Antimicrobial resistance profiles and genetic basis of resistance among non-fastidious Gram-negative bacteria recovered from ready-to-eat foods in Kibera informal housing in Nairobi, Kenya

Objective This cross-sectional study conducted in Kibera, Kenya, sought to gain insights on relative microbial contamination levels of popular unprocessed food types, determine antimicrobial resistance (AMR) burden and the carriage of integrons that are essential elements for spreading antimicrobial resistance genes (ARG). Foods analysed consisted of cooked vegetables (kale, cabbage, and nightshades), boiled cereal foods (beans, rice, and Githeri, which is a mixture of beans and maize), meat, Omena fish (fried silver cyprinids), and Ugali (a product of simmered maize flour in boiled water). Results The analysis detected contamination levels exceeding 2×104 c.f.u. ml−1 in 106 (38 %) of the 281 ready-to-eat foods analysed. The majority of food types had microbial contaminations of between 4.0×104 and 2.3×106 c.f.u. ml−1. Kale was the most contaminated with a mean of 2.3×106 c.f.u. ml−1, while Omena was the least contaminated with 4.0×104 c.f.u. ml−1. Foods sold close to open sewage and refuse sites were more contaminated than those sold in relatively ‘cleaner’ settings (P <0.0001, O.R 0.1162, C.I 0.1162–0.120). A total of 405 bacterial isolates were recovered and included; Klebsiella spp 116 (29 %), Escherichia coli 104 (26 %), Enterobacter agglomerans 88 (22 %), Proteus mirabilis 30 (7 %), Salmonella spp 28 (7 %), Citrobacter freundii 27 (7 %) and Serratia marcescens 12 (3 %). Imipenem (IPM, 100 %) was the most effective antimicrobial agent, followed by cefepime (98 %). Ampicillin (AMP, 33 %), trimethoprim (TMP, 27 %), and sulfamethoxazole (SMX, 23 %) on the other hand, were the least effective antimicrobials. The analysis also found ten isolates (2 %) that had co-resistance to third-generation cephalosporins, fluoroquinolone (CIP), quinolones (NAL) and aminoglycosides (GEN); hereby we refer to this phenotype as the βFQA. The prevalence of multidrug-resistant (MDR) strains was 23 % (93), while that of extended-spectrum β-lactamases (ESBL) producing strains was 4 % (17). The bla TEM was the most prevalent (55 %) β-lactamase (bla) gene among the screened 93 MDR-strains. Carriage of class one integrons (intI1) was more common (23 %) than intl2 (3 %) among these MDR-strains. Bacterial diversity analysis using the GTG5-PCR found no significant clusters for analysed E. coli and K. pneumoniae, suggesting recovered isolates were genetically diverse and not due to non-clonal expansion. The findings of this study are an indication that contaminated foods can be a reservoir for enteric pathogens and a source of AMR strains.


BACKGROUND
The World Health Organization (WHO) estimates that more than 600 million persons worldwide suffer foodborne infections every year, and 420 000 die as a result. Human food may be contaminated at the farm, mainly when unsafe irrigation water is used, at various points in the supply chain, during processing, or due to unhygienic handling [1,2]. Foodborne diseases cause massive economic losses.
The World Bank estimates a total productivity loss of $95.2 billion and an additional $110 billion in treatment annually only in low and middle-income countries [3]. The African continent is most affected by these foodborne diseases partially due to poor urban sanitation. Informal housing characterized by poor planning and lack of proper sanitation infrastructures such as sewage drainage, OPEN ACCESS inadequate clean water supply, poor hygiene, and environmental pollution are the most affected.
Although food contamination includes chemical substances, parasites, and viruses, bacterial contaminants and their toxins are responsible for most foodborne illnesses [4]. Enteric bacteria, in contrast to Gram-positive bacteria, have so far been the most prevalent causes of foodborne illnesses, perhaps due to their abundance in the environment and faecal contamination (WHO fact-sheet/food-safety, 2020). This microbial contamination is higher among ready-to-eat foods sold in many informal housing streets due to unhygienic preparing and serving environments. These street foods are particularly popular in many informal housing areas in Sub-Saharan Africa, partially due to their affordability and retail convenience [5]. However, many of these food-vending points have an open space layout and are often close to refuse sites and over-flowing sewage that further poses a risk of cross-contamination. Unsafe waste disposal, dust, prolonged storage of cooked food without proper refrigeration, and food exposure to vectors also act as possible contamination sources [6]. Therefore, there is a high possibility that foods consumed in such settings are contaminated with microbial agents that may emanate from the immediate surrounding environment. In resource-poor countries, simple fingerprinting methods such as the GTG 5 PCR can be used to assess possible crosscontamination of ready-to-eat unprocessed foods with bacterial contaminates. Although this technique is not as sensitive as those based on whole-genome sequencing and analysis, it gives a preview of possible genetic diversity of bacterial population sets, predicting outbreaks and expansion of significant clones.
The gradual increase of foodborne infections has led to heavy antibiotic reliance across the globe, leading to antimicrobial resistance build-up in previously sensitive bacterial strains [7]. Foodborne pathogens such as Salmonella spp are increasingly becoming resistant to broad-spectrum antimicrobial agents such as cephalosporins (third-and fourth-generation), aminoglycosides (Gentamicin), and fluoroquinolone (Ciprofloxacin) [8]. These three classes of antimicrobial agents are widely used in Kenya to treat infections, especially in hospital settings. Therefore, co-resistance to β-lactams, aminoglycosides, and fluoroquinolone in bacterial strains (hereby referred to as the βFQA phenotype) reduces treatment options leading to poor treatment outcomes. The heavy usage of human medicine in animal feed production, veterinary, and agriculture have also been determined to be sources of emergence and spread of antimicrobial-resistant bacterial strains [9,10]. Antimicrobial resistance, especially among Gram-negative bacteria, is also facilitated by exchanging resistance genes within and across species. This exchange is predominantly mediated by horizontal transfer of genes carried on integrons that may, in turn, be carried on conjugative plasmids. These integrons are gene capture systems in the form of resistance gene cassettes and can accumulate and disseminate antimicrobial resistance genes [11]. Although more than nine integron classes have been documented to date, classes one and two have widely been heavily implicated in antimicrobial resistance (AMR) [12,13]. Integrons have been documented in clinical settings and animal isolates in Kenya, but little is known about carriage in foodborne isolates [14][15][16]. Furthermore, data on food contamination and the diversity of bacterial species recoverable from street foods remains scarce in Kenya. Surveillance of food contamination and bacterial strains' resistance profiles is essential in food safety and contamination prevention measures.
The current study sought to determine the diversity of non-fastidious Gram-negative bacteria, common etiological agents of foodborne infections, and establish their associated antimicrobial resistance patterns. The study also analysed the carriage of β-lactamases genes and possible clonal relatedness of isolates recovered from different readyto-eat foods in a slum setting. Microbial contamination and diversity data in ready-to-eat street foods have the potential advantages of forming the basis for launching antimicrobial resistance surveillance systems. This could help in the early detection of foodborne outbreaks and identify possible hotspots where multidrug-resistant strains may arise and cause outbreaks that could be difficult to treat.

METHODOLOGY Study site
This cross-sectional study was conducted in Kibera, informal housing located in the south west of Nairobi Central Business District. Kibera is the most extensive informal housing in Kenya, with a population of close to a million, with the vast majority living below the poverty line. These informal housings have poor sanitation infrastructure characterized by poor sewage drainage, uncollected refuse, and chronic water shortages. Most street foods sold in this slum are prepared and served close to open and burst sewers, potentially putting consumers at risk of foodborne infections.

Study approval
Ethical clearance was obtained before the study commenced from the scientific ethical review unit of Kenya Medical Research Institute (KEMRI SERU), approval number KEMRI/ SERU/CMR/POOO55/3514 [17].

Sample collection
This study obtained 281 ready-to-eat unprocessed food samples in Kibera informal housings between July to November 2017. A convenient sampling strategy was applied and involved randomly selecting vending points approximately 50 metres apart. Sample collection was done across all 13 villages that make up Kibera's informal settlements to ensure proper representation. Foods collected in this study were cooked vegetables (kales, cabbage, and nightshades) and boiled cereal foods (beans, rice, and Githeri, which is a mixture of beans and maize). Other food samples collected include Omena fish (fried silver cyprinids, meat and Ugali (a product of simmered maize flour in boiled water). About 25 g ml −1 of a food sample was collected using a sterile spoon, put in a sterile container, and transported in a cool box to the laboratory within 3 h. The global positioning system (GPS) coordinates of each sampled site were collected, and MDR hotspots mapping was done using the Micro-react online tool, Fig. 1.

Sample processing
Microbial food contamination levels were assessed using the Enterobacteriaceae-specific 3M Petri film plates (Petrifilm Agua, USA). A 10 g ml −1 of food specimen was added into a stomacher bag containing 90 ml of sterile normal saline (0.85 % sodium hydroxide from Sigma-Aldrich), then homogenized for 1 min using a stomacher machine (Seward). A 1 ml of the homogenate was then serial diluted six-fold. An aliquot of 0.1 ml from the sixth dilution was spread on a 3M Petri-film plate and incubation done aerobically for 24-48 h at 37 °C.
For bacterial isolation, 0.1 µl of the homogenized sample was plated directly onto MacConkey (Oxoid, UK) and Eosin Methylene Blue Agar (Oxoid, UK), and incubation was done at 37 °C for 24 h. Non-duplicate isolates were then subjected to Gram-staining and biochemical test panels that included triple sugar agar iron, citrate, urea, and sulphur indole motility tests for bacterial species identification [18]. Microbial contamination levels were classified according to guidelines stated by the hazard analysis and critical control point system (HACCP) by the Food and Agriculture Organization (FAO). A microbial contamination level of ≤10 2 c.f.u. ml −1 was considered acceptable for human consumption. In contrast, foods with a 10 3 c.f.u. ml −1 value and beyond were deemed to be unacceptable for human consumption [19].

Antimicrobial susceptibility testing
Antimicrobial susceptibility testing (AST) was done for all isolates against significant classes of antimicrobials (Oxoid, UK) on Mueller-Hinton agar (Oxoid, UK) using the disc diffusion technique (Table 1). Emulsifying pure bacterial colonies in 3 ml sterile normal saline made a 0.5 turbidity McFarland standard. A sterile cotton swab was immersed in the 0.5 McFarland suspension and spread on Mueller Hinton agar plate to ensure confluent growth. Antimicrobial discs (Oxoid, UK) were placed using a disc dispenser and plates incubated at 35 °C for 12-18 h. The zone of inhibition was measured in millimetres across the diameter. A commercial E. coli American-type culture collection (ATCC 25922) strain was used for quality assurance of the media and antimicrobial disc potency. The measured zones of inhibition interpretation were based on the Clinical and Laboratory This Kibera informal settlement map shows sampling points of ready-to-eat unprocessed foods. The sites were selected across various villages in Kibera slums based on location and hygiene characteristics. The map shows that most of these vending points are more concentrated at populated sections of the informal housings where consumer's availability is high. This has constrained available resources leading to chronic water shortages and accumulation of refuse that is close to the vending points (within 10 metres radius). It was also noted that these vending points are also very close to open sewage.
Standards Institute (CLSI) 2017 guidelines [20]. Isolates resistant to ampicillin and any or all third-generation cephalosporins were presumed as extended-spectrum β-lactamases producers. Confirmation of presumed ESBL phenotype was done by double-disc synergy test. This was done by placing CAZ, CRO and CTX 30 mm apart from centrally placed AMC [21]. A positive test was indicated by the presence of a synergy zone between cephalosporin and clavulanic inhibitor (Fig. 2). Isolates with combined resistance to β-lactams, fluoroquinolone, and a broad-spectrum class of aminoglycosides such as gentamicin were denoted as βFQAstrains. In contrast, those that were resistant to ≥3 classes of antimicrobial were indicated as multidrugresistance (MDR) strains.

Screening for β-lactam antimicrobial resistance genes (ARG)
A total of 93 isolates that were resistant to multiple-drugs (MDR) were selected for the screening of carriage of ARG and integrons. DNA extraction was done using the boiling method as previously described [22]. Briefly, a loopful of pure culture was emulsified in 1 ml distilled DNase/ RNase-free water and boiling done at 95 °C for 15 min in Table 1. Antimicrobial agents tested against Gram-negative isolates in this study; this table shows the 13 antimicrobial agents belong to different classes tested against recovered Gram-negative bacteria isolates. Using the Kirby Bauer technique, the disc diffusion method was used in this antimicrobial sensitivity testing (AST) a heating block. Centrifuging for 5 min at 14 000 rotations per minute did the separation of bacterial cell debris and DNA. Extracted DNA stained with sybr green was run on gel electrophoresis to determine yield and quality as previously described [23]. This study screened for carriage of bla TEM , bla CTX-M , bla SHV , and bla OXA-1 ARGs that are heavily implicated in resistance towards β-lactams in Kenya [24]. The isolates were also screened for carriage of class I and II integrons associated with MDR strains in Gram-negative bacteria.
The polymerase chain reaction (PCR) preparation consisted of 12 µl master mix (Sigma-Aldrich) (DNA polymerase, dNTPs, MgCL 2 and buffer), 12 µl DNase free PCR water, and 1 µl of forward and 1 µl of reverse primers previously published (Table 2) [25][26][27][28]. Amplification was done under the following conditions; initial denaturation at 95 °C for 2 min, annealing at 50-62 °C for 1 min (depending on the target gene and the primer), extension at 72 °C for 1 min for 30 cycles, and a single final extension step at 72 °C for 15 min.

Assessment of bacterial diversity
The (GTG) 5 -PCR fingerprinting method was used to evaluate bacterial diversity and possible genetic similarities among isolates of the same species using primers listed in Table 2 as described in a previous study [26]. The GTG 5 is a method of repetitive extragenic palindromic PCR that amplifies the GTGGTGGTGGTGGTG (GTG 5 ) repetitive segments present in the bacterial genome [29]. This molecular tool is useful in the differentiation of bacterial strains of the same species. The oligonucleotide primer's binding enables the amplification of DNA fragments of varied sizes detected as multiple bands on a gel electrophoresis image.
E. coli and K. pneumoniae are good indicators of community antimicrobial resistance and were thus used to predict recovered isolates' genetic diversity. Therefore, selected E. coli (8) and K. pneumoniae (11), resistant to at least three antimicrobial classes, were analysed to establish diversity and possible genetic relatedness. PCR amplification for the (GTG) 5 -PCR protocol was conducted under the following conditions: initial denaturation at 95 °C for 5 min, annealing at 40 °C 1 min, extension at 65 °C for 8 min for a total of 30 cycles, and a single final extension step at 65 °C for 8 min.

Analysis of PCR amplicons
PCR amplicons were separated by running in agarose gel at 100 volts for 1 h (1% for GTG 5 -PCR and 1.2 % for ARG PCR). Visualization of banding patterns was done using a Gelmax UV imager. Cluster analysis of GTG 5 banding patterns was done using bionumeric software version 6.6 (Gelcompar2 Fig. 2. Escherichia coli producing extended-spectrum β-lactamases; shows an extended-spectrum β-lactamases producing Escherichia coli phenotype characterized by resistance towards penicillin (ampicillin) and third-generation cephalosporins (CAZ, CRO and CTX). The isolate was also resistant to more advanced fourth-generation cephalosporin (cefepime). There were synergistic reactions indicated by the ghost zones between cephalosporins and amoxicillin-clavulanic acid.
software). Similarity based on banding patterns was set at a threshold of 95 %, as previously described [30].  (Table 3).

Microbial food contamination in relation to vending point proximity to surrounding features
This study found that foods sold close to sewage and refuse sites were the most contaminated, with a mean c.f.u. ml −1 of 5.5×10 5 and 5.1×10 5 , respectively (
Among the ten food types collected and analysed in this study, kale followed by meat isolates were the most resistant overall. In contrast, rice, Ndengu, and Ugali isolates were the least resistant ( Table 7). The analysis also showed that isolates from kale samples were also the most resistant to broad-spectrum antimicrobial agents; AMC 13 %, GEN 7 %, CIP 6 %, FEP 4 %, and CAZ 4 % (Table 7).

Analysis of clustering patterns in selected bacteria species
A similarity matrix of less than 40 % was noted among ndicating low genetic similarity. Tw. coli isolates obtained from various food types across Kibera slums (Fig. 4). The analysis revealed no evidence of the proliferation of specific E. coli clones. E.coli isolates in this dendrogram were resistant to ampicillin, trimethoprim, and sulfamethoxazole in addition to other varying antimicrobial agents, indicating low genetic similarity. Two K. pneumoniae from Omena (Silver cyprinid) and beans foods had a similarity of 80 % likely suggesting microbial cross-contamination (Fig. 5). Most isolates in the K. pneumoniae dendrogram had a similarity range of 40-80 %, and 50 % of these isolates were resistant to ampicillin, trimethoprim, and sulfamethoxazole.

DISCUSSION
The mean contamination of between 4.0×10 4 c.f.u. ml −1 and 2.3×10 6 c.f.u. ml −1 among food analysed in this study are close to the 6.7×10 5 to 1.7×10 6 c.f.u. ml −1 recorded for fish foods in Ethiopia [31]. Among the cereal-type foods, the highest contamination was recorded in beans with a mean of 3.4×10 5 c.f.u. ml −1 , which is lower than 8.1×10 3 c.f.u. ml −1 reported in maize/beans (Githeri) in Mukuru slum in Kenya [32]. Vegetables such as kale were the most contaminated food type with a mean value of 2.3×10 6 c.f.u. ml −1 , close to 6.8×10 6 c.f.u. g −1 recorded in South Africa among the same food type [33]. These findings affirm the World Health Organization (WHO) 2008 Report which indicated that leafy vegetables pose a higher risk of foodborne infection in humans. Microbial contamination of vegetables has previously been attributed to unsafe urban irrigation using sewage water often contaminated with human excreta [34]. This study ratifies that most street foods sold in Kibera are highly contaminated, which is likely to increase diarrhoea cases and other gastrointestinal infections [32,35]. We also recovered some pathogenic strains such as Salmonella spp that have a low infection dose, which further increases the risk of foodborne infections. Notably, diarrhoea is a significant cause of morbidity and mortality in developing countries, with Shigella, E. coli, and Salmonella genera documented as the primary etiological agents in slums such as Kibera [36].
A significant association in microbial contamination to the immediate unhygienic vending environment was noted. A similar study in Kenya has also indicated that foods sold close to refuse sites and burst sewers are more contaminated, which calls for improved sanitation and hygiene standards [37]. We also noted that most vendors lack a constant supply of clean water for washing raw foods and utensils. Poor sanitation and chronic water shortages have been identified as significant contributors to enteric infections in slums such as Kibera [38]. Similarly, our previous study reported a diverse range of MDR bacteria belonging to Salmonella spp, Shigella spp, E. coli, and Klebsiella spp from sewage, sludge, and soil in Kibera near these food vending points [39]. Therefore, there is an excellent possibility that most of the enteric isolates among these foods emanate from unhygienic surroundings. Although we did not screen for virulence genes in recovered isolates, consumption of foods contaminated with Salmonella spp may particularly have the potential to cause gastrointestinal infections and death. Notably, Salmonella spp in this study were recovered without the usual 24 h enrichment in modified Rappaport Vassiliadis protocols recommended for Salmonella spp recovery from contaminated food and therefore, it is possible    Table 6. Relative abundance (%) of isolates antimicrobial resistant from ready-to-eat foods: non-duplicate colonies from the primary plate were subjected to susceptibility testing against some of the most commonly used antimicrobial agents. Antimicrobial activity of these isolates was tested against 15 drugs belonging to penicillin, 17 (4) 7 (2) 17 (4) 7 (2) 21 (5) 46 (11) 39 (10) 15 (4) 40 (10) 10 (2) 36 (9) 0(0) 95 (23) 110 (27) C. freundii   Table 7. Relative abundance in antimicrobial resistance among isolates recovered from the various foods types: the table shows the antimicrobial resistance abundance of various isolates recovered from the ten food sample types collected in this study. The acronym 'n' used in this table indicates the count of bacterial isolates recovered from each of the ten food types collected and analysed in this study 17 (17) 13 (13)   7 (7) 13 (13) 6 (6) 11 ( 17 (4) 7 (2) 17 (4) 7 (2) 21 (5) 46 (11) 39 (10) 13 (3) 40 (10) 10 (2) 36 (9) 0 (0) 95 (23) 110 (27) that occurrence of this pathogen in our food specimen could be higher than that reported.
Our isolates were more resistant to ampicillin, trimethoprim, and sulfamethoxazole. This finding is similar to previous findings in Kenya that recorded 34 % resistance towards AMP and 49.4 % towards sulfamethoxazole-trimethoprim among E. coli isolates from raw chicken [40]. Therefore, it is likely that bacteria strains circulating in Kenya have built resistances towards these antimicrobial agents; however, these assumptions need to be ascertained through further research. Compared to Odwar et al. (2014), our study recorded higher resistances towards amoxicillin-clavulanic acid (AMC 11 % vs. 2.6 %), ceftazidime (CAZ 2 % vs. 0 %), and gentamicin (GEN 5 % vs. 0.6 %). A similar study in Ethiopia has documented higher resistances of up to 80 % for ampicillin, 14.3 % for ceftriaxone and 9.5 % for gentamicin in E. coli from fish [31]. The variation in antimicrobial resistance abundance strongly indicates microbial isolates in these regions are evolving and developing antimicrobial resistance independently and is likely to reflect a pattern of antimicrobial usage and AMR burden, but these assumptions remain to be elucidated as well.
Our recent study among Gram-negative isolates from sewage, sludge, and soil recovered near these vending points revealed high resistances towards ceftazidime (9 %), ceftriaxone (12 %), amoxicillin-clavulanic acid (16%), gentamicin (11%) and ciprofloxacin (8%) [39]. Taken together, these results could be an indication that the resistant strains may be emanating from the immediate surroundings to contaminate slum foods.  Resistances of up to 2 % towards ceftazidime, ciprofloxacin, and 9 % against aztreonam have been documented in Klebsiella species from stool samples in Kenya [41]. These resistances are similar to those recorded in food isolates in our study and also suggest a high possibility that such isolates may also have a clinical origin. Findings in this study indicated that carbapenem (imipenem) is still effective against recovered isolates (100 %). However, co-resistance to β-lactams, aminoglycosides, and fluoroquinolone, commonly available and used antimicrobial agents in Kenya, is worrying [42]. There is a great risk of treatment failure of infections caused by the ESBL and βFQA phenotypes emanating from the consumption of foods contaminated with such enterics [43].
In the current study, the prevalence of class integrons was higher than that of intI2 in Gram-negative isolates, and this correlated with the findings of another study in Iran [44]. Although we did not establish recovered integrons' resistance cassette content, the drfA1-sat2-aadA1, sat2, sat1-aadA1 cassettes in class two integrons have previously been associated with resistance towards sulfonamides and β-lactams [45]. Most isolates that carried class two (intI2) integrase were also positive for intI1 carriage. Therefore, bacterial strains that carry these integrons have a high potential to capture, accumulate, and express ARG leading to AMR emergence. If these integrons are contained in mobile plasmids, these resistance genes can be spread between and across species, consequently worsening AMR's menace. A study in South Africa has also reported carriage of bla CTX-M , bla TEM , bla SHV , bla OXA and intI1 in E. coli and K. pneumoniae isolates from spinach samples [46]. These β-lactams genes code for antimicrobial resistance enzymes that have been associated with resistances in diverse β-lactam antibiotics such as ampicillin, ceftriaxone, cefotaxime and ceftazidime [14].
Fingerprint analysis revealed no significant clones of E. coli and K. pneumonia. These findings suggest that the MDR, βFQA, and/or ESBL phenotypes may be spreading through horizontal or vertical gene transfer mechanisms rather than through the expansion of significant clones. However, a few isolates from different food types had similar resistances suggesting that major food types may have been contaminated from a common source, which we suspect to be the water used for cooking and food preparation.

CONCLUSION
This study's high relative microbial contamination indicates that many foods served and prepared in Kibera Street are unsafe for human consumption. Therefore, affirmative action needs to be taken by public health officials to ensure food safety awareness and hygiene. Deliberate efforts geared towards improved sanitation infrastructure such as organized refuse collection and proper sewage drainage also need to be enforced. Future studies in the informal settlements should also establish the possible origins of multidrugresistance strains, especially in hotspot areas identified by this study.

Study limitations
(1) This study could only screen for the carriage of selected β-lactamase genes; therefore, the full array of antimicrobial resistance genes in recovered isolates is unknown. The whole array of antimicrobial resistance genes can help justify the observed resistance phenotypes. (2) The GTG 5 low resolution fingerprinting technique was used to establish the diversity of recovered bacterial isolates. Therefore, future studies should use highresolution techniques such as SNP typing and wholegenome sequencing to provide insight into recoverable isolates' genetics. Such methods could shed more light on the isolates' transmission pathways, the potential for isolates as pathogens, and the profound molecular basis of resistance. (3) While sample collection was done in 2017, findings dissemination was done in 2021; the data should be updated by conducting frequent surveys. However, data generated in this study forms a basis for robust future studies.