Whole-Genome Sequencing, Annotation and Taxonomic Confirmation of a Multidrug-Resistant Escherichia coli Isolated from the Blood of a Sepsis Patient

Abstract

Sepsis (blood stream infection) caused by multidrug-resistant (MDR) bacteria, particularly Escherichia coli, represents a significant global health threat due to high morbidity, mortality, and limited treatment options. E. coli, a major causative agent of bloodstream infections, has evolved highly virulent and MDR strains, which contribute to the increasing burden of antimicrobial resistance (AMR), complicating clinical management and reducing the efficacy of conventional antibiotic therapies. In this study, we characterised the genomic and phenotypic drug resistance mechanism of E. coli 266631E isolated from a sepsis patient, highlighting the negative implications of MDR E. coli in sepsis. Antimicrobial susceptibility testing and minimum inhibitory concentration analysis revealed resistance to multiple antibiotics, including amoxicillin, cefotaxime, ciprofloxacin, gentamicin, and tobramycin. Whole genome sequencing identified a broad array of AMR genes encoding resistance to various antibiotic classes, such as macrolides, fluoroquinolones, aminoglycosides, carbapenems, and cephalosporins. Notably, the CTX-M-15 gene, a key extended-spectrum {beta}-lactamase determinant, was found in both the bacterial chromosome and an IncF-type plasmid, emphasizing the potential for horizontal gene transfer and rapid dissemination of resistance. Confirming the taxonomy of the novel and unidentified bacterial strain through querying its 16S rRNA sequence and genome in recognised bacterial taxonomic databases presented a challenge. The isolate showed genetic similarity to E. coli, E. fergusonii, and Shigella species despite their phenotypic differences and variations in their pathogenic traits. However, a simple phenotypic laboratory procedure, based on the biochemical and cultural differences among these bacteria in Coliform ChromoSelect Agar, confirmed the isolate as E. coli. This study underscores the critical importance of integrating phenotypic methods with genomic tools for the accurate identification of clinically significant bacteria. It also highlights the need for both phenotypic and genetic surveillance of key MDR variants in healthcare settings to enable timely, precise diagnosis and targeted treatment of life-threatening infections such as sepsis. DATA SUMMARYThe outputs of the MALDI-TOF analysis, AMR analysis using AMRFinderPlus, starAMR, and RGI, the query of bacterial 16S rRNA in the NCBI, Greengenes2, and SILVA databases, as well as Sourmash and pangenome analyses, are available in the supplementary material. The bacterial 16S rRNA gene sequence has been deposited in the NCBI GenBank database under accession number PQ871642. The isolates complete genome sequence has been submitted to the NCBI Genome database under BioProject accession PRJNA1220687 and BioSample accession SAMN46722626. The chromosome is available under GenBank accession number CP183489, while plasmids and other contigs are available under accession numbers CP183490-CP183498. The scripts used in the following bioinformatics analysis - Sourmash, Roary, and Prokka (for pangenome analysis) are available at: https://github.com/LucyDillon/MDR_isolate. IMPACT STATEMENTThis study presents a comprehensive genomic and phenotypic characterization of a multidrug-resistant Escherichia coli strain implicated in sepsis, uncovering extensive antimicrobial resistance genes across both the chromosome and plasmids. It exposes taxonomic ambiguity with closely related species such as E. coli, Shigella, and E. fergusonii, underscoring gaps in current genomic databases and reinforcing the necessity of phenotypic testing. By integrating whole-genome sequencing with biochemical differentiation, the research strengthens diagnostic precision and informs clinical decision-making for life-threatening infections. Overall, it advances AMR and bacterial taxonomy research by demonstrating the value of an integrated genomic-phenotypic framework to accurately identify and guide the treatment and surveillance of emerging MDR pathogens in clinical settings.