Database selection for shotgun metaproteomic of low-diversity dairy microbiomes.

Dairy products Database construction Metagenomics Metaproteomics

Journal

International journal of food microbiology
ISSN: 1879-3460
Titre abrégé: Int J Food Microbiol
Pays: Netherlands
ID NLM: 8412849

Informations de publication

Date de publication:
15 Apr 2024
Historique:
received: 15 02 2024
revised: 12 04 2024
accepted: 13 04 2024
medline: 3 5 2024
pubmed: 3 5 2024
entrez: 2 5 2024
Statut: aheadofprint

Résumé

The metaproteomics field has recently gained more and more interest as a valuable tool for studying both the taxonomy and function of microbiomes, including those used in food fermentations. One crucial step in the metaproteomics pipeline is selecting a database to obtain high-quality taxonomical and functional information from microbial communities. One of the best strategies described for building protein databases is using sample-specific or study-specific protein databases obtained from metagenomic sequencing. While this is true for high-diversity microbiomes (such as gut and soil), there is still a lack of validation for different database construction strategies in low-diversity microbiomes, such as those found in fermented dairy products where starter cultures containing few species are used. In this study, we assessed the performance of various database construction strategies applied to metaproteomics on two low-diversity microbiomes obtained from cheese production using commercial starter cultures and analyzed by LC-MS/MS. Substantial differences were detected between the strategies, and the best performance in terms of the number of peptides and proteins identified from the spectra was achieved by metagenomic-derived databases. However, extensive databases constructed from a high number of available online genomes obtained a similar taxonomical and functional annotation of the metaproteome compared to the metagenomic-derived databases. Our results indicate that, in the case of low-diversity dairy microbiomes, the use of publically available genomes to construct protein databases can be considered as an alternative to metagenome-derived databases.

Identifiants

pubmed: 38696985
pii: S0168-1605(24)00150-8
doi: 10.1016/j.ijfoodmicro.2024.110706
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

110706

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Vinicius da Silva Duarte reports financial support was provided by Norges Forskiningsrad. Davide Porcellato reports financial support was provided by Norges Forskiningsrad. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Vinícius da Silva Duarte (V)

Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, N-1432 Ås, Norway.

Luiza de Paula Dias Moreira (L)

Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, N-1432 Ås, Norway.

Siv B Skeie (SB)

Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, N-1432 Ås, Norway.

Fredrik Svalestad (F)

TINE SA, P.O. Box 7, Kalbakken, N-0902 Oslo, Norway.

Jorun Øyaas (J)

TINE SA, P.O. Box 7, Kalbakken, N-0902 Oslo, Norway.

Davide Porcellato (D)

Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, N-1432 Ås, Norway. Electronic address: davide.porcellato@nmbu.no.

Classifications MeSH