ena-STUDY-UIO-01-10-2020-14:42:05:114-33
Two different approaches of microbial community structure characterization in riverine epilithic biofilms under multiple stressors conditions: developing molecular indicators.
Microbial communities are major players in the biogeochemical processes and ecosystem functioning of river networks. Despite their importance in the ecosystem, there is a lack of integrative methods for the analysis of microbial communities embracing both, quantitative and qualitative data. So far, only a few studies have employed both sequencing of the 16S rRNA and quantitative techniques such as Catalyzed reported deposition in situ fluorescence hybridization (CARD-FISH) to analyse Prokaryotic communities of epilithic biofilms in stream ecosystems. We intended to investigate the efficacy of both the techniques in detecting changes in microbial community structure associated with environmental drivers. We report a significant correlation between the Prokaryotic community composition and pH in rivers from two different geographical areas in Norway. Similarity matrices produced for from both, CARD-FISH and HTS data, were positively correlated with the similarity matrix for environmental variables, confirming the close connection between these biological communities and physico-chemical drivers. Although showing similar patterns, the two techniques seem to have a different accuracy in discriminating the variability of the microbial community structure in the two regions analysed. The results of Beta-dispersion analyses on both, CARD-FISH abundance data and HTS, revealed higher accuracy of the sequencing method in detecting differences in the microbial community composition at large and meso spatial scales. The results from hybridization in situ technique showed high variability, even for samples within the same river. Therefore, absolute cell numbers may highlight sensitivity to microscale environmental conditions. We also propose a method, based on the sequencing results, to detect possible biological indicators, by comparing the prevalence and variance among Prokaryotic taxa. Overall, as it is for other bioindicators (i.e. macroinvertebrates), the use of different methods, including taxonomic resolution and enumeration, will depend on the type, the scale and the purpose of the bio-assessment.
Microbial communities are major players in the biogeochemical processes and ecosystem functioning of river networks. Despite their importance in the ecosystem, there is a lack of integrative methods for the analysis of microbial communities embracing both, quantitative and qualitative data. So far, only a few studies have employed both sequencing of the 16S rRNA and quantitative techniques such as Catalyzed reported deposition in situ fluorescence hybridization (CARD-FISH) to analyse Prokaryotic communities of epilithic biofilms in stream ecosystems. We intended to investigate the efficacy of both the techniques in detecting changes in microbial community structure associated with environmental drivers. We report a significant correlation between the Prokaryotic community composition and pH in rivers from two different geographical areas in Norway. Similarity matrices produced for from both, CARD-FISH and HTS data, were positively correlated with the similarity matrix for environmental variables, confirming the close connection between these biological communities and physico-chemical drivers. Although showing similar patterns, the two techniques seem to have a different accuracy in discriminating the variability of the microbial community structure in the two regions analysed. The results of Beta-dispersion analyses on both, CARD-FISH abundance data and HTS, revealed higher accuracy of the sequencing method in detecting differences in the microbial community composition at large and meso spatial scales. The results from hybridization in situ technique showed high variability, even for samples within the same river. Therefore, absolute cell numbers may highlight sensitivity to microscale environmental conditions. We also propose a method, based on the sequencing results, to detect possible biological indicators, by comparing the prevalence and variance among Prokaryotic taxa. Overall, as it is for other bioindicators (i.e. macroinvertebrates), the use of different methods, including taxonomic resolution and enumeration, will depend on the type, the scale and the purpose of the bio-assessment.