Integrating Computational Methods to Investigate the Macroecology of Microbiomes
Publication year
2019Source
Frontiers in Genetics, 10, (2019), article 1344ISSN
Publication type
Article / Letter to editor
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Organization
RIMLS - Radboud Institute for Molecular Life Sciences
CMBI
Journal title
Frontiers in Genetics
Volume
vol. 10
Subject
Radboudumc 14: Tumours of the digestive tract RIMLS: Radboud Institute for Molecular Life Sciences; CMBI - Radboud University Medical CenterAbstract
Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.
This item appears in the following Collection(s)
- Academic publications [243984]
- Electronic publications [130695]
- Faculty of Medical Sciences [92811]
- Open Access publications [104970]
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