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In search of microbial indicator taxa: shifts in stream bacterial communities along an urbanization gradient
Author(s) -
Simonin Marie,
Voss Kristofor A.,
Hassett Brooke A.,
Rocca Jennifer D.,
Wang SiYi,
Bier Raven L.,
Violin Christy R.,
Wright Justin P.,
Bernhardt Emily S.
Publication year - 2019
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.14694
Subject(s) - acidobacteria , biology , ecology , taxon , betaproteobacteria , ecosystem , microbial population biology , taxonomic rank , microbial ecology , phylum , community structure , actinobacteria , bacteria , genetics , 16s ribosomal rna
Summary A majority of environmental studies describe microbiomes at coarse scales of taxonomic resolution (bacterial community, phylum), ignoring key ecological knowledge gained from finer‐scales and microbial indicator taxa. Here, we characterized the distribution of 940 bacterial taxa from 41 streams along an urbanization gradient (0%–83% developed watershed area) in the Raleigh‐Durham area of North Carolina (USA). Using statistical approaches derived from macro‐organismal ecology, we found that more bacterial taxa were classified as intolerant than as tolerant to increasing watershed urbanization (143 vs 48 OTUs), and we identified a threshold of 12.1% developed watershed area beyond which the majority of intolerant taxa were lost from streams. Two bacterial families strongly decreased with urbanization: Acidobacteriaceae (Acidobacteria) and Xanthobacteraceae (Alphaproteobacteria). Tolerant taxa were broadly distributed throughout the bacterial phylogeny, with members of the Comamonadaceae family (Betaproteobacteria) presenting the highest number of tolerant taxa. Shifts in microbial community structure were strongly correlated with a stream biotic index, based on macroinvertebrate composition, suggesting that microbial assemblages could be used to establish biotic criteria for monitoring aquatic ecosystems. In addition, our study shows that classic methods in community ecology can be applied to microbiome datasets to identify reliable microbial indicator taxa and determine the environmental constraints on individual taxa distributions along environmental gradients.