Literature DB >> 33563315

Guild-based analysis for understanding gut microbiome in human health and diseases.

Guojun Wu1,2,3, Naisi Zhao1,4, Chenhong Zhang3,5, Yan Y Lam1,2,3, Liping Zhao6,7,8,9.   

Abstract

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem's higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same "guild" if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of "guild" to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases.

Entities:  

Keywords:  Guild; Gut microbiota; High dimensionality; High sparsity

Mesh:

Substances:

Year:  2021        PMID: 33563315      PMCID: PMC7874449          DOI: 10.1186/s13073-021-00840-y

Source DB:  PubMed          Journal:  Genome Med        ISSN: 1756-994X            Impact factor:   11.117


  86 in total

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2.  UPARSE: highly accurate OTU sequences from microbial amplicon reads.

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3.  A human gut microbial gene catalogue established by metagenomic sequencing.

Authors:  Junjie Qin; Ruiqiang Li; Jeroen Raes; Manimozhiyan Arumugam; Kristoffer Solvsten Burgdorf; Chaysavanh Manichanh; Trine Nielsen; Nicolas Pons; Florence Levenez; Takuji Yamada; Daniel R Mende; Junhua Li; Junming Xu; Shaochuan Li; Dongfang Li; Jianjun Cao; Bo Wang; Huiqing Liang; Huisong Zheng; Yinlong Xie; Julien Tap; Patricia Lepage; Marcelo Bertalan; Jean-Michel Batto; Torben Hansen; Denis Le Paslier; Allan Linneberg; H Bjørn Nielsen; Eric Pelletier; Pierre Renault; Thomas Sicheritz-Ponten; Keith Turner; Hongmei Zhu; Chang Yu; Shengting Li; Min Jian; Yan Zhou; Yingrui Li; Xiuqing Zhang; Songgang Li; Nan Qin; Huanming Yang; Jian Wang; Søren Brunak; Joel Doré; Francisco Guarner; Karsten Kristiansen; Oluf Pedersen; Julian Parkhill; Jean Weissenbach; Peer Bork; S Dusko Ehrlich; Jun Wang
Journal:  Nature       Date:  2010-03-04       Impact factor: 49.962

4.  Correlation detection strategies in microbial data sets vary widely in sensitivity and precision.

Authors:  Sophie Weiss; Will Van Treuren; Catherine Lozupone; Karoline Faust; Jonathan Friedman; Ye Deng; Li Charlie Xia; Zhenjiang Zech Xu; Luke Ursell; Eric J Alm; Amanda Birmingham; Jacob A Cram; Jed A Fuhrman; Jeroen Raes; Fengzhu Sun; Jizhong Zhou; Rob Knight
Journal:  ISME J       Date:  2016-02-23       Impact factor: 10.302

5.  Metabolic reconstruction for metagenomic data and its application to the human microbiome.

Authors:  Sahar Abubucker; Nicola Segata; Johannes Goll; Alyxandria M Schubert; Jacques Izard; Brandi L Cantarel; Beltran Rodriguez-Mueller; Jeremy Zucker; Mathangi Thiagarajan; Bernard Henrissat; Owen White; Scott T Kelley; Barbara Methé; Patrick D Schloss; Dirk Gevers; Makedonka Mitreva; Curtis Huttenhower
Journal:  PLoS Comput Biol       Date:  2012-06-13       Impact factor: 4.475

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Authors:  Alejandro R Walker; Tyler L Grimes; Somnath Datta; Susmita Datta
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8.  Changes in the Structure of the Microbial Community Associated with Nannochloropsis salina following Treatments with Antibiotics and Bioactive Compounds.

Authors:  Haifeng Geng; Mary B Tran-Gyamfi; Todd W Lane; Kenneth L Sale; Eizadora T Yu
Journal:  Front Microbiol       Date:  2016-07-26       Impact factor: 5.640

Review 9.  From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

Authors:  Eugen Bauer; Ines Thiele
Journal:  mSystems       Date:  2018-03-27       Impact factor: 6.496

10.  Transkingdom network reveals bacterial players associated with cervical cancer gene expression program.

Authors:  Khiem Chi Lam; Dariia Vyshenska; Jialu Hu; Richard Rosario Rodrigues; Anja Nilsen; Ryszard A Zielke; Nicholas Samuel Brown; Eva-Katrine Aarnes; Aleksandra E Sikora; Natalia Shulzhenko; Heidi Lyng; Andrey Morgun
Journal:  PeerJ       Date:  2018-09-19       Impact factor: 2.984

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  16 in total

1.  A transmissible γδ intraepithelial lymphocyte hyperproliferative phenotype is associated with the intestinal microbiota and confers protection against acute infection.

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2.  Ecological dynamics of the gut microbiome in response to dietary fiber.

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3.  Microbiome Heritability and Its Role in Adaptation of Hosts to Novel Resources.

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Journal:  Front Microbiol       Date:  2022-07-05       Impact factor: 6.064

4.  Microbiota and Metabolite Profiling as Markers of Mood Disorders: A Cross-Sectional Study in Obese Patients.

Authors:  Quentin Leyrolle; Renata Cserjesi; Romane Demeure; Audrey M Neyrinck; Camille Amadieu; Julie Rodriguez; Olli Kärkkäinen; Kati Hanhineva; Nicolas Paquot; Miriam Cnop; Patrice D Cani; Jean-Paul Thissen; Laure B Bindels; Olivier Klein; Olivier Luminet; Nathalie M Delzenne
Journal:  Nutrients       Date:  2021-12-29       Impact factor: 5.717

5.  On the Verge of a Catastrophic Collapse? The Need for a Multi-Ecosystem Approach to Microbiome Studies.

Authors:  Olaf F A Larsen; Linda H M van de Burgwal
Journal:  Front Microbiol       Date:  2021-12-02       Impact factor: 5.640

6.  High-Fiber Diet or Combined With Acarbose Alleviates Heterogeneous Phenotypes of Polycystic Ovary Syndrome by Regulating Gut Microbiota.

Authors:  Xuejiao Wang; Ting Xu; Rui Liu; Guojun Wu; Liping Gu; Yahui Zhang; Feng Zhang; Huaqing Fu; Yunxia Ling; Xiaohui Wei; Yunchen Luo; Jian Shen; Liping Zhao; Yongde Peng; Chenhong Zhang; Xiaoying Ding
Journal:  Front Endocrinol (Lausanne)       Date:  2022-02-02       Impact factor: 5.555

7.  Daily Exposure to a Cranberry Polyphenol Oral Rinse Alters the Oral Microbiome but Not Taste Perception in PROP Taster Status Classified Individuals.

Authors:  Neeta Y Yousaf; Guojun Wu; Melania Melis; Mariano Mastinu; Cristina Contini; Tiziana Cabras; Iole Tomassini Barbarossa; Liping Zhao; Yan Y Lam; Beverly J Tepper
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Review 8.  Towards multi-label classification: Next step of machine learning for microbiome research.

Authors:  Shunyao Wu; Yuzhu Chen; Zhiruo Li; Jian Li; Fengyang Zhao; Xiaoquan Su
Journal:  Comput Struct Biotechnol J       Date:  2021-04-28       Impact factor: 7.271

Review 9.  Gut microbiota in obesity.

Authors:  Bing-Nan Liu; Xiao-Tong Liu; Zi-Han Liang; Ji-Hui Wang
Journal:  World J Gastroenterol       Date:  2021-07-07       Impact factor: 5.742

Review 10.  Using Community Ecology Theory and Computational Microbiome Methods To Study Human Milk as a Biological System.

Authors:  Liat Shenhav; Meghan B Azad
Journal:  mSystems       Date:  2022-02-01       Impact factor: 6.496

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