Combined network analysis and interpretable machine learning reveals the environmental adaptations of more than 10,000 ruminant microbial genomes.
machine learning
metagenome-assembled genome
metagenomics
network
ruminants
Journal
Frontiers in microbiology
ISSN: 1664-302X
Titre abrégé: Front Microbiol
Pays: Switzerland
ID NLM: 101548977
Informations de publication
Date de publication:
2023
2023
Historique:
received:
18
01
2023
accepted:
28
08
2023
medline:
6
10
2023
pubmed:
6
10
2023
entrez:
6
10
2023
Statut:
epublish
Résumé
The ruminant gastrointestinal contains numerous microbiomes that serve a crucial role in sustaining the host's productivity and health. In recent times, numerous studies have revealed that variations in influencing factors, including the environment, diet, and host, contribute to the shaping of gastrointestinal microbial adaptation to specific states. Therefore, understanding how host and environmental factors affect gastrointestinal microbes will help to improve the sustainability of ruminant production systems. Based on a graphical analysis perspective, this study elucidates the microbial topology and robustness of the gastrointestinal of different ruminant species, showing that the microbial network is more resistant to random attacks. The risk of transmission of high-risk metagenome-assembled genome (MAG) was also demonstrated based on a large-scale survey of the distribution of antibiotic resistance genes (ARG) in the microbiota of most types of ecosystems. In addition, an interpretable machine learning framework was developed to study the complex, high-dimensional data of the gastrointestinal microbial genome. The evolution of gastrointestinal microbial adaptations to the environment in ruminants were analyzed and the adaptability changes of microorganisms to different altitudes were identified, including microbial transcriptional repair. Our findings indicate that the environment has an impact on the functional features of microbiomes in ruminant. The findings provide a new insight for the future development of microbial resources for the sustainable development in agriculture.
Sections du résumé
Background
UNASSIGNED
The ruminant gastrointestinal contains numerous microbiomes that serve a crucial role in sustaining the host's productivity and health. In recent times, numerous studies have revealed that variations in influencing factors, including the environment, diet, and host, contribute to the shaping of gastrointestinal microbial adaptation to specific states. Therefore, understanding how host and environmental factors affect gastrointestinal microbes will help to improve the sustainability of ruminant production systems.
Results
UNASSIGNED
Based on a graphical analysis perspective, this study elucidates the microbial topology and robustness of the gastrointestinal of different ruminant species, showing that the microbial network is more resistant to random attacks. The risk of transmission of high-risk metagenome-assembled genome (MAG) was also demonstrated based on a large-scale survey of the distribution of antibiotic resistance genes (ARG) in the microbiota of most types of ecosystems. In addition, an interpretable machine learning framework was developed to study the complex, high-dimensional data of the gastrointestinal microbial genome. The evolution of gastrointestinal microbial adaptations to the environment in ruminants were analyzed and the adaptability changes of microorganisms to different altitudes were identified, including microbial transcriptional repair.
Conclusion
UNASSIGNED
Our findings indicate that the environment has an impact on the functional features of microbiomes in ruminant. The findings provide a new insight for the future development of microbial resources for the sustainable development in agriculture.
Identifiants
pubmed: 37799596
doi: 10.3389/fmicb.2023.1147007
pmc: PMC10548237
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1147007Informations de copyright
Copyright © 2023 Yan, Shi, Bao, Gai, Liang, Jiang and Li.
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.
Références
Microbiome. 2019 Jun 13;7(1):92
pubmed: 31196178
Trop Anim Health Prod. 2021 Jul 31;53(4):421
pubmed: 34331133
J Proteomics. 2018 Sep 15;187:235-242
pubmed: 30092381
Front Microbiol. 2020 Jun 26;11:1260
pubmed: 32670222
Sci Rep. 2021 Sep 6;11(1):17710
pubmed: 34489502
ISME J. 2016 Dec;10(12):2958-2972
pubmed: 27152936
J Proteomics. 2021 Jun 15;241:104218
pubmed: 33831599
Nat Biotechnol. 2019 Aug;37(8):953-961
pubmed: 31375809
Nature. 2018 Nov;563(7729):145-146
pubmed: 30375502
Expert Rev Anti Infect Ther. 2020 Oct;18(10):977-985
pubmed: 32530331
Microbiome. 2021 Jun 12;9(1):137
pubmed: 34118976
Antonie Van Leeuwenhoek. 2018 Aug;111(8):1449-1465
pubmed: 29569108
Nat Biotechnol. 2018 Apr;36(4):359-367
pubmed: 29553575
Microbiol Res. 2022 Jan;254:126895
pubmed: 34742104
Lancet Infect Dis. 2018 Jan;18(1):18-20
pubmed: 29303731
Nat Commun. 2022 Mar 23;13(1):1553
pubmed: 35322038
Animals (Basel). 2020 Jan 16;10(1):
pubmed: 31963125
Proc Natl Acad Sci U S A. 2018 Feb 20;115(8):1865-1870
pubmed: 29432191
Anat Histol Embryol. 2016 Oct;45(5):338-49
pubmed: 27593556
Nat Methods. 2021 Apr;18(4):366-368
pubmed: 33828273
Proc Natl Acad Sci U S A. 2009 Nov 3;106(44):18644-9
pubmed: 19846765
Front Microbiol. 2017 Mar 17;8:425
pubmed: 28367142
BMC Vet Res. 2021 Jan 9;17(1):25
pubmed: 33419429
J Anim Sci Biotechnol. 2021 Oct 12;12(1):109
pubmed: 34635155
NPJ Biofilms Microbiomes. 2021 Apr 20;7(1):38
pubmed: 33879801
Microbiome. 2021 Feb 8;9(1):40
pubmed: 33557954
J Environ Manage. 2022 Jan 1;301:113941
pubmed: 34731954