FreshOmics: A manually curated and standardized -omics database for investigating freshwater microbiomes.

Freshwater is a critical resource for human survival but severely threatened by anthropogenic activities and climate change. These changes strongly impact the abundance and diversity of the microbial communities which are key players in the functioning of these aquatic ecosystems. Although widely documented since the emergence of high-throughput sequencing approaches, the information on these natural microbial communities is scattered among thousands of publications and it is therefore difficult to investigate the temporal dynamics and the spatial distribution of microbial taxa within or across ecosystems.

A drift-barrier model drives the genomic landscape of a structured bacterial population.

Bacterial populations differentiate over time and space to form distinct genetic units. The mechanisms governing this diversification are presumed to result from the ecological context of living units to adapt to specific niches. Recently, a model assuming the acquisition of advantageous genes among populations rather than whole genome sweeps has emerged to explain population differentiation.

Meta-analysis of glyphosate contamination in surface waters and dissipation by biofilms.

One consequence of the intensive use of glyphosate is the contamination of rivers by the active substance and its metabolites aminomethyl phosphonic acid (AMPA) and sarcosine, inducing river eutrophication. Biofilms are the predominant lifestyle for microorganisms in rivers, providing pivotal roles in ecosystem functioning and pollutant removal. The persistence of glyphosate in these ecosystems is suspected to be mostly influenced by microbial biodegradation processes.

New insights into the pelagic microorganisms involved in the methane cycle in the meromictic Lake Pavin through metagenomics.

Advances in metagenomics have given rise to the possibility of obtaining genome sequences from uncultured microorganisms, even for those poorly represented in the microbial community, thereby providing an important means to study their ecology and evolution. In this study, metagenomic sequencing was carried out at four sampling depths having different oxygen concentrations or environmental conditions in the water column of Lake Pavin. By analyzing the sequenced reads and matching the contigs to the proxy genomes of the closest cultivated relatives, we evaluated the metabolic potential of the dominant planktonic species involved in the methane cycle.