微米尺度KM鼠肠道菌群空间分布特征研究
Spatial Distribution of Gut Microbiota in KM Mice at the Micrometer Scale
DOI: 10.12677/amb.2025.142009, PDF,    科研立项经费支持
作者: 付瑞标, 李 进, 李忠鹏, 周 瑞, 邵 帅, 张秀智:徐州医科大学附属徐州市立医院(徐州市第一人民医院),胃肠外科,江苏 徐州;王 猛*:深圳市龙岗区疾病预防控制中心,微生物检验科,广东 深圳;肖 栋*:中国矿业大学,煤炭精细勘探与智能开发全国重点实验室,江苏 徐州
关键词: 采样尺度肠道菌群KM小鼠微尺度共现网络Sampling Scale Gut Microbiota KM Mice Micro-Scale Co-Occurrence Network
摘要: 肠道菌群对宿主的健康具有重要影响。目前,相关研究多使用宏观尺度样品(毫米至厘米级),而对于微观尺度(<100 μm)下微生物群落的空间分布特征尚缺乏系统认知。本文以7只昆明小鼠为研究对象,使用16S rRNA基因扩增子测序技术对378个结肠微颗粒样品(20~40 μm)和32个结肠块状样品进行了测序。结果表明,昆明小鼠肠道菌群在物种和功能基因组成上具有明显的空间异质性,其中功能基因的异质性显著小于物种组成的异质性。微颗粒所能容纳的物种和功能基因数显著低于块状样品,微颗粒间的物种和功能基因组成的差异显著高于块状样品。基于块状样品和微颗粒样品构建的共现网络存在明显差异。综上,本研究拓展了微米尺度下小鼠肠道微生物群落空间分布特征的认知,证明使用不同尺度样品推断得到的种间关系存在明显差异。
Abstract: The gut microbiota exerts significant impacts on host health. Current studies primarily utilize bulk samples (millimeter to centimeter), while systematic understanding of the spatial distribution characteristics of microbial communities at micrometer resolutions (<100 μm) remains limited. In this study, we analyzed 7 Kunming mice using 16S rRNA gene amplicon sequencing, including 378 colonic micro-scale grains (20~40 μm) and 32 bulk samples. Distinct spatial heterogeneity in both taxonomic and functional gene composition of gut microbiota in Kunming mice were observed, with functional heterogeneity being significantly lower than taxonomic heterogeneity. Micro-scale grains accommodated significantly fewer species and functional genes compared to bulk samples, while exhibiting significantly greater inter-grain variability in both taxonomic and functional compositions. Co-occurrence networks constructed from bulk samples and micro-scale grains displayed marked topological differences. This study expands our understanding of spatial distribution patterns in gut microbial communities at micrometer scale, and demonstrates that interspecies relationships inferred from samples of different scales exhibit substantial discrepancies.
文章引用:付瑞标, 王猛, 肖栋, 李进, 李忠鹏, 周瑞, 邵帅, 张秀智. 微米尺度KM鼠肠道菌群空间分布特征研究[J]. 微生物前沿, 2025, 14(2): 66-74. https://doi.org/10.12677/amb.2025.142009

参考文献

[1] Schirmer, M., Garner, A., Vlamakis, H. and Xavier, R.J. (2019) Microbial Genes and Pathways in Inflammatory Bowel Disease. Nature Reviews Microbiology, 17, 497-511. [Google Scholar] [CrossRef] [PubMed]
[2] Roje, B., Zhang, B., Mastrorilli, E., Kovačić, A., Sušak, L., Ljubenkov, I., et al. (2024) Gut Microbiota Carcinogen Metabolism Causes Distal Tissue Tumours. Nature, 632, 1137-1144. [Google Scholar] [CrossRef] [PubMed]
[3] Song, X., Zhang, H., Zhang, Y., Goh, B., Bao, B., Mello, S.S., et al. (2023) Gut Microbial Fatty Acid Isomerization Modulates Intraepithelial T Cells. Nature, 619, 837-843. [Google Scholar] [CrossRef] [PubMed]
[4] Liu, C., Zhou, N., Du, M., Sun, Y., Wang, K., Wang, Y., et al. (2020) The Mouse Gut Microbial Biobank Expands the Coverage of Cultured Bacteria. Nature Communications, 11, Article No. 79. [Google Scholar] [CrossRef] [PubMed]
[5] Liu, C., Du, M., Abuduaini, R., Yu, H., Li, D., Wang, Y., et al. (2021) Enlightening the Taxonomy Darkness of Human Gut Microbiomes with a Cultured Biobank. Microbiome, 9, Article No. 119. [Google Scholar] [CrossRef] [PubMed]
[6] Almeida, A., Nayfach, S., Boland, M., Strozzi, F., Beracochea, M., Shi, Z.J., et al. (2020) A Unified Catalog of 204,938 Reference Genomes from the Human Gut Microbiome. Nature Biotechnology, 39, 105-114. [Google Scholar] [CrossRef] [PubMed]
[7] Sheth, R.U., Li, M., Jiang, W., Sims, P.A., Leong, K.W. and Wang, H.H. (2019) Spatial Metagenomic Characterization of Microbial Biogeography in the Gut. Nature Biotechnology, 37, 877-883. [Google Scholar] [CrossRef] [PubMed]
[8] Shi, H., Shi, Q., Grodner, B., Lenz, J.S., Zipfel, W.R., Brito, I.L., et al. (2020) Highly Multiplexed Spatial Mapping of Microbial Communities. Nature, 588, 676-681. [Google Scholar] [CrossRef] [PubMed]
[9] Cao, Z., Zuo, W., Wang, L., Chen, J., Qu, Z., Jin, F., et al. (2023) Spatial Profiling of Microbial Communities by Sequential FISH with Error-Robust Encoding. Nature Communications, 14, Article No. 1477. [Google Scholar] [CrossRef] [PubMed]
[10] Lötstedt, B., Stražar, M., Xavier, R., Regev, A. and Vickovic, S. (2023) Spatial Host-Microbiome Sequencing Reveals Niches in the Mouse Gut. Nature Biotechnology, 42, 1394-1403. [Google Scholar] [CrossRef] [PubMed]
[11] Cordero, O.X. and Datta, M.S. (2016) Microbial Interactions and Community Assembly at Microscales. Current Opinion in Microbiology, 31, 227-234. [Google Scholar] [CrossRef] [PubMed]
[12] Wang, M., Zhao, K., Li, X. and Xie, B. (2023) Insights into the Composition and Assembly Mechanism of Microbial Communities on Intertidal Microsand Grains. Frontiers in Microbiology, 14, Article 1308767. [Google Scholar] [CrossRef] [PubMed]
[13] Apprill, A., McNally, S., Parsons, R. and Weber, L. (2015) Minor Revision to V4 Region SSU rRNA 806R Gene Primer Greatly Increases Detection of SAR11 Bacterioplankton. Aquatic Microbial Ecology, 75, 129-137. [Google Scholar] [CrossRef
[14] Parada, A.E., Needham, D.M. and Fuhrman, J.A. (2015) Every Base Matters: Assessing Small Subunit rRNA Primers for Marine Microbiomes with Mock Communities, Time Series and Global Field Samples. Environmental Microbiology, 18, 1403-1414. [Google Scholar] [CrossRef] [PubMed]
[15] Chen, S., Zhou, Y., Chen, Y. and Gu, J. (2018) Fastp: An Ultra-Fast All-in-One FASTQ preprocessor. Bioinformatics, 34, i884-i890. [Google Scholar] [CrossRef] [PubMed]
[16] Edgar, R.C. (2016) UNOISE2: Improved Error-Correction for Illumina 16S and ITS Amplicon Sequencing. Biorxiv. [Google Scholar] [CrossRef
[17] Edgar, R.C. (2016) UCHIME2: Improved Chimera Prediction for Amplicon Sequencing. Biorxiv. http://dx.doi.org/10.1101/074252. [Google Scholar] [CrossRef
[18] Zhao, B., Chen, L., Zhang, M., Nie, C., Yang, Q., Yu, K., et al. (2023) Electric-Inducive Microbial Interactions in a Thermophilic Anaerobic Digester Revealed by High-Throughput Sequencing of Micron-Scale Single Flocs. Environmental Science & Technology, 57, 4367-4378. [Google Scholar] [CrossRef] [PubMed]
[19] Bastian, M., Heymann, S. and Jacomy, M. (2009) Gephi: An Open Source Software for Exploring and Manipulating Networks. Proceedings of the International AAAI Conference on Web and Social Media, 3, 361-362. [Google Scholar] [CrossRef
[20] Douglas, G.M., Maffei, V.J., Zaneveld, J.R., Yurgel, S.N., Brown, J.R., Taylor, C.M., et al. (2020) PICRUST2 for Prediction of Metagenome Functions. Nature Biotechnology, 38, 685-688. [Google Scholar] [CrossRef] [PubMed]
[21] Liu, H., Hart, M. and Kong, Z. (2022) The Distribution of Arbuscular Mycorrhizal Fungal Communities at Soil Aggregate Level in Subtropical Grasslands. Archives of Agronomy and Soil Science, 68, 1755-1767. [Google Scholar] [CrossRef
[22] Chen, L., Zhao, B., Palomo, A., Sun, Y., Cheng, Z., Zhang, M., et al. (2022) Micron-Scale Biogeography Reveals Conservative Intra Anammox Bacteria Spatial Co-Associations. Water Research, 220, Article 118640. [Google Scholar] [CrossRef] [PubMed]
[23] Richardson, M., Zhao, S., Lin, L., Sheth, R.U., Qu, Y., Lee, J., et al. (2025) SAMPL-Seq Reveals Micron-Scale Spatial Hubs in the Human Gut Microbiome. Nature Microbiology, 10, 527-540. [Google Scholar] [CrossRef] [PubMed]
[24] Geier, B., Sogin, E.M., Michellod, D., Janda, M., Kompauer, M., Spengler, B., et al. (2020) Spatial Metabolomics of in Situ Host-Microbe Interactions at the Micrometre Scale. Nature Microbiology, 5, 498-510. [Google Scholar] [CrossRef] [PubMed]
[25] Louca, S., Polz, M.F., Mazel, F., Albright, M.B.N., Huber, J.A., O’Connor, M.I., et al. (2018) Function and Functional Redundancy in Microbial Systems. Nature Ecology & Evolution, 2, 936-943. [Google Scholar] [CrossRef] [PubMed]
[26] Lloréns-Rico, V., Simcock, J.A., Huys, G.R.B. and Raes, J. (2022) Single-Cell Approaches in Human Microbiome Research. Cell, 185, 2725-2738. [Google Scholar] [CrossRef] [PubMed]