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Akintayo, I. J.

Publications and source records attributed to Akintayo, I. J..

2 recordsLinked to original sources
bioRxiv2024

Genetic basis for antimicrobial resistance in Escherichia coli isolated from household water in municipal Ibadan, Nigeria

Escherichia coli serves as an indicator of recent faecal contamination in water, signaling the potential presence of enteric pathogens. The public health impact of E. coli in water becomes more significant when strains harbor virulence genes, and may themselves be pathogenic, or antimicrobial resistance genes that can be transferred to pathogens. In this study, we used whole genome sequencing (WGS) to characterize E. coli isolated from household water in municipal Ibadan, Nigeria across two seasons. Antimicrobial susceptibility testing was performed on 97 E. coli isolates, and their genomes were assembled using SPAdes. Multi-Locus Sequence Types (MLST), virulence genes and plasmid replicons were determined using ABRicate. Antimicrobial resistance genes (ARGs) were detected using AMRFinderplus. Phylogroups and serotypes were determined using ClermonTyper and ECTyper, respectively. A phylogenetic tree was built using RAxML. Of the 97 isolates, 39(40.2%) were multidrug resistant and 13(15.9%) possessed diarrheagenic E. coli (DEC) virulence genes. Resistance to individual antibiotics was higher and DEC characteristics more frequent among isolates recovered in the dry season compared to the wet season. Thirty-seven resistance genes belonging to nine antibiotic classes were detected. Majority of the isolates belonged to phylogroup A or B1, 35unique Sequence Types (STs) were detected and there were seven expanded clones of four or more isolates. This study determined that multidrug-resistant E. coli, including DEC, were recovered from household water sources in Ibadan. Some isolates were likely derived from point-sources, highlighting the importance of improved water quality management and sanitation in preventing waterborne disease and antimicrobial resistance transmission. IMPORTANCEContamination of household drinking water sources by disease-causing microorganisms is a serious public health concern common in African settings. Escherichia coli, an indicator of faecal contamination, can also be a reservoir for resistance genes. We have previously reported high frequencies of E. coli contamination of household water in municipal Ibadan. In this study we characterized antimicrobial resistance and virulence genes harboured by contaminating isolates. We found potential diarrhoea-causing E. coli in water which often carried antimicrobial resistance genes, irrespective of whether or not they were disease causing. Resistance gene carriage was more common among isolates recovered in the dry, as compared to the wet season. This was attributable to resistant lineages of E. coli bacteria spreading in the dry season. The work shows the importance of monitoring drinking water in urban African cities like Ibadan and that treating ground water sources may be necessary, particularly in the dry season.

microbiology↗
bioRxiv2024

Assessing the performance of current strain resolution tools on long-read metagenomes

Recent advances in long-read sequencing-based methods have greatly enhanced genomics and public health applications. However, the challenge of effectively distinguishing strains within microbial communities from clinical samples using these technologies restricts their widespread use. We assessed the strain resolution capabilities of three currently available bioinformatics tools--TRACS, Strainy, and Strainberry--using both mock communities and authentic metagenomic datasets. Following sample preparation and long-read sequencing using the GridION sequencing platform, raw reads were processed using TRACS, aligning them to a custom reference database, while Strainberry and Strainy mapped reads to metagenome assemblies for strain resolution. Performance on mock microbial community was assessed by comparing predicted microbiota composition to the expected composition, and on both mock and authentic datasets by evaluating strain-resolved genome assemblies. Computational efficiency was measured in terms of task execution time, single-core CPU usage, and physical memory usage. TRACS demonstrated substantial agreement with the known composition, achieving a median score of 86.7% for Escherichia coli-dominant communities and 94.7% for Klebsiella pneumoniae-dominant communities. Strainberry and Strainy exhibited improved concordance after excluding strains with a genome size below 1 Mb, thus showcasing comparable performance metrics to TRACS. In mock and real metagenomic datasets, TRACS demonstrated the highest haplotype completeness compared to the other two tools, while Strainy demonstrated the highest haplotype accuracy. All tools were able to allocate strains to their respective transmission clusters (< 20 SNPs), albeit with varying degrees of success. Except for single core CPU usage, TRACS outperformed Strainy and Strainberry in terms of speed and computational efficiency. Our study underscores the utility of TRACS, Strainy, and Strainberry in resolving strains within microbial communities from clinical samples. TRACS stands out for its better haplotype completeness and computational efficiency, suggesting its potential to streamline advanced genomic analyses and public health initiatives.

bioinformatics↗