Next-generation diagnostics of escherichia coli from community-onset sepsis patients in sweden : Studying the biodiversity of escherichia coli genomes

• Main Author: Mahmoud, Nada
• Format: Others
• Language: English
• Published: Högskolan i Skövde, Institutionen för biovetenskap 2021
• Subjects: Bioinformatics and Systems Biology; Bioinformatik och systembiologi
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19893

Escherichia coli (E. coli) is among the gram-negative bacteria that can cause several infections including sepsis. Confirmed sepsis patients must show a sequential organ failure assessment (SOFA) score of ≥2 with verified infection. Understanding the genotypic characteristics of E. coliclinical isolates from sepsis patients can help directing treatment strategies, tracking antibiotic resistance, and monitoring acquired virulence factors that can contribute to the severity of sepsis. The isolates included in this thesis were collected from confirmed sepsis patients (SOFA 2-3)during a prospective observational study that was conducted in Sweden. The aim was to study the biodiversity in E. coli clinical isolates using whole genome sequencing (WGS) paired-end reads that were produced by the next-generation sequencer Illumina. To perform the WGS-based analysis, two bioinformatics pipelines were used. The first is the in-house developed pipeline and the second is the 1928Diagnostics E. coli pipeline. The obtained in silico results were compared with the phenotypic findings for species identification and the in vitro predictions of antibiotic resistance. Species identification by the bioinformatics pipelines matched the phenotypic method, except for three isolates that were highly contaminated with other species. Both pipelines predicted the exact multi locus sequence types, which revealed that the most common sequence types (STs) were ST73(17%), ST95(9%), and ST131(6%). The phenotype of the isolates resulted in 5% resistant to at least one of the assessed antibiotics. The 1928Diagnostics predicted 28% of the isolates were resistant to at least one class of the tested antibiotic classes, while the in-house pipeline predicted 33% of the isolates to be resistant. Out of the predicted resistant isolates, 52% coded for multi-drug resistance. The in-house pipeline reported virulence genes. The common reported genes were coding for iron reuptake, adhesins, cell outer membrane and increased serum survival. It was observed that the isolates that belonged to ST73 and ST95 showed a more susceptible antibiotic profile than isolates that belonged to ST131, those harbored the highest mean of virulence genes. In conclusion, the present study provided an evidence of the usefulness of the WGS-based analysis to study the biodiversity in E. coli. The obtained results are valuable for surveillances, tracking antibiotic resistance and identifying virulence factors, but with a limited use in clinical settings.