Network analysis of the hot spring microbiome sketches out possible niche differentiations among ecological guilds

Lianwei Li, Wendy Li, Quan Zou and Ma, Zhanshan (Sam)

Ecological Modelling, 2020, vol. 431, issue C

Abstract: It has been nearly a half-century long since the recognition of Archaea as one of the three kingdoms in the tree of life, but the comparative studies on their ecological adaptations with bacteria in the hot spring environment have been relatively few. We present the first few network analyses of the hot-spring microbiome with 165 hot-spring microbiome samples taken globally by Sharp et al (2014) (with the temperature and pH ranged 7.5°C-99°C and 1.8-9.0, respectively), offering an ideal dataset for investigating the structure and functional interactions in the hot-spring microbiome via network analysis. Here we aim to identify the ecologically adaptive differences between Archaea and Bacteria and discover: (i) Competitions as represented by negative correlations seem to be extremely rare among Archaea species; in contrast, the competitions among Bacteria species are much more common. (ii) Archaea and Bacteria can form their own guilds and occupy their own niches, and pH seems to play an important role in niche differentiations. (iii) The abundances of most Bacteria and Archaea are not correlated to the temperature. Bacteria have slightly more species that are thermo-phobic and no Archaea are thermo-phobic. The temperature may have far more significant influences on species compositions than on species abundance. In other words, most ‘resident’ species can prosper in a wide range of temperatures but some ‘nonresidents’ may encounter difficulties to survive. Theoretically, this is consistent with the classic biogeography dogma of microbes—they may reach everywhere, but environment selects who can stay.

Keywords: Hot spring microbiome; Network analysis; Bacteria; Archaea; Niche differentiation; Ecological guilds (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:431:y:2020:i:c:s0304380020302180

DOI: 10.1016/j.ecolmodel.2020.109147

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