International Journal of Microbiology

International Journal of Microbiology / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 6572693 | https://doi.org/10.1155/2020/6572693

Susan W. Muriuki, Johnstone O. Neondo, Nancy L. M. Budambula, "Detection and Profiling of Antibiotic Resistance among Culturable Bacterial Isolates in Vended Food and Soil Samples", International Journal of Microbiology, vol. 2020, Article ID 6572693, 12 pages, 2020. https://doi.org/10.1155/2020/6572693

Detection and Profiling of Antibiotic Resistance among Culturable Bacterial Isolates in Vended Food and Soil Samples

Academic Editor: Clemencia Chaves Lopez
Received09 Mar 2020
Revised13 Jul 2020
Accepted20 Aug 2020
Published07 Sep 2020

Abstract

The emergence and persistence of antibiotic resistance remain formidable health challenges. This study aimed at detecting and profiling antibiotic resistance of bacterial contaminants in vended food and the environment. Seventy antibiotic-resistant bacterial isolates were isolated from fried fish, African sausages, roasted meat, smokies, samosa, chips (potato fries), vegetable salads, and soil samples collected from Embu Town and Kangaru Market in Embu County, Kenya. The antibiotic susceptibility test, morphological and biochemical characterization, antibiosis assay, polymerase chain reaction-based detection of antibiotic resistance genes, and sequencing of the 16S rRNA gene were done. Analysis of variance on all measured data was done, and Tukey’s honest test was used to compare and separate mean diameters of zones inhibition. Resistance of bacterial isolates to antibiotics was chloramphenicol (90%), cefotaxime (84.29%), nalidixic acid (81.43%), tetracycline (77.14%), amoxicillin (72.86%), gentamycin (48.57%), streptomycin (32.86%), and trimethoprim + sulphamethoxazole (30%). Isolate KMP337, Salmonella spp., exhibited highly significant antibiosis against S. aureus recording a mean inhibition diameter and standard error (SE) of 16.33 ± 0.88 mm, respectively, at . The 70 bacterial isolates belonged to Bacillus, Paraclostridium, Lysinibacillus, Virgibacillus, and Serratia genera. The study isolated Bacillus wiedmannii (KC75) which is a risk group 2 as well as Serratia marcescens (KMP95) and Bacillus anthracis (KS606) which are risk group 3 organisms. The presence of antibiotic resistance genes Tet A, BlaTEM, StrB, Dfr A, Amp, and FloR genes was confirmed by a polymerase chain reaction. Samples from Kangaru Market recorded a higher (88.57%) proportion of resistant isolates as compared to isolates from Embu Town (11.43%). The study confirmed the presence of antibiotic-resistant bacteria in vended fast food and the soil in Embu Town and Kangaru Market. This study calls for continuous monitoring of bacterial status and hygienic handling of vended food.

1. Introduction

Urban centers in developing countries face socioeconomic challenges that can adversely affect health standards. Foodborne diseases, particularly those of microbial origin, are a major health problem and contribute to reduced economic growth [1]. Street foods are popular in urban areas because of their availability, convenience, and affordability. However, the hygiene aspects of sales operations are a major source of concern for the health of both handlers and consumers [2]. Running surface water, inadequate sanitation, and the disposal of untreated wastewater provide an environment conducive to the growth of pathogenic microbes. Besides, street foods are prone to cross-contamination due to lack of personal hygiene, sharing of contaminated utensils, and free movement of flies that sporadically land on the food.

Food and environmental samples are reservoirs of foodborne pathogens such as Listeria monocytogenes, Vibrio parahaemolyticus, Escherichia coli, Salmonella spp., Vibrio cholerae, and Staphylococcus aureus [1, 3]. In addition to antibiotic resistance in bacterial pathogens, commensal bacteria and the environment are also reservoirs of antibiotic resistance. The release of animal and human waste into the environment results in the subsequent release of antibiotics into water and soil, which encourages further spread of antibiotic resistance [4]. Bacterial resistance to commonly used antibiotics has been associated with enteric pathogens such as E. coli, Salmonella spp., Shigella spp., Klebsiella spp., and V. cholerae [5].

A cross-sectional study conducted in 2014–2016 in 22 of Kenya’s 47 counties diagnosed 11,033 people with cholera [6]. An outbreak of cholera was reported in Embu County in 2019 [7]. Waterborne diseases in Embu County have been attributed to poor sanitation and contamination of water sources [8]. Despite efforts to report the prevalence of food- and waterborne pathogens in Embu County, data on their susceptibility to antibiotics are scarce, so this study focused on the isolation and characterization of antibiotic-resistant bacteria in food sold in Embu Town and the nearby Kangaru Market.

2. Materials and Methods

2.1. Study Site and Sampling

Samples consisting of fried fish, African sausages, roasted meat, smokies, samosa, chips (potato fries), vegetable salads, and soil were purposively collected from 176 out of the 324 licensed food vendors in the densely populated Central Business District of Embu Town and the nearby Kangaru Market (latitude: 0°31′58.80″N and longitude: 37°27′0.00″) (Figure 1). Samples were collected aseptically and transported to the Microbiology Laboratory at the University of Embu where they were stored in a refrigerator at 4°C. Treated water from Embu Water and Sanitation Company (EWASCO) was also sampled.

2.2. Preparation of Inoculum and Subculturing

The samples were incubated in eight selective media, namely, MacConkey agar, Salmonella Shigella agar, brain-heart infusion agar, phenylalanine agar, Pseudomonas fluorescens agar, brilliant green agar, eosin ethidium bromide agar, and deoxycholate agar. The standard cultivation method for bacterial food contaminants isolation was carried out as recommended by the International Organization for Standardization (ISO) 6579 [9]. The plates were incubated at 37°C for 24 hours, in an inverted position, after which single colonies were subcultured on fresh media.

2.3. Characterization and Identification of Bacterial Isolates

The isolates were characterized as described in [10]. The ability of the isolates to ferment sugars, utilize citrate, and produce catalase enzyme and phenyl-pyruvic acid was determined as previously described [11, 12]. The isolates were screened for their ability to produce amylase, protease, cellulase, and esterase using the methods described in [13, 14]. Probable identification of the isolates was done using Bergey’s manual of determinative bacteriology and confirmed by partial sequencing of the 16S rRNA gene of some isolates.

2.4. Antibiotic Susceptibility Assay

The Kirby Bauer disc diffusion method using Mueller-Hinton agar was used for antimicrobial susceptibility testing [15]. Antimicrobial discs with amoxicillin (20 µg), cefotaxime (30 µg), gentamicin (10 µg), streptomycin (10 µg), tetracycline (30 µg), nalidixic acid (30 µg), trimethoprim + sulphamethoxazole (1.25/23.75 µg), and chloramphenicol (30 µg) were used. Klebsiella pneumoniae 1792880 and E. coli 35218 were used as quality control strains. Bacterial suspensions of pure isolates were prepared based on 0.5 McFarland Turbidity Standard. The plates were incubated in an inverted position at 37°C for 24 hrs. The diameter of the zones of inhibition (in millimeters) was measured and interpreted as either susceptible, intermediate, or resistant according to the Guidelines of CLSI [16].

2.5. Antibiosis Test

Standardized bacterial suspensions were prepared based on 0.5 McFarland turbidity [17]. The antibiosis test was performed as previously described [18]. The isolates were incubated at 37°C and monitored routinely after every 24 hours for two days. The diameter of the zones of inhibition was recorded. The antibiotic-resistant bacteria were tested for antibiosis against six laboratory bacteria strains, namely, Staphylococcus aureus ATCC 1026, Klebsiella pyrope 1792880, E. coli ATCC 35218, Streptococcus pneumoniae ATCC 49619, S. aureus BAA 976, and K. pneumoniae 1792880.

2.6. DNA Extraction from Antibiotic-Resistant Bacteria

The bacterial isolates were grown overnight in Luria Broth for 24 hours, and DNA was extracted using the phenol-chloroform method with some modifications [19]. To isolate plasmid DNA, bacterial isolates were grown overnight in Luria Broth. Plasmids were extracted using a protocol modified from [20].

2.7. Partial Sequencing of Bacterial 16S rRNA Gene

The 16S rRNA gene sequence was amplified by PCR using bacterial universal primers 8F (5′-AGCTTTGATCCTGGCTCAG-3′) and 1492R (5′-CGGCTACCTTGTTACGACTT-3′) for all selected bacterial isolates according to [21] using Phusion-High fidelity PCR Kit (New England and Biolabs Inc). The PCR amplicons were checked by gel electrophoresis, labeled, and shipped to Inqaba Biotech African’s Genomics Company in South Africa for sequencing. The sequence outputs were edited, analyzed, and deposited in GenBank for assignment of accession numbers.

2.8. PCR Amplification of Antibiotic Resistance Genes

Genes encoding resistance to tetracycline, streptomycin, and beta-lactam antibiotics such as ampicillin, chloramphenicol, and trimethoprim were detected using the primer specific PCR approach (Table 1) as described in [22]. The presence of a target gene was confirmed by the presence of a band on the gel.


PrimerSequence (5′ to 3′)Target geneAmplicon size (bp)Annealing temperature (°C)Resistance to antibiotics

Flor-FTTATCTCCCTGTCGTTCCAGCGFloR45057.5Chloramphenicol
Flor-RCCTATGAGCACACGGGGAGC

strB-FGGCACCCATAAGCGTACGCCStr B40061Streptomycin
strB-RTGCCGAGCACGGCGACTACC

DfrA1-FCGAAGAATGGAGTTATCGGGDfr A20055Trimethoprim
DfrA1-RTGCTGGGGATTTCAGGAAAG

TEM-FGCGGTATCATTGCAGCACTGBlaTEM100055Beta-lactam
TEM-RTGCTTAATCAGTGAGGCACC

Amp-FATGCACACGCTGATCGGATTAmp26865Ampicillin
Amp-RGCGGACGCAGACTTCACTAA

Tet-FAACCGGCATTGAGAGCATCATet A69960Tetracycline
Tet-RTTGTCTCCTCTCCCTTGGCT

2.9. Data Analysis

Data on antibiosis, extracellular enzymatic activity, and antibiotic sensitivity were recorded in excel sheets. The general linear model (PROC GLM) procedure of SAS software version 9.1 (SAS Institute, Cary, NC) was used to perform analysis of variance (ANOVA). Tukey’s honest significant difference (HSD) test was used to compare and separate the means of the diameter of zones of inhibition. Correlation profiles of zones of clearance on different substrates and zones of inhibition were visualized as a heatmap generated by a hierarchical clustering R script using R version 3.3.1 software. The genetic affiliation of the sequenced genes of the isolates was deduced from a phylogenetic tree generated using MEGA X. The analysis involved 20 nucleotide sequences. The evolutionary distances were computed using the maximum composite likelihood method and were recorded as units of the number of base substitutions.

3. Results

3.1. Effect of Antibiotics on Bacteria Isolated from Food and Soil

Antibiotic sensitivity test assays revealed that 70 out of 345 bacterial isolates were resistant to at least three (multiple resistant) antibiotics that were tested. Isolate KMP253 affiliated to Salmonella spp., TF152 affiliated to E. coli, and KS120 affiliated to Bacillus subtilis were resistant to all the antibiotics that were tested and were all isolated from Kangaru Market (Table 2). Hierarchical clustering showed that trimethoprim + sulphamethoxazole was the most effective antibiotic, while chloramphenicol was the least effective antibiotic. Isolate KVS120 was resistant to the highest number of antibiotics (Figure 2). The occurrence of antibiotic-resistant bacteria varied among different food samples. Smokies from both sites had the lowest number of resistant bacterial isolates (1.43%) compared to the other food samples. Fish sold in Kangaru Market had the highest proportion of resistant isolates (18.57 %), as shown in Figure 3. No bacteria were recovered from treated water provided by EWASCO.


IsolateProbable identityLocationSampleStrepGentaAmoxTetraChloTri-sulCefotaxNalidResistant to antibiotics (n)

KS7Providencia spp.KangaruSoilRIRRIIIR4
KF27Shigella spp.KangaruFishSRRRRRRR7
KRM34E. coliKangaruRoasted meatSIRRRIRR5
KFR38Bacillus pacificusKangaruFruitISRRRRRR6
KFR42Bacillus amyloliquefaciensKangaruFruitIRRRRIRR6
KMP45Pseudomonas spp.KangaruAfrican sausageRIIIRIRS3
KFR52Bacillus megateriumKangaruFruitIIRRRIRR5
KSM63Shigella sonneiKangaruSmokiesRSIRIIRI3
KS65Bacillus wiedmanniiKangaruSoilISRSRIRS3
KC67Pseudomonas aeruginosaKangaruChipsSSRRISRR4
KVS68Enterobacter spp.KangaruVegetable saladSRRRRRSS5
KVS75Bacillus wiedmanniiKangaruVegetable saladISSRRSRS3
TVS81Bacillus thuringiensisKangaruVegetable saladSSRRRIRR5
KVS82Serratia marcescensKangaruVegetable saladSRRSRSRR5
KVS85Serratia marcescensKangaruVegetable saladSSRSRSIR3
KMP95Serratia marcescensKangaruAfrican sausageRSIRRRRR6
KF101Bacillus velezensisKangaruFishSSSRRSRR4
KS104Virgibacillus phasianinusKangaruSoilSRISRSSR3
KS109Lysinibacillus parviboronicapiensKangaruSoilRRRRRIRR7
KS116Providencia spp.KangaruSoilRRRRRRRR8
KVS120Bacillus subtilisKangaruVegetable saladRRRRRRRR8
KC122Pseudomonas spp.KangaruChipsSSIIRSRR3
KFR131Pseudomonas spp.KangaruFruitRIRRRIRR6
KVS147Staphylococcus aureusKangaruVegetable saladRRRSRSSR5
KF148Shigella spp.KangaruFishISRSRSSR3
TF152E. coliTownFishRRRRRRRR8
KMP159Salmonella spp.KangaruAfrican sausageIRISRSSR3
KS160Citrobacter spp.KangaruSoilRRRRRIRR7
KF169Proteus spp.KangaruFishRRRSRSSR5
KMP188Aerobacter aerogenesKangaruAfrican sausageRRRSRSSR5
KFR200Enterobacter spp.KangaruFruitSISRRIRI3
KFR204Pseudomonas spp.KangaruFruitSIRRRIRR5
KVS214S. pneumoniaeKangaruVegetable saladRRRRSRRR7
KFR217Klebsiella spp.KangaruFruitRSSRRSRR5
KFR222Bacillus mobilisKangaruFruitSSRRRSRR5
KC231S. pneumoniaeKangaruChipsSSISRSRR3
KFR245P. aeruginosaKangaruFruitSSIIRIRR3
KF246S. pneumoniaeKangaruFishISIRRIRR4
KVS249Pseudomonas spp.KangaruVegetable saladIRRRRRRR7
KMP253Salmonella spp.KangaruAfrican sausageRRRRRRRR8
KS260E. coliKangaruSoilIRSRRIRR5
KS267Bacillus wiedmanniiKangaruSoilIRRRRRRR7
KVS271Pseudomonas spp.KangaruVegetable saladIRIRRIRR5
KFR285Hafnia spp.KangaruFruitSRISRSSR3
KFR286Pseudomonas spp.KangaruFruitISRRRSRR5
KFR301Salmonella spp.KangaruFruitIRRRRRRR7
KF317Streptococcus pneumoniaeKangaruFishRSIRRIRR5
KMP321Bacillus wiedmanniiKangaruAfrican sausageRRRRRIRR7
TFR329Bacillus proteolyticusTownFruitSRRRRRRR7
KVS330Citrobacter freundiiKangaruVegetable saladSRIRRRRI5
KMP337Salmonella spp.KangaruAfrican sausageIIIRRIRR4
KRM349Pseudomonas spp.KangaruRoasted meatIIRRRIRR5
KS376E. coliKangaruSoilSRRRRRRR7
TS378Salmonella spp.TownSoilIRRRRIRR6
TS380Pseudomonas spp.TownSoilRSRRRRRR7
KF381Micrococcus spp.KangaruFishSRRRRRRR7
KF389Morganella spp.KangaruFishISRIRIRS3
KF391Serratia marcescensKangaruFishRRRRRRRS7
KF393Yersinia spp.KangaruFishSRRRRIRR6
KF395Pseudomonas aeruginosaKangaruFishSIRRRSRR5
KF399Salmonella entericaKangaruFishIRRRRRRR7
TS427Pseudomonas spp.TownSoilIRRRRIRS5
KC430Pseudomonas spp.KangaruChipsISRRRRRR6
KRM435Bacillus wiedmanniiKangaruRoasted meatISRRISRR4
KF463Bacillus anthracisKangaruFishRRRRRIRR7
TS472Bacillus cereusTownSoilSRRRRRRR7
TS572Bacillus subtilisTownSoilSSRRRIRR5
KS585Enterococcus faecalisKangaruSoilRRRRRRSR7
KS606Bacillus anthracisKangaruSoilRIRRRIRS5
TS621Proteus spp.TownSoilSRRSRIRR5

Strep, streptomycin; Genta, gentamycin; Amox, amoxicillin; tetra, tetracycline; Chlo, chloramphenicol; Tri-Sul, trimethoprim + sulphamethoxazole; Cefotax, cefotaxime; Nalid, nalidixic acid.
3.2. Detection of Antibiotic-Resistant Genes

Antibiotic resistance genes were detected in 36 out of the 70 antibiotic-resistant bacterial isolates (Table 3). The antibiotic resistance genes BlaTEM and Dfr A were frequently detected (Figures 4(a) and 4(b)). Resistance genes were detected at a higher frequency in bacteria isolated from Kangaru Market compared to Embu Town.


Isolate numberLocationSampleProbable identityDetected antibiotic resistance genes
Dfr AStr BTet ABlaTEMAmpFloR

KFR222KangaruFruitB. mobilis+
KF169KangaruFishProteus spp.+
KF463KangaruFishB. anthracis++
KMP253KangaruAfrican sausageSalmonella spp.++
KFR285KangaruFruitHafnia spp.++
KF27KangaruFishShigella spp.++
KMP188KangaruAfrican sausageA. aerogenes++
KF148KangaruFishShigella spp.++
KC67KangaruChipsP. aeruginosa+
TS572TownSoilB. subtilis+++
KMP95KangaruAfrican sausageS. marcescens++
TFR329TownFruitB. proteolyticus++
KFR301KangaruFruitSalmonella spp.++
KVS330KangaruVegetable saladE. coli++
TS380TownSoilSalmonella spp.+
TVS81TownVegetable saladB. thuringiensis++
KF391KangaruFishMorganella spp.+++
KS160KangaruSoilCitrobacter spp.+
KF169KangaruFishProteus spp.++
KF317KangaruFishE. faecalis+
KFR131KangaruFruitPseudomonas spp.+
KFR38KangaruFruitB. pacificus+
KVS85KangaruVegetable saladS. marcescens+
KFR204KangaruFruitPseudomonas spp.+
KS109KangaruSoilL. parviboronicapiens+
KVS214KangaruVegetable saladS. pneumoniae+
KS585KangaruSoilB. toyonensis++
KF399KangaruFishP. aeruginosa++
KS267KangaruSoilB. wiedmannii+
KS116KangaruSoilProvidencia spp.+
KC122KangaruChipsPseudomonas spp.+
KFR245KangaruFruitP. aeruginosa+
KS376KangaruSoilPseudomonas spp.+
KVS249KangaruVegetable saladPseudomonas spp.+
KS606KangaruSoilB. anthracis+
KF393KangaruFishS. marcescens+

+ indicates the presence of the resistance genes following amplification by PCR; − indicates the absence of the target resistance genes following amplification by PCR.
3.3. Antibiosis Activity

Eleven out of the 70 antibiotic-resistant bacterial isolates inhibited the growth of at least one of the following laboratory strains of bacteria: S. aureus ATCC 1026, E. coli ATCC 35218, and K. pneumoniae 1792880. Isolate KFR38 affiliated to B. pacificus inhibited two laboratory strains and exhibited large zones of inhibition (Table 4). None of the antibiotic-resistant isolates was able to inhibit the growth of K. pyrope 1792880, S. pneumoniae ATCC 49619, or S. aureus BAA 976.


Isolate NumberProbable identityLocationSampleE. coli ATCC 35218S. aureus ATCC 1026K. pneumoniae ATCC 35218

KC430Pseudomonas spp.KangaruChips0.00 ± 0.00b0.00 ± 0.00b14.33 ± 0.33a
KC67P. aeruginosaKangaruChips0.00 ± 0.00b0.00 ± 0.00b10.00 ± 0.00b
KF395Yersinia spp.KangaruFish0.00 ± 0.00b0.00 ± 0.00b9.67 ± 0.33b
KFR217Klebsiella spp.KangaruFruit0.00 ± 0.00b0.00 ± 0.00b7.00 ± 0.00c
KFR38B. pacificusKangaruFruit0.00 ± 0.00b8.33 ± 2.33b13.67 ± 0.33a
KMP337C. freundiiKangaruMeat pie0.00 ± 0.00b16.33 ± 0.88a0.00 ± 0.00d
KS260E. coliKangaruSoil7.00 ± 0.00a0.00 ± 0.00b9.00 ± 0.00bc
KSM63S. sonneiKangaruSamosa0.00 ± 0.00b0.00 ± 0.00b10.33 ± 1.33b
KVS271Pseudomonas spp.KangaruVegetable salad0.00 ± 0.00b0.00 ± 0.00b7.00 ± 0.00c
TS380Salmonella spp.TownSoil0.00 ± 0.00b0.00 ± 0.00b11.00 ± 0.58b
TS572B. subtilisTownSoil0.00 ± 0.00b0.00 ± 0.00b14.00 ± 0.58a

value0.0010.0010.001
CV0.0076.769.03
LSD0.003.802.54

Mean with SE for antibiosis activity of the isolates, where the means with the same letters are not significantly different as indicated by Tukey’s HSD test ().
3.4. Risk Groups of Antibiotic-Resistant Bacterial Isolates

The 14 antibiotic-resistant bacteria that were successfully sequenced belonged to risk groups 1, 2, and 3. Isolate KS606 affiliated to B. anthracis and isolate KMP95 affiliated to S. marcescens which are risk group 3 organisms that were isolated from food sold in Kangaru Market (Table 5).


Isolate no.LocationSampleIdentity% similarityResistant to antibiotics (n)Resistance genes detected by PCRRiskgroup

KFR42KangaruFruitB. amyloliquefaciens99.4461
KFR38KangaruFruitB. pacificus99.16StrB1
KS65KangaruSoilP. benzoelyticum99.5731
KC75KangaruChipsB. wiedmannii99.5132
KF101KangaruFishB. velezensis97.8641
KVS120KangaruVegetable saladB. subtilis97.9481
KFR222KangaruFruitB. mobilis99.835BlaTEM2
KF463KangaruFishB. anthracis99.437StrB, BlaTEM1
TFR329TownFruitB. proteolyticus97.187Str B, Dfr A1
KS109KangaruSoilL. parviboronicapiens90.837Amp1
KS104KangaruSoilV. phasianinus99.3131
KMP95KangaruAfrican sausageS. marcescens95.396Dfr A, FloR3
KS606KangaruSoilB. anthracis1005Tet A3
TS572TownSoilB. subtilis97.515Str B, BlaTEM, FloR1

– ,resistance gene not detected.
3.5. Substrate Utilization by Antibiotic-Resistant Bacteria

The antibiotic-resistant bacterial isolates produced different extracellular enzymes, as shown by the zones of clearance on different substrates. Isolates KF148, KF317, KS116, KS7, and KVS249 exhibited the largest zones of clearance with an average diameter and standard error (SE) of 14.67 ± 0.33 mm, 14.00 ± 0.58 mm, 14.00 ± 0.58 mm, 15.00 ± 0.00 mm, and 14.67 ± 0.33 mm, respectively. B. anthracis (KS606) recorded the largest zone of clearance on cellulose, while KC430 affiliated to Pseudomonas spp. had the largest zone of precipitation on the tween-20 substrate.

3.6. Amplification of 16S rRNA Genes and Phylogenetic Analysis

The 16S rRNA gene was successfully amplified in 47 isolates out of the 70 antibiotic-resistant bacterial isolates (Figure 5).

Phylogenetic analysis of successfully sequenced bacterial isolates revealed that the isolates belonged to five genera, namely, Bacillus, Paraclostridium, Lysinibacillus, Virgibacillus, and Serratia with the similarity of above 90%. The Bacillus clade had the highest number of successfully amplified bacterial isolates distributed in nine subclades with bootstrap values of 98 (Figure 6).

4. Discussion

The present study isolated 70 bacterial isolates that were resistant to at least three antibiotics from vended foods and the soil in Embu Town and Kangaru Market. Higher levels of antibiotic resistance were recorded from bacteria isolated from vended food and soil in Kangaru Market compared to Embu Town. The presence of antibiotic-resistant pathogens in street vended foods has been recently reported in Kisumu, Kenya [23]. An earlier study in Kibera, Kenya, reported that food and the environment are reservoirs of antibiotic resistance [24]. Food contaminated with antibiotic-resistant bacteria is a threat to public health as it encourages persistence and dissemination of resistance determinants [25]. The higher level of antibiotic resistance recorded in the Kangaru Market may be due to laxity in the enforcement of public health measures. Resistance to gentamycin and streptomycin which are administered by intramuscular injection was 48.57% and 32.86%, respectively. The intramuscular mode of administration possibly limits the use of these antibiotics and thus contributes to the preservation of the antimicrobial activity [26]. In the present study, the frequency of antibiotic resistance to oral antibiotics was high and ranged from 72.86% for amoxicillin to 81.43% for nalidixic acid. The high level of resistance to oral antibiotics is possibly due to availability, convenient mode of administration, broad-spectrum activity, and affordability.

Fish samples in the present study had the highest (18.52%) proportion of antibiotic-resistant isolates. The contamination of fish with antibiotic-resistant bacteria has been previously attributed to fecal contamination of water due to the unhygienic disposal of human waste [27]. Earlier studies reported contamination of water with bacteria that were multidrug resistant to sulphamethoxazole/trimethoprim, ampicillin, and tetracycline [24, 28]. The present study confirmed that treated water from EWASCO that is used by most of the people in Embu Town and Kangaru Market was free from contamination by bacteria at the time of sampling. Therefore, it is unlikely that antibiotic resistance in this study originated from EWASCO water.

The current study isolated antibiotic-resistant bacteria from vegetable salad and African sausages, which are mostly homemade. Contamination of smokies, which are also a kind of sausage that is factory made and packed, with antibiotic-resistant bacteria was low. Postharvest contamination of vegetables and cross-contamination of African sausages are a major risk factor for disseminating antibiotic resistance [29, 30]. Soil samples from both Embu Town and Kangaru Market recorded a higher proportion of antibiotic-resistant isolates compared to food samples. In a previous study, anthropogenic activities such as long-term manure application were shown to increase antibiotic-resistant bacteria in soil [31]. Such activities were not deduced in the present study. Isolation of Pseudomonas spp. from both soil and fish in Kangaru Market indicates the possibility of food contamination originating from the environment.

The present study showed that antibiotic resistance was encoded by TetA, BlaTEM, StrB, DfrA, Amp, and FloR genes. In this study, genes encoding streptomycin resistance StrB were detected in only nine out of the 23 isolates that were resistant to streptomycin. The StrB genes are known to be encoded by both transposons and plasmids [32]. The present study did not examine transposon-encoded antibiotic resistance, which could explain the detection of StrB in fewer isolates. Five of the nine isolates positive for FloR genes were isolated from food. This could be due to the use of chloramphenicol for domestic purposes [33]. Contamination of food by antibiotic-resistant bacteria could become a major threat to public health since the antibiotic resistance determinants can be transferred to pathogenic bacteria thus complicating the treatment of bacterial infections.

Sequencing of the 16S rRNA gene revealed that most of the antibiotic-resistant bacterial food contaminants detected in this study belonged to the genus Bacillus. Although previous studies have associated Bacillus with food spoilage [34], isolation of B. wiedmannii, a risk group 2 from food, and B. anthracis, a risk group 3 organism from the soil, is of public health concern. The pathogen B. anthracis can cause the death of both human beings and animals [35] (https://my.absa.org/tiki-index). Since S. marcescens occurs naturally in soil and water, it can cause urinary, respiratory, meningitis, pneumonia, septicemia, and endocarditis infections in man. Isolation of S. marcescens from the African sausage in this study could be a result of contamination during preparation, as African sausages are mostly homemade. The presence of S. marcescens a risk group 3 organism [7] in food is of grave concern.

Although isolate TS572 affiliated to B. subtilis was resistant to five antibiotics, it also had antimicrobial activity against K. pneumoniae ATCC 49619. This is not surprising as B. subtilis from soil have been reported to produce antimicrobial agents [36]. KMP337 affiliated to C. freundii recorded the highest antibiosis activity against S. aureus ATCC 1026. Previous studies associated C. freundii with multiple antibiotic resistance but not the production of antimicrobial agents [37]. The present study isolated B. amyloliquefaciens from fruits in Kangaru Market. In a previous study, B. amyloliquefaciens was isolated from banana fruit surfaces and was shown to produce antimicrobial activity against crown root causing pathogens. Thus, B. amyloliquefaciens could be explored further for antimicrobial agents [38]. Isolation of bacteria with antimicrobial activity in the present study supports the need for innovative screening strategies in the search for new antimicrobial agents. Most of the bacteria isolated in the current study were able to produce extracellular enzymes. Other studies have suggested that isolates that exhibit high enzymatic activity also possess high antibiosis activity; thus, these processes could be occurring concurrently [18, 39].

5. Conclusions

This study showed that vended food and the soil in Embu Town and Kangaru Market contain bacterial food contaminants that are resistant to commonly used antibiotics. The study further confirmed that the bacteria harbored antibiotic resistance determinants TetA, BlaTEM, StrB, DfrA, Amp, and FloR. Some of the bacterial food contaminants isolated in this study are risk group 2 and 3 organisms which is a public health concern. More resistance was recorded in the bacteria originating from Kangaru Market as compared to Embu Town. Overall, vended food in Kangaru Market may pose a health risk to the public if mitigating measures are not put in place.

Data Availability

Additional data for this manuscript have been provided as supplementary material.

Disclosure

A license to conduct the research was obtained from the National Commission for Science, Technology and Innovation (NACOSTI) in Kenya. Authorization to collect samples was granted by the Public Health Ministry of Embu County.

Conflicts of Interest

The authors declare that there are no conflicts of interest in the publication of this paper.

Acknowledgments

This research was supported by the University of Embu.

Supplementary Materials

Supplementary Table 1: morphological and biochemical characterization of antibiotic-resistant bacteria isolated from Embu Town and Kangaru Market in 2018. Supplementary Table 2: drug sensitivity interpretation of zone of inhibition diameter based on CLSI (Standard and Testing Guidelines 2018). Supplementary Table 3: enzymatic activity of the bacteria isolated from vended food and soil in Embu Town and Kangaru Market. Supplementary Figure 1: enzymatic activity of the antibiotic-resistant bacterial isolates isolated from fast food and the soil in Embu Town and Kangaru Market. (Supplementary Materials)

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Copyright © 2020 Susan W. Muriuki et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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