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Genomic and metagenomic insights into the microbial community of a thermal spring.

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PubMed ID: 30674352

Imagen Publicación

Pedron R, Esposito A, Bianconi I, Pasolli E, Tett A, Asnicar F, Cristofolini M, Segata N, Jousson O

Microbiome. Jan 2019. doi: 10.1186/s40168-019-0625-6

Comment: A comprehensive study of a spring water microbiome, the taxonomic composition was inferred by 16S amplicon sequencing, shotgun metagenomics, high-throughput culturing and Metagenome-assembled genomes (MAGs).

Objective

This study integrates metagenomics and large-scale culturing approaches to provide a comprehensive view of a spring water microbiome. The taxonomic composition of bacterial communities of the thermal spring of Comano Terme (Italy) is described at four sampling sites and the metabolic potential encoded in the metagenomic dataset is inferred.

Main results

Microbiome composition of Comano Terme water inferred by 16S amplicon sequencing is dominated by Proteobacteria (35.9% s.d. 14.4%) and Nitrospirae (9.9% s.d. 4.4%).

Many isolates and most MAGs were classified as new genera or higher taxonomic ranks, probably due to the peculiarity of this groundwater-fed spring environment.

Shotgun metagenomic sequencing revealed a high proportion of undescribed taxa.

A total of 108 out of 250 (43.2%) unclassified taxa were identified, mainly at the species (84/108, 77.8%) and genus (23/108, 21.3%) levels.

The four samples analyzed (two natural environments and two artificial ones) differed markedly in taxonomic composition and community structure

Proteobacteria dominated the water microbiome in all sampling sites, although in hydra and spring, the dominance was less pronounced (68.9% and 72.2% versus 84.4% and 84.5% in storage tank and bathtub, respectively).

Viruses represent the second most abundant source of DNA and are rather homogeneously distributed between all samples.

Conclusions

Our results confirm that groundwater environments host highly adapted, stable microbial communities. We showed the occurrence of a high functional partitioning where methane production and consumption are spatially separated.

Contributor

Diana López-Farfán