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MRGM:一个增强的小鼠肠道微生物基因组目录,大大拓宽了分类学和功能景观。

MRGM: an enhanced catalog of mouse gut microbial genomes substantially broadening taxonomic and functional landscapes.

机构信息

Department of Biotechnology, College of Life Science & Biotechnology, Yonsei University, Seoul, Republic of Korea.

Department of Biochemistry, College of Life Science & Biotechnology, Yonsei University, Seoul, Republic of Korea.

出版信息

Gut Microbes. 2024 Jan-Dec;16(1):2393791. doi: 10.1080/19490976.2024.2393791. Epub 2024 Sep 4.


DOI:10.1080/19490976.2024.2393791
PMID:39230075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11376411/
Abstract

Mouse gut microbiome research is pivotal for understanding the human gut microbiome, providing insights into disease modeling, host-microbe interactions, and the dietary influence on the gut microbiome. To enhance the translational value of mouse gut microbiome studies, we need detailed and high-quality catalogs of mouse gut microbial genomes. We introduce the Mouse Reference Gut Microbiome (MRGM), a comprehensive catalog with 42,245 non-redundant mouse gut bacterial genomes across 1,524 species. MRGM marks a 40% increase in the known taxonomic diversity of mouse gut microbes, capturing previously underrepresented lineages through refined genome quality assessment techniques. MRGM not only broadens the taxonomic landscape but also enriches the functional landscape of the mouse gut microbiome. Using deep learning, we have elevated the Gene Ontology annotation rate for mouse gut microbial proteins from 3.2% with orthology to 60%, marking an over 18-fold increase. MRGM supports both DNA- and marker-based taxonomic profiling by providing custom databases, surpassing previous catalogs in performance. Finally, taxonomic and functional comparisons between human and mouse gut microbiota reveal diet-driven divergences in their taxonomic composition and functional enrichment. Overall, our study highlights the value of high-quality microbial genome catalogs in advancing our understanding of the co-evolution between gut microbes and their host.

摘要

小鼠肠道微生物组研究对于理解人类肠道微生物组至关重要,有助于深入研究疾病建模、宿主-微生物相互作用以及饮食对肠道微生物组的影响。为了提高小鼠肠道微生物组研究的转化价值,我们需要详细且高质量的小鼠肠道微生物基因组目录。我们介绍了小鼠参考肠道微生物组(Mouse Reference Gut Microbiome,MRGM),这是一个包含 1524 个物种、42245 个非冗余小鼠肠道细菌基因组的综合目录。MRGM 使得已知的小鼠肠道微生物的分类多样性增加了 40%,通过改进的基因组质量评估技术,捕获了以前代表性不足的谱系。MRGM 不仅拓宽了分类学景观,还丰富了小鼠肠道微生物组的功能景观。通过使用深度学习,我们将基于同源性的小鼠肠道微生物蛋白的基因本体(GO)注释率从 3.2%提高到了 60%,提高了 18 倍以上。MRGM 提供了自定义数据库,支持基于 DNA 和标记的分类分析,在性能上超过了以前的目录。最后,人类和小鼠肠道微生物组的分类和功能比较揭示了饮食对其分类组成和功能富集的驱动分歧。总的来说,我们的研究强调了高质量微生物基因组目录在促进我们对肠道微生物与其宿主共同进化的理解方面的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/0fd3f2fda565/KGMI_A_2393791_F0007_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/609daf46dc33/KGMI_A_2393791_F0001_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/3da49d34bcf6/KGMI_A_2393791_F0002_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/f4a1773af306/KGMI_A_2393791_F0003_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/18d0c5b45b63/KGMI_A_2393791_F0004_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/44acee3e658f/KGMI_A_2393791_F0005_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/b2a64e35b233/KGMI_A_2393791_F0006_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/0fd3f2fda565/KGMI_A_2393791_F0007_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/609daf46dc33/KGMI_A_2393791_F0001_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/3da49d34bcf6/KGMI_A_2393791_F0002_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/f4a1773af306/KGMI_A_2393791_F0003_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/18d0c5b45b63/KGMI_A_2393791_F0004_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/44acee3e658f/KGMI_A_2393791_F0005_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/b2a64e35b233/KGMI_A_2393791_F0006_OC.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfc5/11376411/0fd3f2fda565/KGMI_A_2393791_F0007_OC.jpg

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[1]
mechanisms of immune modulation and tolerance.

Gut Microbes. 2023-12

[2]
Quality MAGnified.

Nat Rev Microbiol. 2023-12

[3]
CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning.

Nat Methods. 2023-8

[4]
MetaPhlAn 4 profiling of unknown species-level genome bins improves the characterization of diet-associated microbiome changes in mice.

Cell Rep. 2023-5-30

[5]
From defaults to databases: parameter and database choice dramatically impact the performance of metagenomic taxonomic classification tools.

Microb Genom. 2023-3

[6]
Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4.

Nat Biotechnol. 2023-11

[7]
Impact of microbial genome completeness on metagenomic functional inference.

ISME Commun. 2023-2-16

[8]
KEGG for taxonomy-based analysis of pathways and genomes.

Nucleic Acids Res. 2023-1-6

[9]
HiFi metagenomic sequencing enables assembly of accurate and complete genomes from human gut microbiota.

Nat Commun. 2022-10-26

[10]
Enhanced cultured diversity of the mouse gut microbiota enables custom-made synthetic communities.

Cell Host Microbe. 2022-11-9

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