Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-Seq are one of the most commonly used techniques to perform transcriptional experiments. Computational analysis of such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-Seq datasets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsigand next identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50% of the genes identified as influential had some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes had crucial roles or participated in processes associated with the response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis.
Corynebacterium pseudotuberculosis is the etiological agent of caseous lymphadenitis disease. In this work, we present the first complete genome sequence of Corynebacterium pseudotuberculosis strain PA01, isolated in northern Brazil from an infected sheep. The genome length is 2,337,920 bp, and 2,003 coding sequences (CDS), 12 rRNAs, and 49 tRNAs were predicted.
Corynebacterium pseudotuberculosis is related to several diseases infecting horses and small ruminants, causing economic losses to agribusiness. Here, we present the genome sequence of C. pseudotuberculosis strain E19. The genome includes one circular chromosome 2,367,956 bp (52.1% G+C content), with 2,112 genes predicted, 12 rRNAs, and 48 tRNAs.
The spread and contamination of antimicrobial-resistant bacteria in ambient waters is an emerging concern in urban, rural, medical, and industrial settings. A large amount of domestic, hospital, and industrial wastewater discharged directly into the rivers through the different channels can turn them into extensive reservoirs of antibiotic-resistant bacteria. In the present study, surface water samples from three collection sites were analyzed, according to different levels of anthropogenic impacts, along the Ozama River, one of the most important rivers in the Dominican metropolitan area, a source of water and food for human consumption. Seventy-six bacterial isolates were selected based on resistance to beta-lactams, using culture media previously enriched with cefotaxime and imipenem. Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF) subsequently identified them. The isolates covered 12 genera of bacteria; more than 30% were clinically relevant, and 43% had phenotypes classified as multidrug resistance. A total of 10 (44%) presented resistance. However, only seven presented resistance to 3 or more of the 14 groups of antibiotics, considered to be a multiresistant phenotype, which was sequenced using the high-throughput sequencing technique or New Generation (NGS). This study is part of the initiative to understand the profiles of the dangers of multidrug resistance in the metropolitan and rural areas of the Dominican Republic and its possible implications for human health.
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