Diversity and Expression of Bacterial Metacaspases in an Aquatic Ecosystem.

Asplund-Samuelsson J, Sundh J, Dupont CL, Allen AE, McCrow JP, Celepli NA, Bergman B, Ininbergs K, Ekman M

Front Microbiol 7 (-) 1043 [2016-07-06; online 2016-07-06]

Metacaspases are distant homologs of metazoan caspase proteases, implicated in stress response, and programmed cell death (PCD) in bacteria and phytoplankton. While the few previous studies on metacaspases have relied on cultured organisms and sequenced genomes, no studies have focused on metacaspases in a natural setting. We here present data from the first microbial community-wide metacaspase survey; performed by querying metagenomic and metatranscriptomic datasets from the brackish Baltic Sea, a water body characterized by pronounced environmental gradients and periods of massive cyanobacterial blooms. Metacaspase genes were restricted to ~4% of the bacteria, taxonomically affiliated mainly to Bacteroidetes, Alpha- and Betaproteobacteria and Cyanobacteria. The gene abundance was significantly higher in larger or particle-associated bacteria (>0.8 μm), and filamentous Cyanobacteria dominated metacaspase gene expression throughout the bloom season. Distinct seasonal expression patterns were detected for the three metacaspase genes in Nodularia spumigena, one of the main bloom-formers. Clustering of normalized gene expression in combination with analyses of genomic and assembly data suggest functional diversification of these genes, and possible roles of the metacaspase genes related to stress responses, i.e., sulfur metabolism in connection to oxidative stress, and nutrient stress induced cellular differentiation. Co-expression of genes encoding metacaspases and nodularin toxin synthesis enzymes was also observed in Nodularia spumigena. The study shows that metacaspases represent an adaptation of potentially high importance for several key organisms in the Baltic Sea, most prominently Cyanobacteria, and open up for further exploration of their physiological roles in microbes and assessment of their ecological impact in aquatic habitats.

Bioinformatics Compute and Storage [Service]

NGI Stockholm (Genomics Applications) [Service]

NGI Stockholm (Genomics Production) [Service]

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PubMed 27458440

DOI 10.3389/fmicb.2016.01043

Crossref 10.3389/fmicb.2016.01043

pmc PMC4933709