Biology subjects

Elumogo, N.

Publications and source records attributed to Elumogo, N..

4 recordsLinked to original sources

bioRxiv2025

Case study: Genomic characteristics of the gut microbiome, Campylobacter and Salmonella genotypes in three cases of gastroenteritis co-infections

Campylobacter jejuni and Salmonella enterica co-infections in gastroenteritis cases are underexplored, particularly in relation to microbiome dysbiosis. This study uses metagenomic and culture-based approaches to investigate pathogen genotypes and stool microbiome composition. Stool samples from three patients were analysed using culture, qPCR and whole genome sequencing (WGS) of genomes and metagenomes. Strain typing and antimicrobial resistance (AMR) profiling were conducted for both pathogens. The stool microbiome structure was compared between the three patients and across three time points in one patient. C. jejuni and Salmonella enterica were of different strains and different proportions in the cases. C. jejuni sequence types were identified as ST-794, ST-50 and ST-10025, while S. enterica serovars Enteritidis ST-183 and S. Derby ST-39 were identified. C. jejuni AMR genotypes included blaOXA-447, gyrA (T86I), and tet(O). S. Enteritidis contained AMR gene mdsaA-B, and S. Derby contained mdsaA-B and fosA7 genes. Despite similarities in Bristol scales for stool composition, the three cases exhibited distinct microbiome population structures, suggesting there is no one signature microbial profile of microbiomes with a Campylobacter-Salmonella co-infection. A temporal trend towards microbial diversity was observed within a patient, shifting from Proteobacteria dominance (93.3%) during acute infection towards Bacteroidetes (89.5%) abundance post-infection, suggesting that moving towards diverse communities may play a key role in patient recovery. These findings reveal a case study of microbiome disruption for patients infected with C. jejuni and S. enterica and highlight the value of direct stool sequencing in understanding pathogen abundance in stool and microbiome dysbiosis.

microbiology↗

bioRxiv2025

Genomic diversity of non-typhoidal Salmonella found in patients suffering from gastroenteritis in Norfolk, UK

Salmonella is a significant public health pathogen responsible for a wide spectrum of diseases, ranging from gastroenteritis to invasive non-typhoidal salmonellosis (iNTS) and enteric fever. Although advancements in whole genome sequencing (WGS) have improved surveillance and outbreak investigations, traditional single-colony sequencing methods overlook within-host diversity, potentially underestimating the complexity of infections. This study explores the genome-wide diversity of Salmonella strains recovered from stool samples of eight patients, with up to 20 isolates analysed per sample. A total of 156 Salmonella enterica isolates were recovered. All isolates from individual patients displayed consistent serovars and sequence types. Despite the serotype consistency, microevolution was observed in S. Java ST149 and S. Java ST43, with SNP analyses revealing higher diversity (13 and 5 SNP differences, respectively) compared to the clonal populations of other serovars. Phylogenetic analysis of S. Java ST149 isolates from Patient 2 revealed distinct branching, driven by mutations in genes such as secY and cnoX, while S. Java ST43 isolates from Patient 1 displayed multiple clades with notable SNPs affecting transcriptional regulators. Genome structure (GS) analyses using hybrid assemblies identified uniform GS1.0 across all isolates. Antimicrobial resistance (AMR) profiling revealed the presence of multidrug efflux pump genes (mdsA and mdsB) in all isolates. However, S. Typhimurium isolates from Patient 4 exhibited additional AMR genes, including sul2, aph(3)-Ib, and blaTEM-1, associated with an 8.7 kb resistance region. A single isolate from Patient 4 lacked these additional genes due to the deletion of a [~]19 kb genomic region, highlighting structural variation as a driver of phenotypic differences. These findings emphasise the genetic diversity of Salmonella within hosts, particularly in serovars such as S. Java, and underscore the limitations of single-colony sequencing in capturing this complexity. The study highlights the utility of hybrid sequencing strategies for comprehensive analysis of genome variation, offering valuable insights into transmission dynamics, antimicrobial resistance, and evolutionary processes in Salmonella. Impact statementThis study provides a transformative perspective on Salmonella genomics, uncovering the significant within-host diversity of Salmonella populations through the analysis of multiple single-colony isolates. By leveraging hybrid sequencing technologies, we reveal critical insights into the microevolution of Salmonella during infection, capturing genome-wide variation at both single nucleotide and chromosomal scales. Our findings highlight the inherent limitations of traditional single-colony sequencing in detecting within-host diversity, particularly in genetically diverse serovars such as S. Java ST149. The identification of antimicrobial resistance (AMR) determinants and structural genomic variation demonstrates the dynamic nature of Salmonella genomes, offering crucial implications for clinical management and public health surveillance. Importantly, we show that within-host diversity may influence epidemiological interpretations, particularly in outbreak investigations and source attribution, where genetic differences between isolates can mask deeper transmission links. Data SummaryAll relevant supporting data are available in the accompanying supplementary data files. The online version of this article contains four supplementary table. All Salmonella isolate genome sequences are available in the National Centre for Biotechnology Information (NCBI), Sequence Read Archive (SRA) under the Bioproject accession numbers PRJNA1230128. SRA accession numbers and associated metadata for isolate genomes are included in the supplementary table S2-S4.

genomics↗

bioRxiv2023

Uropathogenic Escherichia coli population structure and antimicrobial susceptibility in Norfolk, UK

SynopsisO_ST_ABSBackgroundC_ST_ABSHalf of all women have experienced a urinary tract infection (UTI) in their lifetime and this remains a persistent issue in rural counties like Norfolk, UK. In alignment globally, Uropathogenic E. coli (UPEC) are the main etiological agent for UTIs in Norfolk and are increasingly difficult to treat due to multi-drug resistance (MDR). ObjectiveWe set out to identify which clonal groups and resistance genes are disseminating in the community and hospitals in Norfolk, the first study of its kind for UPEC in this region. MethodsWe collected 217 clinical E. coli isolates causing UTIs in the community and hospital from the Clinical Microbiology laboratory at Norfolk and Norwich University Hospital. These were whole genome sequenced using the Illumina and MinION platforms for in silico multi-locus sequence typing and antibiotic resistance determinant detection. ResultsThe isolates were composed of 74 sequence types (STs); 8 lineages represented 57% of this population: ST73, ST12, ST69, ST131, ST404, ST95, ST127, and ST1193. Importantly, primary UTI screening deemed 8% of isolates to be MDR, with high rates of resistance to ampicillin (52.1%) and trimethoprim (36.2%) in hospitals. Of concern is the probable clonal expansion of MDR groups ST131 and ST1193 in hospitals and community settings with chromosomally encoded blaCTX-M-15, blaOXA-1, and aac(6)-Ib-cr5. ConclusionsThe burden of reported UTIs in Norfolk is largely caused by non-MDR isolates. The UPEC population is continually evolving, and monitoring samples with consideration of sources will help reduce burden of disease.

microbiology↗

bioRxiv2020

CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with [≥] 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.

genomics↗