Genomic Insights into Possible Zoonotic, Anthroponotic, and Environmental Transmission of Escherichia coli in Ekiti and Ondo States, Nigeria

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Obuotor, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9060994/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Escherichia coli can be pathogenic or non-pathogenic, depending on its genetic makeup, which characterises its virulence potential. The transmission dynamics of E. coli are complex due to its dual nature and its ability to be transmitted among humans, animals, and the environment in both directions. The objective of this study was to gain insight into the resistome, virulome, and mibiolome of E. coli from matched samples using the One-Health Approach in Ekiti and Ondo States, Nigeria. Methods Whole-genome sequencing (WGS) was used to characterise the genomic features of 8 E. coli isolates from humans (n = 3), animals (n = 2), and the environment (n = 3). Antimicrobial resistance genes (ARGs), virulence factors, and mobile genetic elements (MGEs) were identified, followed by multi-locus sequence typing (MLST), core genome MLST, serotyping, phylogrouping, and local and global phylogenomic analysis. Results The 8 E. coli recovered in this study showed variation in the presence of ARGs, virulome, and mobilome, with total ARGs > 30 genes and virulome > 40 genes. There was an identical genetic makeup in three pairs (NGEK1 vs. NGEK1, NGEK13 vs. NGEK17, and NGEK21 vs. NGEK22A) recovered from humans, animals and environments. Some significant resistance genes (blaCTX-M-15, blaCMY-2, blaTEM-1B, blaOXA-1, blaOXA-181 and qnrS1) were found in the isolates. The MGEs analysis found two groups: plasmid-mediated and non-plasmid-mediated, with both carrying resistance (blaTEM, blaCTX-M-15, qnrS1, qnrB19, and blaOXA181) and virulence genes (hylE, hha, senB). The STs found in the study were ST 2, 38,181, 693, and 998. Clonality was observed among some E. coli isolates from the same household or farms, and these isolates were also phylogenetically associated with certain global E. coli isolates. Conclusion Our study emphasised that the E. coli isolates analysed possessed ARGs and virulence factors that drive pathogenicity and presented evidence for possible zoonotic and anthroponotic modes of transmission. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The ubiquitous nature of Escherichia coli is due to its duality [ 1 ]. The duality of E.coli is its ability to act as a commensal in the intestinal tract of humans and other vertebrates, which is necessary for the maintenance of their microbiome, and it’s also able to cause significant infection, ranging from diarrhoea, a self-limiting infection, urinary tract infection, to sepsis [ 2 , 3 ]. This duality makes it a vital bacterium of public health concern. This ability to adapt to different environments is encoded in its genome [ 4 , 5 ]. E. coli possesses an open pangenome with a core set of housekeeping genes, which provides the evolutionary backbone for phylogenomic insight and a vast variable accessory genome that is either borne on the chromosome or an extra-chromosomal element[ 6 – 8 ]. These accessory genomic materials are exchanged between strains, which equip them with antimicrobial resistance and virulence potentials [ 9 , 10 ]. The genomic component of any E.coli determines its behaviour and virulent potential [ 4 ]. These genomic components include the resistome, virulome and mobilome, which are crucial to the pathogenicity and the extent to which it can cause an infection [ 11 – 13 ]. Therefore, understanding the resistome, virulome, and mobilome of an E. coli isolate is fundamental to deciphering the epidemiology of any pathogenic E. coli , its transmission to humans and animals, and its contamination of their shared environment. The line between commensalism and pathogenicity is not fixed but is a dynamic continuum shaped by genetic evolution. A study by Burgaya et al. [ 14 ] investigated and unravelled the genetic determinants that predispose an E. coli strain to cause invasive disease. In that study, a comparison of 912 E. coli strains from bloodstream infections and 370 strains from healthy individuals revealed that pathogenicity is a highly heritable trait, with a striking 69% of the variance explained between the two datasets. Some of these variances could be attributed to E. coli adaptation through the acquisition of MGEs, as reported by Byarugaba et al. [ 15 ] and Saini et al. [ 4 ]. Saini et al. particularly found that E. coli isolates from urban environments evolved by gaining fitness advantages, such as AMR and virulence factors, through horizontal gene transfer (HGT)- mediated acquisition of MGEs. Evidence in the molecular, genetic, and genome-wide analysis of E. coli obtained from a matched sample from different sampling cohorts, from companion animals and their owners, patients and their clinical environment, animals and their handlers and their environment has demonstrated transmission dynamics of pathogenic and MDR E. coli isolates. A global snapshot phylogenomic analysis by Mitra et al. [ 15 ], which used 158 E. coli isolates compared with isolates from India, suggests possible cross-transmission among humans, animals, and the environment, mainly via zoonotic transmission. Zoonosis is an established phenomenon in which an animal transmits an infection or pathogenic microorganism, including resistant bacteria, to humans [ 16 – 18 ]. Globally, this phenomenon, zoonosis, is well-established, as well as the transmission of microorganisms from contaminated environments to humans and animals [ 18 , 19 ]. However, a phenomenon called anthroponoosis, also known as reversed zoonosis, is the process by which an infected human host of microbial origin transmits pathogens to non-humans, whereas zooanthroponoosis is exclusively a process by which humans transmit pathogens to animals; both phenomena are not well established in the literature [ 20 , 21 ]. However, studies agreed that this is generally possible. Some examples of those types include that one by Ewers et al. [ 22 ], which found a specific E. coli clone that was initially restricted to humans; similarly, Rwego et al.[ 23 ] and Nicolas-Chanoine et al.[ 24 ] have independently asserted, based on data found in their studies, the possibilities of anthroponosis, significant efforts have been given to zoonosis, but if the chain of transmission is not fully understood, through concentrated attempt to unravel all possible means of transmission, the battle to turn the tide of infectious disease will yield limited result.. However, even since those earlier studies were done, little interest has been shown in this aspect of research. The gaps that limit this establishment of anthroponosis and zooanthroponosis lie in limitations in methods in sample collection, timing of collection, and pathogen recovery techniques. Also, such studies require large sample sizes, longitudinal designs, and epidemiological approaches. These types of studies require rigorous data analysis, including genome-wide analyses to determine the direction or origin of pathogenicity [ 25 , 26 ]. Although, some subjects in the global north, has analysed large retrospective data set, which shows some evidence [ 4 , 17 ], however, this is not so for global south, where hygiene, biosecurity in interaction with animals and agricultural and animal companion is minimal, as such the need for a study that can determine the direction of transmission of pathogenic micro-organism. This study provides a snapshot of pilot evidence and data that can be built on using genomic data to understand how pathogenic and MDR E. coli are transmitted within the One Health ecosystem. Therefore, this study reported a genomics-wide research on E. coli obtained from matched samples from human, animal, and environmental sources, limited to those with the same similarities in their phenotypic (AST susceptibility) and gene detection from Ekiti and Ondo states, Nigeria, a resource-limited setting and a low- and middle-income country. Method Bacterial Strains The study obtained four hundred and thirty-five (435) E. coli isolates (unpublished). These isolates were cultured from matched samples from three cohorts: clinical settings, animal farms, and slaughterhouses. The clinical cohort includes samples from consenting patients, animals, and environmental samples (water, tables, and bench-top swabs) collected from their homes. In the animal farm cohort, samples were collected from the animal handlers, their animals, and their environment (water samples, animal pens, and bench tops). Lastly, slaughterhouse cohorts included samples from slaughterhouse workers, slaughtered animals, and environmental samples (water, table tops, and bench-top swabs). The isolated E. coli were subjected to Phenotypic antimicrobial susceptibility testing (AST) in accordance with CLSI standards [ 27 ]. Eight E. coli isolates were selected for whole-genome sequencing based on similarities in antimicrobial susceptibility patterns from the same cohort and sample site. Table 1 presents the criteria used to select isolates for WGS. We selected eight E. coli isolates (humans, n = 3, animals, n = 2, and environmental samples, n = 3). DNA Extraction and DNA Quantitation DNA was extracted using the QIAamp DNA Mini Kit for genomic DNA. The modified protocol for Gram-negative bacteria DNA extraction was used, as provided by Yang [ 28 ]. The DNA was quantified using a Qubit fluorometer (Thermo Scientific, USA). The eluted DNA was pipetted into storage tubes and stored in a freezer at -80 degrees Celsius. Whole Genome Sequencing Library construction and the whole genome of the 8 E.coli isolates (NGEK1, NGEK2, NGEK7, NGEK13, NGEK16, NGEK17, NGEK21 and NGEK22A) were sequenced using the Illumina NovaSeq PE150X (300bp) at the Beijing and Singapore Novogene Ltd. After the extracted DNA materials were shipped and passed the quality test. The Libraries were prepared according to the Novogene protocol. The Illumina NovaSeq PE150 was used to generate raw data (short reads). The clean data that was used for further analysis after the sequenced data were filtered and processed according to Cock et al [ 29 ]. Quality Assessment and Assembly Quality analysis was conducted using the Galaxy platform [ 30 ], which was accessed on February 3, 2024 ( https://usegalaxy.org/ ). The quality assessment of raw data was performed using FastQC and MultiQC [ 31 , 32 ]. The short-read sequences were assembled using SPAdes, and the assembly quality was assessed using Quast (Galaxy Version 5.0)[ 33 ]. An assembly was deemed unacceptable if it had more than 400 contigs, a N50 value lower than 40,000, or if it had between 300 and 400 contigs and an N50 value lower than 50,000. Bioinformatic analysis of WGS data for the antimicrobial Resistance determinants of E. coli isolates The identification and categorisation of genes that confer resistance were carried out using ResFinder 4.1, a bioinformatics tool developed by the Centre for Genomics Epidemiology (CGE) ( http://www.genomicepidemiology.org/ ) (accessed on 2024/03/2). Each isolate's genes were compared to an annotated resistance gene using a threshold of 95–100% identity [ 34 ]. The plasmid replicon types of each E. coli isolate were identified using PlasmidFinder 2.1. As documented by Joensen et al. [ 33 ], the strain's O and H serotypes were determined by analysing the generated FASTA files using the Centre for Genomic Epidemiology (CGE) platform ( http://www.genomicepidemiology.org/ and ( https://cge.cbs.dtu.dk/services/CSIPhylogeny/ ) accessed on 2024/03/2). Multilocus sequence typing (MLST) of E. coli isolates Eight E. coli isolates underwent in silico MLST analyses using schemes developed by Achtman [ 35 , 36 ]. The MLST assignment for each E. coli isolate was determined from whole-genome sequence data, yielding complete correspondence with alleles in the MLST database. The MLST Finder 2.0, a bioinformatics tool developed by CGE, was used to assign Sequence Types (STs) to the isolates. Isolates that showed a perfect 100% similarity with known MLST alleles were categorised accordingly. Nevertheless, isolates lacking a precise match were classified as unknown. If an isolate's MLST alleles match an unknown ST in the MLST database, it is classified as a new type. The presence of virulence was determined using Virulence-Finder, a tool developed by Joensen et al [ 37 ]. The MLST, serotype, phylogroup, and fimH subtype were collectively referred to as phylogenetic characteristics. 3.17 Determination of E. coli Phylogroups, SNP Calling and Phylogeny The phylogroups of E. coli genomes were determined using an in-silico Clermont typing method, as outlined by Beghain et al [ 38 ]. CATIBioMed (IAME UMR 1137) hosts the Clermont Typer web interface at http://clermontyping.iame-research.center/ . The phylogenetic trees were constructed to determine the phylogenetic similarity of the E. coli isolates using the Single Nucleotide Polymorphism (SNP) calling technique described by Kaas et al [ 39 ]. The E. coli reference strain was used to identify single-nucleotide polymorphisms (SNPs) and detect variations in the chromosomes of each isolate. A phylogenetic tree was then constructed using the online tool ( https://realphy.unibas.ch/realphy/ ). The resulting phylogenetic tree was analysed and visualised using the interactive Tree of Life tool (iTOL) based on single-nucleotide polymorphisms (SNPs). The tool can be accessed at http://itol.embl.de/itol.cgi . The genomes were examined to determine the number of single-nucleotide polymorphisms (SNPs) between pairs of isolates from distinct sources, thereby evaluating their relationship. The 8 E. coli genomes compiled in this study have been submitted to the NCBI database, and a comparison with global E. coli isolates from different regions and sources was also made. Supplementary file 1 has its metadata and accession numbers. Ethical Clearance Ethical Clearance from the National Health Research Ethics Committee of Nigeria (NHREC/01/01/2007-21/03/2023), the Federal Teaching Hospital, Ido-Ekiti (ERC/2023/09/20/1034B), and the Ondo State Ministry of Agriculture (MNR/V.384/64). The study adhered to all approved guidelines for both human and animal research, as outlined by the relevant ethical bodies. Results Resistome and Virulome Among the 8 E.coli isolates, there were 35 antimicrobial resistance genes (ARGs) with no co-occurrence of any ARGs in all the 8 E.coli isolates. Of the 35 ARGS found in all the E.coli isolates, the blaTEM gene was found in 5 of the eight E.coli isolates, the blaCTX-M-15, qnrS1, aph(3'')-Ib, aph(6)-Id and sul2 genes were found in 4 of the E.coli isolates. ARGs aac(3)-IId, mph(A), qepA4 and tet(A) were found in 3 of the isolates, aadA2, aac(6')-Ib-cr, blaOXA-1, catB3, dfrA17 and qnrB19 were, found in 2 isolates, while aadA5, blaADC-25, sul1, dfrA17, aph(3')-IIb, aadA10, blaPAO, blaOXA-488, blaCMY-2, blaOXA-181, blaOXA-1, fosA, catB7, floR, catB3, crpP, qnrVC1, tet(B) and dfrB5 genes occurred only in one isolates. The occurrence of the ARGs is shown in Fig. 1 . A total of 58 virulence factors were identified in 8 E. coli isolates. Two of the isolates (NGEK1 and NGEK2) had 15 virulence factors; isolates NGEK13 and NGEK17 had 16; isolates NGEK21 and NGEK22A had 31; and isolates NGEK7 and NGEK16 had 17 and 43, respectively. Virulence gene csgA, fdeC, gad, nlpI, terC, yehA, B, C, and D were all found in all the 8 E.coli isolates, followed by hlyE(7), iss(7), fimH (6), hha (6), AslA (5), traT (5), yghJ(4),hra (4), chuA (3), and kpsMII_K5 (2). The occurrence of other virulence genes is shown in Figs. 2 a and 2 b, respectively. Multi-locus Sequence Typing (MLST) and Core Genome Multi-locus Sequence Typing (cgMLST) Multilocus sequence type (MLST) analysis identified five different STs among the E. coli isolates (ST 2, n = 2; ST 181, n = 2; ST 38, n = 2), while ST 693 and 998 were each identified. Equally, five cgMLSTs were identified in the cgMLST analysis, with 6 E. coli isolates, two each having cgST 147613, 195700, and 47723, respectively. The other 2 E. coli isolates had cgST values of 47720 and 137699, respectively. It was observed that isolates NGEK1 from human and NGEK2 from the environment had the same ST and cgMLST, also, isolates NGEK13 from chicken and NGEK17 from the environment had the same ST and cgMLST. Similarly, isolate NGEK21 from an animal handler (poultry worker) and isolate NGEK22A from chicken (poultry) had the same ST and cgMLST. However, E.coli isolate NGEK7 from humans and isolate NGEK16 had different ST and cgMLST, respectively. It was also observed that the cgMLST of NGEK21, 22A, and 7 were relatively close (cgST 77723 vs 47720) as shown in Fig. 3 . The results suggest possible transmission of E. coli among humans, animals, and across different environments. Serotypes and Phylogroups Five serotypes (O101:H9, O55:H35, O76:H9, O2050:H6, and O101:H15) were identified among the 8 E. coli isolates, with similar serotypes observed in 3 matched pairs (Fig. 4 ). The phylogrouping of the 8 E. coli isolates shows that three were in phylogroup A, two each in phylogroups B2 and D, and one in phylogroup C. The results are depicted in Fig. 3 . Mobile Genetic Element The MGEs analysis shows the presence of several plasmids and other MGEs. Table 2 shows the plasmids found in all E. coli isolates. Of the sixteen plasmids found among the 8 E. coli isolates, IncFIA(HI1) found in E. coli isolates NGEK1 and NGEK2 carried a virulence gene (clpK1). Plasmid Col440I was found to carry the qnrB19 gene in isolates NGEK13 and NGEK17 associated with phenotypic resistance to ciprofloxacin and a virulence factor (mrkA). Plasmid IncFII(pRSB107) was found in three isolates (NGEK7, NGEK21, AND NGEK22A). It was found to carry resistance gene blaTEM-1B in NGEK21 AND NGEK22A isolates and virulence genes anr ; however, it was not associated with any resistance or virulence genes in NGEK7. Plasmid ColKP3 carried qnrS1 and blaOXA-181 genes; similarly, plasmid IncQ1 carried aph(6)-Id, aph(3'')-Ib , and sul2 genes, all found in E. coli isolate NGEK7. Plasmid IncFII(pRSB107) in E.coli isolate NGEK16 was found to carry resistance to tetA and virulence genes anr and traT, respectively. In the same E. coli isolates, plasmid Col156 was found to carry the virulence factor senB . Table 3 shows other types of MGEs found among the 8 E. coli strains; some were associated with antimicrobial resistance genes and virulence factors, whereas others were not associated with any function. Five types of non-plasmid MGEs were found in the 8 E. coli. They were: unit transposon, insertion sequence, miniature inverted repeat, integrative conjugative element, and composite transposon. Among the eight E. coli isolates, isolate NGEK16 had the highest number of non-plasmid MGEs carrying genes associated with antibiotic resistance and virulence factors. There were 7 them (Tn5403, ISEc9, IS6100, ICEEcIHE3034-1, MITEEc1, ISEc17, and cn_31761_ISEc17). A Tn2, a unit transposon, was found in E. coli isolates NGEK1 and NGEK2, which carried blaTEM-1B. In the same isolates, ISKox3 and ISEc1, insertion sequences that carried virulence genes (hlyE and fdeC), were found. Insertion sequence ISEc38 was found in E. coli isolates NGK13 and NGEK17, which carried the hha gene, a virulence factor. E. coli isolates NGEK21 and NGEK22A carried ISKpn19, IS30, and MITEEc1, all non-plasmid MGEs; ISKpn19 carried three resistance genes (tet(A), qnrS1, and blaCTX-M-15). While the IS30 and MITEEc1 carried virulence factors. E. coli isolate NGEK7 had ISKpn19 and MITEEc1; the ISKpn19 carried qnrS1 and blaOXA-181 antibiotic resistance genes, while MITEEc1 carried nine virulence genes (fdeC, yehA, B, C, D, hra,papA_F13 papC, and nlpI). Phylogenetic Analysis and Comparative Genomics Local Phylogenetic Analysis Results The phylogenetic tree of the different 8 E. coli isolates is presented in Fig. 3 . Figure 4 also shows the evolutionary history of the local E.coli isolates. Of the 8 E. coli strains, 7 showed a close relationship and were organised into three clades (clade1, clade2, and clade3). Clade 1, where isolates E. coli NGEK1 and NGEK2 were of the exact ancestry origin, as indicated by their distance and relationship, NGEK1 was from a human (blood). In contrast, isolate NGEK2 was isolated from the environment (home table), from which isolate NGEK1 was also isolated. These findings suggest possible transmission between humans and the environment, or vice versa. Similarly, NGEK13 isolated from poultry (chicken) and NGEK17 isolated from the environment (farm water) were also closely related, sharing the same ancestry level (clade 2). Isolate NGEK22A from an animal (chicken), and isolate NGEK21 from a human (rectal swab), which also showed similar ancestry roots but were closely related. Clade 3 showed four isolates from the same root, but only NGEK22A and NGEK21, which originated from the same ancestral root, and also NGEK16 from the environment (home water), seem to be related to some extent. Isolates E.coli NGEK1 was isolated from a human sample, while isolate NGEK2 was isolated from the bench, the house bench, and the home of that individual. Based on this phylogenetic analysis, they are likely from the same source. So, there is a possible cross-transmission between humans and the environment or from the environment to humans. The same explanation applies to isolate pairs NGEK13 and NGEK17 and NGEK22A and NGEK21. The whole-genome sequencing results for E. coli isolates NGEK7 and NGEK16 showed that they were significantly different and did not share a common ancestral root. Global Phylogenetic Analysis Results The analysis of the 8 E. coli isolates compared to global E. coli isolates phylogenetically showed similarity to E. coli isolates from Ghana, South Africa, Cuba, China, the United Kingdom, the Netherlands, Switzerland, Nigeria, and the United States of America, obtained from humans, animals, and wastewater, as shown in Fig. 4 . Of the 8 E.coli isolates, one of the isolates (NGEK16-04-2023) from home water (Environment) was found to be of the same ancestry root as the E. coli isolate (GCA_002510125.1), in a human from Pretoria in South Africa. It was distantly related to the E. coli isolates (GCA_016767775.1 from a chicken in the USA, GCA_002002225.1 from a human in Sydney, Australia, and GCA_002416865.1 from a human in KwaZulu-Natal, South Africa). E. coli isolate (NGEK7-04-2023) from a urine sample in a human was associated with E. coli isolate GCA_024585725.1 from poultry in Santa Cruz del Norte, Cuba. NGEK21-05-2023 and NGEK22A-05-2023 were of the exact ancestry origin and were closely associated with E.coli GCA_048222295.1 and GCA_020883315.1 from human samples in the United Kingdom and the Netherlands, respectively. However, they are distantly associated with GCA_024224055.1 from a chicken sample from Switzerland and GCA_019584715.1 from wastewater in Ibadan, Nigeria. E. coli GCA_024225755.1, GCA_019357435.1, and GCA_022695865.1 from chicken in Switzerland, in Jiaxing, Zhejiang, China, and Athens, USA, were distantly associated with NGEK7-04-2023 and NGEK13-04-2023 obtained from the environment (water) and animal (chicken), respectively, which were of the exact ancestry origin. Lastly, E. coli NGEK1-04-2023 and NGEK2-04-2023, which were from the same branch, were closely associated with E. coli GCA_041877505.1 and GCA_002416915.1 from human samples in Accra, Ghana, and KwaZulu-Natal, South Africa, respectively. Possible Transmission Dynamic Model for 8 E. coli isolates from WGS Data. Figure 5 shows the constructed transmission model for E. coli based on WGS data. The result shows six possible models. Model 1: A human-to-environment-transmission route (NGEK1-Humans to NGEK2-Environment), Model 2: An environment-to-human transmission route (NGEK2-Environment to NGEK1-Humans), Model 3: An environment-to-animals transmission route (NGEK13-Environment to NGEK17-Animals), Model 4: An animals-to-environment transmission route (NGEK17-Animals to NGEK13-Environment), Model 5: An animals-to-human transmission route (NGEK22A-Animals to NGEK21-Humans), and Model 6: A human-to-animal transmission route (NGEK21-Humans to NGEK22A-Animals). Discussion The transmission of E. coli is dynamic, including moving from humans to animals, a process referred to as reverse zoonosis or anthroponosis and also the established nature of E. coli transmission through zoonotic, i.e, from animals to humans through food contamination, domestication or compassionate use [ 40 , 41 ]. Environmental contamination with pathogenic E. coli occurs when animals and humans improperly shed waste into the environment. The environment thereafter became the reservoir for these pathogenic E.coli isolates [ 42 , 43 ]. This study integrates multilayered genomic data, including resistome and virulome profiling and phylogenetic analysis. In this study, we focused on unravelling the whole genetic and genetic relatedness of the 8 E. coli isolates that were obtained from matched samples obtained from three different collection cohort sites (cohort 1:hosipitalised patients and their animals and environment, cohort 2:animal farms, animal handlers, their animals and the environment, including their water sources and cohort 3: slaughterhouses: Buchters, slaughtered animals and their environment including the water sources used in the slaughterhouses). In our study, we identified a large pool of antibiotic resistance genes that could confer distinct phenotypic resistance in the 8 E. coli isolates. Our study identified diverse resistance genes that confer multiple antibiotic resistances, including carbapenem resistance. There were 32 antibiotic resistance genes ( blaTEM, blaCTX-M-15, qnrS1, aph(3'')-Ib, aph(6)-Id, sul2 , ARGs aac(3)-IId, mph(A), qepA4, tet(A), aadA2, aac(6')-Ib-cr, blaOXA-1, catB3, dfrA17 and qnrB19, aadA5, sul1, dfrA17, aph(3')-IIb, aadA10, blaCMY-2, blaOXA-181, blaOXA-1, fosA, catB7, floR, catB3, crpP, qnrVC1, tet(B) and dfrB5).The predominant resistance genes found in the study were blaTEM, blaCTX-M-15 , and qnrS1 . All matched samples (NGEK1 vs NGEK2, NGEK13 vs NGEK17, NGEK21 vs NGEK22A) have the same resistomes and phenotypic characteristics, indicating that each E. coli isolate in a pair is likely of the same origin. Genomic evidence from the 6 E. coli isolates obtained from the three cohort sites provided a compelling snapshot of the transmission dynamics of MDR and virulent E. coli across human, animal, and environmental interfaces in Nigeria. The expectation is that the E. coli isolates in the matched pair (NGEK7 and NGEK16), based on their similar phenotypic susceptibility patterns, would have the same resistomes; however, the WGS result showed that they were not of the same origin as the phenotypic result, and the closeness of the sample collection point suggested. This shows the superiority of the WGS method over the phenotypic method for epidemiological and surveillance purposes. Each resistance gene in each E. coli isolate could be responsible for the observed antibiotic resistance patterns. For example, blaTEM, blaCTX-M-15, blaCMY-2, blaOXA-181 , and blaOXA-1 were found to be associated with resistance to beta-lactam antibiotics, although their resistance spectra differ. The blaTEM gene is associated with resistance to antibiotics like ampicillin and amoxicillin, which are the first-line antibiotics commonly used in clinical settings in Nigeria and other settings [ 44 – 46 ], while the blaOXA-181 gene is associated with carbapenem resistance. One of the significant findings of our study was the genomic agreement observed among E. coli isolates from matched clinical, household, animal, handler, and shared environment samples. For example, the identical Sequence Types (STs), core genome MLST (cgMLSTs), serotypes, and phylogroups between human-animal (NGEK21/NGEK22A), human-environment (NGEK1/NGEK2), and animal-environment (NGEK13/NGEK17) pairs provided potential evidence for the zoonotic or anthroponotic and environmental transmission of pathogenic E. coli isolates. It is important to note that the near-identical core genomes identified in our study could serve as genomic fingerprints for surveillance. This assumption of genomic fingerprinting provides strong evidence for a specific route of transmission, which is vital for tracing the origin of an infection. It can be inferred from the available evidence in our study that zoonotic or anthroponotic transmission may be occurring, given the present tangible, genetically verified events at the study locations, as evidenced by the WGS data. The findings of our study on the possible transmission dynamics align with evidence in the literature, for example, a study by Mitra et al. [ 15 ] on MDR E.coli isolates from humans(animal handlers), animals, and the environment, which was also WGS-based, found a similar relationship in some of the sample cohorts in their study. In Nigeria, a study conducted by Aworh et al. (2021) in the FCT found relatedness among three sample pairs: poultry, their handlers, and the environments. However, further analysis found that they were not clonal. The SNP phylogenetic and core genome analyses of the six E. coli strains discussed in this study revealed clonality, making this one of the first reports of such findings in the study settings. This piece of evidence suggests the possible route of transmission and the movement of pathogenic E.coli isolates across the different settings and further support the need for enforcement of biosecurity guideline in farms where animals are rare and also the need to keep a clean environment as this suggests that the environment could be a significant vehicle that transmit pathogenic, virulent and multi-drug resistance E.coli isolates and also serves as reservoir for them. The results of our study also reveal that the E. coli isolates obtained from the environment, water samples, and poultry (chicken) were not merely commensal, as they harboured antimicrobial resistance genes and virulence factors. For example, the presence of clinically relevant antimicrobial resistance genes (ARGs), such as blaCTX-M-15 , associated with extended-spectrum beta-lactamases (ESBLs), blaOXA-181 , associated with carbapenemases, and qnrS1 , associated with quinolone resistance, is a public health concern. Also, the co-occurrence of all those ARGs with virulence factors related to extraintestinal infection, such as hlyE and iss , which were particularly found in ExPEC-associated phylogroups B2 and D, raises a concern about strains that are both capable of causing severe infection and difficult to treat. This implies that those who get infected with such E. coli pathogens experience extended hospitalisation and an increased burden on the healthcare system [ 47 ]. Equally, this can lead to low productivity as a result of loss of work time due to the time spent managing those types of infection [ 48 , 49 ]. Also, since the health insurance system in Nigeria is in a primitive stage, where most individuals who work in the animal sector do not have coverage, they will have to pay for their treatment out of pocket [ 50 ]. This will deplete their finances, which could have been channelled into other areas of their lives. Also, shedding of these pathogenic E. coli isolates into the environment could contaminate water bodies, as open defecation remains widespread in Nigeria, although it has been outlawed in several states; implementation remains a significant concern. The analysis of mobile genetic elements (plasmid- and non-plasmid-mediated) examines the presence of extrachromosomal elements that can rapidly disseminate to other bacteria, even when those bacteria may not initially have that capacity. Particularly of interest were the presence of blaTEM on a plasmid ( IncFII ) and qnrS1 and blaOXA-181 on an insertion sequence ( ISKpn19 ). These findings provide a possible explanation for the movement of the resistance factor across species or bacteria. It also suggests that the plasmid and other MGEs act as vehicles for distributing resistance and virulence factor traits among different bacterial hosts [ 51 ]. The isolate NGEK16 from the environment harboured the highest number of MGEs. This highlights how a single environmental strain can serve as a potent reservoir for these MGEs, further fuelling the AMR crisis. Such an E. coli isolate can easily transfer its resistance genes via its MGEs to other bacteria in the environment. This observation aligns with the findings of Bethke et al. [ 52 ], Tokuda and Shintani [ 53 ] and recently Ku et al. [ 54 ], who have also observed that E. coli isolates from the environment have several MGEs that could serve as vehicles transmitting resistance and virulence factors to non-resistant, virulent, and pathogenic bacteria, and then make them resistant, virulent, and pathogenic. In the global context, the phylogenetic analysis reveals that the isolates in our study did not cluster only with isolates from Nigeria; they also cluster with isolates from Africa, Europe, Asia, and the Americas. This finding underscores the connection between local transmission cycles in the settings where the samples were obtained and the global epidemiology of AMR E. coli isolates. For example, the relatedness of NGEK21/NGEK22A to human isolates from the United Kingdom and the Netherlands could reflect the global spread of successful high-risk clones. As exemplified in very highly dispersed clones like the ST 131, which has been found in epidemiological studies in clinical and non-clinical settings globally [ 55 – 58 ], although ST131 was not found in this study. Strengths and Limitations of this study The strength of this study is based on the sampling techniques, which were matched samples, which is essential in investigating transmission dynamics and also the focus on unravelling the whole genetic features and genetic relatedness, which includes the resistome, virulome, the MGEs, and extensive phylogenomic analysis in this study, which provide great insight into the creatures of the 8 E.coli isolates investigated. However, the small sample size means that, while the evidence in this study strongly supports the transmission event, it represents only a snapshot rather than comprehensive epidemiological evidence. Therefore, the conclusions are robust for these specific isolates but cannot be generalised to the entire region or setting without a larger-scale surveillance. Also, while the genomic data strongly suggest a transmission link, it cannot definitively determine the direction of transfer. The six proposed models (human-to-environment vs. environment-to-human, human-to-animal vs. animal-to-human, and animal-to-environment vs. environment-to-animal) are equally plausible based on the genetic data alone; therefore, resolving these limitations would require longitudinal sampling and detailed epidemiological data. Despite these limitations, our findings provide a valuable, data-driven foundation. It highlights specific, genetically linked instances of cross-contamination between humans, poultry, water sources, and their immediate environment. The evidence strongly suggests the need for a multifaceted intervention that addresses antibiotic stewardship in both human and veterinary medicine, improves community sanitation, ensures biosecurity in animal farming, and implements other strategies to break this transmission cycle. Conclusion Our study used a genome-wide analysis to investigate the resistome, virulome, MGEs, and phylogenomic relatedness, providing insight into zoonotic, arthropod, and environmental transmission of pathogenic and virulent E. coli isolates from matched samples using the One Health approach in Ekiti and Ondo states, Nigeria. We observed that the E. coli isolates have diverse ARGs, virulence factors, STs , and MGEs. However, samples obtained from the same cohort showed relatedness and clonality, as indicated by genomic data. The presence of antibiotic resistance, virulence factors, and MGEs in isolates from poultry (chicken), water samples, and the environment demonstrates their capacity to cause severe infection in humans. Phylogenomic analysis revealed a close snapshot of the local isolates' relationship to E. coli isolates from Africa, Asia, Europe, and the Americas, collected from humans, poultry, water, and the environment. The presence of such potential strain in hosts other than humans is a key factor in the spread of pathogenic E. coli isolates. Our study emphasises the need to enforce antibiotic stewardship and biosecurity in animal husbandry and poultry farming, as well as environmental sanitation and continuous surveillance of water sources used in homes and farms. Declarations DATA AVAILABILITY AND WGS DATA The WGS data generated in this study have been deposited at NCBI under the project accession PRJNA1295602, and all other associated data are available in the supplementary file. Acknowledgement We appreciate the assistance provided by the laboratory staff at the Department of Microbiology, Faculty of Life Sciences, and the Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmacy, Federal University, Oye-Ekiti, Ekiti State, Nigeria. Author Contributions ULI-Conceptualisation, investigation, software, formal analysis, write first draft, OBS-Supervision, data validation, Editing, Writing. OTM-Supervision, data validation, Editing, Writing, OOE-Supervision, data validation, Editing, Writing, ATA-investigation, formal analysis, writing, project administration, AFA-investigation, formal analysis, writing, project administration, OB-investigation, formal analysis, writing, project administration, AEC-Supervision, data validation, Editing, Writing and OSK-Supervision, data validation, Editing, Writing Funding Declaration There was no external funding associated with this study. Ethics and consent to participate Ethical Clearance from the National Health Research Ethics Committee of Nigeria (NHREC) (NHREC/01/01/2007-21/03/2023), the Federal Teaching Hospital, Ido-Ekiti (ERC/2023/09/20/1034B) and the Ondo State Ministry of Agriculture (MNR/V.384/64) were obtained for this study. 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Ajibola","email":"","orcid":"","institution":"Federal University of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Abiola","middleName":"T.","lastName":"Ajibola","suffix":""},{"id":605772715,"identity":"df92f817-a277-4b2f-8e30-aeb87ed66cd4","order_by":5,"name":"Funmilayo Ajoke Adewumi.","email":"","orcid":"","institution":"Ekiti State University","correspondingAuthor":false,"prefix":"","firstName":"Funmilayo","middleName":"Ajoke","lastName":"Adewumi.","suffix":""},{"id":605772717,"identity":"998e22ec-9e66-4a2c-9ec4-bee52303b93d","order_by":6,"name":"Bola Oluwatosin Ojo","email":"","orcid":"","institution":"Ekiti State University","correspondingAuthor":false,"prefix":"","firstName":"Bola","middleName":"Oluwatosin","lastName":"Ojo","suffix":""},{"id":605772718,"identity":"f83b59b3-c341-4819-8ec4-0a85e462bfd8","order_by":7,"name":"Emmanuel C. Adukwu","email":"","orcid":"","institution":"University of the West of England","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"C.","lastName":"Adukwu","suffix":""},{"id":605772719,"identity":"5c7bbe7e-d4d8-4db5-b0e3-8292e4658042","order_by":8,"name":"Stephen K. Obaro","email":"","orcid":"","institution":"International Foundation Against Infectious Disease in Nigeria (IFAIN)","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"K.","lastName":"Obaro","suffix":""}],"badges":[],"createdAt":"2026-03-07 22:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9060994/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9060994/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104706750,"identity":"865b1621-287f-49b2-81f8-bd201dbb1906","added_by":"auto","created_at":"2026-03-16 09:37:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37787,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAntimicrobial resistance gene (ARG) profiles of eight matched \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eEscherichia coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates.\u003c/strong\u003e The heatmap displays the presence (red) and absence (blue) of ARGs across isolates recovered from clinical, household, animal, handler, and environmental sources in Ekiti and Ondo states, Nigeria. Each column represents an isolate, while each row corresponds to a specific ARG detected using whole-genome sequencing. This distribution illustrates both shared and unique resistome patterns, highlighting potential transmission events and reservoirs of antimicrobial resistance within and between human, animal, and environmental compartments. The Venn diagram was created from http://www.bioinformatics.com.cn./\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/dcef731c3b7cb9599be60b5f.png"},{"id":104706752,"identity":"b733f7de-8de4-4e50-856a-c81831bb4908","added_by":"auto","created_at":"2026-03-16 09:37:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":959584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA and B. Virulence and Antimicrobial Resistance Gene Profiles of Eight Matched \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eEscherichia coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e Isolates.\u003c/strong\u003e These figures illustrate the distribution of virulence factors and antimicrobial resistance genes (ARGs) among eight \u003cem\u003eE. coli\u003c/em\u003e isolates, each obtained from matched human, animal, and environmental samples in Ekiti and Ondo states, Nigeria. The heatmaps display the presence (red) and absence (blue) of specific genes across the isolates, enabling direct comparison of both shared and unique genetic features. This visualisation highlights the complexity of the resistome and virulome within and between different compartments, underscoring the potential for cross-transmission and the importance of integrated surveillance in addressing antimicrobial resistance risks. The Venn diagram was created from http://www.bioinformatics.com.cn./\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/41f31389846f0ee03fecda7d.png"},{"id":104783079,"identity":"c5917e38-5556-41b7-81c8-ca2f41e5128e","added_by":"auto","created_at":"2026-03-17 07:58:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114255,"visible":true,"origin":"","legend":"\u003cp\u003eSNP Phylogenetic Tree for the Eight Recovered \u003cem\u003eE.coli \u003c/em\u003e\u0026nbsp;Isolates from \u0026nbsp;Ekiti and Ondo State. The figure showed three clades (1, 2, and 3). NGEK1 is an \u003cem\u003eE. coli isolate from human blood, and they were found to be in the sample clade with similarity in their MLST, serotypes, cgMLST, and also \u003c/em\u003eto belong to the same phylogroup. \u003cem\u003eE.coli \u003c/em\u003eNGEK2 from the home table of \u0026nbsp;Isolates NGEK1. \u003cem\u003eE.coli \u003c/em\u003eisolate NGEK 17 was obtained from farm water with a similar genetic makeup to E. coli isolate E.coli NGEK12 from an animal (poultry). The same pattern was found in the \u003cem\u003eE. coli \u003c/em\u003eisolate (NGEK22A) from a rectal swab from an animal handler (human) and an animal (poultry) (NGEK21). However, there was a difference in the genetic makeup of the \u003cem\u003eE. coli \u003c/em\u003eisolate (NGEK 7) from the human urine sample and the \u003cem\u003eE.coli \u003c/em\u003eisolate (NGEK16) gotten from the patient's environment (home water). The colour code showed isolates in the same clade.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/74120728731e385994463b59.png"},{"id":104706756,"identity":"f19dc973-8ebb-455d-8736-eae6b4311754","added_by":"auto","created_at":"2026-03-16 09:37:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":372059,"visible":true,"origin":"","legend":"\u003cp\u003eComparative phylogenomic tree of the 8\u003cem\u003e E. coli \u003c/em\u003eisolates (local) and 78 \u003cem\u003eE. coli \u003c/em\u003eisolates (global) obtained from different sample types across Africa, Asia, Europe, and the Americas. The colour code showed the sample types from which the isolates were obtained. (The list of the isolates and their corresponding accession number is in the supplementary file A).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/7ab013c8fde4442903e80660.png"},{"id":104782336,"identity":"965d554d-3293-490d-83b6-6bdc4d6bac73","added_by":"auto","created_at":"2026-03-17 07:57:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":28629,"visible":true,"origin":"","legend":"\u003cp\u003eTransmission Dynamic Matrix Model for E. coli using WGS Data. The transmission dynamic matrix model illustrates the pathways and interactions involved in the dissemination of E. coli across ecological niches, integrating whole-genome sequencing (WGS) data to map genetic relationships and transmission events. Each cell in the matrix represents the direction and magnitude of transmission between sources, including humans, animals, and environmental reservoirs. The model incorporates key mobile genetic elements identified by WGS, such as insertion sequences and transposons, which facilitate the horizontal transfer of resistance and virulence genes. The matrix provides a visual summary of transmission dynamics, supporting the identification of critical control points and informing targeted interventions to manage antimicrobial resistance.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/27bd676ac1355c20db4ea9ab.png"},{"id":105033556,"identity":"5b228838-037d-4475-a2f6-9927558fbaae","added_by":"auto","created_at":"2026-03-20 07:19:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2474697,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/f527841d-4b51-4b59-9562-681467e16e31.pdf"},{"id":104706751,"identity":"3888a7ac-4907-4b8d-9271-297eb2dbe82c","added_by":"auto","created_at":"2026-03-16 09:37:59","extension":"csv","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6074,"visible":true,"origin":"","legend":"","description":"","filename":"GenomicMetaData.csv","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/a7b1002d692e69b48ce7461c.csv"},{"id":104783263,"identity":"378e2bae-16f1-4f6d-bd89-f7bd500e4d1a","added_by":"auto","created_at":"2026-03-17 07:58:29","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22983,"visible":true,"origin":"","legend":"","description":"","filename":"Table.docx","url":"https://assets-eu.researchsquare.com/files/rs-9060994/v1/55fa854570ed54a68f4892d1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genomic Insights into Possible Zoonotic, Anthroponotic, and Environmental Transmission of Escherichia coli in Ekiti and Ondo States, Nigeria","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe ubiquitous nature of \u003cem\u003eEscherichia coli\u003c/em\u003e is due to its duality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The duality of \u003cem\u003eE.coli\u003c/em\u003e is its ability to act as a commensal in the intestinal tract of humans and other vertebrates, which is necessary for the maintenance of their microbiome, and it\u0026rsquo;s also able to cause significant infection, ranging from diarrhoea, a self-limiting infection, urinary tract infection, to sepsis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This duality makes it a vital bacterium of public health concern. This ability to adapt to different environments is encoded in its genome [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. \u003cem\u003eE. coli\u003c/em\u003e possesses an open pangenome with a core set of housekeeping genes, which provides the evolutionary backbone for phylogenomic insight and a vast variable accessory genome that is either borne on the chromosome or an extra-chromosomal element[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These accessory genomic materials are exchanged between strains, which equip them with antimicrobial resistance and virulence potentials [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The genomic component of any \u003cem\u003eE.coli\u003c/em\u003e determines its behaviour and virulent potential [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These genomic components include the resistome, virulome and mobilome, which are crucial to the pathogenicity and the extent to which it can cause an infection [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, understanding the resistome, virulome, and mobilome of an \u003cem\u003eE. coli\u003c/em\u003e isolate is fundamental to deciphering the epidemiology of any pathogenic \u003cem\u003eE. coli\u003c/em\u003e, its transmission to humans and animals, and its contamination of their shared environment.\u003c/p\u003e \u003cp\u003eThe line between commensalism and pathogenicity is not fixed but is a dynamic continuum shaped by genetic evolution. A study by Burgaya et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] investigated and unravelled the genetic determinants that predispose an \u003cem\u003eE. coli\u003c/em\u003e strain to cause invasive disease. In that study, a comparison of 912 \u003cem\u003eE. coli\u003c/em\u003e strains from bloodstream infections and 370 strains from healthy individuals revealed that pathogenicity is a highly heritable trait, with a striking 69% of the variance explained between the two datasets. Some of these variances could be attributed to E. coli adaptation through the acquisition of MGEs, as reported by Byarugaba et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and Saini et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Saini et al. particularly found that \u003cem\u003eE. coli\u003c/em\u003e isolates from urban environments evolved by gaining fitness advantages, such as AMR and virulence factors, through horizontal gene transfer (HGT)- mediated acquisition of MGEs.\u003c/p\u003e \u003cp\u003eEvidence in the molecular, genetic, and genome-wide analysis of \u003cem\u003eE. coli\u003c/em\u003e obtained from a matched sample from different sampling cohorts, from companion animals and their owners, patients and their clinical environment, animals and their handlers and their environment has demonstrated transmission dynamics of pathogenic and MDR \u003cem\u003eE. coli\u003c/em\u003e isolates. A global snapshot phylogenomic analysis by Mitra \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which used 158 \u003cem\u003eE. coli\u003c/em\u003e isolates compared with isolates from India, suggests possible cross-transmission among humans, animals, and the environment, mainly via zoonotic transmission. Zoonosis is an established phenomenon in which an animal transmits an infection or pathogenic microorganism, including resistant bacteria, to humans [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Globally, this phenomenon, zoonosis, is well-established, as well as the transmission of microorganisms from contaminated environments to humans and animals [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, a phenomenon called anthroponoosis, also known as reversed zoonosis, is the process by which an infected human host of microbial origin transmits pathogens to non-humans, whereas zooanthroponoosis is exclusively a process by which humans transmit pathogens to animals; both phenomena are not well established in the literature [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, studies agreed that this is generally possible. Some examples of those types include that one by Ewers \u003cem\u003eet al.\u003c/em\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which found a specific \u003cem\u003eE. coli\u003c/em\u003e clone that was initially restricted to humans; similarly, Rwego et al.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and Nicolas-Chanoine et al.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] have independently asserted, based on data found in their studies, the possibilities of anthroponosis, significant efforts have been given to zoonosis, but if the chain of transmission is not fully understood, through concentrated attempt to unravel all possible means of transmission, the battle to turn the tide of infectious disease will yield limited result.. However, even since those earlier studies were done, little interest has been shown in this aspect of research. The gaps that limit this establishment of anthroponosis and zooanthroponosis lie in limitations in methods in sample collection, timing of collection, and pathogen recovery techniques. Also, such studies require large sample sizes, longitudinal designs, and epidemiological approaches. These types of studies require rigorous data analysis, including genome-wide analyses to determine the direction or origin of pathogenicity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although, some subjects in the global north, has analysed large retrospective data set, which shows some evidence [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], however, this is not so for global south, where hygiene, biosecurity in interaction with animals and agricultural and animal companion is minimal, as such the need for a study that can determine the direction of transmission of pathogenic micro-organism. This study provides a snapshot of pilot evidence and data that can be built on using genomic data to understand how pathogenic and MDR E. coli are transmitted within the One Health ecosystem. Therefore, this study reported a genomics-wide research on \u003cem\u003eE. coli\u003c/em\u003e obtained from matched samples from human, animal, and environmental sources, limited to those with the same similarities in their phenotypic (AST susceptibility) and gene detection from Ekiti and Ondo states, Nigeria, a resource-limited setting and a low- and middle-income country.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eBacterial Strains\u003c/h2\u003e\n \u003cp\u003eThe study obtained four hundred and thirty-five (435) \u003cem\u003eE. coli\u003c/em\u003e isolates (unpublished). These isolates were cultured from matched samples from three cohorts: clinical settings, animal farms, and slaughterhouses. The clinical cohort includes samples from consenting patients, animals, and environmental samples (water, tables, and bench-top swabs) collected from their homes. In the animal farm cohort, samples were collected from the animal handlers, their animals, and their environment (water samples, animal pens, and bench tops). Lastly, slaughterhouse cohorts included samples from slaughterhouse workers, slaughtered animals, and environmental samples (water, table tops, and bench-top swabs). The isolated \u003cem\u003eE. coli\u003c/em\u003e were subjected to Phenotypic antimicrobial susceptibility testing (AST) in accordance with CLSI standards [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eEight \u003cem\u003eE. coli\u003c/em\u003e isolates were selected for whole-genome sequencing based on similarities in antimicrobial susceptibility patterns from the same cohort and sample site. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the criteria used to select isolates for WGS. We selected eight \u003cem\u003eE. coli\u003c/em\u003e isolates (humans, n\u0026thinsp;=\u0026thinsp;3, animals, n\u0026thinsp;=\u0026thinsp;2, and environmental samples, n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eDNA Extraction and DNA Quantitation\u003c/h3\u003e\n\u003cp\u003eDNA was extracted using the QIAamp DNA Mini Kit for genomic DNA. The modified protocol for Gram-negative bacteria DNA extraction was used, as provided by Yang [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. The DNA was quantified using a Qubit fluorometer (Thermo Scientific, USA). The eluted DNA was pipetted into storage tubes and stored in a freezer at -80 degrees Celsius.\u003c/p\u003e\n\u003ch3\u003eWhole Genome Sequencing\u003c/h3\u003e\n\u003cp\u003eLibrary construction and the whole genome of the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates (NGEK1, NGEK2, NGEK7, NGEK13, NGEK16, NGEK17, NGEK21 and NGEK22A) were sequenced using the Illumina NovaSeq PE150X (300bp) at the Beijing and Singapore Novogene Ltd. After the extracted DNA materials were shipped and passed the quality test. The Libraries were prepared according to the Novogene protocol. The Illumina NovaSeq PE150 was used to generate raw data (short reads). The clean data that was used for further analysis after the sequenced data were filtered and processed according to Cock et al [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eQuality Assessment and Assembly\u003c/h3\u003e\n\u003cp\u003eQuality analysis was conducted using the Galaxy platform [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e], which was accessed on February 3, 2024 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://usegalaxy.org/\u003c/span\u003e\u003c/span\u003e). The quality assessment of raw data was performed using FastQC and MultiQC [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. The short-read sequences were assembled using SPAdes, and the assembly quality was assessed using Quast (Galaxy Version 5.0)[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. An assembly was deemed unacceptable if it had more than 400 contigs, a N50 value lower than 40,000, or if it had between 300 and 400 contigs and an N50 value lower than 50,000.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatic analysis of WGS data for the antimicrobial Resistance determinants of\u003c/strong\u003e \u003cstrong\u003eE. coli\u003c/strong\u003e \u003cstrong\u003eisolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe identification and categorisation of genes that confer resistance were carried out using ResFinder 4.1, a bioinformatics tool developed by the Centre for Genomics Epidemiology (CGE) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genomicepidemiology.org/\u003c/span\u003e\u003c/span\u003e) (accessed on 2024/03/2). Each isolate\u0026apos;s genes were compared to an annotated resistance gene using a threshold of 95\u0026ndash;100% identity [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. The plasmid replicon types of each \u003cem\u003eE. coli\u003c/em\u003e isolate were identified using PlasmidFinder 2.1. As documented by Joensen et al. [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e], the strain\u0026apos;s O and H serotypes were determined by analysing the generated FASTA files using the Centre for Genomic Epidemiology (CGE) platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genomicepidemiology.org/\u003c/span\u003e\u003c/span\u003e and (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cge.cbs.dtu.dk/services/CSIPhylogeny/\u003c/span\u003e\u003c/span\u003e) accessed on 2024/03/2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultilocus sequence typing (MLST) of\u003c/strong\u003e \u003cstrong\u003eE. coli\u003c/strong\u003e \u003cstrong\u003eisolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight \u003cem\u003eE. coli\u003c/em\u003e isolates underwent \u003cem\u003ein silico\u003c/em\u003e MLST analyses using schemes developed by Achtman [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. The MLST assignment for each \u003cem\u003eE. coli\u003c/em\u003e isolate was determined from whole-genome sequence data, yielding complete correspondence with alleles in the MLST database. The MLST Finder 2.0, a bioinformatics tool developed by CGE, was used to assign Sequence Types (STs) to the isolates. Isolates that showed a perfect 100% similarity with known MLST alleles were categorised accordingly. Nevertheless, isolates lacking a precise match were classified as unknown.\u003c/p\u003e\n\u003cp\u003eIf an isolate\u0026apos;s MLST alleles match an unknown ST in the MLST database, it is classified as a new type. The presence of virulence was determined using Virulence-Finder, a tool developed by Joensen et al [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. The MLST, serotype, phylogroup, and fimH subtype were collectively referred to as phylogenetic characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.17 Determination of\u003c/strong\u003e \u003cstrong\u003eE. coli\u003c/strong\u003e \u003cstrong\u003ePhylogroups, SNP Calling and Phylogeny\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe phylogroups of \u003cem\u003eE. coli\u003c/em\u003e genomes were determined using an \u003cem\u003ein-silico\u003c/em\u003e Clermont typing method, as outlined by Beghain et al [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. CATIBioMed (IAME UMR 1137) hosts the Clermont Typer web interface at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://clermontyping.iame-research.center/\u003c/span\u003e\u003c/span\u003e. The phylogenetic trees were constructed to determine the phylogenetic similarity of the \u003cem\u003eE. coli\u003c/em\u003e isolates using the Single Nucleotide Polymorphism (SNP) calling technique described by Kaas et al [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eE. coli\u003c/em\u003e reference strain was used to identify single-nucleotide polymorphisms (SNPs) and detect variations in the chromosomes of each isolate. A phylogenetic tree was then constructed using the online tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://realphy.unibas.ch/realphy/\u003c/span\u003e\u003c/span\u003e). The resulting phylogenetic tree was analysed and visualised using the interactive Tree of Life tool (iTOL) based on single-nucleotide polymorphisms (SNPs). The tool can be accessed at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://itol.embl.de/itol.cgi\u003c/span\u003e\u003c/span\u003e. The genomes were examined to determine the number of single-nucleotide polymorphisms (SNPs) between pairs of isolates from distinct sources, thereby evaluating their relationship. The 8 \u003cem\u003eE. coli\u003c/em\u003e genomes compiled in this study have been submitted to the NCBI database, and a comparison with global \u003cem\u003eE. coli\u003c/em\u003e isolates from different regions and sources was also made. Supplementary file 1 has its metadata and accession numbers.\u003c/p\u003e\n\u003ch3\u003eEthical Clearance\u003c/h3\u003e\n\u003cp\u003eEthical Clearance from the National Health Research Ethics Committee of Nigeria (NHREC/01/01/2007-21/03/2023), the Federal Teaching Hospital, Ido-Ekiti (ERC/2023/09/20/1034B), and the Ondo State Ministry of Agriculture (MNR/V.384/64). The study adhered to all approved guidelines for both human and animal research, as outlined by the relevant ethical bodies.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eResistome and Virulome\u003c/h2\u003e \u003cp\u003eAmong the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates, there were 35 antimicrobial resistance genes (ARGs) with no co-occurrence of any ARGs in all the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates. Of the 35 ARGS found in all the \u003cem\u003eE.coli\u003c/em\u003e isolates, \u003cem\u003ethe blaTEM\u003c/em\u003e gene was found in 5 of the eight E.coli isolates, the \u003cem\u003eblaCTX-M-15, qnrS1, aph(3'')-Ib, aph(6)-Id\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e genes were found in 4 of the \u003cem\u003eE.coli\u003c/em\u003e isolates. ARGs aac(3)-IId, mph(A), qepA4 and tet(A) were found in 3 of the isolates, aadA2, aac(6')-Ib-cr, blaOXA-1, catB3, dfrA17 and qnrB19 were, found in 2 isolates, while aadA5, blaADC-25, sul1, dfrA17, aph(3')-IIb, aadA10, blaPAO, blaOXA-488, blaCMY-2, blaOXA-181, blaOXA-1, fosA, catB7, floR, catB3, crpP, qnrVC1, tet(B) and dfrB5 genes occurred only in one isolates. The occurrence of the ARGs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eA total of 58 virulence factors were identified in 8 \u003cem\u003eE. coli\u003c/em\u003e isolates. Two of the isolates (NGEK1 and NGEK2) had 15 virulence factors; isolates NGEK13 and NGEK17 had 16; isolates NGEK21 and NGEK22A had 31; and isolates NGEK7 and NGEK16 had 17 and 43, respectively. Virulence gene csgA, fdeC, gad, nlpI, terC, yehA, B, C, and D were all found in all the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates, followed by hlyE(7), iss(7), fimH (6), hha (6), AslA (5), traT (5), yghJ(4),hra (4), chuA (3), and kpsMII_K5 (2). The occurrence of other virulence genes is shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, respectively.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMulti-locus Sequence Typing (MLST) and Core Genome Multi-locus Sequence Typing (cgMLST)\u003c/h3\u003e\n\u003cp\u003eMultilocus sequence type (MLST) analysis identified five different STs among the \u003cem\u003eE. coli\u003c/em\u003e isolates (ST 2, n\u0026thinsp;=\u0026thinsp;2; ST 181, n\u0026thinsp;=\u0026thinsp;2; ST 38, n\u0026thinsp;=\u0026thinsp;2), while ST 693 and 998 were each identified. Equally, five cgMLSTs were identified in the cgMLST analysis, with 6 \u003cem\u003eE. coli\u003c/em\u003e isolates, two each having cgST 147613, 195700, and 47723, respectively. The other 2 \u003cem\u003eE. coli\u003c/em\u003e isolates had \u003cem\u003ecgST values\u003c/em\u003e of 47720 and 137699, respectively. It was observed that isolates NGEK1 from human and NGEK2 from the environment had the same ST and cgMLST, also, isolates NGEK13 from chicken and NGEK17 from the environment had the same ST and cgMLST. Similarly, isolate NGEK21 from an animal handler (poultry worker) and isolate NGEK22A from chicken (poultry) had the same ST and cgMLST. However, \u003cem\u003eE.coli\u003c/em\u003e isolate NGEK7 from humans and isolate NGEK16 had different ST and cgMLST, respectively. It was also observed that the cgMLST of NGEK21, 22A, and 7 were relatively close (cgST 77723 vs 47720) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The results suggest possible transmission of \u003cem\u003eE. coli\u003c/em\u003e among humans, animals, and across different environments.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSerotypes and Phylogroups\u003c/h2\u003e \u003cp\u003eFive serotypes (O101:H9, O55:H35, O76:H9, O2050:H6, and O101:H15) were identified among the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates, with similar serotypes observed in 3 matched pairs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The phylogrouping of the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates shows that three were in phylogroup A, two each in phylogroups B2 and D, and one in phylogroup C. The results are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMobile Genetic Element\u003c/h2\u003e \u003cp\u003eThe MGEs analysis shows the presence of several plasmids and other MGEs. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the plasmids found in all \u003cem\u003eE. coli\u003c/em\u003e isolates. Of the sixteen plasmids found among the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates, IncFIA(HI1) found in E. coli isolates NGEK1 and NGEK2 carried a virulence gene (clpK1). Plasmid Col440I was found to carry the qnrB19 gene in isolates NGEK13 and NGEK17 associated with phenotypic resistance to ciprofloxacin and a virulence factor (mrkA). Plasmid IncFII(pRSB107) was found in three isolates (NGEK7, NGEK21, AND NGEK22A). It was found to carry resistance gene \u003cem\u003eblaTEM-1B\u003c/em\u003e in NGEK21 AND NGEK22A isolates and virulence genes \u003cem\u003eanr\u003c/em\u003e; however, it was not associated with any resistance or virulence genes in NGEK7. Plasmid ColKP3 carried \u003cem\u003eqnrS1\u003c/em\u003e and \u003cem\u003eblaOXA-181\u003c/em\u003e genes; similarly, plasmid IncQ1 carried \u003cem\u003eaph(6)-Id, aph(3'')-Ib\u003c/em\u003e, and \u003cem\u003esul2\u003c/em\u003e genes, all found in \u003cem\u003eE. coli\u003c/em\u003e isolate NGEK7. Plasmid IncFII(pRSB107) in \u003cem\u003eE.coli\u003c/em\u003e isolate NGEK16 was found to carry resistance to tetA and virulence genes anr and traT, respectively. In the same E. coli isolates, plasmid Col156 was found to carry the virulence factor \u003cem\u003esenB\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows other types of MGEs found among the 8 \u003cem\u003eE. coli\u003c/em\u003e strains; some were associated with antimicrobial resistance genes and virulence factors, whereas others were not associated with any function. Five types of non-plasmid MGEs were found in the 8 \u003cem\u003eE. coli.\u003c/em\u003e They were: unit transposon, insertion sequence, miniature inverted repeat, integrative conjugative element, and composite transposon. Among the eight \u003cem\u003eE. coli\u003c/em\u003e isolates, isolate NGEK16 had the highest number of non-plasmid MGEs carrying genes associated with antibiotic resistance and virulence factors. There were 7 them (Tn5403, ISEc9, IS6100, ICEEcIHE3034-1, MITEEc1, ISEc17, and cn_31761_ISEc17). A Tn2, a unit transposon, was found in \u003cem\u003eE. coli\u003c/em\u003e isolates NGEK1 and NGEK2, which carried blaTEM-1B. In the same isolates, ISKox3 and ISEc1, insertion sequences that carried virulence genes (hlyE and fdeC), were found. Insertion sequence ISEc38 was found in \u003cem\u003eE. coli\u003c/em\u003e isolates NGK13 and NGEK17, which carried the hha gene, a virulence factor. \u003cem\u003eE. coli\u003c/em\u003e isolates NGEK21 and NGEK22A carried ISKpn19, IS30, and MITEEc1, all non-plasmid MGEs; ISKpn19 carried three resistance genes (tet(A), qnrS1, and blaCTX-M-15). While the IS30 and MITEEc1 carried virulence factors. \u003cem\u003eE. coli\u003c/em\u003e isolate NGEK7 had ISKpn19 and MITEEc1; the ISKpn19 carried qnrS1 and blaOXA-181 antibiotic resistance genes, while MITEEc1 carried nine virulence genes (fdeC, yehA, B, C, D, hra,papA_F13 papC, and nlpI).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic Analysis and Comparative Genomics\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eLocal Phylogenetic Analysis Results\u003c/h2\u003e \u003cp\u003eThe phylogenetic tree of the different 8 \u003cem\u003eE. coli\u003c/em\u003e isolates is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e also shows the evolutionary history of the local \u003cem\u003eE.coli\u003c/em\u003e isolates. Of the 8 \u003cem\u003eE. coli\u003c/em\u003e strains, 7 showed a close relationship and were organised into three clades (clade1, clade2, and clade3). Clade 1, where isolates \u003cem\u003eE. coli\u003c/em\u003e NGEK1 and NGEK2 were of the exact ancestry origin, as indicated by their distance and relationship, NGEK1 was from a human (blood). In contrast, isolate NGEK2 was isolated from the environment (home table), from which isolate NGEK1 was also isolated. These findings suggest possible transmission between humans and the environment, or vice versa. Similarly, NGEK13 isolated from poultry (chicken) and NGEK17 isolated from the environment (farm water) were also closely related, sharing the same ancestry level (clade 2). Isolate NGEK22A from an animal (chicken), and isolate NGEK21 from a human (rectal swab), which also showed similar ancestry roots but were closely related. Clade 3 showed four isolates from the same root, but only NGEK22A and NGEK21, which originated from the same ancestral root, and also NGEK16 from the environment (home water), seem to be related to some extent. Isolates \u003cem\u003eE.coli\u003c/em\u003e NGEK1 was isolated from a human sample, while isolate NGEK2 was isolated from the bench, the house bench, and the home of that individual. Based on this phylogenetic analysis, they are likely from the same source. So, there is a possible cross-transmission between humans and the environment or from the environment to humans. The same explanation applies to isolate pairs NGEK13 and NGEK17 and NGEK22A and NGEK21. The whole-genome sequencing results for E. coli isolates NGEK7 and NGEK16 showed that they were significantly different and did not share a common ancestral root.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eGlobal Phylogenetic Analysis Results\u003c/h2\u003e \u003cp\u003eThe analysis of the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates compared to global \u003cem\u003eE. coli\u003c/em\u003e isolates phylogenetically showed similarity to \u003cem\u003eE. coli\u003c/em\u003e isolates from Ghana, South Africa, Cuba, China, the United Kingdom, the Netherlands, Switzerland, Nigeria, and the United States of America, obtained from humans, animals, and wastewater, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Of the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates, one of the isolates (NGEK16-04-2023) from home water (Environment) was found to be of the same ancestry root as the \u003cem\u003eE.\u003c/em\u003ecoli isolate (GCA_002510125.1), in a human from Pretoria in South Africa. It was distantly related to the \u003cem\u003eE. coli\u003c/em\u003e isolates (GCA_016767775.1 from a chicken in the USA, GCA_002002225.1 from a human in Sydney, Australia, and GCA_002416865.1 from a human in KwaZulu-Natal, South Africa).\u003c/p\u003e \u003cp\u003e \u003cem\u003eE. coli\u003c/em\u003e isolate (NGEK7-04-2023) from a urine sample in a human was associated with \u003cem\u003eE. coli\u003c/em\u003e isolate GCA_024585725.1 from poultry in Santa Cruz del Norte, Cuba. NGEK21-05-2023 and NGEK22A-05-2023 were of the exact ancestry origin and were closely associated with \u003cem\u003eE.coli\u003c/em\u003e GCA_048222295.1 and GCA_020883315.1 from human samples in the United Kingdom and the Netherlands, respectively. However, they are distantly associated with GCA_024224055.1 from a chicken sample from Switzerland and GCA_019584715.1 from wastewater in Ibadan, Nigeria.\u003c/p\u003e \u003cp\u003e \u003cem\u003eE. coli GCA_024225755.1, GCA_019357435.1, and GCA_022695865.1\u003c/em\u003e from chicken in Switzerland, in Jiaxing, Zhejiang, China, and Athens, USA, were distantly associated with NGEK7-04-2023 and NGEK13-04-2023 obtained from the environment (water) and animal (chicken), respectively, which were of the exact ancestry origin. Lastly, \u003cem\u003eE. coli\u003c/em\u003e NGEK1-04-2023 and NGEK2-04-2023, which were from the same branch, were closely associated with E. coli GCA_041877505.1 and GCA_002416915.1 from human samples in Accra, Ghana, and KwaZulu-Natal, South Africa, respectively.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePossible Transmission Dynamic Model for 8\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e \u003cb\u003eisolates from WGS Data.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the constructed transmission model for \u003cem\u003eE. coli\u003c/em\u003e based on WGS data. The result shows six possible models. Model 1: A human-to-environment-transmission route (NGEK1-Humans to NGEK2-Environment), Model 2: An environment-to-human transmission route (NGEK2-Environment to NGEK1-Humans), Model 3: An environment-to-animals transmission route (NGEK13-Environment to NGEK17-Animals), Model 4: An animals-to-environment transmission route (NGEK17-Animals to NGEK13-Environment), Model 5: An animals-to-human transmission route (NGEK22A-Animals to NGEK21-Humans), and Model 6: A human-to-animal transmission route (NGEK21-Humans to NGEK22A-Animals).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe transmission of \u003cem\u003eE. coli\u003c/em\u003e is dynamic, including moving from humans to animals, a process referred to as reverse zoonosis or anthroponosis and also the established nature of \u003cem\u003eE. coli\u003c/em\u003e transmission through zoonotic, i.e, from animals to humans through food contamination, domestication or compassionate use [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Environmental contamination with pathogenic \u003cem\u003eE. coli\u003c/em\u003e occurs when animals and humans improperly shed waste into the environment. The environment thereafter became the reservoir for these pathogenic \u003cem\u003eE.coli\u003c/em\u003e isolates [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This study integrates multilayered genomic data, including resistome and virulome profiling and phylogenetic analysis.\u003c/p\u003e \u003cp\u003eIn this study, we focused on unravelling the whole genetic and genetic relatedness of the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates that were obtained from matched samples obtained from three different collection cohort sites (cohort 1:hosipitalised patients and their animals and environment, cohort 2:animal farms, animal handlers, their animals and the environment, including their water sources and cohort 3: slaughterhouses: Buchters, slaughtered animals and their environment including the water sources used in the slaughterhouses).\u003c/p\u003e \u003cp\u003eIn our study, we identified a large pool of antibiotic resistance genes that could confer distinct phenotypic resistance in the 8 \u003cem\u003eE. coli\u003c/em\u003e isolates. Our study identified diverse resistance genes that confer multiple antibiotic resistances, including carbapenem resistance. There were 32 antibiotic resistance genes ( \u003cem\u003eblaTEM, blaCTX-M-15, qnrS1, aph(3'')-Ib, aph(6)-Id, sul2\u003c/em\u003e, ARGs aac(3)-IId, mph(A), qepA4, tet(A), aadA2, aac(6')-Ib-cr, blaOXA-1, catB3, dfrA17 and qnrB19, aadA5, sul1, dfrA17, aph(3')-IIb, aadA10, blaCMY-2, blaOXA-181, blaOXA-1, fosA, catB7, floR, catB3, crpP, qnrVC1, tet(B) and dfrB5).The predominant resistance genes found in the study were \u003cem\u003eblaTEM, blaCTX-M-15\u003c/em\u003e, and \u003cem\u003eqnrS1\u003c/em\u003e. All matched samples (NGEK1 vs NGEK2, NGEK13 vs NGEK17, NGEK21 vs NGEK22A) have the same resistomes and phenotypic characteristics, indicating that each \u003cem\u003eE. coli\u003c/em\u003e isolate in a pair is likely of the same origin. Genomic evidence from the 6 \u003cem\u003eE. coli\u003c/em\u003e isolates obtained from the three cohort sites provided a compelling snapshot of the transmission dynamics of MDR and virulent \u003cem\u003eE. coli\u003c/em\u003e across human, animal, and environmental interfaces in Nigeria. The expectation is that the \u003cem\u003eE. coli\u003c/em\u003e isolates in the matched pair (NGEK7 and NGEK16), based on their similar phenotypic susceptibility patterns, would have the same resistomes; however, the WGS result showed that they were not of the same origin as the phenotypic result, and the closeness of the sample collection point suggested. This shows the superiority of the WGS method over the phenotypic method for epidemiological and surveillance purposes.\u003c/p\u003e \u003cp\u003eEach resistance gene in each \u003cem\u003eE. coli\u003c/em\u003e isolate could be responsible for the observed antibiotic resistance patterns. For example, \u003cem\u003eblaTEM, blaCTX-M-15, blaCMY-2, blaOXA-181\u003c/em\u003e, and \u003cem\u003eblaOXA-1\u003c/em\u003e were found to be associated with resistance to beta-lactam antibiotics, although their resistance spectra differ. The \u003cem\u003eblaTEM\u003c/em\u003e gene is associated with resistance to antibiotics like ampicillin and amoxicillin, which are the first-line antibiotics commonly used in clinical settings in Nigeria and other settings [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], while the \u003cem\u003eblaOXA-181\u003c/em\u003e gene is associated with carbapenem resistance.\u003c/p\u003e \u003cp\u003eOne of the significant findings of our study was the genomic agreement observed among \u003cem\u003eE. coli\u003c/em\u003e isolates from matched clinical, household, animal, handler, and shared environment samples. For example, the identical Sequence Types (STs), core genome MLST (cgMLSTs), serotypes, and phylogroups between human-animal (NGEK21/NGEK22A), human-environment (NGEK1/NGEK2), and animal-environment (NGEK13/NGEK17) pairs provided potential evidence for the zoonotic or anthroponotic and environmental transmission of pathogenic \u003cem\u003eE. coli\u003c/em\u003e isolates. It is important to note that the near-identical core genomes identified in our study could serve as genomic fingerprints for surveillance. This assumption of genomic fingerprinting provides strong evidence for a specific route of transmission, which is vital for tracing the origin of an infection. It can be inferred from the available evidence in our study that zoonotic or anthroponotic transmission may be occurring, given the present tangible, genetically verified events at the study locations, as evidenced by the WGS data.\u003c/p\u003e \u003cp\u003eThe findings of our study on the possible transmission dynamics align with evidence in the literature, for example, a study by Mitra \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] on MDR \u003cem\u003eE.coli\u003c/em\u003e isolates from humans(animal handlers), animals, and the environment, which was also WGS-based, found a similar relationship in some of the sample cohorts in their study. In Nigeria, a study conducted by Aworh et al. (2021) in the FCT found relatedness among three sample pairs: poultry, their handlers, and the environments. However, further analysis found that they were not clonal. The SNP phylogenetic and core genome analyses of the six E. coli strains discussed in this study revealed clonality, making this one of the first reports of such findings in the study settings. This piece of evidence suggests the possible route of transmission and the movement of pathogenic \u003cem\u003eE.coli\u003c/em\u003e isolates across the different settings and further support the need for enforcement of biosecurity guideline in farms where animals are rare and also the need to keep a clean environment as this suggests that the environment could be a significant vehicle that transmit pathogenic, virulent and multi-drug resistance \u003cem\u003eE.coli\u003c/em\u003e isolates and also serves as reservoir for them.\u003c/p\u003e \u003cp\u003eThe results of our study also reveal that the \u003cem\u003eE. coli\u003c/em\u003e isolates obtained from the environment, water samples, and poultry (chicken) were not merely commensal, as they harboured antimicrobial resistance genes and virulence factors. For example, the presence of clinically relevant antimicrobial resistance genes (ARGs), such as \u003cem\u003eblaCTX-M-15\u003c/em\u003e, associated with extended-spectrum beta-lactamases (ESBLs), \u003cem\u003eblaOXA-181\u003c/em\u003e, associated with carbapenemases, and \u003cem\u003eqnrS1\u003c/em\u003e, associated with quinolone resistance, is a public health concern. Also, the co-occurrence of all those ARGs with virulence factors related to extraintestinal infection, such as \u003cem\u003ehlyE\u003c/em\u003e and \u003cem\u003eiss\u003c/em\u003e, which were particularly found in ExPEC-associated phylogroups B2 and D, raises a concern about strains that are both capable of causing severe infection and difficult to treat. This implies that those who get infected with such \u003cem\u003eE. coli\u003c/em\u003e pathogens experience extended hospitalisation and an increased burden on the healthcare system [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Equally, this can lead to low productivity as a result of loss of work time due to the time spent managing those types of infection [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Also, since the health insurance system in Nigeria is in a primitive stage, where most individuals who work in the animal sector do not have coverage, they will have to pay for their treatment out of pocket [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This will deplete their finances, which could have been channelled into other areas of their lives. Also, shedding of these pathogenic \u003cem\u003eE. coli\u003c/em\u003e isolates into the environment could contaminate water bodies, as open defecation remains widespread in Nigeria, although it has been outlawed in several states; implementation remains a significant concern.\u003c/p\u003e \u003cp\u003eThe analysis of mobile genetic elements (plasmid- and non-plasmid-mediated) examines the presence of extrachromosomal elements that can rapidly disseminate to other bacteria, even when those bacteria may not initially have that capacity. Particularly of interest were the presence of \u003cem\u003eblaTEM\u003c/em\u003e on a plasmid (\u003cem\u003eIncFII\u003c/em\u003e) and \u003cem\u003eqnrS1\u003c/em\u003e and \u003cem\u003eblaOXA-181\u003c/em\u003e on an insertion sequence (\u003cem\u003eISKpn19\u003c/em\u003e). These findings provide a possible explanation for the movement of the resistance factor across species or bacteria. It also suggests that the plasmid and other MGEs act as vehicles for distributing resistance and virulence factor traits among different bacterial hosts [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The isolate NGEK16 from the environment harboured the highest number of MGEs. This highlights how a single environmental strain can serve as a potent reservoir for these MGEs, further fuelling the AMR crisis. Such an \u003cem\u003eE. coli\u003c/em\u003e isolate can easily transfer its resistance genes via its MGEs to other bacteria in the environment. This observation aligns with the findings of Bethke \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], Tokuda and Shintani [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and recently Ku et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], who have also observed that \u003cem\u003eE. coli\u003c/em\u003e isolates from the environment have several MGEs that could serve as vehicles transmitting resistance and virulence factors to non-resistant, virulent, and pathogenic bacteria, and then make them resistant, virulent, and pathogenic.\u003c/p\u003e \u003cp\u003eIn the global context, the phylogenetic analysis reveals that the isolates in our study did not cluster only with isolates from Nigeria; they also cluster with isolates from Africa, Europe, Asia, and the Americas. This finding underscores the connection between local transmission cycles in the settings where the samples were obtained and the global epidemiology of AMR \u003cem\u003eE. coli\u003c/em\u003e isolates. For example, the relatedness of NGEK21/NGEK22A to human isolates from the United Kingdom and the Netherlands could reflect the global spread of successful high-risk clones. As exemplified in very highly dispersed clones like the ST 131, which has been found in epidemiological studies in clinical and non-clinical settings globally [\u003cspan additionalcitationids=\"CR56 CR57\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], although ST131 was not found in this study.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations of this study\u003c/h2\u003e \u003cp\u003eThe strength of this study is based on the sampling techniques, which were matched samples, which is essential in investigating transmission dynamics and also the focus on unravelling the whole genetic features and genetic relatedness, which includes the resistome, virulome, the MGEs, and extensive phylogenomic analysis in this study, which provide great insight into the creatures of the 8 \u003cem\u003eE.coli\u003c/em\u003e isolates investigated. However, the small sample size means that, while the evidence in this study strongly supports the transmission event, it represents only a snapshot rather than comprehensive epidemiological evidence. Therefore, the conclusions are robust for these specific isolates but cannot be generalised to the entire region or setting without a larger-scale surveillance. Also, while the genomic data strongly suggest a transmission link, it cannot definitively determine the direction of transfer. The six proposed models (human-to-environment vs. environment-to-human, human-to-animal vs. animal-to-human, and animal-to-environment vs. environment-to-animal) are equally plausible based on the genetic data alone; therefore, resolving these limitations would require longitudinal sampling and detailed epidemiological data.\u003c/p\u003e \u003cp\u003eDespite these limitations, our findings provide a valuable, data-driven foundation. It highlights specific, genetically linked instances of cross-contamination between humans, poultry, water sources, and their immediate environment. The evidence strongly suggests the need for a multifaceted intervention that addresses antibiotic stewardship in both human and veterinary medicine, improves community sanitation, ensures biosecurity in animal farming, and implements other strategies to break this transmission cycle.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study used a genome-wide analysis to investigate the resistome, virulome, MGEs, and phylogenomic relatedness, providing insight into zoonotic, arthropod, and environmental transmission of pathogenic and virulent E. coli isolates from matched samples using the One Health approach in Ekiti and Ondo states, Nigeria. We observed that the \u003cem\u003eE. coli\u003c/em\u003e isolates have diverse ARGs, virulence factors, \u003cem\u003eSTs\u003c/em\u003e, and MGEs. However, samples obtained from the same cohort showed relatedness and clonality, as indicated by genomic data. The presence of antibiotic resistance, virulence factors, and MGEs in isolates from poultry (chicken), water samples, and the environment demonstrates their capacity to cause severe infection in humans. Phylogenomic analysis revealed a close snapshot of the local isolates' relationship to \u003cem\u003eE. coli\u003c/em\u003e isolates from Africa, Asia, Europe, and the Americas, collected from humans, poultry, water, and the environment. The presence of such potential strain in hosts other than humans is a key factor in the spread of pathogenic \u003cem\u003eE. coli\u003c/em\u003e isolates. Our study emphasises the need to enforce antibiotic stewardship and biosecurity in animal husbandry and poultry farming, as well as environmental sanitation and continuous surveillance of water sources used in homes and farms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY AND WGS DATA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe WGS data generated in this study have been deposited at NCBI under the project accession PRJNA1295602, and all other associated data are available in the supplementary file.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate the assistance provided by the laboratory staff at the Department of Microbiology, Faculty of Life Sciences, and the Department of Pharmaceutical Microbiology and Biotechnology, Faculty of Pharmacy, Federal University, Oye-Ekiti, Ekiti State, Nigeria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eULI-Conceptualisation, investigation, software, formal analysis, write first draft, OBS-Supervision, data validation, Editing, Writing. \u0026nbsp; OTM-Supervision, data validation, Editing, Writing, OOE-Supervision, data validation, Editing, Writing, ATA-investigation, formal analysis, writing, project administration, AFA-investigation, formal analysis, writing, project administration, OB-investigation, formal analysis, writing, project administration, AEC-Supervision, data validation, Editing, Writing and OSK-Supervision, data validation, Editing, Writing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no external funding associated with this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical Clearance from the National Health Research Ethics Committee of Nigeria (NHREC) (NHREC/01/01/2007-21/03/2023), the Federal Teaching Hospital, Ido-Ekiti (ERC/2023/09/20/1034B) and the Ondo State Ministry of Agriculture (MNR/V.384/64) were obtained for this study. Consent was gotten from the participants to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFoster-Nyarko E, Pallen MJ. The microbial ecology of Escherichia coli in the vertebrate gut. 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F1000 Faculty Rev-195.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9060994/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9060994/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e can be pathogenic or non-pathogenic, depending on its genetic makeup, which characterises its virulence potential. The transmission dynamics of \u003cem\u003eE. coli\u003c/em\u003e are complex due to its dual nature and its ability to be transmitted among humans, animals, and the environment in both directions. The objective of this study was to gain insight into the resistome, virulome, and mibiolome of \u003cem\u003eE. coli\u003c/em\u003e from matched samples using the One-Health Approach in Ekiti and Ondo States, Nigeria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWhole-genome sequencing (WGS) was used to characterise the genomic features of 8 \u003cem\u003eE. coli\u003c/em\u003e isolates from humans (n\u0026thinsp;=\u0026thinsp;3), animals (n\u0026thinsp;=\u0026thinsp;2), and the environment (n\u0026thinsp;=\u0026thinsp;3). Antimicrobial resistance genes (ARGs), virulence factors, and mobile genetic elements (MGEs) were identified, followed by multi-locus sequence typing (MLST), core genome MLST, serotyping, phylogrouping, and local and global phylogenomic analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe 8 \u003cem\u003eE. coli\u003c/em\u003e recovered in this study showed variation in the presence of ARGs, virulome, and mobilome, with total ARGs\u0026thinsp;\u0026gt;\u0026thinsp;30 genes and virulome\u0026thinsp;\u0026gt;\u0026thinsp;40 genes. There was an identical genetic makeup in three pairs (NGEK1 vs. NGEK1, NGEK13 vs. NGEK17, and NGEK21 vs. NGEK22A) recovered from humans, animals and environments. Some significant resistance genes (blaCTX-M-15, blaCMY-2, blaTEM-1B, blaOXA-1, blaOXA-181 and qnrS1) were found in the isolates. The MGEs analysis found two groups: plasmid-mediated and non-plasmid-mediated, with both carrying resistance (blaTEM, blaCTX-M-15, qnrS1, qnrB19, and blaOXA181) and virulence genes (hylE, hha, senB). The STs found in the study were ST 2, 38,181, 693, and 998. Clonality was observed among some \u003cem\u003eE. coli\u003c/em\u003e isolates from the same household or farms, and these isolates were also phylogenetically associated with certain global E. coli isolates.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study emphasised that the \u003cem\u003eE. coli\u003c/em\u003e isolates analysed possessed ARGs and virulence factors that drive pathogenicity and presented evidence for possible zoonotic and anthroponotic modes of transmission.\u003c/p\u003e","manuscriptTitle":"Genomic Insights into Possible Zoonotic, Anthroponotic, and Environmental Transmission of Escherichia coli in Ekiti and Ondo States, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-16 09:37:54","doi":"10.21203/rs.3.rs-9060994/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b734a5a7-3bf8-4e06-8425-928e91601420","owner":[],"postedDate":"March 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T09:37:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-16 09:37:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9060994","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9060994","identity":"rs-9060994","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}