Molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemases-producing Escherichia coli and Klebsiella spp., isolated from human, animal, environment, and drinking water in Burkina Faso

Molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemases-producing Escherichia coli and Klebsiella spp., isolated from human, animal, environment, and drinking water in Burkina Faso | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemases-producing Escherichia coli and Klebsiella spp., isolated from human, animal, environment, and drinking water in Burkina Faso Djifahamaï Soma, Fatimata B.J. Diarra, Namwin Siourimè Somda, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8961524/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 Antimicrobial resistance (AMR) poses a significant threat to global public health. Escherichia coli ( E. coli ) and Klebsiella species are currently considered as key contributors to AMR and it spread. The objective of this study was to investigate the molecular epidemiology of ESBL, AmpC-β-lactamase and carbapenemase-encoding genes in E. coli and Klebsiella isolated from animal, human, environmental and drinking water sources. E. coli and Klebsiella were isolated from a several samples sources, including humans, animals, soil, and drinking water. Molecular techniques, such as PCR, were utilised for the detection of ESBL, AmpC-β-lactamase, and carbapenemase encoding genes detection. Subsequently, resistance profiles were analysed, and a heatmap analysis and hierarchical clustering were performed to assess the relationship between genotypic and phenotypic resistance profiles using R software. Amongst 215 ESBL isolates (90.7% gene-positive), bla CTX−M was the most prevalent gene, with a predominance in cattle ( E. coli : 67.7%, Klebsiella spp.: 20.6%). Sapone exhibited the highest prevalence of bla CTX−M (56.3%) and triple-gene combinations (21.8%). The cluster analysis revealed two key findings: the presence of cattle-specific Klebsiella spp. and the interspecies clusters. Positive and negative correlations between bla CTX−M and cefotaxime resistance (r = 0.48) and nalidixic acid susceptibility (r=-0.35) respectively was observed. Bla IMP, bla KPC, bla OXA−48 and bla DHA were detected with a prevalence not exceeded 1.52%. This study highlighted bla CTX−M and bla TEM as the most prevalent ESBL E. coli and Klebsiella -producing found in various samples. Low prevalence of AmpC-β-lactamase, and carbapenemase encoding genes were observed. These findings emphasise the critical role of livestock farming, environmental contamination, and horizontal gene transfer in the spread of antimicrobial resistance. In view of these results, ongoing One Health approach should focus on antimicrobial stewardship, environmental monitoring, and improved veterinary and healthcare practices. Epidemiology ESBL AmpC-β-lactamase carbapenemases Escherichia coli Klebsiella human animal environment Burkina Faso Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The emergence and global spread of antimicrobial resistance (AMR) constitutes a systemic health crisis, threatening the effectiveness of modern anti-infective therapies. Among the most critical threats identified by the World Health Organisation (WHO), enterobacteria resistant to third-generation cephalosporins and carbapenems are a top priority [ 1 , 2 ]. This resistance is mainly mediated by the production of extended-spectrum β-lactamases (ESBLs), AmpC-type β-lactamases and, more alarmingly, carbapenemases [ 3 ]. The latter, including metallo-β-lactamases (VIM, NDM) and serine carbapenemases (KPC, OXA-48), hydrolyse almost all β-lactams, including carbapenems, which are the last resort molecules in hospitals [ 4 , 5 ]. Historically, resistance genes such as bla TEM and bla SHV dominated the molecular landscape, but the last decade has been marked by the pandemic expansion of the bla CTX−M genotype, particularly the CTX-M-15 variant [ 6 ]. The persistence of these genetic determinants is facilitated by their location on mobile genetic elements (MGEs), such as high-conjugation plasmids, integrons and transposons, which facilitate horizontal gene transfer (HGT) between commensal and pathogenic bacterial species [ 7 , 8 ]. This genetic dynamism allows resistance to circulate freely beyond hospital boundaries, infiltrating agricultural and environmental ecosystems [ 9 ]. Within the framework of the One Health paradigm, it is now accepted that the interface between humans, animals and their shared environment is the main driver of AMR evolution [ 10 ]. In sub-Saharan Africa, and particularly in Burkina Faso, pastoral and semi-intensive livestock farming plays a central role in the national economy. However, the intensive and often unsupervised use of antimicrobials as growth promoters or prophylactics induces constant selection pressure within the intestinal microbiota of livestock [ 11 , 12 ]. Animal waste, rich in multidrug-resistant (MDR) bacteria, contaminates soil and water resources, creating routes of transmission to human populations via the food chain or direct contact [ 13 , 14 ]. In Burkina Faso, data on the prevalence of BLSE, AmpC and, above all, carbapenemase genes in non-clinical sectors remain insufficient to accurately map the risks of zoonotic transfer. Furthermore, the influence of agro-ecological variations and livestock farming systems on the diversity of circulating clones remains poorly understood. This study aims to provide a comprehensive surveillance data on the prevalence and molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemase-producing E. coli and Klebsiella spp. in Burkina Faso. By isolating these pathogens from a variety of sources, including animals, humans, environmental samples, and drinking water, this study will examine the distribution of resistance genes, explore potential transmission routes, and analyse the genetic mechanisms responsible for these resistance profiles. The molecular characterization of these pathogens will also offer insights into the genetic diversity and potential clonal spread of these resistant strains in Burkina Faso. Materials and methods ESBL, AmpC-β-lactamase and carbapenemase (CP)-producing E. coli and Klebsiella spp. detection The data collection and sampling phase spanned from May 2018 to May 2021. This longitudinal study period covered several seasonal cycles, ensuring an in-depth analysis of the persistence and circulation dynamics of resistance genes within the 39 semi-intensive farms and 28 traditional farms in the peri-urban area of Ouagadougou. It should be noted that the methodology employed in the sampling, bacterial isolation and identification, antibiotic sensitivity testing, phenotypic detection of ESBL production, and the total number of samples utilised for the isolation of these strains has been previously documented in a published article [ 15 ]. A total of 215 CHROMagar positive, including ESBL-producing presumptive E. coli (122) and Klebsiella spp. (79) isolates were confirmed by antimicrobial susceptibility test (AST). Indeed, these isolates were screened for genetic element determinants of ESBL ( bla CTX−M , bla SHV , bla TEM ). All isolates with a meropenem inhibition zone diameter less than 22 mm (≤ 22 mm) in the AST were investigated for potential production of carbapenemases ( bla KPC , bla NDM , bla OXA_48 , bla VIM and bla IMP ). Morever, all isolates with a cefoxitin inhibition zone diameter less than 18 mm (≤ 18 mm) were presumed as AmpC-β-lactamase producers according to CLSI guideline [ 16 ]. Three multiplex polymerase chain reaction (PCR) were used to screening ESBL, carbapenemases and AmpC-β-lactamase encoding genes. Additional file 1 shows set of specific primers used for the detection of ESBL, carbapenemase and AmpC-β-lactamase genes. DNA extraction The DNA was extracted from all 215 fresh colony samples by the boiling method as descripbed by Seman et al . [ 17 ] with some modification. Briefly, 3 to 4 bacterial colonies were suspended in 600 µl of nuclease-free water. This suspension was then homogenised and subjected to heat shock at 100°C for 10 minutes, followed by cooling to room temperature for 15 minutes. After centrifugation at 18,000 g for 10 minutes at 4°C, a volume of 300 µl of the supernatant was removed and transferred to a sterile Eppendorf tube before being stored at -20°C until analysis. Detection of ESBL, carbapenemase and AmpC-β-lactamase associated genes by PCR ESBL, carbapenemase and AmpC-β-lactamase resistance genes were detected using conventional polymerase chain reaction (PCR). Three multiplex PCR assays were performed in a Bio-Rad T100 thermal cycler to screen for ESBL, AmpC-β-lactamase and carbapenemases encoding genes screening. Additional file 2 provides a summary of the PCR conditions and thermal cycling parameters used. Once the PCR was complete, 10 µl of each amplicon were deposited in the wells on the agarose gel (1.5%) contained in a 0.5X TBE migration buffer) starting from the bottom to the top. A 100 bp molecular weight marker (Hyper Ladder1, Bioline) was used to evaluate the size of the different genes. Electrophoresis was carried out at 220 V and 300 mA using a voltage generator for 25 minutes to ensure complete separation of the bands. Following electrophoresis, the gels were visualized using a GelDoc Go imaging system (Bio-Rad). Statistical analysis The data were collected and processed using Microsoft Excel 2016 (Microsoft Office, Washington, USA). A correlation analysis was performed to determine the association between the antimicrobial resistance genes and phenotypic antimicrobial resistances among the isolates. The resistance phenotypes and genotypes results were converted into binary data (0/1); the absence of resistance genes or susceptibility to antimicrobials had scores of 0, while the presence of a resistance gene or resistance to antimicrobials received scores of 1. Binary data were imported into R software (version R software version 4.2.2.); with the “corrplot” package, the correlations were determined at a significance of p < 0.05 using the functions “cor” and “cor.mtest”. A heatmap with hierarchical clustering was also generated using the R packages “heatmap”, ggplot2, reshape2 and “colorRampPalette”, in order to cluster the examined isolates based on their phenotypic and genotypic resistance profile. Results Distribution of ESBL, AmpC-β-lactamase and carbapenemases encoding genes in E. coli and Klebsiella spp. across hnimal, human, environmental, and drinking water samples in Burkina Faso A total of 215 phenotypically confirmed ESBL samples were amplified to confirm the presence of genes encoding ESBL. Of these, 195 (90.7%) harboured at least one ESBL-encoding gene. In this study, the prevalence of bla CTX−M and bla TEM in both E. coli and Klebsiella spp. considerably varied among sample types, and particularly highest in animal samples. For E. coli , bla CTX−M (67.65%) and bla TEM (61.76%) were the most common detected, while bla KPC , bla IMP , bla OXA_48 , and bla DHA were not detected. In human samples, the prevalence of bla CTX−M and bla TEM was 35% and 26.67% respectively; however, bla KPC , bla IMP , and bla OXA_48 were not detected. Soil and drinking water samples showed moderate to low levels of bla CTX−M and bla TEM , and none of the other resistance genes ( bla KPC , bla IMP , bla OXA_48 , bla DHA ) were found in these environmental sources (Table 1). For Klebsiella spp., the results mirrored those of E. coli , with bla CTX−M (20.59%) and bla TEM (19.12%) being the most prevalent in animal samples. No bla KPC , bla IMP , or bla OXA_48 genes were detected in any of the samples. Soil and drinking water samples showed similar trends, with higher prevalence in drinking water for bla CTX−M (25.76%) and bla TEM (21.21%). The bla OXA_48 gene was detected at 1.52% in the drinking water samples, whereas bla KPC and bla IMP were absent (Table 1). Table 1 . Distribution of ESBL, AmpC-β-lactamase and carbapenemases encoding genes. Positive Isolates Samples Types (N) ESBL Positive samples a (%) bla CTX−M b (%) bla TEM b (%) bla SHV b (%) bla CTX−M+ bla TEM+ bla SHV b (%) bla CTX - M+ bla TEM b (%) bla CTX−M+ bla SHV b (%) bla TEM+ bla SHV b (%) bla DHA b (%) bla KPC b (%) bla IMP b (%) bla OXA_48 b (%) E. coli (n = 122) Animal (68) 47(69.11) 46(67.65) 42(61.76) 9(13.23) 3(4.41) 41(60.29) 8(11.76) 4(5.88) 0(0) 0(0) 1(1.47) 0(0) Human (120) 45(37.50) 42(35) 32(26.67) 14(11.67) 5(4.17) 30(25) 13(10.83) 5(4.17) 0(0) 0(0) 0(0) 0(0) Soil (68) 28(41.18) 22(32.36) 25(36.76) 3(4.41) 0(0.0) 19(27.94) 1(1.47) 2(2.94) 0(0) 0(0) 1(1.47) 1(1.47) Drinking water (66) 2(3.03) 2(3.03) 2(3.03) 1(0.8) 1(1.51) 2(3.03) 1(1.51) 1(1.51) 0(0) 0(0) 0(0) 0(0) Klebsiella spp (n = 73) Animal (68) 17(25) 14(20.59) 13(19.12) 13(19.12) 7(10.29) 11(16.18) 10(14.71) 9(13.24) 0(0) 0(0) 0(0) 0(0) Human (120) 26(21.67) 24(20) 21(17.5) 23(19.17) 17(14.17) 20(16.67) 21(17.5) 18(15) 0(0) 0(0) 0(0) 0(0) Soil (68) 13(19.12) 10(14.71) 11(16.18) 9(13.24) 7(10.29) 8(11.76) 8(11.76) 8(11.76) 1(1.47) 0(0) 0(0) 0(0) Drinking water (66) 17(25.76) 17(25.76) 14(21.21) 15(22.73) 12(18.19) 14(21.21) 15(22.73) 12(18.19) 1(1.52) 1(1.52) 0(0) 1(1.52) N= total number of samples collected n= total number of ESBL positive isolates tested a= total number of ESBL positive per sample type b= total number of gene positive sample Distribution of ESBL encoding genes per site As illustrated in Fig 1, the prevalence of beta-lactamase resistance genes ( bla CTX-M , bla TEM , bla SHV ) and their combinations were investigated across four locations (Saaba, Koubri, Loumbila, Sapone). The data indicate that bla CTX-M was the most dominant (53.97-56.32%), followed by bla TEM (46.03-51%) and bla SHV (20.63-37.93%). The most prevalent co-occurrence was bla CTX-M + bla TEM (42.86-47.22%), while the triple combination ( bla CTX-M + bla TEM + bla SHV ) was less common but most prevalent in Sapone (21.84%), who also exhibited the highest overall resistance rates. Distribution of ESBL encoding gene detected by farms types The comparison between semi-intensive and traditional farming systems highlights minor differences in the prevalence of ESBL-producing genes: bla CTX-M and bla TEM are most prevalent in Traditional farming (89.3% and 85.7%, respectively) compared to Semi-intensive farming (82.1% and 76.9%). bla SHV is most prevalent in Semi-intensive farming (30.8%) than in Traditional farming (25%). Multidrug-resistant gene combinations ( bla CTX-M + bla TEM + bla SHV ) are most common in Traditional farming (21.4%), suggesting more multidrug-resistant strains in this system (Fig 2 ) . Cluster analysis of antimicrobial resistance and ESBL-producing genes in Escherichia coli and Klebsiella isolates from cattle, humans, soil and drinking water The cluster analysis based on antimicrobial susceptibility testing and ESBL-producing genes bla CTX-M , bla TEM , and bla SHV shows 3 clusters: Cluster 3 consists exclusively of Klebsiella from animals (kba7), which are characterized by distinct antimicrobial resistance profiles and the presence of bla CTX-M , bla TEM , and bla SHV genes. This suggests a unique resistance pattern in Klebsiella from animals. Clusters 1 and 2 are mixed, containing isolates from both E. coli and Klebsiella , sourced from human, animal, soil, and drinking water. The mixing of these species reflects shared antimicrobial resistance patterns and the widespread distribution of bla CTX-M , bla TEM , and bla SHV genes across various environments and hosts (Fig 3 ) . Correlation of ESBL encoding gene and antibiotics tested Correlation analysis determines the associations between resistance genes and antimicrobial resistance phenotypes among Escherichia coli and Klebsiella isolates from cattle, humans, soil and drinking water. A positive correlation was observed between bla CTX-M and CTX (r=0.48), suggesting that an increase in the presence of the bla CTX-M gene is associated with a higher resistance to CTX (Fig 4 ) . This could indicate that the bla CTX-M gene, which is responsible for β-lactamase producing, contributes to more pronounced resistance to this antibiotic. In contrast, a negative correlation was found between bla CTX-M and NAL (r= -0.35), meaning that in some cases, a higher presence of bla CTX-M is associated with a decrease in resistance to NAL (Fig 4 ) . This phenomenon could be related to competing resistance mechanisms, where bacteria resistant to certain antibiotics may exhibit increased sensitivity to others. Discussion This study investigated the molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemase encoding genes in E. coli and Klebsiella species isolated from animal, human, environmental, and drinking water sources in Burkina Faso. The finding corroborate phenotypic tests [ 15 ] and revealed a high prevalence of bla CTX−M and bla TEM in both E. coli and Klebsiella spp compared to bla SHV and low level of AmpC-β-lactamase and carbapenemase encoding genes. The high prevalence of bla CTX−M and bla TEM genetic determinants in isolates of animal origin highlights the worrying spread of ESBL-producing bacteria in livestock farming in Africa. This observation corroborates epidemiological data collected in South Africa and other geographical areas of the continent, where an identical predominance of these genotypes has been documented in faecal samples from livestock [ 18 ], [ 19 – 22 ]. These results confirm that these enzymes constitute one of the main classes of ESBLs involved in β-lactam resistance mechanisms. Their ubiquity is all the more problematic given that these molecules remain the therapeutic mainstay of antibacterial treatments in both human and veterinary medicine throughout Africa [ 22 ]. Furthermore, our findings are consistent with data from a recent systematic review and meta-analysis, which identify the bla CTX−M gene as the most prevalent resistance determinant in West Africa. This genotype is involved in 70.8% of reports recorded under the integrated One Health approach, confirming its epidemiological dominance in the region [ 23 ]. It is important to note that cefotaximases, and more specifically the bla CTX−M type, have become the dominant ESBL variant worldwide. This enzymatic hegemony is accompanied by rapid progression within various ecological niches, a phenomenon that has been widely documented in international scientific literature. Today, the widespread dissemination of this gene across continents makes it the most prevalent and most closely monitored resistance marker worldwide [ 24 ]. Indeed, the last decade has been marked by the rapid emergence of CTX-M-type β-lactamases. This category of ESBLs, whose spread is facilitated by plasmid mediation, has transformed the landscape of antibiotic resistance. Its capacity for horizontal transfer has led to a dramatic increase in its prevalence, thereby redefining contemporary clinical challenges [ 26 , 27 ]. The co-occurrence of the bla CTX−M , bla TEM and bla SHV genes highlighted in our work is consistent with observations reported in livestock farms [ 28 , 29 ] and agricultural ecosystems [ 30 , 31 ]. In these environments, the co-expression of bla CTX−M and bla TEM appears to be the predominant genotypic profile, confirming a co-resistance dynamic frequently encountered in the field. The assessment conducted among 120 agricultural workers revealed an ESBL carriage rate of 37.5%, with a marked prevalence of bla CTX−M (35%) and bla TEM (26.67%) genes. These data suggest that occupational exposure, characterised by sustained interaction with livestock and soil environments, promotes human colonisation. Notably, the frequency of bla CTX−M identified among farmers in Burkina Faso (35%) is quite comparable to the rates of 38–42% reported by Aworh et al . (2022) among their Nigerian counterparts, confirming a consistent regional trend [ 18 ]. Our observations, revealing the presence of bla CTX−M in 35% of Burkinabe agricultural workers, are part of a growing body of evidence. These data unequivocally confirm that this gene is the major determinant of ESBLs in West Africa, with systematic recurrence among the different populations studied in the sub-region [ 23 ]. Although these results are in line with global trends, they sharply highlight the unique challenges facing the subregion in the fight against antimicrobial resistance (AMR). The notable co-occurrence of bla CTX−M and bla TEM genes (25%), as well as the identification of profiles carrying the triple genetic combination (4.17%), indicate constant selection pressure in agricultural environments. This phenomenon could result from intensive veterinary use or prolonged exposure to contaminated environmental niches. Finally, the prevalence of bla CTX−M in humans poses a major threat to public health: these determinants are regularly associated with resistance genes that confer protection against other essential therapeutic classes, including fluoroquinolones, aminoglycosides and trimethoprim-sulfamethoxazole [ 31 ]. The environmental compartment also reveals worrying contamination: soil analyses show a positivity rate of 41.2%, characterised by a predominance of bla CTX−M (32.4%) and bla TEM (36.8%). The high co-occurrence of these two determinants (27.9%) suggests the existence of particularly active genetic transfer mechanisms within the soil. Furthermore, although the prevalence in water resources is more modest (3.0%), the identification of multi-resistant strains illustrated by triple positivity for bla CTX−M , bla TEM and bla SHV (1.5%) raises major health safety concerns. The presence of such profiles in water highlights the risk of large-scale dissemination of these superbugs in the ecosystem [ 32 ]. The identification of bla OXA−48 carbapenemase (1.5%) in soil samples, although still marginal, indicates the emergence of new environmental threats. Conversely, the absence of the bla KPC gene suggests that it remains confined to the clinical environment for the time being. These data point to soil as a major reservoir of resistance genes linked to agricultural and pastoral activities, contrasting with the role of water which, despite its lower prevalence, could act as a more fluid vector for dissemination [ 33 ]. Furthermore, the low occurrence of bla OXA−48 - and bla DHA -producing E. coli and Klebsiella spp. in drinking water and soil indicates that the risk of carbapenem and AmpC resistance is still limited. Nevertheless, these findings require the implementation of integrated interventions under the One Health approach, aimed at both optimising agricultural practices and securing water treatment systems to contain the spread of AMR in the ecosystem. The comparative analysis reveals a marked predominance of BLSE within the animal compartment, surpassing the incidence rates recorded in human and environmental sources. This disparity likely reflects the heterogeneity of practices and the regulatory framework governing the use of antimicrobials across sectors [ 18 ]. More specifically, animal production sectors are characterised by more frequent use of antibiotic molecules, often combined with less rigorous monitoring than that observed in human health [ 34 ]. This finding confirms the decisive role of farm animals as primary reservoirs of resistant strains. Indeed, the widespread use of antibiotics whether for prophylactic purposes, curative protocols or growth promotion is the main driver of the emergence of this phenomenon on farms [ 28 ]. Although our work highlights a higher prevalence in animal samples than in humans, an Egyptian study reports the opposite findings regarding carbapenem-resistant K. pneumoniae (CR- Kp ) in poultry farms. In this context, prevalence was significantly higher among agricultural workers (67%) than among veterinarians (33%). This disparity suggests that transmission is facilitated by close contact between broiler chickens and humans: unlike veterinarians, workers are in constant contact with the animals and live directly on the farm throughout the fattening phase [ 35 ]. This therapeutic challenge is exacerbated by the concomitant production of AmpC-type β-lactamases. Furthermore, the presence of these genetic determinants is frequently correlated with multidrug resistance (MDR) profiles, drastically limiting the available treatment options [ 36 ]. At the local level, significant geographical disparities were observed. Saponé has the most critical resistance rates, contrasting with the more modest prevalence recorded in Loumbila. These variations between the four localities highlight the complexity of the dynamics of antimicrobial resistance (AMR). This spatial heterogeneity can be explained by the influence of key local factors, such as disparities in antimicrobial use practices, the specific dynamics of local infections, and the genetic diversity of circulating bacterial strains [ 37 ]. These observations suggest a multifactorial causality in which the interaction of various parameters determines the extent of the emergence, spread and persistence of antibiotic resistance. In the context of our study, the geographical distance between Saponé and Ouagadougou could explain the increased prevalence of ESBL-producing bacteria in this area. Our previous work has shown that access to veterinary services is a major determinant of healthcare practices. Farmers who receive regular veterinary supervision are less likely to misuse antibiotics. This finding highlights the urgent need to facilitate access to qualified veterinary care. Strengthening these services and providing support to producers by competent professionals would be essential levers for promoting the rational management of antibiotics and, ultimately, curbing the spread of AMR [ 38 ]. According to Ferraz's research, structural factors such as limited access to healthcare infrastructure, inadequate regulatory oversight and the intensification of agricultural practices could be major drivers of increased resistance rates [ 39 ]. A comparison between semi-intensive and traditional farming systems reveals minor disparities in the prevalence of ESBL-producing genes. Both farming methods show high rates of bla CTX−M and bla TEM , with the traditional system even showing slightly higher frequencies (89.3% and 85.7% respectively) than the semi-intensive system (82.1% and 76.9%). Conversely, the bla SHV gene is marginally more prevalent in semi-intensive farming (30.8%) than in traditional farming (25%). Although genetic co-expression is more frequent in the traditional system (21.4%), these overall differences are not statistically significant. These results suggest that, in the context of Burkina Faso, the spread of ESBL-producing bacteria does not depend exclusively on the production model. Rather, it seems to be governed by cross-cutting variables such as antimicrobial use patterns, environmental contamination pressure and animal health management standards [ 37 ]. Analysis of the heat map associated with hierarchical clustering (Fig. 3) highlights a distinct structuring of isolates according to their respective hosts. Remarkably, strictly identical phenotypic and genotypic (PCR) resistance profiles were identified within pairs of isolates from sources as varied as cattle, humans, soil and drinking water. Such convergence of profiles was anticipated: it illustrates the dynamics of shared plasmid-mediated resistance genes ( bla TEM , bla SHV , bla CTX−M ), whose horizontal transfer promotes inter-species and environmental dissemination [ 40 ]. This finding is corroborated by studies conducted in Ghana and Germany, which have demonstrated a close relationship between isolates of human and animal origin [ 19 ], [ 28 ]. These genetic similarities support the hypothesis of bidirectional circulation of resistance genes between these two populations, transcending species barriers [ 41 ]. However, these results contrast with certain studies that have shown that the genetic diversity of ESBL-producing E. coli (ESBL- E. coli ) in humans, poultry and their environment appear to be associated with distinct sequence types (STs) [ 22 , 42 , 43 ]. This divergence highlights that, although the resistance genes may be identical, the bacterial strains that harbour them may belong to different phylogenetic lineages, suggesting a more complex transmission dynamic than simple clonal circulation Despite the identification of identical BLSE genes in animal and human compartments, our study cannot establish formal proof that the resistance observed is of bovine origin or strictly attributable to the farm environment. The homology of genes in livestock and agricultural workers does not, in itself, constitute evidence of zoonotic transfer. It is equally likely that a common source of transmission exists, as suggested by the epidemiological link observed. Furthermore, it is crucial to emphasise that livestock play a role as vectors in the environmental spread of ESBL-producing bacteria, particularly through the spreading of contaminated manure used as agricultural fertiliser. In order to resolve these uncertainties and accurately characterise the transmission dynamics, it is recommended that in-depth molecular investigations be conducted using whole genome sequencing (WGS). This approach will clarify the phylogenetic relationships between ESBL- Ec and ESBL- Kp isolates circulating among animals, humans, soil and water resources [ 28 ]. In addition, antimicrobial resistance (AMR) spreads through complex networks connecting humans, animals and the environment. These exchanges occur mainly through faecal contamination and the food chain, particularly through the consumption of raw milk or contaminated meat [ 44 , 45 ]. One of the fundamental drivers of this dissemination is horizontal gene transfer (HGT), a mechanism by which bacteria acquire resistance determinants from their counterparts. This process is greatly facilitated by various mobile genetic elements, such as plasmids, bacteriophages, transposons and integrons. Consequently, bacteria develop AMR either through the direct acquisition of pre-existing resistance genes via these genetic vectors, or through the accumulation of mutations under selection pressure [ 44 ]. An in-depth analysis was conducted to assess the direct impact of BLSE genes on increased resistance levels. The results reveal a moderate positive correlation between the presence of bla CTX−M and resistance to cefotaxime (CTX) (r = 0.48; Fig. 4). This association suggests that the expression of this gene, which codes for a specific β-lactamase, is a major determinant of pronounced resistance to this antibiotic in our sample. This could indicate that the bla CTX−M gene, which is responsible for β-lactamase producing, contributes to more pronounced resistance to this antibiotic. These observations are consistent with the findings of Nossair et al., who reported a similar relationship between the bla TEM gene and resistance to CTX (r = 0.36) [ 40 ]. Taken together, these results confirm that various ESBL genes contribute to the emergence of the resistance phenotype, although their respective contributions may vary in intensity. Conclusion This study provides tangible evidence of an interconnected antimicrobial resistance (AMR) crisis in Burkina Faso, characterised by the ubiquitous spread of bla CTX−M and bla TEM genes in human, animal and environmental reservoirs. Our work identifies the agricultural sector as a major driver of this dynamic, while the regional disparities observed highlight the influence of access to healthcare and the heterogeneity of antibiotic use practices across the country. The complexity of this multidimensional threat calls for immediate action based on the One Health approach. On the one hand, it is imperative to regulate the use of antibiotics in the agricultural sector and to set up integrated surveillance systems combining clinical, veterinary and environmental monitoring. On the other hand, improving water treatment infrastructure and the safe management of livestock effluents are crucial to breaking the cycles of transmission. Finally, the systematic application of whole genome sequencing (WGS) will need to be coupled with public health programmes dedicated to the proper use of antimicrobials (stewardship). In conclusion, the fight against AMR in Burkina Faso requires cross-cutting and sustained coordination between human medicine, animal health and environmental management in order to curb the spread of this global health challenge. Declarations Acknowledgments This manuscript was developed with guidance from the PAPERI–SSI Scientific Writing Workshop (22–25 September 2025), organized by the Pan-African PGS Education and Research Initiative (PAPERI) in collaboration with the Sustainable Sciences Institute (SSI).We would like to thank the managers of the Livestock Technical Support Zones (ZATE) and the farmers involved in the study for their participation and accompaniment at the sites and for facilitating data collection. Author Contributions Authors D.S., I.J.O.B., and F.B.J.D. developed the conceptualisation of this study. The methodology was defined jointly by I.J.O.B., D.S., F.B.J.D., and Z.G. The formal analysis and drafting of the first version of the manuscript were carried out by D.S. The entire team was involved in reviewing and editing the text, namely D.S., I.J.O.B., F.B.J.D., Z.G., N.S.S., E.B., N.B., S.S. and M.E.M.N. The work was supervised by Z.G. and I.J.O.B. Finally, all authors have read and approved the final version of the published manuscript. Funding The author(s) did not receive any specific funding for this work. Data availability The datasets used and analysed in this study are available from the corresponding author upon reasonable request. All data generated or analysed during this study are also included in this article. Ethical approval and consent to participate Ethics committee approval was obtained from the health research ethics committee (CERS) of Burkina Faso (N◦2018-15-1153). The purpose of this study and the sampling procedure were explained to the farmers orally, after which written consent to participate in the study was requested. Consent for publication Not applicable Competing interests The authors declare no competing interests. References Antimicrobials, WL of MI. WHO List of Medically Important Antimicrobials WHO List of Medically Important Antimicrobials A risk management tool for mitigating. 2024. 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Extended-Spectrum ß-Lactamase-Producing Escherichia coli Among Humans, Beef Cattle, and Abattoir Environments in Nigeria. Front Cell Infect Microbiol. 2022;12:1–11. Falgenhauer L, Imirzalioglu C, Oppong K, Akenten CW, Hogan B, Krumkamp R, et al. Detection and characterization of ESBL-producing Escherichia coli from humans and poultry in Ghana. Front Microbiol. 2019;10 JAN:1–8. Iweriebor BC, Iwu CJ, Obi LC, Nwodo UU, Okoh AI. Multiple antibiotic resistances among Shiga toxin producing Escherichia coli O157 in feces of dairy cattle farms in Eastern Cape of South Africa Clinical microbiology and vaccines. BMC Microbiol. 2015;15:1–9. Aworh MK, Kwaga J, Okolocha E, Harden L, Hull D, Hendriksen RS et al. Extended-spectrum ß-lactamase-producing Escherichia coli among humans, chickens and poultry environments in Abuja, Nigeria. One Heal Outlook. 2020;2. Negeri AA, Mamo H, Gahlot DK, Gurung JM, Seyoum ET, Francis MS. Characterization of plasmids carrying bla CTX-M genes among extra-intestinal Escherichia coli clinical isolates in Ethiopia. Sci Rep. 2023;13:1–14. Yartey SN-A, Kungu F, Asantewaa AA, Donkor ES. Extended Spectrum Beta-Lactamase-Producing Bacterial Clones in West Africa: A Systematic Review and Meta-Analysis from a One Health Perspective. Sci Rep. 2025;15:29625. Olaitan MO, Orababa OQ, Shittu RB, Oyediran AA, Obunukwu GM, Arowolo MT et al. Extended-spectrum beta-lactam-resistant Klebsiella pneumoniae in sub-Saharan Africa: a systematic review and meta-analysis from a One Health perspective. BMC Infect Dis. 2025;25. Cantón R, Coque TM. The CTX-M β-lactamase pandemic. Curr Opin Microbiol. 2006;9:466–75. Tamang MD, Nam HM, Gurung M, Jang GC, Kim SR, Jung SC, et al. Molecular characterization of CTX-M β-lactamase and associated addiction systems in Escherichia coli circulating among cattle, farm workers, and the farm environment. Appl Environ Microbiol. 2013;79:3898–905. Founou LL, Founou RC, Allam M, Ismail A, Djoko CF, Essack SY. Genome sequencing of extended-spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae isolated from pigs and abattoir workers in Cameroon. Front Microbiol. 2018;9 FEB:1–12. Dahms C, Hubner NO, Kossow A, Mellmann A, Dittmann K, Kramer A. Occurrence of ESBL-producing Escherichia coli in livestock and farm workers in Mecklenburg-Western Pomerania, Germany. PLoS ONE. 2015;10:1–13. Kagambèga AB, Dembélé R, Traoré O, Wane AA, Mohamed AH, Coulibaly H, et al. Isolation and Characterization of Environmental Extended Spectrum β-Lactamase-Producing Escherichia coli and Klebsiella pneumoniae from Ouagadougou. Burkina Faso Pharmaceuticals. 2024;17:1–13. Mgaya FX, Matee MI, Muhairwa AP, Hoza AS. Occurrence of multidrug resistant escherichia coli in raw meat and cloaca swabs in poultry processed in slaughter slabs in Dar Es Salaam, Tanzania. Antibiotics. 2021;10:0–9. Sudarwanto MB, Lukman DW, Latif H, Pisestyani H, Sukmawinata E, Akineden Ö, et al. CTX-M producing Escherichia coli isolated from cattle feces in Bogor slaughterhouse, Indonesia. Asian Pac J Trop Biomed. 2016;6:605–8. Cheung C, Naughton PJ, Dooley JSG, Corcionivoschi N, Brooks C. The spread of antimicrobial resistance in the aquatic environment from faecal pollution: a scoping review of a multifaceted issue. Environ Monit Assess. 2025;197. Mahmud ZH, Kabir MH, Ali S, Moniruzzaman M, Imran KM, Nafiz TN, et al. Extended-Spectrum Beta-Lactamase-Producing Escherichia coli in Drinking Water Samples From a Forcibly Displaced, Densely Populated Community Setting in Bangladesh. Front Public Heal. 2020;8:1–14. Oladeji OM, Mugivhisa LL, Olowoyo JO. Antibiotic Residues in Animal Products from Some African Countries and Their Possible Impact on Human Health. Antibiotics. 2025;14. Hamza E, Dorgham SM, Hamza DA. Carbapenemase-producing Klebsiella pneumoniae in broiler poultry farming in Egypt. J Glob Antimicrob Resist. 2016;7:8–10. Egbule OS, Iweriebor BC, Odum EI. Beta-lactamase-producing escherichia coli isolates recovered from pig handlers in retail shops and abattoirs in selected localities in Southern Nigeria: Implications for public health. Antibiotics. 2021;10:1–10. Österberg J, Wingstrand A, Jensen AN, Kerouanton A, Cibin V, Barco L, et al. Antibiotic resistance in Escherichia coli from pigs in organic and conventional farming in four european countries. PLoS ONE. 2016;11:1–12. Soma D, Diarra FBJ, Bonkoungou IJO, Somda NS. Assessing antibiotic use practices on central Burkina Faso cattle farms and the associated risks to environmental and human health contamination: A pilot study. 2025;11:1–12. Ferraz MP. Antimicrobial Resistance: The Impact from and on Society According to One Health Approach. Societies. 2024;14:1–22. Nossair MA, Abd El Baqy FA, Rizk MSY, Elaadli H, Mansour AM, El-Aziz AHA et al. Prevalence and Molecular Characterization of Extended-Spectrum β-Lactamases and AmpC β-lactamase-Producing Enterobacteriaceae among Human, Cattle, and Poultry. Pathogens. 2022;11. Day MJ, Hopkins KL, Wareham DW, Toleman MA, Elviss N, Randall L, et al. Extended-spectrum β-lactamase-producing Escherichia coli in human-derived and foodchain-derived samples from England, Wales, and Scotland: an epidemiological surveillance and typing study. Lancet Infect Dis. 2019;19:1325–35. Trung NV, Jamrozy D, Matamoros S, Carrique-Mas JJ, Mai HH, Hieu TQ, et al. Limited contribution of non-intensive chicken farming to ESBL-producing Escherichia coli colonization in humans in Vietnam: An epidemiological and genomic analysis. J Antimicrob Chemother. 2019;74:561–70. Checcucci A, Trevisi P, Luise D, Modesto M, Blasioli S, Braschi I, et al. Exploring the Animal Waste Resistome: The Spread of Antimicrobial Resistance Genes Through the Use of Livestock Manure. Front Microbiol. 2020;11:1–9. Pandey S, Doo H, Keum GB, Kim ES, Kwak J, Ryu S, et al. Antibiotic resistance in livestock, environment and humans: One Health perspective. J Anim Sci Technol. 2024;62:266–78. Yadav S, Kapley A. Exploration of activated sludge resistome using metagenomics. Sci Total Environ. 2019;692:1155–64. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Additional informations Additional file 1.docx. Primers used for detection of ESBL, AmpC and carbapenemase-encoding genes. Additionalfile2.docx Additional file 2.docx. Reaction components and thermal cycling parameters for resistance gene PCR assays. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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The strength of the colour corresponds to the numerical value of the correlation coefficient (r). Significance was calculated at p \u0026lt; 0.05, and boxes with non-significant correlations were left blank.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8961524/v1/be3e26caa57d1ea15b089281.png"},{"id":108802996,"identity":"2192078c-8d5b-4d32-8ecc-e16ea9847016","added_by":"auto","created_at":"2026-05-08 14:30:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1716992,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8961524/v1/aaac4d30-af59-4762-89ed-f46e1b128eaa.pdf"},{"id":104019126,"identity":"89b59c79-eda5-42fc-ad6f-f71dab2e97cf","added_by":"auto","created_at":"2026-03-05 17:57:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24603,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional informations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditional file 1.docx. Primers used for detection of ESBL, AmpC and carbapenemase-encoding genes.\u003c/p\u003e","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8961524/v1/13eadccfca15fab46f39025a.docx"},{"id":104402742,"identity":"90b94236-cce9-421b-9b57-95e5540dc18c","added_by":"auto","created_at":"2026-03-11 12:16:16","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15844,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2.docx. Reaction components and thermal cycling parameters for resistance gene PCR assays.\u003c/p\u003e","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8961524/v1/d9a421d65c8437f26ab4d6a5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemases-producing Escherichia coli and Klebsiella spp., isolated from human, animal, environment, and drinking water in Burkina Faso","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe emergence and global spread of antimicrobial resistance (AMR) constitutes a systemic health crisis, threatening the effectiveness of modern anti-infective therapies. Among the most critical threats identified by the World Health Organisation (WHO), enterobacteria resistant to third-generation cephalosporins and carbapenems are a top priority [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This resistance is mainly mediated by the production of extended-spectrum β-lactamases (ESBLs), AmpC-type β-lactamases and, more alarmingly, carbapenemases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The latter, including metallo-β-lactamases (VIM, NDM) and serine carbapenemases (KPC, OXA-48), hydrolyse almost all β-lactams, including carbapenems, which are the last resort molecules in hospitals [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHistorically, resistance genes such as \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e dominated the molecular landscape, but the last decade has been marked by the pandemic expansion of the bla\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e genotype, particularly the CTX-M-15 variant [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The persistence of these genetic determinants is facilitated by their location on mobile genetic elements (MGEs), such as high-conjugation plasmids, integrons and transposons, which facilitate horizontal gene transfer (HGT) between commensal and pathogenic bacterial species [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This genetic dynamism allows resistance to circulate freely beyond hospital boundaries, infiltrating agricultural and environmental ecosystems [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Within the framework of the One Health paradigm, it is now accepted that the interface between humans, animals and their shared environment is the main driver of AMR evolution [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In sub-Saharan Africa, and particularly in Burkina Faso, pastoral and semi-intensive livestock farming plays a central role in the national economy. However, the intensive and often unsupervised use of antimicrobials as growth promoters or prophylactics induces constant selection pressure within the intestinal microbiota of livestock [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Animal waste, rich in multidrug-resistant (MDR) bacteria, contaminates soil and water resources, creating routes of transmission to human populations via the food chain or direct contact [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Burkina Faso, data on the prevalence of BLSE, AmpC and, above all, carbapenemase genes in non-clinical sectors remain insufficient to accurately map the risks of zoonotic transfer. Furthermore, the influence of agro-ecological variations and livestock farming systems on the diversity of circulating clones remains poorly understood.\u003c/p\u003e \u003cp\u003eThis study aims to provide a comprehensive surveillance data on the prevalence and molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemase-producing \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e spp. in Burkina Faso. By isolating these pathogens from a variety of sources, including animals, humans, environmental samples, and drinking water, this study will examine the distribution of resistance genes, explore potential transmission routes, and analyse the genetic mechanisms responsible for these resistance profiles. The molecular characterization of these pathogens will also offer insights into the genetic diversity and potential clonal spread of these resistant strains in Burkina Faso.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003eESBL, AmpC-β-lactamase and carbapenemase (CP)-producing\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eKlebsiella\u003c/b\u003e \u003cb\u003espp. detection\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe data collection and sampling phase spanned from May 2018 to May 2021. This longitudinal study period covered several seasonal cycles, ensuring an in-depth analysis of the persistence and circulation dynamics of resistance genes within the 39 semi-intensive farms and 28 traditional farms in the peri-urban area of Ouagadougou. It should be noted that the methodology employed in the sampling, bacterial isolation and identification, antibiotic sensitivity testing, phenotypic detection of ESBL production, and the total number of samples utilised for the isolation of these strains has been previously documented in a published article [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA total of 215 CHROMagar positive, including ESBL-producing presumptive \u003cem\u003eE. coli\u003c/em\u003e (122) and \u003cem\u003eKlebsiella\u003c/em\u003e spp. (79) isolates were confirmed by antimicrobial susceptibility test (AST). Indeed, these isolates were screened for genetic element determinants of ESBL (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e). All isolates with a meropenem inhibition zone diameter less than 22 mm (\u0026le;\u0026thinsp;22 mm) in the AST were investigated for potential production of carbapenemases (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eNDM\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eVIM\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e). Morever, all isolates with a cefoxitin inhibition zone diameter less than 18 mm (\u0026le;\u0026thinsp;18 mm) were presumed as AmpC-β-lactamase producers according to CLSI guideline [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Three multiplex polymerase chain reaction (PCR) were used to screening ESBL, carbapenemases and AmpC-β-lactamase encoding genes. \u003cb\u003eAdditional file 1\u003c/b\u003e shows set of specific primers used for the detection of ESBL, carbapenemase and AmpC-β-lactamase genes.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction\u003c/h2\u003e \u003cp\u003eThe DNA was extracted from all 215 fresh colony samples by the boiling method as descripbed by Seman \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] with some modification. Briefly, 3 to 4 bacterial colonies were suspended in 600 \u0026micro;l of nuclease-free water. This suspension was then homogenised and subjected to heat shock at 100\u0026deg;C for 10 minutes, followed by cooling to room temperature for 15 minutes. After centrifugation at 18,000 g for 10 minutes at 4\u0026deg;C, a volume of 300 \u0026micro;l of the supernatant was removed and transferred to a sterile Eppendorf tube before being stored at -20\u0026deg;C until analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetection of ESBL, carbapenemase and AmpC-β-lactamase associated genes by PCR\u003c/h3\u003e\n\u003cp\u003eESBL, carbapenemase and AmpC-β-lactamase resistance genes were detected using conventional polymerase chain reaction (PCR). Three multiplex PCR assays were performed in a Bio-Rad T100 thermal cycler to screen for ESBL, AmpC-β-lactamase and carbapenemases encoding genes screening. \u003cb\u003eAdditional file 2\u003c/b\u003eprovides a summary of the PCR conditions and thermal cycling parameters used. Once the PCR was complete, 10 \u0026micro;l of each amplicon were deposited in the wells on the agarose gel (1.5%) contained in a 0.5X TBE migration buffer) starting from the bottom to the top. A 100 bp molecular weight marker (Hyper Ladder1, Bioline) was used to evaluate the size of the different genes. Electrophoresis was carried out at 220 V and 300 mA using a voltage generator for 25 minutes to ensure complete separation of the bands. Following electrophoresis, the gels were visualized using a GelDoc Go imaging system (Bio-Rad).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were collected and processed using Microsoft Excel 2016 (Microsoft Office, Washington, USA). A correlation analysis was performed to determine the association between the antimicrobial resistance genes and phenotypic antimicrobial resistances among the isolates. The resistance phenotypes and genotypes results were converted into binary data (0/1); the absence of resistance genes or susceptibility to antimicrobials had scores of 0, while the presence of a resistance gene or resistance to antimicrobials received scores of 1. Binary data were imported into R software (version R software version 4.2.2.); with the \u0026ldquo;corrplot\u0026rdquo; package, the correlations were determined at a significance of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 using the functions \u0026ldquo;cor\u0026rdquo; and \u0026ldquo;cor.mtest\u0026rdquo;. A heatmap with hierarchical clustering was also generated using the R packages \u0026ldquo;heatmap\u0026rdquo;, ggplot2, reshape2 and \u0026ldquo;colorRampPalette\u0026rdquo;, in order to cluster the examined isolates based on their phenotypic and genotypic resistance profile.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDistribution of ESBL, AmpC-\u0026beta;-lactamase and carbapenemases encoding genes in\u003c/strong\u003e \u003cstrong\u003eE. coli\u003c/strong\u003e \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eKlebsiella\u003c/strong\u003e \u003cstrong\u003espp. across hnimal, human, environmental, and drinking water samples in Burkina Faso\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 215 phenotypically confirmed ESBL samples were amplified to confirm the presence of genes encoding ESBL. Of these, 195 (90.7%) harboured at least one ESBL-encoding gene. In this study, the prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e in both \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e spp. considerably varied among sample types, and particularly highest in animal samples. For \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (67.65%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (61.76%) were the most common detected, while \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e, and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eDHA\u003c/sub\u003e were not detected. In human samples, the prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e was 35% and 26.67% respectively; however, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e, and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e were not detected. Soil and drinking water samples showed moderate to low levels of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, and none of the other resistance genes (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eDHA\u003c/sub\u003e) were found in these environmental sources (Table 1). For \u003cem\u003eKlebsiella\u003c/em\u003e spp., the results mirrored those of \u003cem\u003eE. coli\u003c/em\u003e, with \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (20.59%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (19.12%) being the most prevalent in animal samples. No \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e, or \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e genes were detected in any of the samples. Soil and drinking water samples showed similar trends, with higher prevalence in drinking water for \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (25.76%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (21.21%). The \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e gene was detected at 1.52% in the drinking water samples, whereas \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e were absent (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. \u003cstrong\u003eDistribution of ESBL, AmpC-\u0026beta;-lactamase and carbapenemases encoding genes.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive Isolates\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSamples Types (N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eESBL Positive samples a (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eb (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eb (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M+\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM+\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u003c/sub\u003e\u003cem\u003e-\u003c/em\u003e\u003csub\u003eM+\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M+\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM+\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eDHA\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eIMP\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA_48\u003c/sub\u003e b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;122)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnimal (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47(69.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46(67.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42(61.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(13.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(4.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41(60.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(11.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(5.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman (120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45(37.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42(35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(11.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(4.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(10.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(4.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoil (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28(41.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22(32.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(36.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(4.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(27.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(2.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrinking water (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella\u003c/em\u003e spp (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnimal (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(20.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(19.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(19.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(10.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(16.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(14.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(13.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman (120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26(21.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(19.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(14.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(16.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoil (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(19.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(14.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(16.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(13.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(10.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(11.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(11.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(11.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrinking water (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(25.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(25.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(21.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(18.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(21.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(18.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eN= total number of samples collected\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;n= total number of ESBL positive isolates\u0026nbsp;tested\u003c/p\u003e\n\u003cp\u003ea= total number of ESBL positive per sample type\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eb= total number of gene positive sample\u003c/p\u003e\n\u003ch2\u003eDistribution of ESBL encoding genes per site\u003c/h2\u003e\n\u003cp\u003eAs illustrated in Fig 1, the prevalence of beta-lactamase resistance genes (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u003c/sub\u003e\u003cem\u003e, bla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e\u003cem\u003e, bla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e) and their combinations were investigated across four locations (Saaba, Koubri, Loumbila, Sapone). The data indicate that \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003ewas the most dominant (53.97-56.32%), followed by \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (46.03-51%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e (20.63-37.93%). The most prevalent co-occurrence was \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003e+ \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (42.86-47.22%), while the triple combination (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003e+\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u0026nbsp;\u003c/sub\u003e+ \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e)\u003csub\u003e\u0026nbsp;\u003c/sub\u003ewas less common but most prevalent in Sapone (21.84%), who also exhibited the highest overall resistance rates.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eDistribution of ESBL encoding gene detected by farms types\u003c/h2\u003e\n\u003cp\u003eThe comparison between semi-intensive and traditional farming systems highlights minor differences in the prevalence of ESBL-producing genes: \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003eand \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u0026nbsp;\u003c/sub\u003eare most prevalent in Traditional farming (89.3% and 85.7%, respectively) compared to Semi-intensive farming (82.1% and 76.9%). \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e is most prevalent in Semi-intensive farming (30.8%) than in Traditional farming (25%). Multidrug-resistant gene combinations (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003e\u003cem\u003e+ bla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e\u003cem\u003e\u0026nbsp;+ bla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e) are most common in Traditional farming (21.4%), suggesting more multidrug-resistant strains in this system (Fig 2\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003ch2\u003eCluster analysis of antimicrobial resistance and ESBL-producing genes in \u003cem\u003eEscherichia\u003c/em\u003e coli and \u003cem\u003eKlebsiella\u003c/em\u003e isolates from cattle, humans, soil and drinking water\u003c/h2\u003e\n\u003cp\u003eThe cluster analysis based on antimicrobial susceptibility testing and ESBL-producing genes \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u003c/sub\u003e\u003cem\u003e, bla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e shows 3 clusters: Cluster 3 consists exclusively of \u003cem\u003eKlebsiella\u003c/em\u003e from animals (kba7), which are characterized by distinct antimicrobial resistance profiles and the presence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u003c/sub\u003e\u003cem\u003e, bla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e genes. This suggests a unique resistance pattern in \u003cem\u003eKlebsiella\u003c/em\u003e from animals. Clusters 1 and 2 are mixed, containing isolates from both \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003eand \u003cem\u003eKlebsiella\u003c/em\u003e, sourced from human, animal, soil, and drinking water. The mixing of these species reflects shared antimicrobial resistance patterns and the widespread distribution of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u003c/sub\u003e\u003cem\u003e, bla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e genes across various environments and hosts (Fig 3\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003ch2\u003eCorrelation of ESBL encoding gene and antibiotics tested\u003c/h2\u003e\n\u003cp\u003eCorrelation analysis determines the associations between resistance genes and antimicrobial resistance phenotypes among \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e isolates from cattle, humans, soil and drinking water. A positive correlation was observed between \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003eand CTX (r=0.48), suggesting that an increase in the presence of the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u003c/sub\u003e gene is associated with a higher resistance to CTX (Fig 4\u003cstrong\u003e)\u003c/strong\u003e. This could indicate that the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003egene, which is responsible for \u0026beta;-lactamase producing, contributes to more pronounced resistance to this antibiotic. In contrast, a negative correlation was found between \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003eand NAL (r= -0.35), meaning that in some cases, a higher presence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX-M\u0026nbsp;\u003c/sub\u003eis associated with a decrease in resistance to NAL (Fig 4\u003cstrong\u003e)\u003c/strong\u003e. This phenomenon could be related to competing resistance mechanisms, where bacteria resistant to certain antibiotics may exhibit increased sensitivity to others.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemase encoding genes in \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e species isolated from animal, human, environmental, and drinking water sources in Burkina Faso. The finding corroborate phenotypic tests [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and revealed a high prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e in both \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e spp compared to \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e and low level of AmpC-β-lactamase and carbapenemase encoding genes. The high prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e genetic determinants in isolates of animal origin highlights the worrying spread of ESBL-producing bacteria in livestock farming in Africa. This observation corroborates epidemiological data collected in South Africa and other geographical areas of the continent, where an identical predominance of these genotypes has been documented in faecal samples from livestock [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These results confirm that these enzymes constitute one of the main classes of ESBLs involved in β-lactam resistance mechanisms. Their ubiquity is all the more problematic given that these molecules remain the therapeutic mainstay of antibacterial treatments in both human and veterinary medicine throughout Africa [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Furthermore, our findings are consistent with data from a recent systematic review and meta-analysis, which identify the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e gene as the most prevalent resistance determinant in West Africa. This genotype is involved in 70.8% of reports recorded under the integrated One Health approach, confirming its epidemiological dominance in the region [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It is important to note that cefotaximases, and more specifically the bla\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e type, have become the dominant ESBL variant worldwide. This enzymatic hegemony is accompanied by rapid progression within various ecological niches, a phenomenon that has been widely documented in international scientific literature. Today, the widespread dissemination of this gene across continents makes it the most prevalent and most closely monitored resistance marker worldwide [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Indeed, the last decade has been marked by the rapid emergence of CTX-M-type β-lactamases. This category of ESBLs, whose spread is facilitated by plasmid mediation, has transformed the landscape of antibiotic resistance. Its capacity for horizontal transfer has led to a dramatic increase in its prevalence, thereby redefining contemporary clinical challenges [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The co-occurrence of the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e genes highlighted in our work is consistent with observations reported in livestock farms [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and agricultural ecosystems [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In these environments, the co-expression of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e appears to be the predominant genotypic profile, confirming a co-resistance dynamic frequently encountered in the field.\u003c/p\u003e \u003cp\u003eThe assessment conducted among 120 agricultural workers revealed an ESBL carriage rate of 37.5%, with a marked prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (35%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (26.67%) genes. These data suggest that occupational exposure, characterised by sustained interaction with livestock and soil environments, promotes human colonisation. Notably, the frequency of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e identified among farmers in Burkina Faso (35%) is quite comparable to the rates of 38\u0026ndash;42% reported by Aworh \u003cem\u003eet al\u003c/em\u003e. (2022) among their Nigerian counterparts, confirming a consistent regional trend [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our observations, revealing the presence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e in 35% of Burkinabe agricultural workers, are part of a growing body of evidence. These data unequivocally confirm that this gene is the major determinant of ESBLs in West Africa, with systematic recurrence among the different populations studied in the sub-region [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Although these results are in line with global trends, they sharply highlight the unique challenges facing the subregion in the fight against antimicrobial resistance (AMR). The notable co-occurrence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e genes (25%), as well as the identification of profiles carrying the triple genetic combination (4.17%), indicate constant selection pressure in agricultural environments. This phenomenon could result from intensive veterinary use or prolonged exposure to contaminated environmental niches. Finally, the prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e in humans poses a major threat to public health: these determinants are regularly associated with resistance genes that confer protection against other essential therapeutic classes, including fluoroquinolones, aminoglycosides and trimethoprim-sulfamethoxazole [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe environmental compartment also reveals worrying contamination: soil analyses show a positivity rate of 41.2%, characterised by a predominance of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (32.4%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e (36.8%). The high co-occurrence of these two determinants (27.9%) suggests the existence of particularly active genetic transfer mechanisms within the soil. Furthermore, although the prevalence in water resources is more modest (3.0%), the identification of multi-resistant strains illustrated by triple positivity for \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e (1.5%) raises major health safety concerns. The presence of such profiles in water highlights the risk of large-scale dissemination of these superbugs in the ecosystem [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The identification of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e carbapenemase (1.5%) in soil samples, although still marginal, indicates the emergence of new environmental threats. Conversely, the absence of the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e gene suggests that it remains confined to the clinical environment for the time being. These data point to soil as a major reservoir of resistance genes linked to agricultural and pastoral activities, contrasting with the role of water which, despite its lower prevalence, could act as a more fluid vector for dissemination [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Furthermore, the low occurrence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e- and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eDHA\u003c/sub\u003e-producing \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e spp. in drinking water and soil indicates that the risk of carbapenem and AmpC resistance is still limited. Nevertheless, these findings require the implementation of integrated interventions under the One Health approach, aimed at both optimising agricultural practices and securing water treatment systems to contain the spread of AMR in the ecosystem.\u003c/p\u003e \u003cp\u003eThe comparative analysis reveals a marked predominance of BLSE within the animal compartment, surpassing the incidence rates recorded in human and environmental sources. This disparity likely reflects the heterogeneity of practices and the regulatory framework governing the use of antimicrobials across sectors [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. More specifically, animal production sectors are characterised by more frequent use of antibiotic molecules, often combined with less rigorous monitoring than that observed in human health [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This finding confirms the decisive role of farm animals as primary reservoirs of resistant strains. Indeed, the widespread use of antibiotics whether for prophylactic purposes, curative protocols or growth promotion is the main driver of the emergence of this phenomenon on farms [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Although our work highlights a higher prevalence in animal samples than in humans, an Egyptian study reports the opposite findings regarding carbapenem-resistant \u003cem\u003eK. pneumoniae\u003c/em\u003e (CR-\u003cem\u003eKp\u003c/em\u003e) in poultry farms. In this context, prevalence was significantly higher among agricultural workers (67%) than among veterinarians (33%). This disparity suggests that transmission is facilitated by close contact between broiler chickens and humans: unlike veterinarians, workers are in constant contact with the animals and live directly on the farm throughout the fattening phase [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This therapeutic challenge is exacerbated by the concomitant production of AmpC-type β-lactamases. Furthermore, the presence of these genetic determinants is frequently correlated with multidrug resistance (MDR) profiles, drastically limiting the available treatment options [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the local level, significant geographical disparities were observed. Sapon\u0026eacute; has the most critical resistance rates, contrasting with the more modest prevalence recorded in Loumbila. These variations between the four localities highlight the complexity of the dynamics of antimicrobial resistance (AMR). This spatial heterogeneity can be explained by the influence of key local factors, such as disparities in antimicrobial use practices, the specific dynamics of local infections, and the genetic diversity of circulating bacterial strains [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These observations suggest a multifactorial causality in which the interaction of various parameters determines the extent of the emergence, spread and persistence of antibiotic resistance. In the context of our study, the geographical distance between Sapon\u0026eacute; and Ouagadougou could explain the increased prevalence of ESBL-producing bacteria in this area. Our previous work has shown that access to veterinary services is a major determinant of healthcare practices. Farmers who receive regular veterinary supervision are less likely to misuse antibiotics. This finding highlights the urgent need to facilitate access to qualified veterinary care. Strengthening these services and providing support to producers by competent professionals would be essential levers for promoting the rational management of antibiotics and, ultimately, curbing the spread of AMR [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. According to Ferraz's research, structural factors such as limited access to healthcare infrastructure, inadequate regulatory oversight and the intensification of agricultural practices could be major drivers of increased resistance rates [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA comparison between semi-intensive and traditional farming systems reveals minor disparities in the prevalence of ESBL-producing genes. Both farming methods show high rates of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, with the traditional system even showing slightly higher frequencies (89.3% and 85.7% respectively) than the semi-intensive system (82.1% and 76.9%). Conversely, the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e gene is marginally more prevalent in semi-intensive farming (30.8%) than in traditional farming (25%). Although genetic co-expression is more frequent in the traditional system (21.4%), these overall differences are not statistically significant. These results suggest that, in the context of Burkina Faso, the spread of ESBL-producing bacteria does not depend exclusively on the production model. Rather, it seems to be governed by cross-cutting variables such as antimicrobial use patterns, environmental contamination pressure and animal health management standards [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnalysis of the heat map associated with hierarchical clustering (Fig.\u0026nbsp;3) highlights a distinct structuring of isolates according to their respective hosts. Remarkably, strictly identical phenotypic and genotypic (PCR) resistance profiles were identified within pairs of isolates from sources as varied as cattle, humans, soil and drinking water. Such convergence of profiles was anticipated: it illustrates the dynamics of shared plasmid-mediated resistance genes (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eSHV\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e), whose horizontal transfer promotes inter-species and environmental dissemination [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This finding is corroborated by studies conducted in Ghana and Germany, which have demonstrated a close relationship between isolates of human and animal origin [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These genetic similarities support the hypothesis of bidirectional circulation of resistance genes between these two populations, transcending species barriers [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, these results contrast with certain studies that have shown that the genetic diversity of ESBL-producing \u003cem\u003eE. coli\u003c/em\u003e (ESBL-\u003cem\u003eE. coli\u003c/em\u003e) in humans, poultry and their environment appear to be associated with distinct sequence types (STs) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This divergence highlights that, although the resistance genes may be identical, the bacterial strains that harbour them may belong to different phylogenetic lineages, suggesting a more complex transmission dynamic than simple clonal circulation Despite the identification of identical BLSE genes in animal and human compartments, our study cannot establish formal proof that the resistance observed is of bovine origin or strictly attributable to the farm environment. The homology of genes in livestock and agricultural workers does not, in itself, constitute evidence of zoonotic transfer. It is equally likely that a common source of transmission exists, as suggested by the epidemiological link observed. Furthermore, it is crucial to emphasise that livestock play a role as vectors in the environmental spread of ESBL-producing bacteria, particularly through the spreading of contaminated manure used as agricultural fertiliser. In order to resolve these uncertainties and accurately characterise the transmission dynamics, it is recommended that in-depth molecular investigations be conducted using whole genome sequencing (WGS). This approach will clarify the phylogenetic relationships between ESBL-\u003cem\u003eEc\u003c/em\u003e and ESBL-\u003cem\u003eKp\u003c/em\u003e isolates circulating among animals, humans, soil and water resources [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition, antimicrobial resistance (AMR) spreads through complex networks connecting humans, animals and the environment. These exchanges occur mainly through faecal contamination and the food chain, particularly through the consumption of raw milk or contaminated meat [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. One of the fundamental drivers of this dissemination is horizontal gene transfer (HGT), a mechanism by which bacteria acquire resistance determinants from their counterparts. This process is greatly facilitated by various mobile genetic elements, such as plasmids, bacteriophages, transposons and integrons. Consequently, bacteria develop AMR either through the direct acquisition of pre-existing resistance genes via these genetic vectors, or through the accumulation of mutations under selection pressure [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn in-depth analysis was conducted to assess the direct impact of BLSE genes on increased resistance levels. The results reveal a moderate positive correlation between the presence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and resistance to cefotaxime (CTX) (r\u0026thinsp;=\u0026thinsp;0.48; Fig.\u0026nbsp;4). This association suggests that the expression of this gene, which codes for a specific β-lactamase, is a major determinant of pronounced resistance to this antibiotic in our sample. This could indicate that the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e gene, which is responsible for β-lactamase producing, contributes to more pronounced resistance to this antibiotic. These observations are consistent with the findings of Nossair et al., who reported a similar relationship between the \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e gene and resistance to CTX (r\u0026thinsp;=\u0026thinsp;0.36) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Taken together, these results confirm that various ESBL genes contribute to the emergence of the resistance phenotype, although their respective contributions may vary in intensity.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides tangible evidence of an interconnected antimicrobial resistance (AMR) crisis in Burkina Faso, characterised by the ubiquitous spread of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e genes in human, animal and environmental reservoirs. Our work identifies the agricultural sector as a major driver of this dynamic, while the regional disparities observed highlight the influence of access to healthcare and the heterogeneity of antibiotic use practices across the country. The complexity of this multidimensional threat calls for immediate action based on the One Health approach. On the one hand, it is imperative to regulate the use of antibiotics in the agricultural sector and to set up integrated surveillance systems combining clinical, veterinary and environmental monitoring. On the other hand, improving water treatment infrastructure and the safe management of livestock effluents are crucial to breaking the cycles of transmission. Finally, the systematic application of whole genome sequencing (WGS) will need to be coupled with public health programmes dedicated to the proper use of antimicrobials (stewardship). In conclusion, the fight against AMR in Burkina Faso requires cross-cutting and sustained coordination between human medicine, animal health and environmental management in order to curb the spread of this global health challenge.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript was developed with guidance from the PAPERI–SSI Scientific Writing Workshop (22–25 September 2025), organized by the Pan-African PGS Education and Research Initiative (PAPERI) in collaboration with the Sustainable Sciences Institute (SSI).We would like to thank the managers of the Livestock Technical Support Zones (ZATE) and the farmers involved in the study for their participation and accompaniment at the sites and for facilitating data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors D.S., I.J.O.B., and F.B.J.D. developed the conceptualisation of this study. The methodology was defined jointly by I.J.O.B., D.S., F.B.J.D., and Z.G. The formal analysis and drafting of the first version of the manuscript were carried out by D.S. The entire team was involved in reviewing and editing the text, namely D.S., I.J.O.B., F.B.J.D., Z.G., N.S.S., E.B., N.B., S.S. and M.E.M.N. The work was supervised by Z.G. and I.J.O.B. Finally, all authors have read and approved the final version of the published manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) did not receive any specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed in this study are available from the corresponding author upon reasonable request. All data generated or analysed during this study are also included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cstrong\u003eand consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics committee approval was obtained from the health research ethics committee (CERS) of Burkina Faso (N◦2018-15-1153). The purpose of this study and the sampling procedure were explained to the farmers orally, after which written consent to participate in the study was requested.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAntimicrobials, WL of MI. WHO List of Medically Important Antimicrobials WHO List of Medically Important Antimicrobials A risk management tool for mitigating. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N et al. 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Assessing antibiotic use practices on central Burkina Faso cattle farms and the associated risks to environmental and human health contamination: A pilot study. 2025;11:1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerraz MP. Antimicrobial Resistance: The Impact from and on Society According to One Health Approach. Societies. 2024;14:1\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNossair MA, Abd El Baqy FA, Rizk MSY, Elaadli H, Mansour AM, El-Aziz AHA et al. Prevalence and Molecular Characterization of Extended-Spectrum β-Lactamases and AmpC β-lactamase-Producing Enterobacteriaceae among Human, Cattle, and Poultry. Pathogens. 2022;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDay MJ, Hopkins KL, Wareham DW, Toleman MA, Elviss N, Randall L, et al. 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Front Microbiol. 2020;11:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePandey S, Doo H, Keum GB, Kim ES, Kwak J, Ryu S, et al. Antibiotic resistance in livestock, environment and humans: One Health perspective. J Anim Sci Technol. 2024;62:266\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYadav S, Kapley A. Exploration of activated sludge resistome using metagenomics. Sci Total Environ. 2019;692:1155\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Epidemiology, ESBL, AmpC-β-lactamase, carbapenemases, Escherichia coli, Klebsiella, human, animal, environment, Burkina Faso","lastPublishedDoi":"10.21203/rs.3.rs-8961524/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8961524/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAntimicrobial resistance (AMR) poses a significant threat to global public health. \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) and \u003cem\u003eKlebsiella\u003c/em\u003e species are currently considered as key contributors to AMR and it spread. The objective of this study was to investigate the molecular epidemiology of ESBL, AmpC-β-lactamase and carbapenemase-encoding genes in \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e isolated from animal, human, environmental and drinking water sources. \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e were isolated from a several samples sources, including humans, animals, soil, and drinking water. Molecular techniques, such as PCR, were utilised for the detection of ESBL, AmpC-β-lactamase, and carbapenemase encoding genes detection. Subsequently, resistance profiles were analysed, and a heatmap analysis and hierarchical clustering were performed to assess the relationship between genotypic and phenotypic resistance profiles using R software. Amongst 215 ESBL isolates (90.7% gene-positive), \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e was the most prevalent gene, with a predominance in cattle (\u003cem\u003eE. coli\u003c/em\u003e: 67.7%, \u003cem\u003eKlebsiella\u003c/em\u003e spp.: 20.6%). Sapone exhibited the highest prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e (56.3%) and triple-gene combinations (21.8%). The cluster analysis revealed two key findings: the presence of cattle-specific \u003cem\u003eKlebsiella\u003c/em\u003e spp. and the interspecies clusters. Positive and negative correlations between \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and cefotaxime resistance (r\u0026thinsp;=\u0026thinsp;0.48) and nalidixic acid susceptibility (r=-0.35) respectively was observed. \u003cem\u003eBla\u003c/em\u003e\u003csub\u003eIMP,\u003c/sub\u003e \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC,\u003c/sub\u003e \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eDHA\u003c/sub\u003e were detected with a prevalence not exceeded 1.52%. This study highlighted \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eCTX\u0026minus;M\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eTEM\u003c/sub\u003e as the most prevalent ESBL \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e-producing found in various samples. Low prevalence of AmpC-β-lactamase, and carbapenemase encoding genes were observed. These findings emphasise the critical role of livestock farming, environmental contamination, and horizontal gene transfer in the spread of antimicrobial resistance. In view of these results, ongoing One Health approach should focus on antimicrobial stewardship, environmental monitoring, and improved veterinary and healthcare practices.\u003c/p\u003e","manuscriptTitle":"Molecular epidemiology of ESBL, AmpC-β-lactamase, and carbapenemases-producing Escherichia coli and Klebsiella spp., isolated from human, animal, environment, and drinking water in Burkina Faso","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-05 17:57:09","doi":"10.21203/rs.3.rs-8961524/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":"6f0d1183-3f0f-4146-864f-92036f3f4943","owner":[],"postedDate":"March 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-10T13:55:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-05 17:57:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8961524","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8961524","identity":"rs-8961524","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}