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Biomedical subjects

Jesus M Eraso

Publications and source records attributed to Jesus M Eraso.

3 recordsLinked to original sources

Gene Contribution of Streptococcus dysgalactiae Subspecies equisimilis, an Emerging Pathogen, to Experimental Primate Necrotizing Myositis.

Streptococcus dysgalactiae subspecies equisimilis (SDSE) is an emerging human pathogen closely related to group A Streptococcus. However, its genetic requirements for survival and growth in different conditions and for causing invasive infections remain poorly understood. To address this gap, transposon-directed insertion-site sequencing was used to identify genes contributing to fitness in experimental necrotizing myositis in nonhuman primates. Using two SDSE stG62647 human clinical isolates, MGCS36044 and MGCS36089, highly saturated transposon mutant libraries were generated and analyzed following in vitro growth and in vivo infection in eight nonhuman primates. A total of 398 essential genes were identified to be shared by both strains during growth in vitro and in vivo, and 17 and 7 conditionally essential genes required only in vitro or only in vivo, respectively. Additionally, 117 and 110 genes in MGCS36044 and MGCS36089, respectively, were found to be associated with fitness during necrotizing myositis. Transposon insertions in 34 MGCS36044 genes conferred increased fitness, whereas mutation of 83 genes conferred decreased fitness. Similarly, in MGCS36089, mutations in 38 and 72 genes conferred increased or decreased fitness, respectively. Importantly, both strains shared 46 fitness-associated genes, including an enrichment of transporter genes, highlighting nutrient acquisition as a dominant requirement during infection. The results provide critical information for guiding future translational efforts to develop preventive and therapeutic strategies against human SDSE infections.

Animals↗

Combining microarray and genomic data to predict DNA binding motifs.

The ability to detect regulatory elements within genome sequences is important in understanding how gene expression is controlled in biological systems. In this work, microarray data analysis is combined with genome sequence analysis to predict DNA sequences in the photosynthetic bacterium Rhodobacter sphaeroides that bind the regulators PrrA, PpsR and FnrL. These predictions were made by using hierarchical clustering to detect genes that share similar expression patterns. The DNA sequences upstream of these genes were then searched for possible transcription factor recognition motifs that may be involved in their co-regulation. The approach used promises to be widely applicable for the prediction of cis-acting DNA binding elements. Using this method the authors were independently able to detect and extend the previously described consensus sequences that have been suggested to bind FnrL and PpsR. In addition, sequences that may be recognized by the global regulator PrrA were predicted. The results support the earlier suggestions that the DNA binding sequence of PrrA may have a variable-sized gap between its conserved block elements. Using the predicted DNA binding sequences, a whole-genome-scale analysis was performed to determine the relative importance of the interplay between the three regulators PpsR, FnrL and PrrA. Results of this analysis showed that, compared to the regulation by PpsR and FnrL, a much larger number of genes are candidates to be regulated by PrrA. The study demonstrates by example that integration of multiple data types can be a powerful approach for inferring transcriptional regulatory patterns in microbial systems, and it allowed the detection of photosynthesis-related regulatory patterns in R. sphaeroides.

Bacterial Proteins↗