Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters.
biodiversity
cluster annotation
metagenomes
metatranscriptomes
microbial dark matter
protein clustering
protein families
Journal
Frontiers in bioinformatics
ISSN: 2673-7647
Titre abrégé: Front Bioinform
Pays: Switzerland
ID NLM: 9918227263306676
Informations de publication
Date de publication:
2023
2023
Historique:
received:
07
02
2023
accepted:
21
02
2023
entrez:
24
3
2023
pubmed:
25
3
2023
medline:
25
3
2023
Statut:
epublish
Résumé
Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.
Identifiants
pubmed: 36959975
doi: 10.3389/fbinf.2023.1157956
pii: 1157956
pmc: PMC10029925
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
1157956Informations de copyright
Copyright © 2023 Baltoumas, Karatzas, Paez-Espino, Venetsianou, Aplakidou, Oulas, Finn, Ovchinnikov, Pafilis, Kyrpides and Pavlopoulos.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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