Abstract

Background:

Escherichia coli (E. coli) is the most prominent bacterial pathogen that causes urinary tract infections (UTIs), and the rate of resistance to most used antibiotics is alarmingly increasing.

Methods:

This study assessed the hostel gutters of two Nigerian universities, the University of Nigeria, Nsukka (UNN) and Kogi State University, Anyigba (KSU), for E. coli and its antimicrobial resistance genes (ARGs). Oxoid Chromogenic UTI agar was used to isolate uropathogenic E. coli (UPEC), identified using standard biochemical tests. The virulence and resistance genes of the isolates were further characterized using molecular techniques.

Results:

A total of 906 UPEC were isolated in this study, of which 63 isolates were selected for antimicrobial susceptibility tests. The UPEC isolates showed 100% resistance to amoxicillin/clavulanic acid, vancomycin, and penicillin G, while a complete sensitivity of the isolates to meropenem and ciprofloxacin was observed. The index of isolates showing multidrug resistance ranged from 0.33 to 0.73. The level of multiple drug resistance (MDR) exhibited by the UPEC isolates from effluent was significantly higher compared to those from influent (p < 0.05). The ARGs detected were blaOXA-1 8 (38.1%), blaCTX-M3 8 (38.1%), and ant(2)-la 20 (95.2%). Virulence genes encodings beta-glucuronidase (uidA) and hemolysin A (hlyA) were detected in 95.2% of UPEC isolates.

Conclusion:

The current study showed that UPEC is widely distributed in the environment of two Nigerian universities. The index range of MDR and the circulation of ARGs and virulence genes in the environment suggest a potential health concern, thus warranting further investigation.

1. Introduction

Globally, wastewater represents an important hotspot for the rapid dissemination of antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs) in the environment [1]. Antimicrobial resistance (AMR) can spread between people, animals, and the environment through different pathways [2]. Significantly, the environment has been identified as a bridge for different transmission pathways, from animals to compost, soil to water, and sediments to sewage. As a reservoir, the environment may simultaneously mix mobile genetic elements (MGEs) before their eventual diffusion into human and animal hosts [3]. Notably, the ARGs are not biodegradable and can be distributed among microbial communities when they find their way into natural environments, which carries additional implications for promoting the emergence of multidrug-resistant organisms. Discharging improperly treated effluent into surface waters greatly impacts the quality of these surface waters. The presence of antibiotics, ARB, and ARGs causes changes to indigenous microbial communities in surface waters and contributes to the acquisition and spread of waterborne diseases in people who use them [1].

Escherichia coli (E. coli) was recently listed among the high-priority pathogens since their presence may threaten human health [4]. In addition, the transmission of uropathogenic E. coli strains via environmental water-related routes remains an emerging concern globally [4]. Notably, multidrug resistance in E. coli is becoming a growing concern for humans worldwide. Intrinsically, E. coli is vulnerable to virtually every important clinical antimicrobial. However, the microbe can store resistant genes, often via horizontal gene transfer [5]. The highest challenging E. coli mechanisms match with the ability to acquire extended-spectrum β-lactamase (ESBL) genes, which confer non-susceptibility on genes for plasmid-mediated quinolone resistance, carbapenemases, which confer carbapenems resistance, mcr genes, which codes for polymyxins resistance, and methylases 16S rRNA, which encodes aminoglycosides pan-resistance. Enterobacteriaceae AMR is a challenging concern for public health, especially for developing nations. The E. coli genome is very flexible, as the virulence factors can be moved between strains within extrachromosomal plasmids on large pathogenicity islands (PAIs) [6]. The presence of ESBL in Enterobacteriaceae has contributed to the emerging concern of antibiotic resistance globally. ESBLs hydrolyze and inactivate beta-lactam antibiotics and those of the third-generation cephalosporins [7]. ESBL-producing bacteria exhibit co-resistance to aminoglycosides, quinolones, and sulphonamides, which has led to the emergence of multidrug resistance [6]. The isolates’ resistance to penicillin G and some other beta-lactams is chromosomes conciliated with a broad diversity of genetic determinants, while resistance to many of the glycopeptides and carbapenems often results in stable mutations. This chromosome-mediated resistance has been reported mainly against third-generation cephalosporins [7]. Among the uropathogens associated with developing urinary tract infections (UTIs), uropathogenic Escherichia coli (UPEC) is most frequently involved. Most UPEC isolates were found to secrete soluble toxins, especially α-hemolysin (hlyA), and a strong correlation was found between hlyA expression by UPEC and UTI severity [6].

The WHO has rated wastewater treatment plants (WTPs) as the leading cause of environmental contamination by antibiotics [4]. WTP refining has been shown to select antimicrobial-resistant isolates [8], and reports of multidrug resistance are common in hospital environments [9]. Effluents of WTPs, as well as wastewater directly dumped into the University of Nigeria, Nsukka (UNN), and Kogi State University (KSU)’s hostel drains are used to water vegetables as well as other food crops within the area, and this may add to causes of human infections after such vegetables are consumed. Reportedly, these disposal habits have been associated with antibiotic resistance spread via horizontal gene transfer [10]. In the study areas, little or no data regarding the occurrence and distribution of UPEC and associated genes in wastewater environments are available. Thus, it is important to appraise the quality of effluent and surface waters in the area and to determine if wastewater plays a role in the spread of virulence genes and antibiotic resistance. Therefore, the current study was designed to isolate UPEC from water samples obtained from UNN-WTP presumptively and hostel drains at UNN and KSU, determine the antimicrobial susceptibility patterns of the isolates, and further screen the isolates showing multiple drug resistance for resistance and virulence genes using the molecular technique.

2. Materials and Methods
2.1 Area of Study

The study area comprised two university environments: The University of Nigeria, Nsukka (UNN), and Kogi State University, Anyigba (KSU). UNN is situated at 6°5210.07′′N and 7°242.46′′E in the Southeastern part of Nigeria while KSU is situated at 7°293.60′′N and 7°1051.62′′E in the North-central region of Nigeria (Fig. 1). Irrigation with wastewater in the surrounding of UNN-WTP and hostel drains has been a common practice since 2000 at KSU and 1976 in UNN. One rationale behind selecting these universities is that farming activities go on around the site of the UNN-WTP, and hostel drains and wastewater are scooped to irrigate the vegetable farms during dry periods. In addition, students patronize these farmers for their farm produce, which may pose a risk of infection when contaminated. Notably, an outbreak of UTI and gastrointestinal tract infections was recorded at both campuses due to the interaction with hospital management boards.

Fig. 1.

Map representation of study area/sampling sites. Source: Google Earth (Access date: 25 January 2024).

2.2 Sample Collection and Study Design

Grab samples of hostel drains, influent, and effluent of wastewater were obtained from UNN at the marked points, while hostel drain samples were obtained only from KSU. A total of 27 samples and 18 samples were obtained from hostel drains at KSU and UNN, respectively. In the latter location, 9 samples each were collected from WTP influent and effluent. At each point, 250 mL of sample volume was collected into a well-labeled sterile bottle. Samples were then transported in ice boxes to the laboratory for analysis. In total, 63 samples were collected over 9 months.

2.3 E. coli Presumptive Characterization

Chromogenic UTI agar (Oxoid/Thermo Fisher Scientific, Waltham, MA, USA) was employed from each sample to recover UPEC. Gram staining and regular biochemical analyses were conducted on each isolate [11]. Tryptic soy broth (Oxoid, Basingstoke, UK; Catalog number: CM0876) and 15% glycerol (Thermo Fisher Scientific, Waltham, MA, USA, Catalog number: A16205.AP) were used to preserve the presumptive isolates for additional tests and molecular confirmation of the UPEC strains. The glycerol stocks in Eppendorf bottles were stored in a biofreezer (Thermo Fisher Scientific, Model: IUE30086LA) at –80 °C. An E. coli (NCTC 13353) positive control was used. The color (pink/red) shown on UTI chromogenic agar plates was used to identify the organisms.

2.4 Antibiotics Susceptibility Test

This test was performed on every confirmed UPEC isolate following the Kirby–Bauer disc diffusion method [12] and the guidelines of the Clinical and Laboratory Standards Institute [13]. Altogether, 15 antibacterial susceptibility testing discs (Oxoid Thermo Fisher Scientific) were used to test the susceptibilities of the isolates to ciprofloxacin (CIP 5 mcg), amoxicillin/clavulanic acid (AMC 30 mcg), gentamycin (CN 30 mcg), ampicillin (AMP 10 mcg), meropebem (MEM 10 mcg), streptomycin (S 10 mcg), erythromycin (E 15 mcg), cefotaxime (CTX 30 mcg); sulphamethoxazole/trimethoprim (SXT 25 mcg), vancomycin (VA 30 mcg), levofloxacin (LEV 1 mcg), penicillin G (P 10 IU), ceftazidime (CAZ 30 mcg), nitrofurantoin (F 300 mcg), and tetracycline (TE 30 mcg).

2.5 Virulence-Factor and Antibiotic Resistance Genes Characterization
2.5.1 Genomic DNA Extraction

Genomic DNA was extracted from each isolate pure culture grown on nutrient agar for 24 hours (37 °C) via the traditional method of boiling [14]. The template DNA was briefly prepared by suspending a loopful of bacterial cells from an overnight culture in 1 mL of sterile distilled water. The suspensions of bacterial cells were then heated (100 °C for 5 min) and centrifuged (12,000 ×g for 5 min) to eliminate the debris. Further, the GeneJET Purification kit (ThermoFisher Scientific, Waltham, MA, USA; Catalog number: K0512.278) was employed to clean the extracted DNA, which was stored at –20 °C for polymerase chain reaction (PCR) analysis.

2.5.2 Polymerase Chain Reaction

PCR assays were performed using MyGene Gradient Thermal Cycler (Model MG96G; LongGene Scientific Instruments Co., Ltd., East Lyme, CT, USA), as described elsewhere [15, 16]. The 50 µL total reaction volume contained 0.5 µL each of forward and reverse primers (Inqaba Biotechnological Industries, Pretoria, South Africa), 25 µL of the PCR master mix (Thermo Scientific), 14 µL nuclease-free water, and 10 µL of the template DNA. The PCR cycling conditions included an initial activation at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 1 min, annealing at 55 °C for 1 min, and extension at 74 °C for 1 min. Final elongation was at 74 °C for 9 min following the method of Iredell et al. [15]. E. coli strain (NCTC 13353) was utilized as the positive control for the generic identification of E. coli. Table 1 (Ref. [15, 16]) contains the genes targeted, oligonucleotide sequence primers used, and the expected amplicon sizes.

Table 1. Primers for characterizing uropathogenic E. coli virulence genes.
Organism/pathogen DNA target Virulence factor/gene product Primer sequence (5′ to 3′) Product size (bp) PCR cycling conditions References
E. coli uidA Beta-D-glucuronidase F AAAACGGCAAGAAAAAGCAG 147 Initial activation at 94 °C for 3 min, 30 cycles comprising denaturation at 94 °C for 1 min, annealing at 55 °C for 1 min, extension at 74 °C for 1 min and final elongation at 72 °C for 9 min [15, 16]
R ACGCGTGGTTACAGTCTTGCG
UPEC hlyA Hemolysin A F TGTTGAAAGATCAGTCCTCA 500 Same as above
R CTGCGTAGATATTGGCTGAG

Note: Gel electrophoresis consisted of template DNA (10 µL), 6 µL positive control as well as 3 µL DNA ladder (ladder of DNA+1 kb; Invitrogen, Waltham, MA, USA), 2.5% (w/v) agarose gels at 100 V (30 min) in 1× TBE buffer (0.09 M trisborate and 0.002 M EDTA, pH 8). DigiDoc-It® Imaging System 97-0243-01 (Thomas Scientific, Swedesboro, NJ, USA) was then used to snap and view the gels. PCR, polymerase chain reaction; uidA, beta-glucuronidase; hlyA, hemolysin A; E. coli, Escherichia coli; UPEC, uropathogenic E. coli.

2.5.3 Antibiotic Resistance Genes (ARGs) Screening

As described elsewhere, a hot start PCR technique was used to screen the isolates for bla OXA, bla CTM1, and ant(2)-Ia resistance genes [14]. Table 2 (Ref. [16, 17]) shows the expected primers and amplicon sizes. The 20 µL total PCR reaction volume contained 1.5 µL template, 10 µL 1× Quick Taq® HS DyeMix (Thermo Fisher), 0.4 µL of each primer (Inqaba Biotechnological Industries), and 7.7 µL nuclease-free water. The thermal cycling profiles comprised an initial denaturation step (94 °C for 1 min), followed by 30 cycles of denaturation (94 °C for 30 sec), annealing (55 °C for 30 sec), extension (74 °C for 50 sec), and final extension (74 °C for 7 min). Mygene series Peltier-thermal cycler (Model MG96G; Long-Gene Scientific Instruments Co., Ltd.) was used for amplification. PCR products were electrophoresed using 1.5% (w/v) agarose gel in a 1× TAE buffer (20 mM acetate, 1 mM EDTA, and 40 mM Tris pH 8.6) at 100 V for 30 min. Gel staining was performed using RedSafe Staining solution made at iNtRON Biotechnology, Koria. DigiDoc-It® Imaging-System 97-0243-01 (Thomas-Scientific, Swedesboro, NJ, USA) was used to visualize the PCR products under UV light.

Table 2. Primers for characterizing antibiotic resistance genes.
Primers name Primers sequence (5ʹ–3ʹ) Amplicon size (bp) PCR conditions References
ant(2)-laF CATCATGAGGGAAGCGGTG 787 Initial activation step (94 °C for 5 min); 30 cycles: denaturation (94 °C for 1 min), annealing (60 °C for 1 min), extension (74 °C for 2 min); final elongation (74 °C for 15 min) [16, 17]
ant(2)-laR GAGTACCTTGGTGATCTCG
blaCTX-M1F AAAAATCACTGCGCCAGTTC 585 Same as above
blaCTX-M1R AGCTTATTCATCGCCACGTT
blaOXA-F TCAACAAATCCCCAGAGAAG 276 Same as above
blaOXA-R TCCCACACCAGAAGAACCAG
2.6 Statistical Analysis

Data were analyzed using SPSS version 20 (IBM Corp., Armonk, NY, USA). The chi-square test or one-way analysis of variance (ANOVA) was used where appropriate to compute p-values. p values of <0.05 were considered significant.

3. Results
3.1 Total Count of E.coli from UNNWTP and Hostel Drains of Two Campuses

The influent from UNNWTP had a higher viable UPEC count (mean count: 3.3 × 108 cfu/mL; range: 4.5 × 107–5.6 × 108 cfu/mL) than the corresponding effluents (mean count: 2.9 × 107 cfu/mL, range: 4.8 × 106–5.3 × 107 cfu/mL) (Table 3). A statistically significant difference in viable UPEC counts was observed between influents and effluent samples in January (p = 0.004), March (p = 0.0150), August (p = 0.02), September (p = 0.02), October (p = 0.001), and December (p = 0.012). A viable UPEC count ranging from 1.0 × 105 to 9.0 × 105 cfu/mL (mean colony count: 1.83 × 105 cfu/mL) was recorded at the UNN campus against 2.9 × 103–4.0 × 105 cfu/mL (mean colony count: 9.82 × 104 cfu/mL) of KSU. Generally, the viable UPEC count was higher during dry compared to rainy seasons (Table 3). However, there was no significant association between E.coli count and the sampling months (February, p = 0.09; July, p = 0.09; October, p = 0.06; November, p = 0.09).

Table 3. Mean viable E. coli colony counts from July 2017 to March 2018 (cfu/mL).
Month/year Inf Eff Nkr Alv Dan Och Ink Mean
July 2017 3.2 × 108 3.5 × 107 3.1 × 105 1.5 × 105 2.3 × 105 4.2 × 103 4.0 × 105 3.5 × 108
August 2017 4.0 × 108 5.3 × 107 1.0 × 105 2.3 × 105 4.0 × 103 3.8 × 103 3.9 × 105 4.5 × 108
September 2017 4.9 × 108 3.3 × 107 1.2 × 105 9.0 × 105 3.6 × 103 3.2 × 103 3.5 × 105 5.4 × 108
October 2017 5.4 × 108 4.5 × 107 2.5 × 105 5.2 × 105 3.2 × 103 4.5 × 103 3.7 × 105 5.9 × 108
November 2017 5.6 × 108 5.8 × 106 2.2 × 105 1.0 × 105 2.9 × 103 4.2 × 103 2.0 × 105 5.7 × 108
December 2017 5.2 × 108 4.8 × 107 3.0 × 105 3.0 × 105 3.8 × 103 3.6 × 103 3.6 × 105 5.7 × 108
January 2018 6.3 × 107 3.5 × 107 2.8 × 105 4.5 × 105 3.6 × 103 3.2 × 103 3.5 × 105 9.9 × 107
February 2018 5.8 × 107 5.2 × 106 1.6 × 105 1.0 × 105 2.9 × 103 4.2 × 103 2.0 × 105 6.3 × 107
March 2018 4.5 × 107 4.8 × 106 1.8 × 105 3.0 × 105 3.8 × 103 3.6 × 103 3.6 × 105 9.3 × 106

Note: Inf, influent; Eff, effluent; Nkr, Nkruma female hostel; Alv, Alvan Ikoku male hostel; Dan, Dangana male hostel; Och, Ocheja male hostel; Ink, Inikpi female hostel.

3.2 Total Count of E.coli from Male and Female Hostel Drains at Two Universities

The water samples from female hostel drains of KSU had a higher number of viable UPEC count than those from the UNN female hostel (mean colony count: 3.3 × 105 cfu/mL vs 2.1 × 105 (cfu/mL). At KSU, with the highest E. coli count, the lowest colony count (2.0 × 105 cfu/mL) was recorded in two months (February and November), while July recorded the highest count (4.0 × 105 cfu/mL) (Table 3). However, the E. coli count was not significantly higher at KSU female hostels compared with UNN. Analysis of E.coli counts concerning the male hostel drains at the two universities revealed that the samples from Alvan-Ikoku hostel (UNN) were more polluted with E.coli (mean colony count: 3.0 ×106 cfu/mL), followed by Dangana (KSU) (4.2 × 104 cfu/mL), and Ocheja (KSU) (4.8 × 103 cfu/mL) (Table 3).

3.3 Mean Colony Counts of E.coli from July 2017 to March 2018

Fluctuations were observed in the UPEC mean colony counts across the sampling months. Microbial counts of over 108 were recorded in all nine months for influents isolates, and in the effluents, more than 107 counts were recorded in August (5.3 × 107 cfu/mL), December (4.8 × 107 cfu/mL), January (3.5 × 107 cfu/mL), July (3.5 × 107 cfu/mL), and September (3.3 × 107 cfu/mL). The lowest bacterial count was recorded in February and November in Dangana isolates, with 2.9 × 103 cfu/mL each (Table 3). These fluctuations in E.coli counts in wastewater could be due to the differential influx rates of domestic, industrial, and agricultural effluent into the drains and treatment plants and non-adherence to standard treatment protocol.

3.4 E.coli Isolation, Molecular Identification, and Antibiotic Resistance Genes Profiling
3.4.1 E. coli Isolates Antimicrobial-Resistance Profile Comparison between UNN-WTP Influent and Effluent

A total of 906 UPEC were isolated in this study, of which 147 isolates were from samples drawn from UNN hostel drains (55 from Alvan Ikoku, 92 from Nkrumah), 167 were from UNN-WTP influent, and 192 were from UNN-WTP effluent. The remaining 400 isolates were from KSU hostel drains, with the most isolates (150) recorded from Inikpi, followed by Ocheja (131) and Dangana (119). A total of 63 isolates were selected for antibiotics susceptibility tests from 906 isolated E.coli, and 21 were selected for molecular analyses. The 63 UPEC isolates were chosen to represent a number of samples collected from seven sites over 9 months (7 × 9 = 63). The seven sites were UNNWTP influent, UNNWTP effluent, UNN Nkruma hall drain, UNN Alvan Ikoku hall drain, Inikpi hall drain, Ocheja hall drain, and Dangan hall drain. The 21 UPEC selected for molecular analyses were the isolates showing antibiotic resistance after an antimicrobial susceptibility test was conducted on the 63 UPEC isolates. The susceptibility patterns of these 63 isolates against 15 different antibiotics used are shown in Table 4.

Table 4. Comparative antibiotics susceptibility pattern of E. coli from influent and effluent of WTP in UNN.
Treatments Influent Effluent Statistical significance
Antibiotics Resistant Sensitive Intermediate Resistant Sensitive Intermediate Chi-square
AMC 9 0 0 9 0 0 NA
CIP 0 9 0 0 9 0 0.331
CN 7 1 1 7 1 1 0.929
AMP 8 0 1 8 0 1 0.131
MEM 0 9 0 0 9 0 NA
S 8 0 1 8 0 1 NA
E 8 1 0 8 1 0 NA
CTX 0 9 0 0 9 0 NA
SXT 0 0 0 0 0 0 NA
VA 9 0 0 9 0 0 NA
LEV 2 7 0 2 7 0 NA
P 9 0 0 9 0 0 NA
CAZ 0 9 0 0 9 0 NA
F 2 8 0 2 8 0 NA
TE 8 0 1 8 0 1 0.303

Note: WTP, Waste water treatment plant; UNN, University of Nigeria Nsukka; NA, not applicable; AMC, amoxicillin/clavulanic acid; CIP, ciprofloxacin; CN, gentamycin; AMP, ampicillin; MEM, meropebem; S, streptomycin; E, erythromycin; CTX, cefotaxime; SXT, sulphamethoxazole/trimethoprim; VA, vancomycin; LEV, levofloxacin; P, penicillin G; CAZ, ceftazidime; F, nitrofurantoin; TE, tetracycline.

The antibiotic susceptibility test results showed that the UPEC isolates were 100% resistant to AMC, VA, and P. In decreasing order, the antibiotic resistance of the E. coli isolates was 95.2%, 88.9%, 69.8%, 66.7%, and 65.1% against E, S, AMP, TE, and CN, respectively. Conversely, the E. coli isolates were most sensitive to MEM (100%), CTX (87.3%), CIP (81.0%), and SXT (85.7%) (Supplementary Fig. 1).

3.4.2 E.coli Isolates Antimicrobial-Resistance Profile Comparison for UNN and KSU Wastewater Drains

The E. coli isolates from both campuses demonstrated a 100% resistance to AMC, S, and P. In general, the isolates from the KSU water drains showed more resistance to the antibiotics compared to those from UNN (Supplementary Fig. 2). However, no significant difference was observed in the antibiotic resistance profiles between UPEC isolates from both universities (p = 0.09) (Table 5).

Table 5. Comparative antibiotics susceptibility pattern of E. coli from drains at both UNN and KSU campuses.
Treatment KSU UNN Statistical significance
Antibiotics Resistant Sensitive Intermediate Resistant Sensitive Intermediate Pearson chi-square
AMC 27 0 0 18 0 0 0.3407
CIP 0 22 5 0 18 0 NA
CN 17 9 1 9 0 9 0.0003
AMP 20 7 0 16 2 0 0.6089
MEM 0 27 1 18 0 0 NA
S 27 0 0 18 0 0 NA
E 27 0 0 17 1 0 NA
CTX 0 27 0 6 12 0 NA
SXT 2 24 1 0 18 0 0.4960
VA 27 0 0 18 0 0 NA
LEV 3 24 0 4 12 2 NA
P 27 0 0 18 0 0 NA
CAZ 5 22 0 18 0 0 NA
F 8 19 0 0 18 0 0.0358
TE 19 6 2 9 5 4 0.0580

Note: NA, not applicable; KSU, Kogi State University; UNN, University of Nigeria, Nsukka.

3.4.3 Multidrug Resistance (MDR) Patterns of E. coli Isolates from Wastewater Drains of UNN and KSU

In this study, antimicrobial resistance to AMC, VA, and P was generally observed. The index of isolates showing multidrug resistance ranged from 0.33 to 0.73, with a broad range discovered in isolates from both KSU female (Inikpi) and male (Ocheja) hostel drains (Table 6). The multiple antimicrobial drug resistance (MAR) index was calculated as the ratio of the number of antibiotics to which an organism is resistant against the total number of antibiotics to which the organism is exposed.

Table 6. Multidrug resistance (MDR) patterns of E. coli isolates from this study.
Sampling Area Campus Sampling point Resistant isolates Antibiotic resistance Number of antibiotics resisted (%) MAR index range
Female hostels drains UNN Nkrumah UNKEC3 UNKEC10 MEM, CAZ, P, CTX, E 5 (33.3) 0.33–0.67
UNKEC12 UNKEC9
UNKEC11
KSU Inikpi KIKEC9 KIKEC12 MEM, CAZ, P, CTX, E, CN 6 (40.0) 0.33–0.73
KIKEC8 KIKEC3
KIKEC1 KIKEC10
Male hostels drains UNN Alvan Ikoku UAVEC2 UAVEC9 MEM, CAZ, P, CTX, E 5 (33.3) 0.33–0.67
UAVEC10 UAVEC1
UAVEC3
KSU Ocheja KOCEC3 KOCEC1 MEM, CAZ, P, CTX, E 5 (33.3) 0.33–0.73
KOCEC2 KOCEC8
KOCEC11
KSU Dangana KDGEC8 KDGEC7 MEM, CAZ, P, CTX, E 5 (33.3) 0.33–0.67
KDGEC10 KDGEC2
KDGEC12
WTP UNN Influent UIFEC8 UIFEC3 MEM, CAZ, P, CTX, E, 5 (33.3) 0.33–0.5
UIFEC9 UIFEC11
UIFEC10 UIFEC1
UNN Effluent UEFEC3 UEFEC1 MEM, CAZ, P, CTX, E, 5 (33.3) 0.33–0.53
UEFEC9 UEFEC8
UEFEC2 UEFEC7
UEFEC10

Note: UIF, UNN-WTP influent; UEF, UNN-WTP effluent; UAV, UNN Alvan Ikoku male hostel; UNK, UNN Nkruma female hostel; KDG, KSU Dangana male hostel; KOC, KSU Ocheja male hostel; KIK, KSU Inipki female hostel; EC, E.coli; 1, January 2018; 2, February 2018; 3, March 2018; 7, July 2017; 8, August 2017; 9, September 2017; 10, October 2017; 11, November 2017; 12, December 2017; MAR, multiple antimicrobial drug resistance.

3.4.4 Detection of Virulence and Antibiotic-Resistance Genes in UPEC Isolates

Twenty-one isolates showing resistance to multiple antibiotics were screened for antibiotic-resistance genes using a molecular approach. In 100% of the isolates, uidA and hlyA genes were detected, confirming they are from E. coli and UPEC. ARGs detected were blaOXA-1 8 (38.1%), blaCTX-M3 8 (38.1%), and ant(2)-la 20 (95.2%) (Table 7). The gel results of the virulence and antibiotic-resistance genes of UPEC isolates identified in the study are shown in Supplementary Figs. 3,4,5,6,7.

Table 7. Detected antibiotic resistance genes in E. coli isolates.
Genes Present no. (%) Absent no. (%)
ant(2)-la 20 (95.2) 1 (4.8)
blaOXA-1 8 (38.1) 13 (61.9)
blaCTXM3 8 (38.1) 13 (61.9)
4. Discussion

The presence of pathogens in the environment is a great challenge because of their negative impact on human health. The presence of E. coli in the environment is frequently used to predict pathogen presence in the environment, most importantly, surface water. Evidently, WTP has been identified as a common source of E. coli contamination for most surface water worldwide [18]. Nevertheless, there is currently no documented information regarding the presence of this pathogen and the occurrence of its antimicrobial resistance genes in the study area.

In the present study, various degrees of resistance to antibiotics (100%: AMC, VA, and P; 95.2% against E; 88.9% against S; 69.8% against AMP; 66.7% against TE; 65.1% against CN) were observed, which suggest that the circulation of this environmental strains may be contributing to antimicrobial resistance spreads in the area. The high resistance levels to AMC, VA, and P observed with UPEC strains in the current study have been previously documented [7]. Previously, 100% resistance to tetracycline, amoxicillin/clavulanic acid, vancomycin, ciprofloxacin, penicillin, erythromycin, and gentamycin have been reported [19], corroborating the observations in our current study except for ciprofloxacin, which indicated a complete sensitivity. Various levels of resistance to some classes of antibiotics have been observed elsewhere. For instance, a study by Pokharel et al. [18] showed that tetracycline was the least potent, followed by ampicillin. A similar antibiotic resistance pattern was reported in more recent studies by Karam et al. [19] and Whelan et al. [20].

MDR has been regularly recorded among UPEC strains in Nigeria [17, 21, 22]. In the current study, the UPEC isolates from the KSU hostel drains had a higher multiple antimicrobial resistance range (0.33–0.73) than those from UNN (0.33–0.67). The maximum level (66.7%–73%) of multidrug resistance demonstrated by the isolates in our study is comparable with the 77% MAR level in E. coli strains previously isolated from a wastewater treatment facility [23]. According to Osundiya et al. [23], the level of non-susceptibility to amoxicillin/clavulanic acid demonstrated by the isolates in this study remains a regular occurrence in E. coli. Previously, Tang et al. [24] determined antibiotic resistance profiles of E. coli strains from a river watershed in France, and the study demonstrated antimicrobial resistance in 42% of the E. coli isolates, of which 35% exhibited MAR—the MAR index range among UPEC isolates in this study is considerably higher than those published by Tang et al. [24].

The level of potential UPEC strains observed in association with UNN-WTP influents and effluents is above the acceptable threshold. This observation may relate to the influx rates differential of domestic and industrial effluent into the plant, inefficient wastewater treatment processes, and non-adherence to standard treatment protocol. In our study, the findings of a significantly higher MAR in connection with UPEC strain from UNN effluent discharges support the assertion of Fouz et al. [2], who posited that high levels of ARB, MDR strains, and diverse ARGs are common in wastewater worldwide. Unsurprisingly, many studies have shown that effluent samples collected from urban, environmental, hospital, and pharmaceutical-treated wastewater still contain elevated levels of diverse ARGs, ARB, and antimicrobial drugs. For instance, a recent study demonstrated that the abundance of ARGs was significantly higher in effluent wastewater samples than in influents collected from low-income countries compared to high-income countries [25]. The spotting of potentially pathogenic E. coli in effluent from WTP could be associated with the inefficient removal of this bacteria during the treatment process. In another study, potentially pathogenic E. coli bacteria were reported in samples from a wastewater treatment facility at Hawassa University Referral Hospital [26]. According to the authors, the treatment could only remove larger dirt, leaving more organic matter for the remaining pathogens to use as substrates, further increasing the virulence and pathogenicity of pathogens [26].

A relatively high prevalence (96%) of E. coli that produces ESBL in wastewater of a rural and urban hospital in central India has been reported [10, 26]. In our study, the presumptive UPEC isolates showing multidrug resistance were all found to contain beta-beta-D-glucuronidase (uidA) and hemolysin A (hlyA). The presence of the uidA marker genetically confirmed that the isolates were of the genus E. coli [19], which, in this study, were phenotypically typed as UPEC strains. The hlyA detected in the study is commonly found in most uropathogenic E. coli (UPEC) strains reported worldwide [27]; thus, it raises serious concerns about the E. coli strains circulating in the study environment. In several case-based surveillance studies, a significant percentage of UPEC isolates have been reported to secrete hemolysin, which is directly associated with the onset of urinary tract infections (UTIs) [27]. This strain has been reported to cause acute renal failure in renal transplant patients and healthy individuals [28]. The UPEC-bearing hlyA gene was documented to increase cellular toxicity and urothelial damage [27, 28]. The gene (uidA) detected in the isolates codes for beta-D-glucuronidase, an enzyme that catalyzes the cleavage of numerous varieties of 3-glucuronides [29]. This enzyme is why the uidA gene is often employed as a marker for E. coli in water quality determination. Hence, the uidA PCR method is recommended for use because of its sensitivity for specific detection in substrate tests of E. coli by the US Environmental Protection for water quality monitoring [29].

The findings of ARGs comprising the blaOXA-1, blaCTX-M3, and ant(2)-la genes in the isolates suggest that their circulation in the environment may contribute to drug resistance in the area. Unlike the equal circulation of blaOXA genes in the study, Öztürk and Murt [28] and Bush and Jacoby [29] have reported the occurrence of blaOXA-and blaCTX-M3, respectively, as predominant genes in the environmental reservoirs. However, This result differs from the report of Chandran et al. [30], who reported blaCTX-M more frequently compared to blaTEM and ant(2)-la in isolates of E. coli from hospital-associated wastewater in India. In Enterobacteriaceae that produce ESBL, genes blaTEM, blaCTXM group1, bla SHV, and blaCTXM9 have been detected in effluents of hospitals [31]. The ESBLs detected in the study, especially CTX-M enzymes, represent a significant health concern in clinical practice [32]. As previously reported [33], the ESBL-producing UPEC strains currently account for most community and healthcare-associated infections. However, our study has a limitation, as the lack of a separate set of virulence genes in UPEC makes it difficult to ascertain the true pathogenic potential of the presumptive UPEC strains from environmental reservoirs [33]. Consequently, uncertainty may exist regarding determining the actual public health risks associated with the presence of presumptive UPEC isolates in wastewater environments.

5. Conclusion

The current study confirms the circulation of potential uropathogenic E. coli in the various wastewater environments of two Nigerian tertiary institutions. Generally, more UPEC was isolated from KSU than the UNN campus. The UPEC strains were completely susceptible to meropenem and 100% non-susceptible to amoxicillin/clavulanic acid, vancomycin, and penicillin G. The high rate of multidrug resistance observed in the UPEC isolates coupled with the detection of virulence genes in the current study suggest a public health risk in association with wastewater reuse in the area. Thus, there is a need for continuous wastewater-based surveillance programs to monitor the spread and any potential effects associated with the distribution of antimicrobial resistance and virulence genes through wastewater treatment plants and sewage-receiving hostel gutters in the area.

Availability of Data and Materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author Contributions

OME and CA designed the research study. OME performed the research. CA supervised the work. OME, CAO, RFA, JOA, GKN, SOS and STG analyzed the data. OME, CA, CAO, JOA, RFA, GKN, SOS, and STG wrote the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity.

Ethics Approval and Consent to Participate

This study did not involve human participants or animal subjects and was conducted in compliance with regional regulations, which do not require ethical approval for environmentally based research.

Acknowledgment

Not applicable.

Funding

This research received no external funding.

Conflict of Interest

The authors declare no conflict of interest.

Supplementary Material

Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/j.fbe1604038.

References

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