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Rojas-Vargas, J.

Publications and source records attributed to Rojas-Vargas, J..

3 recordsLinked to original sources

Evolutionary fingerprinting of protein-coding genes in RNA viruses

RNA viruses evolve rapidly to adapt to changing host environments. Much of this adaptation occurs at the level of protein-coding genes. Thus, some of the most well-characterized examples of rapid adaptation have been found in virus proteins that are exposed on the surface of the viral particle, where they mediate host receptor binding and cell entry. To investigate whether surface-exposed proteins and other proteins encoded by viruses exhibit different patterns of evolution under selection, we analyzed 244 protein-coding genes from 28 species of RNA viruses representing 15 taxonomic families. First, we show that gene-wide rates of non-synonymous (dN) and synonymous (dS) substitutions do not differentiate between categories of proteins. To provide a more detailed comparison between genes, we inferred for each alignment the bivariate posterior distribution over a fixed grid of codon site-specific dN and dS values. This distribution is the genes evolutionary fingerprint. Next, we computed the Wasserstein distance for every pair of fingerprints, which is analogous to amount of work required to reshape one distribution to another. After compensating for differences in genetic variation among viruses and proteins, we found that surface-exposed proteins could not be distinguished from non-exposed proteins in the space induced by the Wasserstein distance matrix. However, surface-exposed proteins from enveloped viruses were significantly clustered apart from their counterparts in non-enveloped viruses. In contrast, there was no significant separation between these categories of viruses for proteins with polymerase activity. We show that this pattern is more consistent with relaxed purifying selection than adaptive evolution in proteins associated with viral envelopes.

evolutionary biology↗

The vaginal microbiota, symptoms, and local immune correlates in transmasculine individuals using sustained testosterone therapy

Transmasculine individuals (assigned female at birth, masculine gender identity, TM) may use gender-affirming testosterone therapy, and some TM report adverse genital symptoms during treatment. In cis women, the vaginal microbiota is a key determinant of reproductive and sexual health outcomes; Lactobacillus-dominant communities are considered optimal, while more even, diverse, Lactobacillus-depleted microbiota are considered non-optimal. Prior studies suggest Lactobacillus deficiency in TM vaginal microbiota, but associations with symptoms and immune markers remain unclear. We launched the TransBiota study to characterize the TM vaginal microbiota, soluble mediators of local inflammation (SMI), and self-reported symptoms over three weeks. Fewer than 10% of TM possessed Lactobacillus-dominant microbiota, and most exhibited more diverse, Lactobacillus-depleted microbiota. We identified 11 vaginal microbiota community state types (tmCSTs), with Lactobacillus-dominant tmCSTs unexpectedly linked to abnormal odor and elevated IL-1. These findings indicate that Lactobacillus dominance may no longer be an optimal state for TM during gender-affirming testosterone therapy and change in clinical management is needed.

microbiology↗

HADEG: A Curated Database of Hydrocarbon Aerobic Degradation Enzymes and Genes

Databases of genes and enzymes involved in hydrocarbon degradation have been previously reported. However, these databases specialize on only a specific group of hydrocarbons and/or are constructed partly based on enzyme sequences with putative functions indicated by in silico research, with no experimental evidence. Here, we present a curated database of Hydrocarbon Aerobic Degradation Enzymes and Genes (HADEG) containing proteins and genes involved in alkane, alkene, aromatic, and plastic aerobic degradation and biosurfactant production based solely on experimental evidence, which are present in bacteria, and fungi. HADEG includes 259 proteins for petroleum hydrocarbon degradation, 160 for plastic degradation, and 32 for biosurfactant production. This database will help identify and predict hydrocarbon degradation genes/pathways and biosurfactant production in genomes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/505856v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@6019a4org.highwire.dtl.DTLVardef@1337dfaorg.highwire.dtl.DTLVardef@193b3fcorg.highwire.dtl.DTLVardef@d80de_HPS_FORMAT_FIGEXP M_FIG C_FIG Data summaryThe HADEG database repository is https://github.com/jarojasva/HADEG. All Supplementary Material file is available on: https://figshare.com/articles/dataset/Supplementary_Material_HADEG/20752642.

bioinformatics↗