Temperate oceans are inhabited by diverse and temporally dynamic bacterioplankton communities. However, the role of the environment, resources and phytoplankton dynamics in shaping marine bacterioplankton communities at different time scales remains poorly constrained. Here, we combined time-series observations (time scales of weeks to years) with molecular analysis of formalin-fixed samples from a coastal inlet of the northwest Atlantic Ocean to show that a combination of temperature, nitrate, small phytoplankton and Synechococcus abundances are best predictors for annual bacterioplankton community variability, explaining 38% of the variation. Using Bayesian mixed modeling we identified assemblages of co-occurring bacteria associated with different seasonal periods, including the spring bloom (e.g. Polaribacter, Ulvibacter, Alteromonadales, and ARCTIC96B-16) and the autumn bloom (e.g. OM42, OM25, OM38 and Arctic96A-1 clades of Alpha-proteobacteria and SAR86, OM60, and SAR92 clades of Gamma-proteobacteria). Community variability over spring bloom development was best explained by silicate (32%) - an indication of rapid succession of bacterial taxa in response to diatom biomass- while nanophytoplankton as well as picophytoplankton abundance explained community variability (16-27%) over the transition into and out of the autumn bloom. Moreover, the seasonal structure was punctuated with short-lived blooms of rare bacteria including the KSA-1 clade of Sphingobacteria related to aromatic hydrocarbon-degrading bacteria.
Adequate modeling of mitochondrial sequence evolution is an essential component of mitochondrial phylogenomics (comparative mitogenomics). There is wide recognition within the field that lineage-specific aspects of mitochondrial evolution should be accommodated through lineage-specific amino-acid exchangeability matrices (e.g., mtMam for mammalian data). However, such a matrix must be applied to all sites and this implies that all sites are subject to the same, or largely similar, evolutionary constraints. This assumption is unjustified. Indeed, substantial differences are expected to arise from three-dimensional structures that impose different physiochemical environments on individual amino acid residues. The objectives of this paper are (1) to investigate the extent to which amino acid evolution varies among sites of mitochondrial proteins, and (2) to assess the potential benefits of explicitly modeling such variability. To achieve this, we developed a novel method for partitioning sites based on amino acid physiochemical properties. We apply this method to two datasets derived from complete mitochondrial genomes of mammals and fish, and use maximum likelihood to estimate amino acid exchangeabilities for the different groups of sites. Using this approach we identified large groups of sites evolving under unique physiochemical constraints. Estimates of amino acid exchangeabilities differed significantly among such groups. Moreover, we found that joint estimates of amino acid exchangeabilities do not adequately represent the natural variability in evolutionary processes among sites of mitochondrial proteins. Significant improvements in likelihood are obtained when the new matrices are employed. We also find that maximum likelihood estimates of branch lengths can be strongly impacted. We provide sets of matrices suitable for groups of sites subject to similar physiochemical constraints, and discuss how they might be used to analyze real data. We also discuss how the general approach might be employed to improve a variety of mitogenomic-based research activities.
Sequential antimicrobial therapy is an important part of antimicrobial stewardship and intends to improve the timeliness of switch to oral antimicrobials. The aim of this study was to assess the impact of the introduction of guidelines and criteria for switching to oral antimicrobials.
There is growing evidence for a discontinuity between genomic and ecological divergence in several groups of bacteria. This evidence is difficult to reconcile with the traditional concept that ecologically divergent species maintain a cohesive gene pool isolated from other gene pools by barriers to homologous recombination (HR). There have been several innovative models of bacterial divergence that permit such discontinuity; we refer to these, collectively, as "mosaic genome concepts" (MGCs). These concepts remain a point of contention. Here, we undertake an investigation among ecologically divergent lineages of genus Listeria, and report our assessment of both niche-specific selection pressure and HR in their core genome. We find evidence of a mosaic Listeria core genome. Some core genes appear to have been free to recombine across ecologically divergent lineages or across named species. In contrast, other core genes have histories consistent with the expected organism relationships and have evolved under niche-specific selective pressures. The products of some of those genes can even be linked to metabolic phenotypes with ecological significance. This finding indicates a potentially strong connection between ecological divergence and core-genome evolution, even among lineages that also experience frequent recombination. Based on these findings, we propose an expanded role for natural selection in core-genome evolution under the MGC.
The RAS-mitogen-activated protein kinase signaling pathway is often deregulated in cancer cells. In metastatic HRAS-transformed mouse fibroblasts (Ciras-3), the RAS-MAPK pathway is constitutively activated. We show here that Ciras-3 cells exhibit a higher incidence of chromosomal instability than 10T1/2 cells, including higher levels of clonal and nonclonal chromosomal aberrations. Stimulation of serum starved 10T1/2 and Ciras-3 cells with phorbol esters (TPA) results in the phosphorylation of histone H3 at serine 10 and serine 28. Regardless of the increased genomic instability in Ciras-3 cells, TPA-induced H3 phosphorylated at serine 10 and H3 phosphorylated at serine 28 partitioned into distinct nuclear subdomains as they did in the parental cells. However, the timing of the response of the H3 phosphorylation event to TPA induction was delayed in Ciras-3 cells. Further Ciras-3 cells, which have a more open chromatin structure, had increased steady state levels of phosphorylated H3 and HMGN1 relative to parental 10T1/2 cells. TPA-induced H3 phosphorylated at serine 10 and 28 were colocalized with the transcriptionally initiated form of RNA polymerase II in 10T1/2 and Ciras-3 cells. Chromatin immunoprecipitation assays demonstrated that TPA-induced H3 phosphorylation at serine 28 was associated with the immediate early JUN promoter, providing direct evidence that this histone post-translational modification is associated with transcriptionally active genes. Together our results demonstrate the increased genomic instability and alterations in the epigenetic program in HRAS-transformed cells.
Leveraging The Cancer Genome Atlas (TCGA) multidimensional data in glioblastoma, we inferred the putative regulatory network between microRNA and mRNA using the Context Likelihood of Relatedness modeling algorithm. Interrogation of the network in context of defined molecular subtypes identified 8 microRNAs with a strong discriminatory potential between proneural and mesenchymal subtypes. Integrative in silico analyses, a functional genetic screen, and experimental validation identified miR-34a as a tumor suppressor in proneural subtype glioblastoma. Mechanistically, in addition to its direct regulation of platelet-derived growth factor receptor-alpha (PDGFRA), promoter enrichment analysis of context likelihood of relatedness-inferred mRNA nodes established miR-34a as a novel regulator of a SMAD4 transcriptional network. Clinically, miR-34a expression level is shown to be prognostic, where miR-34a low-expressing glioblastomas exhibited better overall survival. This work illustrates the potential of comprehensive multidimensional cancer genomic data combined with computational and experimental models in enabling mechanistic exploration of relationships among different genetic elements across the genome space in cancer.
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