Introduction Food and water safety is an important component of public health and economic prosperity. A large proportion of contaminated food results in diarrheal diseases, with diarrheal disease agents accounting for 550 million of the 600 million cases of foodborne illness [ 1 ]. Each year, an estimated 600 million people fall ill and 420,000 people die from unsafe food [ 2 ].
Global Burden of Foodborne Diseases report estimated that 111 million illnesses and 63,000 deaths are caused by diarrhoeagenic E. coli globally each year [ 3 ]. Low- and middle-income countries (LMICs) bear the highest burden of diarrheal disease, predominantly caused by E. coli [ 4 ]. The sale of ready-to-eat street food represents an important source of income in many developing countries, however, studies have highlighted street foods as a major public health risk [ 5 ].
In Kenya, diarrheal diseases rank as the third most significant cause of pediatric morbidity and mortality, after malaria and tuberculosis [ 6 ]. E. coli is a major contributor to ill health, including neonatal meningitis, urinary tract infections (UTIs), pyelonephritis, cystitis, septicemia, and traveler’s diarrhea [ 7 ]. Exposure to E. coli most commonly occurs through ingesting contaminated food and water.
Previous studies have indicated that pathogenic strains of E. coli develop from commensal/naïve bacteria by acquiring specific virulence genes and operons either on the chromosome or through extra-chromosomal elements [ 8 ]. Diarrheagenic E. coli is categorized into five distinct pathotypes based on their clinical manifestation’ phenotypic traits, epidemiological evidence, and virulence factors specific to each pathotype [ 9 ]. They include; Enteroaggregative (EAEC), Shiga-toxigenic (STEC), Enteroinvasive (EIEC), Enteropathogenic (EPEC) and Enterotoxigenic (ETEC).
Antibiotic treatment is the primary method for preventing and managing bacterial infections. However, the growing antibiotic resistance among bacterial pathogens transmitted through food poses a major challenge, leading to increased mortality and morbidity from foodborne illnesses resulting in high socioeconomic costs [ 10 ]. Different studies conducted on different items of ready-to-eat foods vended on the street in low-income countries, revealed different levels of contamination and the majority of foodborne bacterial pathogens were resistant to commonly prescribed antibiotics [ 11 ].
The emergence of antimicrobial resistance has led to challenges in the management of infectious diseases that affect both animals and humans [ 12 ]. The World Health Organization has ranked E. coli as the second most important pathogen globally that is resistant to antimicrobials [ 13 ]. The spread of antimicrobial resistance in pathogenic strains of E. coli is critical because infections caused by these strains are often harder to treat, resulting in increased severity and duration of infection [ 14 ].
One important group of antimicrobial-resistant E. coli is the ESBL-producing E. coli [ 15 ]. Since bacteria are highly prone to exchanging genetic material, these resistance genes are easily disseminated between bacteria [ 16 ]. The rise of multidrug-resistant E. coli strains poses a significant public health challenge and complicates the management of serious infections [ 17 ].
In Kenya, there is evidence of multidrug-resistant E. coli isolated from clinical and environmental samples [ 18 ]. The prevalence of diarrheagenic E. coli (DEC) and its resistance profiles from street food and water is not well known especially in low-resource settings such as slums. The present study sought to determine the occurrence, distribution and AMR profiles of DEC pathotypes in street foods and water samples from Mukuru informal settlement.
This study investigated multidrug-resistant E. coli and the prevalence of pathogenic E. coli isolated from street food and water samples in the Mukuru informal settlement in Nairobi. Materials and methods Study site and design This was a cross-sectional study where samples were randomly collected from food vendors and water samples from boreholes in Mukuru Informal settlement. Mukuru is located 20 km East of Nairobi city center.
With a population of approximately 150,000, it covers an area of approximately 2 km 2 (population density, 75,000/km 2 ) [ 19 ]. Only 1% of residents in Mukuru have access to a private or individual water source. There is an average of 234 households per public water tap in Mukuru and the households are water insecure, since they have access to 1.8 cubic meters of water per month, while the international recommendation for health and hygiene is 4 cubic meters per month [ 20 ].
Sample collection We standardized the SaniPath protocol [ 21 ] that has been applied in exposure assessment to obtain our samples ( S1 Fig ) [ 21 ]. After obtaining verbal consent, we collected the street food vendors prepared as a single serving and aseptically poured/placed the food into a 500 mL Whirl-Pak bag. Drinking water was collected from communal municipal water points into a 500 mL Whirl-Pak bag while wastewater sampling points were randomly selected based on areas where human interaction was most frequent.
The study employed the Fischer formula n = Z 2 PQ/d 2 to determine a sample size of 384 where n is the estimated sample size, Z is the Z-score corresponding to the desired confidence level (1.96 for a 95% confidence level), P is the estimated proportion (0.50 or 50% in this case since no previous estimate is available), Q is the complementary probability to P, which is equal to 1 -P and d is degree of accuracy (0.05 at 95% confidence level) Samples were then aseptically transported to the KEMRI microbiology laboratory in cooler boxes and processed within six hours of sample collection. Laboratory analysis. Samples from street foods were rinsed in distilled water and then a loopful of the 10 mL of rinse solution was cultured in Chromocult® Coliform Agar (Millipore at # ISO 9308−1).
Water samples were cultured directly in Chromocult® Coliform Agar. After 18 hours of incubation, E. coli suspects (blue colonies) were sub-cultured on Muller Hilton agar and incubated for 18hrs. E. coli identification was done using analytical profile index (API) 20E strips (bioMerieux, Inc., Durham, North Carolina, United States).
DNA was extracted from pure E. coli colonies using the boiling method [ 22 ]. Briefly, a loop full of the colony was suspended in 200 µl of PCR water in an Eppendorf tube and heated at 95°C or 8 minutes on a heating block. Centrifugation was then done at 15,000g for 5 minutes at 25°C.
The DNA-containing supernatant was aliquoted to a sterile Eppendorf tube. Detection of E. coli pathotypes. Multiplex polymerase chain reaction assays were used for the detection of five types of DEC as previously described [ 23 ].
Multiplex was done in EPEC, ETEC, and EIEC while singleplex was done on EAEC and STEC. The targeted genes for the pathogenic E. coli strains ( Table 1 ) included ETEC ( lt encoding heat-labile enterotoxins), STEC ( stx 1 encoding Shiga-toxin), EPEC ( bfp encoding bundle forming pili), EAEC ( aggR encoding transcription regulator for aggregative adherence fimbria I), and EIEC ( ipaH encoding invasion plasmid antigen H). All E. coli isolates and positive controls ( E. coli ATCC 25922) for each of the genes tested had their DNA extracted using the boiling method as previously described [ 22 ].
PCR water was used as a negative control. The cycling conditions for all the PCR amplifications of pathotypes genes were as follows: 94˚C for 5 minutes for initial denaturation and 30 cycles of 95˚C for 30 seconds (denaturation), annealing at 62˚C for 1 minute (for other primers) and 72˚C for 1 minute 30 seconds (extension), followed by 72˚C for 10 minutes (final extension); performed in 0.2 mL Eppendorf PCR tubes in a thermal cycler (MJ Research PTC-200). Amplified PCR products were separated and visualized by electrophoresis using 1% agarose tris-acetate-EDTA gel containing 0.5 μg EtBr staining.
A 100–1,000 bp DNA ladder (Fermenters) was used to determine molecular weight. 10.1371/journal.pone.0340081.t001 Table 1 Escherichia coli pathotypes genes analyzed and the primers. Genes Primer sequence (5’-3’) Product size (Bp) Annealing temp Reference bfpA F: AATGGTGCTTGCGCTTGCTGC 324 60 [ 24 ] R: CCGCTTTATCCAACCTGGTA stx1 F: AGTTAATGTGGTGGCGAA 817 58 [ 25 ] R:GACTTGCCGCTTCCAT aggR F: GTATACACAAAGAAGGAAGC 254 58 [ 25 ] R: ACAGAATCGTCAGCATCAGC LT F: GCACACGGAGCTCCTCAGTC 218 60 [ 25 ] R: TCCTTCATCCTTTCAATGGCTTT IpaH F- AGGTCGCTGCATGGCTGGAA R- CACGGTCCTCACAGCTCTCA 99 61 [ 26 ] Antibiotic susceptibility testing.
The antimicrobial sensitivity profiles of all the isolated E. coli isolates were performed using the Kirby Bauer disk diffusion method against 12 antibiotics according to the Clinical and Laboratory Standards Institute guidelines [ 27 ]. There were seven drug classes tested: Beta-lactam, Amoxicillin + Clavulanic acid AMC (30 µg).; ampicillin AMP (10 µg); ceftriaxone CRO (30 µg); ceftazidime CAZ (30 µg), cefotaxime CTX(30 µg), cefpodoximine CPD(10 µg) Aminoglycosides (gentamicin CN(10 µg), Quinolones (nalidixic acid NA(30 µg); ciprofloxacin CIP(5 µg), Sulfonamides (trimethoprim-sulfamethoxazole STX (25 µg), Macrolides (azithromycin(15 µg), Phenicols (chloramphenicol CHL (30 µg). Tetracyclines (tetracycline TCY (30 µg) guidelines were provided by the Clinical and Laboratory Standards Institute (CLSI) in 2023.
E. coli ATCC 25922 was used as a positive control. MDR was defined as resistance to at least one antibiotic from different antibiotic classes. The zones of inhibitions were measured and interpreted using CLSI M100.
Isolates that were resistant to 3 rd cephalosporin were scored as ESBLs (Extended Spectrum Beta-lactamase). Screening for extended-spectrum β-lactamase. Phenotypic methods were used for further confirmation of β-lactamase production for all the isolates showing resistance to 3 rd generation cephalosporin, namely ceftazidime, cefotaxime, and ceftriaxone.
A combination of clavulanic acid (10 µg) and ceftazidime (30 µg) was used. Both discs were placed on Muller Hinton agar plates which were earlier swabbed by respective cultures and incubated for 24 hours at 37°C. More than 5 mm increase in the zone diameter for ceftazidime-clavulanic acid was considered positive ESBL production.
ESBL detection and ESBL-associated genes ( bla CTX-M , bla TEM , and bla SHV ) were detected using conventional PCR and previously described primers. Table 2 [ 19 ] 10.1371/journal.pone.0340081.t002 Table 2 Resistance genes analyzed and the primers used. Target Gene Primer sequence (5’-3’) Product size bp Annealing temp (°C) References bla TEM F: GCGGA ACCCCTA TTTG 1120 62 [ 25 ] R: TCTAAAGTATATATGAGTAAACTTGGTCTGAC bla CTX-M F: ATGTGCAGGACCAGTAARGTATGGC 593 58 [ 25 ] R:TGGGTRAARTARGTSACCAGAAYCAGCGG bla SHV F:TTCGCCTGTGTATTATCTCTCCTG 854 58 [ 25 ] R:TTAGCGTTGCCAGTGTYTCG Data analysis.
Descriptive analysis was used to show the distribution of E. coli and E. coli pathotypes per samples. Inferential statistics, using Pearson’s chi-square test, were applied to assess associations between: sample type and E. coli positivity, E. coli pathotype and detection rate, and sample type and antibiotic resistance. Antimicrobial-resistant patterns were interpreted and analyzed using the M 100 Clinical and Laboratory Standards Institute (CLSI 2022) and also analyzed using WHONET 2024 https://whonet.org/ .
Ethical considerations. Ethical approval was obtained from the institutional review board at Kenya Medical Research Institute; Scientific and Ethics Review Unit (KEMRI/SERU/CMR/P00240/4770). Verbal informed consent was sought from the street food vendors before buying the street foods.
Results Distribution of E. coli and DEC in Street food and water samples A total of 384 samples (wastewater, drinking water, and street food (fries, githeri and mandazi]) each 77, were collected and analyzed. Of these 384 samples, 62 (16.1%) were positive for E. coli . Majority (58.1%, 36) of the 62 E. coli- positive samples were wastewater samples, with drinking water constituting 25.8% of the E. coli- positive samples ( Table 3 ).
Additionally, DEC pathotypes were detected in 77.4% (48/62) of the E. coli -positive samples. Wastewater samples had the highest proportion (64.6%, 31/48) of DEC isolates, with no DEC being detected in French fries ( Table 3 ). 10.1371/journal.pone.0340081.t003 Table 3 Distribution of E. coli and DEC from different samples.
Sample Type E. coli -positive samples ( N = 62) n (%) DEC-positive samples ( N = 48) n (%) Wastewater 36 (58.1) 31 (64.6) Drinking water 16 (25.8) 11 (22.9) French fries 1 (1.6) 0 Mandazi 3 (4.8) 2 (4.2) Githeri 6 (9.7) 4 (8.3) Distribution of DEC recovered from different samples collected Five DEC pathotypes were detected, with ETEC being the most prevalent pathotype (69%, 33/48), followed by STEC 52% (25/48) Fig 1 . ETEC was common across all samples while hybrid pathotypes were detected in 30 isolates. All five pathotypes were detected in wastewater isolates with ETEC being the most predominant pathotype.
In drinking water and mandazi, four pathotypes were detected while githeri had three pathotypes, as shown in Fig 2 . 10.1371/journal.pone.0340081.g001 Fig 1 This graph illustrates the overall prevalence of E. coli pathotypes identified from the analyzed samples(Street food and water samples) in Mukuru Informal Settlement, Nairobi, Kenya. 10.1371/journal.pone.0340081.g002 Fig 2 Presents the prevalence of E. coli pathotypes across different sample types collected in Mukuru informal settlements, Nairobi.
Hybrid pathogenic types detected Of the 48 DEC isolates identified, 30 had a combination of multiple genes resulting in hybrid pathogenic types made of two, three and four pathotypes(S2). The most diverse hybrid pathotypes were found in E. coli isolates recovered from wastewater, as shown in Fig 3 . The hybrid strains in githeri and mandazi samples were relatively low compared to other sample types.
ETEC, STEC, and ETEC, EIEC were the most prevalent hybrid combinations with a prevalence of 23% (7/30) ETEC, STEC, EIEC had a prevalence of 20% (6/30). Among the hybrid DEC, ETEC was the most prevalent pathotype. 10.1371/journal.pone.0340081.g003 Fig 3 Percentage distribution of hybrid Escherichia coli pathotypes across different sample types.
Antimicrobial resistance profiles The highest overall resistance of the 62 E. coli isolates was observed against tetracyclines (77.4%), sulfonamides (71.0%), and ampicillin (59.7%). Moderate resistance was observed to cefotaxime (50.0%), ciprofloxacin (41.9%), and azithromycin (37.1%). Low resistance rates were observed in kanamycin (16.1%), chloramphenicol (8.1%) and amoxicillin-clavulanic acid (4.8%) ( Table 4 ).
10.1371/journal.pone.0340081.t004 Table 4 Antibiotic resistance of E.coli isolated from the samples ( N = 62). Drug Drinking water Fries Githeri Mandazi Waste water Total n % n % n % n % n % n % TCY 13 21.0% 1 1.6% 2 3.2% 3 4.8% 29 46.8% 48 77.4% SXT 11 17.7% 1 1.6% 3 4.8% 3 4.8% 26 41.9% 44 71.0% AMP 11 17.7% 1 1.6% 2 3.2% 2 3.2% 21 33.9% 37 59.0% CTX 8 12.9% 2 3.2% 21 33.9% 31 50.0% CIP 10 16.1% 16 25.8% 26 41.9% AZM 6 9.7% 3 4.8% 1 1.6% 13 21.0% 23 37.1% CRO 7 11.3% 2 3.2% 13 21.0% 22 35.5% CPD 6 9.7% 1 1.6% 1 1.6% 12 19.4% 20 32.3% GEN 6 9.7% 1 1.6% 1 1.6% 12 19.4% 20 32.3% CAZ 5 8.1% 2 3.2% 11 17.7% 18 29.0% NAL 7 11.3% 7 11.3% 14 22.6% KAN 3 4.8% 1 1.6% 6 9.7% 10 16.1% CHL 2 3.2% 3 4.8% 5 8.1% AMC 3 4.8% 3 4.8% KEY: TCY -tetracycline, SXT -trimethoprim-sulfamethoxazole, AMP–ampicillin, CTX-cefotaxime, CIP –ciprofloxacin, AZM –azithromycin, CRO –ceftriaxone, CPD-cefpodoxime, GEN-gentamicin, CAZ –ceftazidime, NAL-nalidixic acid, KAN-kanamycin, CHL-chloramphenicol, AMC-amoxicillin-clavulanic acid. DEC resistance patterns to antibiotics All 48 pathotypes exhibited varying levels of resistance to the antibiotics.
ETEC exhibited high resistance rates to all the antibiotics compared to the other pathotypes, as shown in Fig 4 . ETEC exhibited resistance to tetracycline (47.9%), trimethoprim-sulfamethoxazole (41.7%), cefotaxime (39.6%), and ampicillin (37.5%). STEC showed resistance to trimethoprim-sulfamethoxazole (45.8%), tetracycline (41.7%) ampicillin (35.4%).
EAEC exhibited low resistance to ampicillin (6.3%), trimethoprim-sulfamethoxazole (6.3%), and tetracycline (6.3%); EPEC exhibited resistance to ampicillin (10.4%), trimethoprim-sulfamethoxazole (8.3%), and tetracycline (8.3%). EIEC had varying resistance rates to ampicillin (22.9%), trimethoprim-sulfamethoxazole (29.2%), and tetracycline (35.42%). EIEC did not exhibit resistance to amoxicillin-clavulanic acid, while EAEC did not exhibit resistance to azithromycin, chloramphenicol, and nalidixic acid.
10.1371/journal.pone.0340081.g004 Fig 4 Illustrates the percentage of drug resistance for various E. coli pathotypes against different antibiotic drugs from samples obtained in Mukuru informal Settlements,Nairobi,Kenya. Association between sample type and antibiotic resistance. Inferential analysis, using chi-square statistics, was applied to assess associations between sample type and antibiotics .
E. coli isolates from wastewater had resistance to all the tested antibiotics ( Table 5 ), with significant resistance to ampicillin (21/62 isolates), cefotaxime (21/62 isolates), and tetracycline (29/62 isolates). E. coli isolates from drinking water also had high resistance to tetracycline (13/62), ampicillin (11/62), trimethoprim-sulfamethoxazole (11/62), and ciprofloxacin (10/62). E. coli isolates from Mandazi and githeri had lower resistance overall but still exhibited resistance to beta-lactams, tetracycline, and sulfonamides.
There was a significant difference in resistance to ciprofloxacin ( p = 0.030). 10.1371/journal.pone.0340081.t005 Table 5 Association between sample type and Antibiotics. Sample type Antibiotic Resistance AMC AMP AZM CTX CPD CAZ CRO CHL CIP GEN KAN NAL TCY SXT Drinking water 11 6 8 6 5 7 2 10 6 3 7 13 11 French fries 1 1 1 Githeri 2 3 2 1 2 2 1 2 3 Mandazi 2 1 1 1 1 3 3 Wastewater 3 21 13 21 12 11 13 3 16 12 6 7 29 26 P-Values 0.533 0.849 0.937 0.359 0.699 0.608 0.619 0.956 0.030 0.731 0.582 0.059 0.172 0.561 TCY -tetracycline, SXT -trimethoprim-sulfamethoxazole, AMP–ampicillin, CTX-cefotaxime, CIP –ciprofloxacin, AZM –azithromycin, CRO –ceftriaxone, CPD-cefpodoxime, GEN-gentamicin, CAZ –ceftazidime, NAL-nalidixic acid, KAN-kanamycin, CHL-chloramphenicol, AMC-amoxicillin-clavulanic acid.
Multidrug resistance in E. coli. Majority 60% (27/45) of the MDR resistant E.coli isolates were recovered from wastewater, with 28.9% [ 13 ] from drinking water, 4.4% [ 2 ] from githeri, 4.4% [ 2 ] from mandazi and 2.2% [ 1 ] from French fries 2.2% [ 1 ] Fig 5 . The frequency of resistance to 3, 4, 5, 6, and 7 classes of antimicrobial agents were 17.8% (8/45), 22.2% (10/45), 24.4% (10/45), 24.4% (10/45), 11.1% (5/45), respectively.
10.1371/journal.pone.0340081.g005 Fig 5 Illustrates the percentage of Multi-Drug Resistant (MDR) E. coli detected across various sample types. Distribution of ESBL genes per sample. Of the 62 E. coli isolates, 12.9% [ 8 ] carried bla TEM gene, of these, six were detected in wastewater while two in drinking water.
The bla CTXM gene (S3) was detected in 3.2% [ 2 ] of the E. coli isolates; one in drinking water and one in wastewater The bla TEM gene was detected in multiple pathotypes, including ETEC, EAEC, STEC, EIEC, and EPEC. The bla CTXM gene was found in a nonpathogenic isolate and a hybrid isolate of ETEC, EPEC, and EIEC as shown in Table 6 10.1371/journal.pone.0340081.t006 Table 6 Distribution of ESBL genes Per Sample. Sample Type E. coli Pathotype ESBL Gene Wastewater ETEC, EAEC TEM Wastewater EPEC, STEC, ETEC TEM Wastewater ETEC, STEC, EIEC TEM Wastewater ETEC, STEC, EIEC TEM Wastewater ETEC, STEC TEM Wastewater ETEC, STEC, EPEC TEM Drinking water ETEC, STEC TEM Drinking water STEC TEM Drinking water Negative CTX-M Wastewater ETEC, EPEC, EIEC CTX-M Discussion Foodborne diseases caused by E. coli contamination are responsible for a huge public health challenge globally especially in low- and middle-income countries LMICs [ 1 ].
Understanding the role of environmental reservoirs in disseminating multidrug resistant diarrheagenic E. coli is crucial for mitigation strategies. This study was conducted in an urban informal settlement characterized by high population, dilapidated water, sanitation, and hygiene (WASH) infrastructure; therefore, most residents use common water points for drinking water and street foods are very popular within because they are relatively inexpensive, convenient, and easily accessible [ 28 ]. These conditions could contribute to a high burden of diarrheal morbidity within the population especially among children [ 19 ].
In this study, DEC were detected in 12.5% (48/384) of different samples with ETEC being the most prevalent pathotype. A huge proportion (72.6%, 45/62) of the E. coli isolates were observed to multi-drug resistant with high levels of resistance to ampicillin, tetracyclines and sulfonamides. The detection of DEC in drinking water and food samples highlight the potential public health risks associated with these samples [ 29 ] in this setting.
Wastewater had a high E.coli isolation rate compared to drinking water: similar findings were observed in a study conducted in Peru that showed drinking water samples had a lower prevalence of E. coli contamination, yet still posed a health concern [ 30 ] according to WHO standards, 2023. Although, 1% of French fries were E. coli positive this is concerning as these are ready to eat food and could easily result in foodborne infections. Detection of E. coli in street foods ( French fries , mandazi and githeri ) might be attributed to improper handling post-preparation or cross-contamination during storage, given that it is prepared in high temperatures capable of eliminating bacterial pathogens [ 31 – 33 ].
In this study, ETEC was the predominant DEC pathotype detected, these finding is comparable to findings observed in Kat River and Fort Beaufort abstraction water where ETEC was the most prevalent pathotype [ 34 ]. On the contrary, these findings were different from a study conducted in South Africa where diffusely adherent E. coli (DAEC) was the only pathotype isolated from wastewater [ 35 ]. Another study conducted in Johannesburg, South Africa, observed that EPEC was the dominant pathotype detected in environmental water samples [ 36 ].
The high prevalence of ETEC in environmental samples observed in this study is a huge public health concern, given that ETEC is a leading cause of bacterial diarrhea, particularly in children under five and travelers in low-resource settings [ 37 ]. The transmission of ETEC through contaminated food or water can cause outbreaks, especially where sanitation and hygienic conditions are poor. The presence of ETEC in water and food samples suggests widespread fecal contamination which highlights the poor water and sanitation conditions in the urban informal settlement.
Hybrid DEC pathotypes were detected in this study which is comparable to previous findings observed in South Africa. Interestingly, one street food sample had 4 different DEC strains detected ETEC, STEC, EIEC and EAEC. The simultaneous presence of a combination of virulence factors in one isolate greatly increases the potential for infection and disease transmission among consumers [ 38 ].
A previous foodborne outbreak in Germany which spread out to Europe and North America was attributed to contamination of food samples by a hybrid DEC [ 39 ]. The presence of such hybrid DEC in Mukuru could pose a high risk of severe outbreaks, especially given the community’s poor sanitation infrastructure. Antimicrobial resistance in bacteria from food and water is a major threat to global public health [ 40 ] as it limits the management of foodborne diseases.
In this study, high resistance to ampicillin, sulfamethoxazole and tetracycline was observed across all sample types. These results are similar to a study done in Korogocho, an urban slum in Nairobi, Kenya [ 41 ]. This observation suggests that environmental compartments in urban slums are plausible reservoirs of antibiotic resistant bacteria [ 42 ].
Resistance to ciprofloxacin showed a statistically significant association with sample type particularly in wastewater samples, which suggests that such environments might act as reservoirs for resistant bacteria [ 42 ]. The high resistance in E. coli recovered from wastewater observed in this study highlights the need for better waste management systems to prevent the spread of resistant bacteria. E. coli isolates from French fries and mandazi displayed alarmingly complete resistance to tetracyclines and sulfonamides underscoring the increasing resistance.
These findings align with studies in sub-Saharan Africa, where resistance to tetracyclines and sulfonamides is also consistently reported as high [ 43 ]. A study in Kenya by Omulo et al. found that over 80% of E. coli isolates from both human and environmental sources exhibited resistance to these antibiotic classes, similar to the trends observed in this study [ 41 ]. Additionally, studies from Nigeria and Tanzania reported comparable patterns, with tetracyclines and sulfonamides showing the highest resistance rates across environmental and food samples [ 44 , 45 ].
The findings on multidrug resistance among E. coli and its pathotypes is a significant public health concerns. Multidrug resistance was observed across nonpathogenic and pathogenic E. coli with isolates from wastewater demonstrating notably high resistance across several antibiotic classes. Among the extended spectrum beta lactamase genes analysed, bla TEM was the most prevalent gene identified.
These results are similar to other studies showing bla TEM and bla CTXM as the most prevalent ESBL genes with no isolation of bla SHV. [ 46 ]. This occurrence could likely be attributed to the widespread use of third- and fourth-generation cephalosporins. The high resistance to third-generation cephalosporins could lead to the clinical challenges in treating infections, especially with the limited availability of alternative antibiotics in low-resource settings [ 46 ].
The high rates of multidrug resistance including the presence of extended-spectrum β-lactamase -producing E. coli, have serious implications that suggest widespread environmental contamination with antibiotic resistance genes, potentially due to the overuse or misuse of antibiotics in both human and animal populations. In conclusion, street food and water samples in Mukuru serve as reservoirs for pathogenic E. coli, with the detection of diverse and hybrid pathotypes posing a public health concern, highlighting fecal contamination as a major route for the transmission of waterborne and foodborne pathogens. The presence of hybrid pathotypes, with varied virulence mechanisms and disease outcomes, complicates infections and treatment, particularly with the emergence of multidrug-resistant (MDR) and extended-spectrum beta-lactamase (ESBL)-producing strains resistant to key antibiotics like ampicillin, nalidixic acid, and trimethoprim-sulfamethoxazole.
These findings highlight the need for enhanced surveillance and stricter regulations on antibiotic use in agricultural, clinical, and environmental sectors, particularly in low-resource settings. Addressing the One Health dimensions of AMR requires a coordinated approach to mitigate its spread across human, animal, and environmental interfaces. Supporting information S1 Fig The Ingredients and description of street foods collected and analyzed from Mukuru informal settlement Nairobi Kenya.
(ZIP)