Integrating Computational Methods to Investigate the Macroecology of Microbiomes
Mascarenhas, Rilquer; Ruziska, Flávia M; Moreira, Eduardo Freitas; Campos, Amanda B; Loiola, Miguel; Reis, Kaike; Trindade-Silva, Amaro E; Barbosa, Felipe A S; Salles, Lucas; Menezes, Rafael; Veiga, Rafael; Coutinho, Felipe H; Dutilh, Bas E; Guimarães, Paulo R; Assis, Ana Paula A; Ara, Anderson; Miranda, José G V; Andrade, Roberto F S; Vilela, Bruno; Meirelles, Pedro Milet
(2020) Frontiers in Genetics, volume 10
(Article)
Abstract
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
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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.
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Keywords: microbial community modeling, microbial macroecology, spatial scales, machine learning, co-occurrence networks
ISSN: 1664-8021
Publisher: Frontiers Media S.A.
Note: Copyright © 2020 Mascarenhas, Ruziska, Moreira, Campos, Loiola, Reis, Trindade-Silva, Barbosa, Salles, Menezes, Veiga, Coutinho, Dutilh, Guimarães, Assis, Ara, Miranda, Andrade, Vilela and Meirelles.
(Peer reviewed)