed its quality using modularity and structural and biological criteria. The L. lactis MG1363 GCN has structural properties similar to those of the gold-standard networks of Escherichia coli K-12 and Bacillus subtilis 168. We showcase that the network can be used to mine for genes with similar expression profiles that are also generally linked to the same biological process.
Identifiants
pubmed: 31116749
doi: 10.1371/journal.pone.0214868
pii: PONE-D-18-32742
pmc: PMC6530827
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0214868Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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