Modeling spatial interaction networks of the gut microbiota
How the gut microbiota is organized across space is postulated to influence microbial succession and its mutualistic relationships with the host. The lack of dynamic or perturbed abundance data poses considerable challenges for characterizing the spatial pattern of microbial interactions. We integra...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-12-01
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| Series: | Gut Microbes |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19490976.2022.2106103 |
| _version_ | 1811313895011254272 |
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| author | Xiaocang Cao Ang Dong Guangbo Kang Xiaoli Wang Liyun Duan Huixing Hou Tianming Zhao Shuang Wu Xinjuan Liu He Huang Rongling Wu |
| author_facet | Xiaocang Cao Ang Dong Guangbo Kang Xiaoli Wang Liyun Duan Huixing Hou Tianming Zhao Shuang Wu Xinjuan Liu He Huang Rongling Wu |
| author_sort | Xiaocang Cao |
| collection | DOAJ |
| description | How the gut microbiota is organized across space is postulated to influence microbial succession and its mutualistic relationships with the host. The lack of dynamic or perturbed abundance data poses considerable challenges for characterizing the spatial pattern of microbial interactions. We integrate allometric scaling theory, evolutionary game theory, and prey-predator theory into a unified framework under which quasi-dynamic microbial networks can be inferred from static abundance data. We illustrate that such networks can capture the full properties of microbial interactions, including causality, the sign of the causality, strength, and feedback loop, and are dynamically adaptive along spatial gradients, and context-specific, characterizing variability between individuals and within the same individual across time and space. We design and conduct a gut microbiota study to validate the model, characterizing key spatial determinants of the microbial differences between ulcerative colitis and healthy controls. Our model provides a sophisticated means of unraveling a complete atlas of how microbial interactions vary across space and quantifying causal relationships between such spatial variability and change in health state. |
| first_indexed | 2024-04-13T11:02:43Z |
| format | Article |
| id | doaj.art-e18d3332586b4c4a91ec193366b14957 |
| institution | Directory Open Access Journal |
| issn | 1949-0976 1949-0984 |
| language | English |
| last_indexed | 2024-04-13T11:02:43Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Gut Microbes |
| spelling | doaj.art-e18d3332586b4c4a91ec193366b149572022-12-22T02:49:23ZengTaylor & Francis GroupGut Microbes1949-09761949-09842022-12-0114110.1080/19490976.2022.2106103Modeling spatial interaction networks of the gut microbiotaXiaocang Cao0Ang Dong1Guangbo Kang2Xiaoli Wang3Liyun Duan4Huixing Hou5Tianming Zhao6Shuang Wu7Xinjuan Liu8He Huang9Rongling Wu10Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, ChinaSchool of Chemical Engineering and Technology, Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, ChinaDepartment of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, ChinaDepartment of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, ChinaDepartment of Gastroenterology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaSchool of Chemical Engineering and Technology, Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, ChinaCenter for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA, USAHow the gut microbiota is organized across space is postulated to influence microbial succession and its mutualistic relationships with the host. The lack of dynamic or perturbed abundance data poses considerable challenges for characterizing the spatial pattern of microbial interactions. We integrate allometric scaling theory, evolutionary game theory, and prey-predator theory into a unified framework under which quasi-dynamic microbial networks can be inferred from static abundance data. We illustrate that such networks can capture the full properties of microbial interactions, including causality, the sign of the causality, strength, and feedback loop, and are dynamically adaptive along spatial gradients, and context-specific, characterizing variability between individuals and within the same individual across time and space. We design and conduct a gut microbiota study to validate the model, characterizing key spatial determinants of the microbial differences between ulcerative colitis and healthy controls. Our model provides a sophisticated means of unraveling a complete atlas of how microbial interactions vary across space and quantifying causal relationships between such spatial variability and change in health state.https://www.tandfonline.com/doi/10.1080/19490976.2022.2106103Gut microbiotaspatial biologyevolutionary game theorymicrobial interaction networkquasi-dynamic ordinary differential equation |
| spellingShingle | Xiaocang Cao Ang Dong Guangbo Kang Xiaoli Wang Liyun Duan Huixing Hou Tianming Zhao Shuang Wu Xinjuan Liu He Huang Rongling Wu Modeling spatial interaction networks of the gut microbiota Gut Microbes Gut microbiota spatial biology evolutionary game theory microbial interaction network quasi-dynamic ordinary differential equation |
| title | Modeling spatial interaction networks of the gut microbiota |
| title_full | Modeling spatial interaction networks of the gut microbiota |
| title_fullStr | Modeling spatial interaction networks of the gut microbiota |
| title_full_unstemmed | Modeling spatial interaction networks of the gut microbiota |
| title_short | Modeling spatial interaction networks of the gut microbiota |
| title_sort | modeling spatial interaction networks of the gut microbiota |
| topic | Gut microbiota spatial biology evolutionary game theory microbial interaction network quasi-dynamic ordinary differential equation |
| url | https://www.tandfonline.com/doi/10.1080/19490976.2022.2106103 |
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