Adja Bousso Gueye

Salmonella is a major bacterial pathogen in low-income countries, where it circulates among humans, animals, and the environment. Children with sickle cell disease (SCD) are particularly vulnerable to severe Salmonella infections. This study aimed to characterize Salmonella isolates causing infections in Senegalese children with SCD. Using antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatic analysis, we investigated antibiotic resistance, serovar diversity, and virulence factors on 23 isolates from SCD patients with diverse clinical infections. The isolates belonged to 12 serovars, with Enteritidis predominating (n = 7). Twenty-two isolates were fully susceptible to antibiotics, while one was multidrug-resistant. Eight isolates (Enteritidis and Typhimurium) carried a virulence plasmid harboring the spvRABCD gene cluster. Core Salmonella pathogenicity islands (SPIs-1 to -5, -11, and -13), as well as SPI-10 and SPI-23, were detected in all isolates, whereas other SPIs were variably present. These results show high serovar diversity and low antimicrobial resistance among Salmonella isolates in children with SCD in Dakar, Senegal. Our findings suggest that strains causing diarrhea in healthy individuals may also cause invasive disease in SCD patients, highlighting the need for dedicated surveillance in this vulnerable population.

Background: Despite the huge burden of deaths associated with or attributable to antimicrobial resistance, studies on sequencing based antimicrobial resistance (AMR) monitoring in Africa are scarce, specifically in the animal sector. Objective and Methods: With a view to deploy rapid AMR monitoring through leveraging advanced technologies, in the current study, nanopore sequencing was performed with 10 E. coli strains isolated from rectal swabs of pigs and poultry layers in Nigeria. Two sequence analysis methods including command line, where bacterial genomes were assembled, and subsequently antimicrobial resistance genes (ARGs) were detected through online databases, and EPI2ME, an integrated cloud-based data analysis platform with MinION, was used to detect ARGs. Results: A total of 95 ARGs were identified and most of the genes are known to be expressed in the chromosome. Interestingly, few genes including qnrS1, qnrS15, qnrS10, kdpE, cmlA1, MIR-14, sul3 and dfrA12 were identified which were previously reported as transferred through Mobile Genetic Elements (MGEs). The antibiotic susceptibility assay determined that the E. coli isolates were resistant to Penicillin (100%), Ciprofloxacin (70%), tetracycline (50%) and Ampicillin (40%). The accuracies of the command line and EPI2ME methods have been found to be 57.14% and 32.14%, respectively, in predicting AMR. Moreover, the analysis methods showed 62.5% agreement in predicting AMR for the E. coli isolates. Conclusions: Considering the multiple advantages of nanopore sequencing, the application of this rapid and field-feasible sequencing technique holds promise for rapid AMR monitoring in low- and middle-income countries (LMICs), including Nigeria. However, the development of a robust sequence analysis pipeline and the optimization of the existing analysis tools are crucial to streamline the deployment of nanopore sequencing in LMICs for AMR monitoring both in animal and human sectors.