{"paper_id":"06deb891-021f-4bce-8d5c-0fc77844d12b","body_text":"1 \n \nGenomic and Bioinformatic Insights into Enterococcus faecalis from Retail Meats in Nigeria 1 \nCharles Ayodeji Osunla a, b*, Ayorinde Akinbobola a, Arif Elshafea c, Esther Eyram Asare Yeboah 2 \nd, Olayemi Stephen Bakare e, Aderonke Fayanju a, Dorcas Oladayo Fatoba f, g, Bright Boamah h, I , 3 \nDaniel Gyamfi Amoako c,  j* 4 \n 5 \na Department of Microbiology, Adekunle Ajasin University, Akungba Akoko, Nigeria 6 \nb  School of Public Health, University of Saskatchewan, Saskatoon, Canada 7 \nc Department of Pathobiology, University of Guelph, Ontario, Canada 8 \nd Department of Pharmaceutical Sciences, Central University. P. O. Box 2305, Miotso, Ghana 9 \ne School of Biological and Behavioural Sciences, Queen Mary University of London 10 \nf Health Research Incorporated, Wadsworth Center, New York State Department of Health, USA 11 \ng The University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA 12 \nh Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada 13 \nI Canadian Food Inspection Agency, Ottawa, Ontario, Canada 14 \nJ Antimicrobial Research Unit, University of KwaZulu-Natal, South Africa 15 \n 16 \n*Correspondence: Charles Ayodeji Osunla ; charles.osunla@aaua.edu.ng and Daniel Gyamfi 17 \nAmoako, amoakodg@gmail.com (http://orcid.org/0000-0003-3551-3458). 18 \n 19 \nRunning title: Genomic analysis of E. faecalis from retail meat in Nigeria 20 \n 21 \nKeywords: Enterococcus faecalis, antimicrobial resistance, whole-genome sequencing, virulence, 22 \nplasmids, retail meat, Nigeria 23 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n2 \n \nAbstract 24 \nBackground: Enterococcus faecalis  (E. faecalis)  is a commensal and opportunistic pathogen 25 \nincreasingly recognized for its antimicrobial resistance (AMR) and zoonotic potential.  This study 26 \nemploys whole -genome sequencing (WGS) to characterize  E. faecalis  isolates from retail meat 27 \nsamples, focusing on antimicrobial resistance genes (ARGs), virulence determinants, mobile genetic 28 \nelements, and phylogenomic relationships.  Materials and Methods: Fifty raw meat samples, 29 \nincluding chicken (n=18), beef (n=17), and turkey (n=15), were collected from retail markets in 30 \nAkungba-Akoko, Nigeria. E. faecalis  isolates were identified using standard microbiological 31 \nmethods and subjected to antimicrobial susceptibility testing were further analysed using WGS.   32 \nResults: Ten E. faecalis  isolates were recovered, with the highest prevalence in chicken (n=6), 33 \nfollowed by beef (n=2) and turkey (n=2). All isolates were resistant to clindamycin, erythromycin, 34 \nand tetracycline. Frequent ARGs included  aac(6’)-aph(2’’), ant(6)-Ia, lsa(A), erm(B), tet(M), 35 \nand tet(L). Plasmid replicons rep9c and repUS43 showed ST-specific associations with ST477 and 36 \nST16, respectively. MGEs such as  IS3, IS6, IS256, and  IS1380 co-localized with ARGs and 37 \nvirulence determinants. Phylogenomic analysis revealed two major lineages, with ST477 distributed 38 \nacross meat types and ST16 restricted to chicken. Comparative genomic analysis with publicly 39 \navailable African  E. faecalis  isolates revealed distinct clonal lineages and geographic clustering 40 \nacross the continent. Conclusion: The co-occurrence of multidrug resistance, virulence factors, and 41 \nMGEs in foodborne  E. faecalis poses a public health concern due to the risk of horizontal gene 42 \ntransfer and zoonotic spread. These findings underscore the need for genomic surveillance and 43 \nantimicrobial stewardship in food systems, particularly in low- and middle-income countries. 44 \n 45 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n3 \n \n1. Introduction 46 \nEnterococcus faecalis  is a commensal bacterium of the gastrointestinal tracts of humans and 47 \nanimals, yet it has emerged as a notable opportunistic pathogen, especially in healthcare settings 48 \nwhere multidrug -resistant (MDR) strains contribute to severe and difficult -to-treat infections 49 \n(Farman et al., 2019). Beyond clinical contexts, its presence in food system particularly in raw meats 50 \nraises significant concerns about its role in the dissemination of antimicrobial resistance genes 51 \n(ARGs) and virulence factors via the food chain (de Mesquita Souza Saraiva et al., 2022). The 52 \nspecies' adaptability is bolstered by its remarkable capacity to acquire and transfer mobile genetic 53 \nelements (MGEs), which facilitates horizontal gene transfer and complicates therapeutic strategies 54 \n(Hegstad et al., 2010). These characteristics collectively pose a dual threat to both food safety and 55 \npublic health, necessitating a comprehensive understanding of its genomic architecture across 56 \ndiverse ecological niches. 57 \nGlobally, genomic studies have examined the resistance mechanisms and genetic diversity 58 \nof E. faecalis across clinical, livestock, and environmental settings (Daniel et al., 2017; Guan et al., 59 \n2024). However, substantial gaps remain in low -resource regions where genomic surveillance of 60 \nfoodborne isolates is limited (Okeke et al., 2022). In Nigeria, retail meat is a dietary staple, yet little 61 \nis known about the genomic features of E. faecalis circulating in these products (Wada et al., 2020). 62 \nExisting research has largely focused on phenotypic antibiotic resistance (Ndahi et al., 2023), with 63 \nminimal exploration into the genetic determinants of resistance, virulence, and gene transfer that 64 \ncontribute to its pathogenic potential (Okeke et al., 2022). This is particularly concerning in a country 65 \nwhere antibiotic use in agriculture remains poorly regulated and surveillance infrastructure is still 66 \nevolving (Schnirring, 2023), potentially accelerating the emergence of MDR lineages. 67 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n4 \n \nThe public health implications of foodborne E. faecalis are further underscored by increasing 68 \nevidence of clonal transmission across animals, humans, and the environment (Monteiro Marques 69 \net al., 2023; Poulsen et al., 2012). Hospital-adapted lineages of E. faecalis have been shown to carry 70 \nMGEs conferring resistance to clinically critical antibiotics such as vancomycin and β -lactams, as 71 \nwell as virulence genes that promote biofilm formation, immune evasion, and tissue invasion (Raven 72 \net al., 2016; Hourigan et al., 2024). If food -derived strains harbor similar genomic traits, this could 73 \nsignal a critical interface between agricultural and clinical reservoirs, a hypothesis that remains 74 \nlargely untested in key distribution hubs such as Akungba -Akoko, a prominent meat market in 75 \nsouthwestern Nigeria (Alimi, 2013). 76 \nThis study addresses this knowledge gap by performing a comprehensive genomic 77 \ncharacterization of  E. faecalis  isolates recovered from retail meat in Akungba -Akoko. Utilizing 78 \nwhole-genome sequencing (WGS) and bioinformatics approaches, we aim to (1) assess the 79 \nprevalence and diversity of ARGs, including those conferring resistance to critically important 80 \nantimicrobials; (2) characterize virulence determinants associated with adhesion, biofilm formation, 81 \nand immune evasion; and (3) investigate the mobile genetic elements (MGEs) facilitating gene 82 \nexchange. These findings will contribute to our understanding of the genomic plasticity of  E. 83 \nfaecalis in Nigeria’s food systems and inform mitigation strategies to reduce the public health risks 84 \nposed by this emerging foodborne pathogen. 85 \n 86 \n2. Materials and methods 87 \n2.1. Sample collection and study site 88 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n5 \n \nThe study was carried out over a three-month period between April and June 2022: 50 samples of 89 \nraw retail meat, including chicken (n=18), beef (n=17), and turkey (n=15), from the Ibaka market 90 \n(7.473500° N, 5.736250° E) in Akungba Akoko, Nigeria. The Ibaka market is a rural periodic day 91 \nmarket located in Akoko, which is the host community of Adekunle Ajasin University.  92 \n2.2. Isolation and identification of Enterococcus faecalis isolates 93 \nIn the laboratory, each meat sample was aseptically homogenized. Smears of the homogenates were 94 \nprepared and subjected to Gram staining to identify gram -positive cocci arranged in pairs or short 95 \nchains, which are characteristic of  Enterococcus species. For bacterial isolation, aliquots of the 96 \nhomogenized samples were inoculated onto blood agar plates and incubated aerobically at 37°C for 97 \n24–48 hours. Colonies exhibiting typical  Enterococcus morphology were selected for further 98 \ntesting. Presumptive  Enterococcus isolates were identified on the basis of their Gram staining 99 \ncharacteristics and ability to grow on blood agar. Biochemical tests were performed to confirm that 100 \nthe isolates were Enterococcus species. These tests included the Voges‒Proskauer (VP) test for 101 \ndetecting acetoin production and the potassium tellurite (PT) test to assess the ability to reduce 102 \ntellurite. Additionally, fermentation tests for glucose, lactose, and sucrose were conducted to 103 \nevaluate the carbohydrate utilization profiles of the isolates. Staphylococcus aureus ATCC 29213 104 \nand E. faecalis ATCC 29212 served as negative and positive controls, respectively. Confirmed  E. 105 \nfaecalis isolates were preserved by storing them in brain heart infusion broth (Difco) supplemented 106 \nwith 20% glycerol at −70°C for long-term storage. 107 \n2.3. Antibiotic susceptibility testing of Enterococcus faecalis strains 108 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n6 \n \nThe antibiotic resistance profiles of  E. faecalis isolates were determined via the disk diffusion 109 \nmethod on Mueller‒Hinton agar (MHA), following the guidelines of the Clinical and Laboratory 110 \nStandards Institute (CLSI, 2023). Overnight cultures of the isolates were used to prepare bacterial 111 \nsuspensions adjusted to a turbidity equivalent to a 0.5 McFarland standard. A sterile cotton swab 112 \nwas dipped into each suspension and evenly streaked across the entire surface of the MHA plates to 113 \nensure a uniform bacterial lawn. Commercial antibiotic disks (Hi -Media, India) were placed onto 114 \nthe inoculated plates via sterile forceps. The antibiotics used and their corresponding disk 115 \nconcentrations were as follows: tetracycline (30 μg), chloramphenicol (30 μg), streptomycin (10 μg), 116 \nkanamycin (30 μg), erythromycin (15 μg), vancomycin (30 μg), clindamycin (2 μg), and tobramycin 117 \n(10 μg). The plates were incubated aerobically at 37 °C for 18 –24 hours. After incubation, the 118 \ndiameters of the inhibition zones around each antibiotic disk were measured in millimeters. 119 \nStaphylococcus aureus ATCC 25923 was used as the control. The results were interpreted according 120 \nto CLSI guidelines (CLSI, 2023), categorizing the isolates as susceptible, intermediate, or resistant 121 \nto each antibiotic tested. 122 \n2.4. DNA Extraction, Whole -Genome Sequencing, and Assembly  of Enterococcus 123 \nfaecium strains 124 \nGenomic DNA was extracted from E. faecalis isolates via the MasterPure™ Gram Positive DNA 125 \nPurification Kit (Lucigen, Middleton, WI, USA) according to the manufacturer's instructions. The 126 \nquality and concentration of the extracted DNA were assessed via a NanoDrop 1000 127 \nspectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The genomic DNA libraries 128 \nwere prepared via the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) 129 \nfollowing the manufacturer's protocol. Sequencing was performed on an Illumina NovaSeq 6000 130 \nsystem (Illumina, San Diego, CA, USA) to generate paired-end reads. The raw sequence reads were 131 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n7 \n \nassembled into contigs via the Shovill pipeline version 1.0.4, which incorporates Trimmomatic 132 \nversion 0.38  for read trimming and quality control. Genome annotation was conducted via Prokka 133 \nversion 1.13.3. 134 \n2.5. Identification of resistance genes, virulence genes, plasmids  and multi -locus 135 \nsequence typing 136 \nAntimicrobial resistance genes were identified via ResFinder version 4. 6.0 137 \n(http://genepi.food.dtu.dk/resfinder). Virulence genes were detected via VirulenceFinder version 2.0 138 \n(https://cge.food.dtu.dk/services/VirulenceFinder/). Plasmid types were determined by analysing the 139 \nassembled genome sequences with PlasmidFinder version 2.1 140 \n(https://cge.food.dtu.dk/services/PlasmidFinder/). Multilocus sequence typing (MLST) was 141 \nperformed via the MLST tool version 2.0  (https://cge.food.dtu.dk/services/MLST/)  to assign 142 \nsequence types to the E. faecalis isolates. 143 \n2.6. Phylogenomic analysis and metadata insights 144 \nThe de novo assembled contigs of the E. faecalis isolates were submitted to CSI Phylogeny version 145 \n1.4 ( https://cge.cbs.dtu.dk/services/CSIPhylogeny-1.4), an online tool that identifies single 146 \nnucleotide polymorphisms (SNPs) from whole-genome sequencing (WGS) data, filters and validates 147 \nSNP positions, and infers phylogeny on the basis of concatenated SNP profiles. The Enterococcus 148 \nfaecalis ATCC BAA-2128 strain (Accession number: NAQY00000000.1) was used as an outgroup 149 \nto root the tree, facilitating the assessment of phylogenetic relationships among the  E. 150 \nfaecalis strains. The phylogenetic tree was visualized and annotated with isolate metadata, including 151 \ndemographic information, sequence types, resistome profiles, and mobile genetic elements (MGE), 152 \nvia ITOL version 7 (https://itol.embl.de). This approach provided a comprehensive analysis of the 153 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n8 \n \nphylogenomic relationships among the isolates. Additionally, whole -genome sequences of  E. 154 \nfaecalis isolates from  Africa, curated from public databases such as PATRIC 155 \n(https://www.patricbrc.org/) and NCBI between 201 3 and 2023, were downloaded and included in 156 \nthe phylogenomic analysis to provide epidemiological and evolutionary context (Table S1). The 157 \ntrees were edited and visualized via FigTree version 1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/). 158 \nIsolates belonging to the same STs are highlighted with the same color, and isolates from the same 159 \ngeographical regions are labelled with the same text color to facilitate visual interpretation. 160 \n2.7. Nucleotide sequence 161 \nThe sequences of the E. faecalis strains analysed in this study were deposited in the National Center 162 \nfor Biotechnology Information GenBank database under BioProject number PRJNA928459. 163 \n 164 \n3. Results 165 \n3.1. Prevalence and Antibiotic Resistance Patterns of E. faecalis in Retail Meats 166 \nFrom the 50 retail meat samples analyzed, a total of 10  Enterococcus faecalis  isolates were 167 \nrecovered, corresponding to an overall prevalence of 20%. The isolates were unevenly distributed 168 \namong the meat types: chicken accounted for the highest number of isolates (n=6, 60%), followed 169 \nby beef (n=2, 20%) and turkey (n=2, 20%). Antimicrobial susceptibility testing revealed consistent 170 \nresistance profiles across the isolates. All strains exhibited complete resistance (100%) to 171 \nclindamycin, erythromycin, and tetracycline, antibiotics commonly used in veterinary and clinical 172 \nsettings. Moderate resistance was observed against streptomycin (80%), and tobramycin (80%). In 173 \ncontrast, resistance to chloramphenicol was comparatively lower (20%), and no resistance to 174 \nvancomycin was detected among any of the isolates. The distribution and co-occurrence of resistance 175 \nphenotypes are illustrated in Figure 1 using an Upset plot.  176 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n9 \n \n 177 \nFigure 1. The Upset plot illustrates the distribution of antimicrobial resistance patterns across the  178 \nisolates. The top bar chart quantifies unique combinations of antibiotic resistance among the isolates, 179 \nwhile the horizontal bar chart on the left shows the number of isolates resistant to individual 180 \nantibiotics. Co -resistance to clindamycin, erythromycin, tetracycline, and aminoglycosides 181 \n(streptomycin and tobramycin) was common. Vancomycin was excluded from the visualization due 182 \nto the absence of resistance. The arrangement highlights both dominant and infrequent co-resistance 183 \nprofiles across the dataset. 184 \n3.2. ARG profiles and mobile genetic elements 185 \nGenomic analysis identified a diverse repertoire of antimicrobial resistance genes (ARGs) among 186 \nthe E. faecalis isolates, many of which confer resistance to critically important antimicrobials. The 187 \nmost frequently detected ARGs included  aac(6’)-aph(2’’) and ant(6)-Ia (aminoglycoside 188 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n10 \n \nresistance), lsa(A) (lincosamide resistance),  erm(B) (macrolide resistance), 189 \nand tet(M) and tet(L) (tetracycline resistance). Notably,  dfrG (trimethoprim resistance) and  catA8 190 \n(chloramphenicol resistance) were detected exclusively in two isolates recovered from retail 191 \nchicken, suggesting lineage-specific acquisition or exposure to unique selective pressures.  192 \nAcross meat sources, the core resistome was largely conserved; however, isolates NigeriaC1 193 \nand NigeriaC11 (from chicken) harbored a broader range of ARGs, reflecting potential differential 194 \nantibiotic exposure in poultry production systems (Table 1). Analysis of mobile genetic elements 195 \n(MGEs) revealed lineage - and source-specific patterns. The plasmid replicon  rep9cwas the most 196 \nprevalent, detected in all isolates regardless of meat source and consistently associated with sequence 197 \ntype ST477. Conversely,  repUS43 was uniquely found in ST16 isolates from retail chicken, 198 \nindicating a possible plasmid-lineage specificity. 199 \nInsertion sequences (ISs) played a prominent role in the resistome architecture. The IS6 200 \nfamily was frequently identified in ST477 isolates from all meat types. A unique combination of IS 201 \nelements; IS3, IS6, IS110, IS256, and  IS1380 was observed only in ST16 isolates, co -localized 202 \nwith dfrG and catA8.  Further analysis showed identified a resistance gene cassette 203 \ncomprising aac(6’)-aph(2’’), ant(6)-Ia, and tet(M) embedded within a genomic region enriched with 204 \nmobile genetic elements, including  IS1380 and IS6 family transposases, as well as plasmid 205 \nrecombinase family proteins (Figure 2). 206 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n11 \n \n 207 \nFigure 2. Circular genomic annotation of the genetic cassette carrying resistance genes 208 \nin Enterococcus faecalis  isolate NigeriaC2. This figure presents a visualization of the genomic 209 \nregion containing resistance determinants  aac(6’)-aph(2’’), ant(6)-Ia, and tet(M) in isolate 210 \nNigeriaC2 (Accession number: JAQOOR010000014). The annotation highlights the relative 211 \npositioning and orientation of these resistance genes alongside associated mobile genetic elements, 212 \nincluding IS1380 transposase, IS6 family transposase, and plasmid recombinase family proteins. 213 \nGenes are color -coded, with green representing resistance genes and regulatory elements, while 214 \nyellow indicates protein-coding sequences (CDS). Arrows denote the transcriptional orientation of 215 \nindividual genes, providing insights into their synteny and potential functional interactions within 216 \nthe genomic context. 217 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n12 \n \nTable 1: Genomic and Phenotypic Characteristics of E. faecalis Isolates 218 \n 219 \n220 Isolate ID Isolation \nSource \nAntibiogram Resistance Genes Insertion Sequences Plasmid \nreplicons \nMLST Virulence Factors \nNigeriaB142 Beef STP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, camE, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaB242 Beef STP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, came, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaC1 Retailed \nChicken \nTET-ERY-CLI-CHL lsa(A), erm(B), catA8, \ntet(M), dfrG \nIS3, IS6, IS110, IS256, \nIS1380 \nrepUS43 ST16 ElrA, SrtA, ace, agg, cCF10, cOB1, cad, came, cylA, \ncylB, cylL, cylM, ebpA, ebpB, ebpC, efaAfs, hylA, tpx \nNigeriaC11 Retailed \nChicken \nTET-ERY-CLI-CHL lsa(A), erm(B), catA8, \ntet(M), dfrG \nIS3, IS6, IS110, IS256, \nIS1380 \nrepUS43 ST16 ElrA, SrtA, ace, agg, cCF10, cOB1, cad, came, cylA, \ncylB, cylL, cylM, ebpA, ebpB, ebpC, efaAfs, hylA, tpx \nNigeriaC2 Retailed \nChicken \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, camE, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaC24 Retailed \nChicken \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, came, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaC242 Retailed \nChicken \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, came, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaC243 Retailed \nChicken \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, camE, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaT23 Retailed \nTurkey \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, camE, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \nNigeriaT44 Retailed \nTurkey \nSTP-TOB-TET-\nERY-CLI \naac(6’)-aph(2’’), ant(6)-Ia, \nlsa(A), erm(B), tet(M), tet(L) \nIS6 rep9c ST477 ElrA, SrtA, ace, cCF10, cOB1, cad, camE, ebpA, \nebpB, ebpC, efaAfs, fsrB, gelE, hylB, tpx \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n13 \n \n3.3. Virulence factors, sequence types and phylogenetic insights 221 \nGenome analysis revealed that  E. faecalis  isolates harbored an extensive repertoire of virulence 222 \nfactors associated with colonization, tissue invasion, and immune evasion. Conserved genes across 223 \nall isolates included  ace (collagen adhesion),  efaAfs (endocarditis 224 \nantigen), ElrA (adhesion), SrtA (anchoring protein), and the biofilm -associated pili 225 \ngenes ebpA, ebpB, and  ebpC. Additionally, all isolates carried  cCF10 and cOB1, encoding 226 \naggregation substances that enhance horizontal gene transfer and biofilm development. 227 \nThe distribution of virulence genes displayed clear sequence type (ST) -specific patterns. 228 \nST477, the most prevalent lineage, was recovered from beef, chicken, and turkey, and consistently 229 \ncarried fsrB, gelE (gelatinase), and  hylB (hyaluronidase), key factors implicated in biofilm 230 \nformation, extracellular matrix degradation, and immune modulation. In contrast, ST16 isolates 231 \n(NigeriaC1 and NigeriaC11), found exclusively in chicken, exhibited a distinct virulence profile. 232 \nThese isolates harbored agg, cylA, cylB, cylL, and cylM genes encoding the cytolysin toxin complex, 233 \nwhich contributes to tissue damage and enhanced pathogenicity. ST16 also possessed  hylA, an 234 \nalternative hyaluronidase variant, and camE (calcium-binding protein). 235 \nPlasmid replicons showed strong lineage associations.  rep9c was universally detected in 236 \nST477 isolates and co -occurred with the  fsrB–gelE–hylB virulence gene set. 237 \nConversely, repUS43 was exclusive to ST16 and linked to the presence of cytolysin genes and hylA. 238 \nInsertion sequences (ISs) were also associated with virulence profiles. ST477 isolates commonly 239 \ncarried IS6, while ST16 harbored a broader array of MGEs, including IS3, IS110, IS256, and IS1380, 240 \npossibly facilitating mobilization of cytolysin and adhesion genes. Phylogenetic reconstruction using 241 \nSNP-based analysis revealed two well -defined clades corresponding to ST16 and ST477 lineages 242 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n14 \n \n(Figure 3). ST16 isolates clustered together and were uniquely associated with poultry, distinct 243 \nARGs, and virulence factors. ST477 formed a separate, more diverse clade encompassing isolates 244 \nfrom all meat types and displaying a conserved resistome-virulome profile. 245 \n 246 \nFigure 3: SNP-based maximum likelihood tree showing phylogenetic relationships among E. 247 \nfaecium isolates recovered from retail meat. The tree illustrates two main clades, each linked to 248 \nspecific sequence types (STs) and genomic characteristics. Annotations highlight key genomic 249 \nfeatures, including STs, isolation sources, resistance genes, plasmid replicons, and insertion 250 \nsequences. Isolates are visually distinguished by color -coded boxes, indicating their distribution 251 \nacross different meat sources. 252 \n3.4. Comparative phylogenomic analysis and  metadata insights of  E. faecalis isolates 253 \nfrom Africa 254 \nTo contextualize the Nigerian E. faecalis isolates within broader regional dynamics, we conducted 255 \na comparative phylogenomic analysis of 149 publicly available African genomes collected between 256 \n2013 and 2023. South Africa contributed the highest number of isolates (n=60), followed by 257 \nTanzania (n=33) and Ghana (n=20), reflecting the uneven distribution of genomic surveillance 258 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n15 \n \nefforts across the continent. Nigeria, the focus of this study, accounted for 10 isolates, while 259 \nCameroon, Zimbabwe, Tunisia, and Egypt contributed fewer (Figures 4 and 5a). 260 \nTemporally, most isolates were obtained between 2017 and 2021, with peaks in 2017 (n=42) 261 \nand 2021 (n=57). Earlier years (2013–2016) were underrepresented, limiting historical comparisons 262 \nbut indicating a growing interest in enterococcal genomics in recent years (Figure 5b). Sequence 263 \ntype analysis identified 47 distinct STs across the dataset, with both shared and country -specific 264 \nlineages. ST16 was the most widely distributed, detected in South Africa, Tanzania, Cameroon, and 265 \nGhana (Figure 5c). In contrast, ST477 found exclusively in the current Nigerian isolates  appeared 266 \ngeographically restricted. Other notable country -specific lineages included ST21 (Tunisia and 267 \nEgypt) and ST646 (South Africa).  A network analysis of the top 10 STs and their country 268 \nassociations (Figure 5d) further illustrated these patterns. South Africa and Tanzania exhibited the 269 \nhighest ST diversity, with multiple connections to ST6, ST16, and ST646 (Figure 5d).  270 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n16 \n \n 271 \nFigure 4. Maximum likelihood phylogenetic tree of  Enterococcus faecalis isolates from African 272 \ncountries (2013 –2023). A core -genome phylogenetic tree was constructed from 149  E. 273 \nfaecalis genomes retrieved from BV -BRC and annotated using iTOL. The tree is rooted using  E. 274 \nfaecalis ATCC BAA-2128 (Accession: NAQY00000000.1) as the reference genome. The outer ring 275 \nrepresents the sequence type (ST), the middle ring denotes the  year of isolation, and the inner ring 276 \ndisplays the country of origin . The phylogeny illustrates both temporal and geographic diversity 277 \nof E. faecalis across the African continent. 278 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n17 \n \n279 \nFigure 5. (a) Geographic distribution of E. faecalis isolates across Africa. A bar chart illustrating 280 \nthe number of  E. faecalis isolates obtained from different African countries. (b) Temporal trends 281 \nin E. faecalis  isolations across Africa.  A bar chart depicting the number of  E. faecalis  isolates 282 \ncollected per year from 2013 to 2023. (c) Distribution of major sequence types ( STs) among 283 \nAfrican E. faecalis Isolates. A stacked bar chart showing the distribution of the most prevalent STs 284 \nacross different African countries. (d) A network graph visualizing relationships between African 285 \ncountries and their associated  E. faecalis  STs. Nodes represent countries and  STs, with edges 286 \nindicating connections based on isolate presence.  287 \n 288 \n4. Discussion 289 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n18 \n \nThe presence of E. faecalis in retail meats highlights the potential role of foodborne transmission in 290 \nthe dissemination of AMR (Conceição et al, 2023). Consistent with previous reports, chicken meat 291 \nyielded the highest recovery rate of  E. faecalis , reinforcing its role as a major reservoir for 292 \nenterococci in food systems (Hayes et al., 2003; Aslam et al., 2012). Although not a classical 293 \nfoodborne pathogen, the species’ capacity to horizontally transfer resistance genes within the human 294 \ngut microbiota elevates its public health significance (Krawczyk et al., 2021). These findings support 295 \ncalls for strengthened hygiene protocols and antimicrobial stewardship in poultry production, a 296 \nsector characterized by intensive antimicrobial use (Conceição et al., 2023). 297 \nAll isolates exhibited resistance to clindamycin, erythromycin, and tetracycline  mirroring 298 \nglobal resistance trends and suggesting sustained selection pressure from widespread use of these 299 \nagents in animal husbandry (Arias & Murray, 2012; Lebreton et al., 2014; Landers et al., 2012). The 300 \nabsence of vancomycin resistance is encouraging; however, the species’ genomic flexibility raises 301 \nconcerns about future acquisition through horizontal gene transfer (van Hal et al., 2016). The 302 \ndetection of  catA8 among chicken isolates, despite the relatively low phenotypic resistance to 303 \nchloramphenicol, signals the emergence of latent resistance and highlights the risk of resurgence 304 \n(Bae et al., 2021). These findings reinforce the critical need for integrated AMR surveillance across 305 \nfood and clinical sectors, especially in high-burden regions (WHO, 2019). 306 \nGenomic analysis revealed a consistent resistome dominated by  aac(6')-aph(2''), ant(6)-307 \nIa, lsa(A), erm(B), tet(M), and  tet(L) conferring resistance to aminoglycosides, macrolides, 308 \nlincosamides, and tetracyclines. These genes, conserved across meat types and lineages, mirror 309 \nglobally recognized resistance profiles and likely reflect co -selection pressures exerted by 310 \nagricultural antibiotic use (Hegstad et al., 2010). Of particular note,  dfrG and catA8 were confined 311 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n19 \n \nto ST16 isolates from chicken, suggesting lineage-specific resistance acquisition possibly driven by 312 \npoultry-associated selective environments (Kristich et al., 2014). These resistance determinants were 313 \nnot randomly distributed but instead embedded within complex mobile genetic architectures. A 314 \nmultidrug resistance gene cassette co-localizing aac(6’)-aph(2’'), ant(6)-Ia, and tet(M) was detected 315 \nwithin a genomic region enriched with IS6 and IS1380 transposases and plasmid recombinase genes, 316 \nforming a transferable module capable of en bloc dissemination of resistance traits. Such modularity 317 \nenhances the potential for inter -species gene flow, especially within gut microbiota of exposed 318 \nconsumers (Hegstad et al., 2010). 319 \nPlasmid replicons further delineated lineage -specific resistance pathways. The 320 \nwidespread rep9c replicon, present in all ST477 isolates, was consistently co-located with the fsrB–321 \ngelE–hylB virulence cluster, suggesting clonal expansion and vertical maintenance of resistance –322 \nvirulence hybrids (Willems et al., 2012). In contrast,  repUS43 was exclusive to ST16 isolates, co -323 \noccurring with  catA8 and dfrG, reinforcing its role in ST -specific resistance dissemination (van 324 \nSchaik et al., 2010). The structural linkage between plasmid types, insertion sequences, and ARGs 325 \nunderscores the dynamic interplay of vertical inheritance and horizontal transfer in shaping the 326 \nresistome of E. faecalis. Insertion sequences (IS3, IS6, IS110, IS256, and IS1380) were found at 327 \nmultiple resistance loci and appear to drive genomic fluidity by facilitating recombination and gene 328 \nmobilization. Their lineage -specific distribution highlights ongoing adaptive evolution under 329 \nantimicrobial pressure. These findings illustrate a highly structured yet flexible resistance landscape 330 \nin foodborne  E. faecalis , propelled by mobile elements and reinforced by selective agricultural 331 \npractices. 332 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n20 \n \nThe widespread detection of virulence genes among  E. faecalis isolates from retail meats 333 \nreveals a pathogenic potential far beyond commensal behavior. Conserved adhesion  factors 334 \nincluding ace, efaAfs, ElrA, SrtA, and the  ebp operon (ebpA, ebpB, ebpC) were uniformly present, 335 \nunderscoring a baseline capacity for epithelial colonization, biofilm formation, and immune 336 \nmodulation (Nallapareddy et al., 2006; Șchiopu et al., 2023). The concurrent presence of conjugative 337 \nfactors ( cCF10, cOB1) suggests an additional role in promoting gene exchange within host or 338 \nenvironmental niches, facilitating co-selection and persistence of resistance–virulence traits. 339 \nLineage-specific virulence signatures were particularly striking. ST477 isolates  recovered 340 \nfrom beef, chicken, and turkey  harbored the  fsrB–gelE–hylB cluster, a constellation of genes 341 \nassociated with quorum sensing, extracellular matrix degradation, and immune evasion, previously 342 \nlinked to device- and bloodstream-associated infections (Van Tyne et al., 2013; Johnson et al., 2024). 343 \nThis combination of biofilm -promoting and immunomodulatory functions positions ST477 as a 344 \nhigh-risk foodborne lineage with potential for clinical crossover.  In contrast, ST16 isolates  345 \nexclusively from chicken exhibited an enhanced virulence profile characterized by cytolysin operon 346 \ngenes ( cylA, cylB, cylL, cylM) and  hylA, features associated with epithelial disruption and pro -347 \ninflammatory host responses (Zheng et al., 2017). Notably, these isolates also carried agg, a plasmid-348 \nborne aggregation substance linked to increased virulence and conjugation efficiency. The co -349 \noccurrence of repUS43 with this virulence suite suggests a plasmid-mediated mechanism facilitating 350 \nthe emergence of hypervirulent clones. 351 \nThe convergence of resistance and virulence within specific plasmid backgrounds and 352 \nsequence types  especially ST16 and ST477  raises substantial public health concerns. Mobile 353 \nelements, including IS3, IS110, IS256, and IS1380, were frequently associated with virulence loci, 354 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n21 \n \nfurther implicating horizontal gene transfer in the amplification of pathogenic potential. These 355 \nfindings parallel global reports of virulence -enriched E. faecalis STs and affirm their relevance in 356 \nzoonotic transmission and foodborne disease (McBride et al., 2007; Fiore et al., 2019).  In this 357 \ncontext, foodborne  E. faecalis  strains function not only as reservoirs of resistance but also as 358 \npotential vectors for invasive disease, particularly in immunocompromised hosts. Their emergence 359 \nin the food chain paired with genomic signatures linked to hospital-adapted strains underscores the 360 \nurgency of a One Health surveillance framework integrating food safety, environmental monitoring, 361 \nand clinical microbiology. 362 \nComparative phylogenomics of E. faecalis isolates across Africa uncovered a geographically 363 \nstructured but genetically diverse population. South Africa  contributed the highest number of 364 \nisolates an observation likely shaped by differences in surveillance capacity, sequencing 365 \ninfrastructure, and public health prioritization. The scarcity of isolates from earlier years (2013 –366 \n2016) and the sharp rise in submissions post-2017, interrupted briefly by the COVID-19 pandemic, 367 \nreflect both historical data gaps and the growing momentum of genomics -based AMR monitoring 368 \non the continent (Baker et al., 2023; Kajumbula et al., 2024; Tegally et al., 2022). 369 \nTemporal and geographic analyses revealed that sequence type ST16 was the most broadly 370 \ndistributed, identified in multiple countries and across diverse ecological contexts, suggesting a well-371 \nadapted and potentially mobile lineage (Zaheer et al., 2020; Monteiro Marques et al., 2023). Its 372 \nwidespread detection aligns with prior observations of ST16’s capacity for environmental 373 \npersistence and inter -host transmission. In contrast, ST477 was restricted to Nigeria, while ST21 374 \nwas confined to Tunisia and Egypt, implying localized evolutionary trajectories shaped by selective 375 \npressures such as antimicrobial usage patterns, ecological boundaries, and food production systems 376 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n22 \n \n(Baquero et al., 2021; Bottery et al., 2021).  Network-based analysis reinforced these findings by 377 \nrevealing distinct ST -country associations, with South Africa and Tanzania exhibiting the highest 378 \nsequence type diversity. These clusters suggest transboundary transmission possibly facilitated by 379 \ntrade, food import/export routes, or shared agricultural practices (Tatem et al., 2006; Salem et al., 380 \n2023). Conversely, the geographic confinement of ST477 to Nigeria raises concerns about the 381 \nemergence of a potentially endemic, foodborne high-risk clone with a stable resistome and virulome 382 \nsignature. 383 \nThese patterns support a dual model of E. faecalis evolution in Africa: one shaped by clonal 384 \nexpansion of regionally successful lineages, and another driven by horizontal gene transfer across 385 \nenvironmental and host reservoirs. This genomic duality complicates control efforts and underscores 386 \nthe need for longitudinal, cross-sectoral surveillance. The convergence of clinically relevant traits in 387 \nisolates recovered from food reinforces the risk of zoonotic spill -over, particularly in settings with 388 \nlimited food safety regulation and AMR control.  In light of these findings, a coordinated genomic 389 \nsurveillance strategy that integrates human, animal, and environmental health  guided by the One 390 \nHealth framework is essential for tracking the emergence, evolution, and dissemination of high -391 \nrisk E. faecalis clones in Africa. This study, while limited by its modest sample size and geographic 392 \nscope, contributes a critical dataset to the continental AMR landscape and provides a foundation for 393 \nfuture longitudinal studies on  E. faecalis  as a foodborne pathogen of increasing public health 394 \nconcern. 395 \n 396 \nConclusion  397 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n23 \n \nThis study provides critical genomic insights into the antimicrobial resistance and virulence 398 \nlandscape of Enterococcus faecalis isolates recovered from retail meats in Nigeria, underscoring the 399 \nrole of food systems as reservoirs and potential amplifiers of clinically relevant pathogens. The 400 \nidentification of high -risk lineages such as ST477 and ST16 harboring multidrug resistance 401 \ndeterminants, virulence genes, and mobile genetic elements highlights the convergence of resistance 402 \nand pathogenicity within the food chain. The presence of plasmid -encoded resistance –virulence 403 \nmodules and the widespread occurrence of insertion sequences suggest an active mobilome 404 \nfacilitating gene exchange and adaptation across ecological boundaries. Comparative phylogenomic 405 \nanalysis across Africa revealed geographically structured transmission dynamics, marked by the 406 \nemergence of regionally dominant clones and country -specific evolutionary trajectories. These 407 \nfindings reflect broader challenges in AMR control, particularly in low - and middle -income 408 \ncountries where food safety infrastructure and genomic surveillance remain limited.  409 \nTo mitigate the growing threat of foodborne antimicrobial resistance, we advocate for 410 \nenhanced genomic monitoring of foodborne pathogens, stringent regulation of antimicrobial use in 411 \nagriculture, and integration of One Health strategies across the human –animal–environment 412 \ninterface. The insights presented here serve as a foundation for future regional surveillance initiatives 413 \nand emphasize the need for proactive, genomics-informed interventions to safeguard public health. 414 \n 415 \nDeclarations 416 \nFunding: This research received no specific grant from any funding agency in the public, 417 \ncommercial, or not-for-profit sectors. 418 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted April 16, 2025. ; https://doi.org/10.1101/2025.04.15.648955doi: bioRxiv preprint \n\n24 \n \nConflicts of Interest: The authors declare no competing interests. 419 \nEthics Approval: Institutional approval for the study protocol and sampling approach was granted 420 \nby the Department of Microbiology, Adekunle Ajasin University (Approval Reference: 421 \nDM:AAU/2021). All meat samples were obtained from open retail markets in Akungba -Akoko, 422 \nNigeria, and were purchased anonymously as part of routine food supply, without involving live 423 \nanimals or interventions. The objectives of the study were clearly explained to meat vendors to 424 \nensure transparency and voluntary participation in the sampling process. 425 \nClinical Trial: Not applicable 426 \n 427 \nData Availability 428 \nThe s equence data that support the findings of this study has been deposited in GenBank and 429 \nassigned accession numbers under BioProject PRJNA928459. All other data supporting this study 430 \nfindings are available within the manuscript and supplementary material. 431 \n 432 \nReferences  433 \n1. Alimi, R. S. (2013). An analysis of meat demand in Akungba-Akoko, Nigeria. Nigerian 434 \nJournal of Applied Behavioural Sciences, 1, 96–104. 435 \n2. Arias, C. A., & Murray, B. E. (2012). The rise of the Enterococcus: beyond vancomycin 436 \nresistance. Nature Reviews Microbiology, 10, 266–278. 437 \n3. Aslam, M., Diarra, M. S., Checkley, S., Bohaychuk, V., & Masson, L. 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