Presence of pathogenicity island related and plasmid encoded virulence genes in cytolethal distending toxin producing Escherichia coli isolates from diarrheal cases

Classification of bacterial plasmid and chromosome derived sequences using machine learning

Plasmids are important genetic elements that facilitate horizonal gene transfer between bacteria and contribute to the spread of virulence and antimicrobial resistance. Most bacterial genome sequences in the public archives exist in draft form with many contigs, making it difficult to determine if a contig is of chromosomal or plasmid origin. Using a training set of contigs comprising 10,584 chromosomes and 10,654 plasmids from the PATRIC database, we evaluated several machine learning models including random forest, logistic regression, XGBoost, and a neural network for their ability to classify chromosomal and plasmid sequences using nucleotide k-mers as features. Based on the methods tested, a neural network model that used nucleotide 6-mers as features that was trained on randomly selected chromosomal and plasmid subsequences 5kb in length achieved the best performance, outperforming existing out-of-the-box methods, with an average accuracy of 89.38% ± 2.16% over a 10-fold cross validation. The model accuracy can be improved to 92.08% by using a voting strategy when classifying holdout sequences. In both plasmids and chromosomes, subsequences encoding functions involved in horizontal gene transfer-including hypothetical proteins, transporters, phage, mobile elements, and CRISPR elements-were most likely to be misclassified by the model. This study provides a straightforward approach for identifying plasmid-encoding sequences in short read assemblies without the need for sequence alignment-based tools.

The Enterobacterial Genotoxins: Cytolethal Distending Toxin and Colibactin

While the DNA damage induced by ionizing radiation and by many chemical compounds and drugs is well characterized, the genotoxic insults inflicted by bacteria are only scarcely documented. However, accumulating evidence indicates that we are exposed to bacterial genotoxins. The prototypes of such bacterial genotoxins are the Cytolethal Distending Toxins (CDTs) produced by Escherichia coli and Salmonella enterica serovar Typhi. CDTs display the DNase structure fold and activity, and induce DNA strand breaks in the intoxicated host cell nuclei. E. coli and certain other Enterobacteriaceae species synthesize another genotoxin, colibactin. Colibactin is a secondary metabolite, a hybrid polyketide/nonribosomal peptide compound synthesized by a complex biosynthetic machinery. In this review, we summarize the current knowledge on CDT and colibactin produced by E. coli and/or Salmonella Typhi. We describe their prevalence, genetic determinants, modes of action, and impact in infectious diseases or gut colonization, and discuss the possible involvement of these genotoxigenic bacteria in cancer.

Alteration of Homeostasis in Pre-osteoclasts Induced by Aggregatibacter actinomycetemcomitans CDT

The dysbiotic microbiota associated with aggressive periodontitis includes Aggregatibacter actinomycetemcomitans, the only oral species known to produce a cytolethal distending toxin (AaCDT). Give that CDT alters the cytokine profile in monocytic cells, we aimed to test the hypothesis that CDT plays a role in bone homeostasis by affecting the differentiation of precursor cells into osteoclasts. Recombinant AaCDT was added to murine bone marrow monocytes (BMMC) in the presence or absence of RANKL and the cell viability and cytokine profile of osteoclast precursor cells were determined. Multinucleated TRAP(+) cell numbers, and relative transcription of genes related to osteoclastogenesis were also evaluated. The addition of AaCDT did not lead to loss in cell viability but promoted an increase in the average number of TRAP(+) cells with 1-2 nuclei in the absence or presence of RANKL (Tukey, p < 0.05). This increase was also observed for TRAP(+) cells with ≥3nuclei, although this difference was not significant. Levels of TGF-β, TNF-α, and IL-6, in the supernatant fraction of cells, were higher when in AaCDT exposed cells, whereas levels of IL-1β and IL-10 were lower than controls under the same conditions. After interaction with AaCDT, transcription of the rank (encoding the receptor RANK), nfatc1 (transcription factor), and ctpK (encoding cathepsin K) genes was downregulated in pre-osteoclastic cells. The data indicated that despite the presence of RANKL and M-CSF, AaCDT may inhibit osteoclast differentiation by altering cytokine profiles and repressing transcription of genes involved in osteoclastogenesis. Therefore, the CDT may impair host defense mechanisms in periodontitis.