Sulfate reducing prokaryotes (SRP) are a phylogenetically and physiologically diverse group of microorganisms that use sulfate as an electron acceptor. SRP have long been recognized as key players of the carbon and sulfur cycles, and more recently, they have been identified to play a relevant role as part of syntrophic and symbiotic relations and the human microbiome. Despite their environmental relevance, there is a poor understanding about the prevalence of prophages and CRISPR arrays and how their distribution and dynamic affect the ecological role of SRP. We addressed this question by analyzing the results of a comprehensive survey of prophages and CRISPR in a total of 91 genomes of SRP with several genotypic, phenotypic, and physiological traits, including genome size, cell volume, minimum doubling time, cell wall, and habitat, among others. Our analysis discovered 81 prophages in 51 strains, representing the 56% of the total evaluated strains. Prophages are non-uniformly distributed across the SRP phylogeny, where prophage-rich lineages belonged to Desulfovibrionaceae and Peptococcaceae. Furthermore, our study found 160 CRISPR arrays in 71 SRP, which is more abundant and widely spread than previously expected. Although there is no correlation between presence and abundance of prophages and CRISPR arrays at the strain level, our analysis showed that there is a directly proportional relation between cellular volumes and number of prophages per cell. This result suggests that there is an additional selective pressure for strains with smaller cells to get rid of foreign DNA, such as prophages, but not CRISPR, due to less availability of cellular resources. Analysis of the prophage genes encoding viral structural proteins reported that 44% of SRP prophages are classified as Myoviridae, and comparative analysis showed high level of homology, but not synteny, among prophages belonging to the Family Desulfovibrionaceae. We further recovered viral-like particles and structures that resemble outer membrane vesicles from D. vulgaris str. Hildenborough. The results of this study improved the current understanding of dynamic interactions between prophages and CRISPR with their hosts in both cultured and hitherto-uncultured SRP strains, and how their distribution affects the microbial community dynamics in several sulfidogenic natural and engineered environments.

Selecting physics parameterizations for meteorological simulations is typically guided by univariate metrics, which are computed separately for each variable and station and frequently yield contradictory rankings and force subjective decisions. Although the Mahalanobis distance (MD) has previously been used for multivariate analysis, to the best of our knowledge, it has not previously been used as a decision criterion for selecting physics parameterizations in meteorological simulations. This study proposes the MD as a single multivariate performance metric that is dimensionless, invariant to measurement scales, and corrects for inter-variable correlations. The framework was demonstrated using 40 meteorological simulations combining microphysics, radiation, surface-layer, planetary boundary layer, and cumulus schemes, evaluated against hourly observations of temperature, relative humidity, and wind at surface stations in the Biobío region, south-central Chile. The traditional univariate metrics nominated different optimal configurations depending on the variable and station. In contrast, the MD identified a single configuration attaining the minimum distance at three of the four stations and the minimum cross-station mean, and revealed that performance was governed primarily by the surface-layer/PBL pairing rather than by microphysics or radiation choices. The MD thus provides an objective, reproducible, and easily interpretable criterion for parameterization selection, directly applicable to meteorological inputs for air quality modeling.