Contemporary environmental variation determines microbial diversity patterns in acid mine drainage
A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiat...
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| Published in | The ISME Journal Vol. 7; no. 5; pp. 1038 - 1050 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
01.05.2013
Oxford University Press Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance.
Betaproteobacteria
, mostly affiliated with the ‘
Ferrovum
’ genus, were explicitly predominant in assemblages under moderate pH conditions, whereas
Alphaproteobacteria
,
Euryarchaeota
,
Gammaproteobacteria
and
Nitrospira
exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems. |
|---|---|
| AbstractList | A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance. Betaproteobacteria, mostly affiliated with the 'Ferrovum' genus, were explicitly predominant in assemblages under moderate pH conditions, whereas Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria and Nitrospira exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems. A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance. Betaproteobacteria , mostly affiliated with the ‘ Ferrovum ' genus, were explicitly predominant in assemblages under moderate pH conditions, whereas Alphaproteobacteria , Euryarchaeota , Gammaproteobacteria and Nitrospira exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems. A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance. Betaproteobacteria, mostly affiliated with the 'Ferrovum' genus, were explicitly predominant in assemblages under moderate pH conditions, whereas Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria and Nitrospira exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems.A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance. Betaproteobacteria, mostly affiliated with the 'Ferrovum' genus, were explicitly predominant in assemblages under moderate pH conditions, whereas Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria and Nitrospira exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems. |
| Author | Hu, Min Li, Jin-Tian Kuang, Jia-Liang Chen, Lin-Xing Hua, Zheng-Shuang Shu, Wen-Sheng Huang, Li-Nan Li, Sheng-Jin |
| Author_xml | – sequence: 1 givenname: Jia-Liang surname: Kuang fullname: Kuang, Jia-Liang organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 2 givenname: Li-Nan surname: Huang fullname: Huang, Li-Nan organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 3 givenname: Lin-Xing surname: Chen fullname: Chen, Lin-Xing organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 4 givenname: Zheng-Shuang surname: Hua fullname: Hua, Zheng-Shuang organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 5 givenname: Sheng-Jin surname: Li fullname: Li, Sheng-Jin organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 6 givenname: Min surname: Hu fullname: Hu, Min organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 7 givenname: Jin-Tian surname: Li fullname: Li, Jin-Tian organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University – sequence: 8 givenname: Wen-Sheng surname: Shu fullname: Shu, Wen-Sheng email: shuws@mail.sysu.edu.cn organization: State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23178673$$D View this record in MEDLINE/PubMed |
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| Keywords | pyrosequencing acid mine drainage contemporary environmental variation microbial diversity biogeography geographical distance |
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| Title | Contemporary environmental variation determines microbial diversity patterns in acid mine drainage |
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