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Article

Antibiotic Resistance Patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa Isolated from Hospital Wastewater

by
Petro Karungamye
1,2,*,
Anita Rugaika
2,
Kelvin Mtei
2 and
Revocatus Machunda
2
1
Department of Chemistry, The University of Dodoma (UDOM), Dodoma P.O. Box 338, Tanzania
2
School of Materials Energy Water and Environmental Sciences, The Nelson Mandela African Institution of Science and Technology, Arusha P.O. Box 447, Tanzania
*
Author to whom correspondence should be addressed.
Appl. Microbiol. 2023, 3(3), 867-882; https://doi.org/10.3390/applmicrobiol3030060
Submission received: 8 July 2023 / Revised: 27 July 2023 / Accepted: 31 July 2023 / Published: 8 August 2023
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Abstract

:
Antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in treated hospital wastewater effluents constitute a major environmental and public health concern. The aim of this study was to investigate the antibiotic resistance patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa isolated from wastewater effluent at the Benjamin Mkapa Hospital (BMH) in Dodoma, Tanzania. These bacteria were selected to represent the most prevalent gram-negative bacteria found in hospital wastewater, and they have the potential to generate resistance and spread resistance genes to antibiotics. The wastewater BMH is treated in a Constructed Wetland (CW) planted with Typha latifolia before being released into the environment. The bacteria were isolated from wastewater effluent collected at the outlet of the CW. Isolated bacteria were analyzed for antibiotic resistance by disc diffusion method. Molecular identification of bacterial species was performed by using 16S rRNA. The results show that Klebsiella ssp. was the most common isolate detected, with a prevalence of 39.3%, followed by E. coli (27.9%) and Pseudomonas ssp. (18.0%). Klebsiella ssp. were more resistant than Pseudomonas ssp. for Tetracycline, Gentamycin, Ciprofloxacin, and Sulfamethoxazole. Pseudomonas ssp. were more resistant than Klebsiella ssp. for Ceftriaxone and Azithromycin. Klebsiella ssp. harbored more resistance genes (40%), followed by Pseudomonas ssp. (35%) and E. coli (20%). The findings of this investigation indicate that the effluent from the CW requires additional treatment to reduce discharged ARB and ARGs in the receiving water bodies. As a result, the effluent quality of the CW should be continuously monitored and assessed, and further developments for treating the final effluent are necessary.

1. Introduction

Antibiotics are secondary metabolites produced by microbes as well as chemically synthesized or semi-synthesized similar chemicals that can inhibit both the growth and survival of other microbes [1,2]. These compounds are used for the treatment of bacterial infections, to support surgical operations, to treat cancer, and as a preventative measure. They are also frequently used in aquaculture as growth promoters and in the veterinary care of domestic and livestock animals [3]. Antibiotic use is rapidly growing every year, and it is estimated that by 2030, use of antibiotics will have increased by 200% [4]. When these compounds are used for any given purpose, they do not become fully metabolized. According to studies, only small portions are fully metabolized by both humans and animals, with 20–90% of them being eliminated through the urine and feces as the parent compound or metabolite [5]. As a result, the parent compounds or their metabolites will reach and contaminate the environment.
Different sources, including hospital effluents, household sewage treatment plants, inappropriate disposal, and leachates from landfills, can release antibiotics or their metabolites into the environment [3]. Antibiotics can be transported directly from sewage treatment facilities into surface waters or by surface runoff. The use of sewage sludge biosolids as a source of fertilizer on agricultural land can expose ground waterways. Veterinary antibiotics reach the aquatic environment directly if treated animals are poorly managed and have access to surface water or, indirectly, through groundwater from treated cattle dung [6].
Antibiotics are emerging environmental pollutants of concern due to their possible adverse impacts on nontarget organisms and increasing resistance among bacteria [7,8]. When antibiotics enter the environment, they can change the dominant flora, community composition, and structure, as well as microbial diversity and richness. However, some environmental conditions significantly moderate the severity of the impacts [9]. Antibiotic resistance is an adaptive genetic characteristic that some subpopulations of bacteria exhibit or acquire that allows them to survive and grow even when exposed to therapeutic doses of an antibiotic agent that would typically kill or inhibit them [10]. This occurs because certain antibiotics, which are often released into the environment at low concentrations, exert significant selective pressure on bacterial communities, resulting in the development of their resistance [11,12]. The mechanism for bacterial resistance development is by gene mutation or horizontal gene transfer. As a result, organisms can develop resistance to a single antibiotic and become open to a variety of mobile genetic elements. Additionally, bacteria may develop multidrug resistance, making it challenging to treat patients in healthcare facilities [13]. It is difficult to assess and replace antibiotics to which resistance has arisen with newly developed ones in the quickest way possible. This reduces the number of therapy options, raises treatment expenses, lengthens hospital stays, results in unsuccessful treatments, and can cause deaths [12].
One of the sources of antibiotics in the environment is hospital wastewater effluent. A variety of factors influence hospital wastewater production, including water supply, bed availability, general services—such as air conditioning, kitchen, and laundry—the types and number of units or wards, and management practices. All of these processes contribute to the total amount of wastewater produced [14]. For the purpose of removing contaminants from hospital wastewater, a variety of technologies, such as functionalized membrane filtration, persulfate activated degradation, heterogeneous photocatalysis, Fenton-like degradation, and adsorption, have been investigated [15]. Conventional wastewater treatment facilities are designed to remove pollutants, such as total organic carbon, and nutrients, such as nitrates and phosphates. They are not intended to particularly remove micropollutants, such as antibiotics and antibiotic resistance genes (ARGs). The removal of antibiotics and ARGs in these systems varies by 1–2 log [5]. As a result, large amounts of antibiotics and ARGs are released into water bodies [16,17]. Humans can receive resistant bacteria from contaminated food and water, infected animals—through direct contact, meat, or milk consumption—contact with infected humans, and manure used as fertilizer [18,19,20,21,22]. Even if antibiotic-resistant bacteria have been damaged or eradicated during wastewater treatment, ARGs may still be discharged into the environment and transformed into other bacteria. Previous research has found that ARGs are abundant in wastewater lagoons and municipal wastewater even after treatment [23]. This necessitates the development of effective antibiotic removal techniques that can also inhibit the spread of ARGs [24].
Disinfection processes, membrane treatment technologies, advanced oxidation processes, and constructed wetlands (CWs) are some of the current methods for removing antibiotics and ARGs from wastewater [25]. The efficiency of these techniques toward the removal of ARB and ARGs differs. For instance, biochar can be used as an adsorbent for removing ARGs from wastewater. However, with time, the amount of ARGs that biochar could effectively remove was reduced [26]. Researchers have found that membrane filtration can reduce ARGs and ARB by 3.3–3.6 log at 20 °C thereby preventing them from entering the receiving water [27,28]. ARGs and ARB removal can also be accomplished through disinfection, such as utilizing chlorine. This chemical, which is a disinfectant that is widely used, performs very well as an oxidant to destroy bacteria cells, nucleic acids, and DNA [29]. ARG-carrying bacteria, such as Escherichia coli and Enterococcus faecium, were used as an example in a study where, within 30 min of adding 0.5 mg/L chlorine, more than 3.8–5.6 logs of bacteria and 0.8–2.8 logs of ARGs were concurrently eliminated [30]. However, this method elevates antibiotic resistance, which makes it harder to eradicate ARGs and also promotes the transmission and spread of ARGs among bacteria genera that can carry antibiotic resistance [31]. Advanced oxidation processes (AOPs) have the capacity to cause free radical reactions which destroy DNA and the cell surface of the bacteria. This indicates that AOPs would be a practical method for inactivating bacterial cells and removing ARGs [32,33].
A CW is a cost-effective and environmentally friendly wastewater treatment technique that effectively removes organic matter, bacteria, antibiotics, pharmaceuticals, and personal care products from wastewater and has great potential for ARG removal [31,34]. CW performance is based on natural processes that involve plants, soil/sediment, and microorganisms [35]. The benefits of CWs over activated sludge processes include improved wastewater purification performance, less energy utilization, low build-up and upkeep costs, and less demand for labor [23]. These benefits make CWs an environmentally sound and economically viable wastewater treatment technique in developing countries [36]. According to some studies, the absolute abundances of ARGs can be reduced in wastewater by using a CW with log units up to 3.3 [37]. However, other research indicates that, in addition to ARG reduction, CWs may also have the potential to induce ARGs in the process of antibiotic removal [23].
As a result, the purpose of this study was to look at the antibiotic resistance patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa isolated from wastewater effluent at the Benjamin Mkapa Hospital (BMH) in Dodoma, Tanzania. The selected bacteria represent the most prevalent gram-negative bacteria found in hospital wastewater, and they have the potential to generate resistance and spread genes that with a resistance to antibiotics [38,39,40,41]. The wastewater BMH is treated in a CW planted with Typha latifolia before being released into the environment. This study will hopefully assist in the advancement of knowledge and decision-making about the use of CWs for the treatment of antibiotic-containing wastewater.

2. Materials and Methods

2.1. Description of the Study Area

The research was conducted in November 2022 at the Benjamin Mkapa Hospital (BMH) in Dodoma, Tanzania. BMH is a tertiary public hospital located on the University of Dodoma’s campus. This hospital was established in 2015 to provide specialized and super-specialized health services, as well as to coordinate and oversee research and educational activities. Dodoma, Tanzania’s capital, has a total area of 2769 km2 and is located between 6°00′ and 6°30′ South and 35°30′ and 36°02′ East. Approximately 85% of the 570 mm of annual rainfall that falls on the area’s surface does so between December and April. The temperature often ranges between 18 °C to 31 °C [42]. Figure 1 shows the location of the studied CW.

2.2. Samples Collection

Research clearance was provided by the Tanzania Commission for Science and Technology (COSTECH). The permission to collect wastewater samples was provided by Dodoma Urban Water Supply and Sanitation Authority (DUWASA). In four months, a total of 32 treated hospital wastewater samples were taken from the CW outlet (Figure 2), 8 samples once every month. Grab samples were collected using sterilized syringes [43,44] put in sterile 250 mL bottles, and storsed in ice containers [45]. The samples were transported to the Department of Microbiology Parasitology and Biotechnology laboratories at Sokoine University of Agriculture (SUA) for microbiological analysis.

2.3. Isolation and Biochemical Identification

For isolation and identification of bacteria, culture was performed by enriched sample of water using Peptone Buffer water of which 2 mL of sample was inoculated into 10 mL of buffer peptone water and incubation was performed at 37 °C for 24 h [46]. Aseptically culturing was performed on blood agar (Oxoid), MacConkey agar (Oxoid), and Nutrient agar (Oxoid), and was then incubated between 24 and 48 h at 37 °C. Then, a subculture was prepared until a pure culture was obtained. Bacteria were stained using the gram staining technique to ascertain their microscopic features [47]. Classical identification of bacterial colonies and bio typing were performed according to the method described [48,49] with slight modifications. Briefly, the isolates were conventionally studied for their macro-and micro-morphological characteristics and then by biochemical assays. The assays included lactose, citrate, indole, motility, and oxidase [50]. Triple sugar iron agar and IMViC were also used for characterization of members of the family Enterobacteriaceae [51].

2.4. Phenotypic Antibiotic Susceptibility Testing

Antimicrobial susceptibility testing was performed using the disc diffusion method. The isolates were tested against Tetracycline (TET), Gentamycin (GEN), Ceftriaxone (CEF), Ciprofloxacin (CIP), Azithromycin (AZT), and sulfamethoxazole (SUL), which were all supplied by Sigma-Aldrich (St. Louis, MO, USA). The decision to utilize these antibiotics was based on their availability for testing and their frequency of use in hospitals. For antimicrobial susceptibility assays, a pool of bacterial colonies was used to prepare suspensions corresponding to 0.5 McFarland standards (1.5 × 108 CFU/mL) using normal saline, and then bacteria were spread on top of Müller–Hinton agar using a sterile swab. Discs were placed on top of the medium, and the plates were incubated at 37 °C for 24 h. Zones of inhibition were measured by means of a simple ruler, and the diameter was recorded in millimeters (mm). Isolates were defined as susceptible, intermediate, or resistant in accordance with the CLSI [52] Enterobacteriaceae breakpoints.

2.5. Genotypic Analysis

2.5.1. DNA Extraction

The genomic DNA was isolated from an overnight growth bacterial colony using a boiling method. Briefly, the colonies were put in an Eppendorf tube containing 100 μL of the nuclease free water and boiled in a water bath at 95 °C for 10 min and immediately transferred into the ice for 5 min. This procedure was repeated, and the suspension was centrifuged at 10,000 rpm for 10 min. Five microliters of the supernatant were taken for further process. The concentration and quality of the extracted DNA were checked by electrophoresis (1% agarose gel) and spectrophotometrically quantified using NanoDrop Spectrophotometer. All extracted DNA were stored at −20 °C [53,54,55].

2.5.2. Molecular Identification of Bacterial Species

All isolates presumptively identified based on biochemical and phenotypic characteristics were subjected to molecular identification. The universal primers designed to give a product of approximately 1500 base pairs and are complementary to conserved regions of 16S rRNA genes were used for PCR amplification. PCR was performed using a master mix (Bioneers premix, Daejeon, Korea), and the amplification was performed as follows: initial denaturation steps at 95 °C for 3 min and followed by 35 cycles of denaturation at 95 °C for the 30 s, annealing at 58 °C for 30 s, and extension at 72 °C for 1 min followed by terminal extension at 72 °C for 3 min. The agarose gel (1%) stained with ethidium bromide was used to analyze PCR products by electrophoresis. Positive bands were visualized by ultraviolet trans-illumination [56,57,58,59].

2.5.3. Identification of Resistance Genes

All isolates that expressed phenotypical resistance were screened by PCR for the presence of various recognized resistance genes to different antibiotics. Positive and negative controls were used for resistance genes. However, it was impossible to source positive controls for some screened genes. Without positive controls, optimized and previously published primers and PCR protocols were used. The amplification conditions for the Sul1 and Sul2 genes were as follows: 94 °C for 5 min; 30 cycles of 94 °C for 30 s, 69 °C for 30 s and 72 °C for 45 s; and one cycle of 72 °C for 7 min. To detect bla SHV, bla TEM, and bla CTX-M, PCR amplification conditions were as follows: initial denaturation step at 95 °C for 5 min; 30 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 30 s. Extension at 72 °C for 2 min, followed by a final extension step at 72 °C for 10 min. Gel electrophoresis was performed on 1.5% agarose gels [60,61,62,63]. Table 1 provides details of the primers used to detect Cephalosporins (bla SHV, bla TEM and bla CTX-M), Sulfonamides, and 16S rRNA used in the present study.

2.5.4. Sequencing and Phylogenetic Analysis

The PCR products were purified using the QIAquick PCR Purification Kit. Sequencing was performed by Macrogen Company, Korea under commercial basis. Sequence assembly was performed using CLC Main Workbench version 6.7.1 (http://www.clcbio.com (accessed on 1 July 2023)). Sequence similarity was compared with published sequences in the GenBank database using the nucleotide BLAST program [67]. Isolates were identified at the species level based on ≥99% sequence identity with type strains or reported strains. Multiple alignments were performed using a Cluster W program in the Mega7 software [68]. Phylogenetic trees were inferred by the neighbor-joining method [69], which bootstrapped 1,000 replicates based on the pdistance model [70]. Alignment gaps or missing data were deleted, and the tree was rooted with Rickettsia ssp. ATCC VR 141 as the outgroup.

3. Results

3.1. Isolation and Biochemical Identification

A total of 32 wastewater effluent samples were analyzed. Of these samples, 87.5% (28 samples) tested positive for one or more isolates. A total of 61 bacterial isolates were recovered from the samples. These isolates were identified as Klebsiella pneumoniae (n = 24, 39.3%), Pseudomonas aeruginosa (n = 11, 18.0%), and Escherichia coli (n = 17, 27.9%). Other isolated bacteria were Staphylococcus aureus (n = 5, 8.2%) and Proteus mirabilis (n = 4, 6.6%). These data show that Klebsiella ssp. has the highest prevalence among the bacterial isolates, followed by E. coli, Pseudomonas ssp., Staphylococcus ssp., and Proteus ssp.

3.2. Phenotypic Antibiotic Susceptibility Testing

An antibiotic susceptibility test was performed for Klebsiella ssp., E. coli, and Pseudomonas ssp. The results show that Klebsiella pneumoniae (n = 24) had 13 strains resistant to Tetracycline, 12 were resistant to Gentamycin, 8 were resistant to Ceftriaxone, 7 were resistant to Ciprofloxacin, 10 were resistant to Azithromycin, and 9 were resistant to Sulfamethoxazole. Pseudomonas aeruginosa (n = 11) had 3 strains resistant to Tetracycline, 2 were resistant to Gentamycin, 4 were resistant to Ceftriaxone, 3 were resistant to Ciprofloxacin, 5 were resistant to Azithromycin, and 3 were resistant to Sulfamethoxazole. Escherichia coli (n = 17) had 6 strains resistant to Tetracycline, 3 were resistant to Gentamycin, 4 were resistant to Ceftriaxone, 3 were resistant to Ciprofloxacin, 4 were resistant to Azithromycin, and 5 were resistant to Sulfamethoxazole. The percentage of resistance is presented in Figure 3.

3.3. Molecular Identification of Bacterial Species

A total of 12 g-negative bacterial isolates were amplified using universal primers targeting the T 16S rRNA gene. Results showed that all positive isolates (Amplicons) appeared at 1500 bp, as shown in Figure 4. Whereby M is a 100 bp marker, lanes 1, 5, 7, and 10 are Klebsiella species, lanes 2, 3, 4, and 11 are Pseudomonas species, and lanes 6, 8, 9 and 12 are Escherichia coli species. Positive products are located at 1500 bp as shown in Figure 4.

3.4. Identification of Resistance Genes

The detection of antibiotic-resistant genes on 12 bacterial isolates showed that Klebsiella ssp. harbored more resistance genes (40%), followed by Pseudomonas ssp. (35%) and E. coli (20%), as shown in Table 2. Six (6) isolates out of 12 contained sulphonamide resistant genes as follows: Sul1 (n = 4) and Sul2 (n = 2), making up 50% of the total resistant genes analyzed in this study (Figure 5 and Table 2). β-lactamases (bla CTX-M, bla TEM, and bla SHV) were found in all isolates, with Klebsiella harboring more resistance genes than others as shown in Table 2 and Figure 5a–c below.

3.5. Sequencing and Phylogenetic Analysis

The 16S rRNA gene sequences of all isolates were subjected to BLAST analysis (Figure 6) to identify the closest reference sequences available in GenBank. BLAST analysis revealed that all isolates belonged to the family Enterobacteriaceae. Escherichia coli from this study showed similarity with other E. coli species from the GeneBank database. While other members such as Klebsiella ssp. and Pseudomonas ssp. revealed high similarity (99–100%) to their respective genus as shown in the figure below. These results confirm the findings obtained from the convectional diagnosis (Culture and Biochemical tests) obtained earlier in the present study.

4. Discussion

In this study, Klebsiella pneumoniae was the most common isolate detected, with a prevalence of 39.3%, followed by Escherichia coli (27.9%), Pseudomonas aeruginosa (18.0%), Staphylococcus aureus (8.2%), and Proteus mirabilis (6.6%). It is worth noting that different studies have documented diverse microbial compositions in hospital wastewater. It has been reported in a similar study that the overall isolates found in treated hospital wastewater samples were 39.5% E. coli, 35.1% Staphylococcus, and 30.7% Klebsiella species [12]. In Ghana, a study was conducted to assess the presence of multidrug-resistant bacteria in hospital wastewater. The results showed that Escherichia coli made up 30.6%, Klebsiella pneumoniae 11.2%, Citrobacter freundii 10.9%, Alcaligenes faecalis 5.8%, and Pseudomonas mendocina 5.4% [71]. Common pathogenic microorganisms found in hospital wastewater include bacteria, fungus, yeasts, viruses, algae, protozoa, parasites, and bacteriophages [72]. Bacteria make up approximately 95% of all microorganisms in complex ecosystems and are vital for wastewater treatment [73]. The most common pathogen in hospital wastewater is Staphylococcus aureus. Other common pathogens include Klebsiella Proteus, Candida albicans, Pseudomonas aeruginosa, Escherichia coli, and Enterobacter species [74,75].
Gram-negative bacteria, including Klebsiella pneumoniae, Escherichia coli, and Pseudomonas aeruginosa, were tested for antibiotic resistance. The results show that different levels of antibiotic resistance exist among the studied bacteria and antibiotics. Bacteria as a group or species are not necessarily equally susceptible to or resistant to a certain antimicrobial agent. Even among closely related bacterial groups, resistance levels might differ significantly [76]. Bacteria have several defensive mechanisms to defend against the effects of antimicrobials and to endure environmental stress. The most prevalent antibiotic resistance mechanisms include inhibiting drug absorption, modifying drug targets, making drugs inactive, and active drug efflux [77,78,79]. The sorts of mechanisms utilized by gram-negative bacteria on antibiotic resistance differ from those used by gram-positive bacteria due to variations in the structure of the cell wall. Gram-positive bacteria lack the ability for some forms of drug efflux mechanisms and are less frequently employed in limiting the absorption of a drug, whereas gram-negative bacteria use all four of the basic mechanisms [76]. The major cause of gram-negative bacteria’s resistance to a variety of antibiotics is their outer membrane. To reach their targets, most antibiotics must cross the outer membrane. Resistance can be produced by gram-negative bacteria altering the outer membrane in any way, including by mutating porins, modifying the hydrophobic characteristics, or altering other variables. Because gram-positive bacteria lack this crucial layer, gram-negative bacteria are more resistant to antibiotics than gram-positive bacteria [80,81]. Medically important gram-negative bacteria include Acinetobacter ssp., Bordetella pertussis, Campylobacter ssp., Enterobacteriaceae (Citrobacter ssp., Enterobacter ssp., Escherichia coli, Klebsiella ssp., Salmonella ssp., Serratia marcescens, Shigella ssp., Yersinia ssp.), Haemophilus influenzae, Helicobacter pylori, Legionella pneumophila, Neisseria ssp., Pseudomonas aeruginosa, and Vibrio cholerae [82]. Results from the current study show that Klebsiella ssp. were more resistant than Pseudomonas ssp. for TET, GEN, CIP, and SUL. Pseudomonas ssp. were more resistant than Klebsiella ssp. for CEF and AZT. Studies show that Staphylococcus aureus is the most common pathogenic gram-positive bacterium with a high level of multidrug resistance [72]. The results from the current study suggest that disposing of hospital wastewater effluent with a high intensity of these resistant bacteria poses a health risk to the general public.
Antibiotic resistance genes (ARGs) are currently regarded as an emerging contaminant and an ecological issue since they are present in practically every ecosystem. ARGs found in the environment may operate as a reservoir and spread horizontally to bacteria that are linked with humans, contributing to the emergence of new antibiotic-resistant strains [83]. Compared to other wastewater systems, such as municipal sewage systems, hospital wastewater has higher risks of spreading ARGs [84,85]. More global awareness should be given to the role that hospital wastewater plays in the spread of ARGs in the environment. The present study shows that Klebsiella ssp. harbored more resistance genes (40%), followed by Pseudomonas ssp. (35%) and E. coli (20%).
Sulfonamides (SN) or sulfanilamides are a significant family of synthetic antimicrobial drugs that are used pharmacologically as broad-spectrum antibiotics to treat bacterial infections in both humans and animals. A distinctive 6- or 5-membered heterocyclic ring and the presence of the sulfanilamide group define Sulfonamide structures, which are organo-sulfur compounds containing the -SO2NH2 and/or -SO2NH- group [86]. Bacterial resistance to sulfonamides typically results from mutations in the folP gene, which encodes the dihydropteroate synthase (DHPS) enzyme involved in nucleotide biosynthesis, or from the acquisition of alternative DHPS genes (sul1, sul2, and sul3), whose byproducts have low affinity for sulfonamides. Since sul genes are frequently found in plasmids, they serve as the most prevalent mechanism of sulfonamide resistance and have been found in a variety of bacterial species from a variety of habitats, including agricultural soils and wastewaters [87]. The results of the present study indicate that, of the 12 isolates tested, six (6) included sulfonamide resistant genes, specifically Sul1 (n = 4) and Sul2 (n = 2), which together accounted for 50% of the total resistance genes examined in this study.
The class of antibiotics known as β-lactams all have the same basic structure: the beta-lactam ring, which is a four-membered cyclic amide. Due to their bactericidal action and low toxicity, beta-lactam antibiotics are most often used in antibacterial drugs for treating bacterial infections, with the exception of individuals who have allergies [88]. Examples of β-lactam antibiotics include penicillins, cephalosporins, carbapenems, and monobactams [89]. β-lactam antibiotics work by inhibiting the formation of bacterial cell walls, which results in cell lysis and death. The enzyme necessary for the building of the bacterial cell wall, penicillin-binding protein (PBP), is specifically bound and acylated by beta-lactam antibiotics [90]. The most prevalent mechanism of resistance in gram-negative bacteria, and very rarely experienced by gram-positive bacteria, is the formation of β-lactamases, enzymes that hydrolyze β-lactam antibiotics, rendering them ineffective [91]. Numerous gram-negative bacteria, such as Acinetobacter, Aeromonas caviae, Proteus mirabilis, Providencia ssp., Escherichia coli, and Klebsiella pneumoniae, have also been reported to have several AmpC β-lactamase genes [92]. The results from this study show β-lactamases (bla CTX-M, bla TEM and bla SHV) were found in all isolates, with Klebsiella harboring more resistance genes than others. One Klebsiella pneumoniae isolate contained bla SHV and five isolates contained bla CTX-M. One Escherichia coli isolate contained bla SHV and two isolates contained bla TEM. Three isolates of Pseudomonas aeruginosa contained bla SHV and one isolate contained bla TEM. The presence of β-lactamases genes in hospital wastewater effluent isolates implies that the effluent still harbors these ARGs despite CW treatment, posing a health concern.

5. Conclusions

The findings of this investigation indicate that there are significant levels of ARB and ARGs in the hospital wastewater despite treatment in the CW. All bacteria such as Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa contained isolates resistant to the tested antibiotics. Additionally, all bacteria contained ARGs such as sul1, sul2, sul3, bla CTX-M, bla TEM and bla SHV where Klebsiella ssp. harbored more resistance genes (40%), followed by Pseudomonas ssp. (35%) and E. coli (20%). This suggests that in order to preserve the public health, appropriate measures with the goal of reducing the pollution of the environment by ARB and ARGs need to be taken. This can be accomplished by improving the CW’s performance and combining the CW with other treatment techniques that remove ARB and ARGs. The general interventions may consist of improving antibiotic treatments, finding alternative therapies, and improving hygienic conditions in order to limit the use of antibiotics.

Author Contributions

Conceptualization, P.K., A.R. and K.M.; methodology, R.M.; resources, K.M. and R.M.; writing—original draft preparation, P.K.; writing—review and editing, P.K., A.R., K.M. and R.M.; supervision, A.R., K.M. and R.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We are grateful to the Tanzania Commission for Science and Technology (COSTECH) for providing us with a research clearance and Dodoma Urban Water Supply and Sanitation Authority (DUWASA) for allowing us to collect and analyze wastewater samples. We would like to express our gratitude to Gideon Sangiwa, a Laboratory Scientist at UDOM, Hussein Idd, a Laboratory Scientist at NM-AIST, Erick Osward, and Elisa Mwega of Sokoine University of Agriculture for allowing us to use their laboratory facilities and for their significant technical and analytical support.

Conflicts of Interest

The authors declare no conflict of interest.

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Applmicrobiol 03 00060 g001
Figure 1. Map of Tanzania, Dodoma urban district and the studied constructed wetland.
Figure 1. Map of Tanzania, Dodoma urban district and the studied constructed wetland.
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Figure 2. Photographic appearance of the CW (a) and sampling point (b).
Figure 2. Photographic appearance of the CW (a) and sampling point (b).
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Figure 3. Antibiotic resistance patterns of bacterial isolates in wastewater effluent.
Figure 3. Antibiotic resistance patterns of bacterial isolates in wastewater effluent.
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Figure 4. PCR amplification of 16S rRNA.
Figure 4. PCR amplification of 16S rRNA.
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Applmicrobiol 03 00060 g005aApplmicrobiol 03 00060 g005b
Figure 5. (a): PCR amplification of Sulfonamide 1 and 2 (Sul1 and Sul2) resistance genes. M is a 100 bp marker and lanes 1–4, 7, 8 are samples, where lanes 1–4 are positive for the Sul1 resistance gene located at 450 bp, lanes 5 and 6 are negative and positive controls for the Sul1 gene, respectively, lanes 7 and 8 are positives for the Sul2 resistant gene located at 625 bp, and lanes 9 and 10 are negative and positive controls for Sul2, respectively. (b): PCR amplification of bla CTX-M resistance gene. M is a 100 bp marker and lanes 1–9 are samples, where lanes 1, 2, 4, 5 and 8 are positives located at 554 bp. Lanes 10 and 11 are negative and positive controls, respectively. (c): PCR amplification of bla SHV and bla TEM resistance genes. M is a 100 bp marker and lanes 1–5, 8–10 are samples, where lanes 1–5 are positive for the bla SHV resistance gene located at 862 bp, lanes 6 and 7 are negative and positive controls for bla SHV, respectively, lanes 8–10 are positives for the bla TEM resistant gene located at 858 bp, and lanes 11 and 12 are negative and positive controls for bla TEM, respectively.
Figure 5. (a): PCR amplification of Sulfonamide 1 and 2 (Sul1 and Sul2) resistance genes. M is a 100 bp marker and lanes 1–4, 7, 8 are samples, where lanes 1–4 are positive for the Sul1 resistance gene located at 450 bp, lanes 5 and 6 are negative and positive controls for the Sul1 gene, respectively, lanes 7 and 8 are positives for the Sul2 resistant gene located at 625 bp, and lanes 9 and 10 are negative and positive controls for Sul2, respectively. (b): PCR amplification of bla CTX-M resistance gene. M is a 100 bp marker and lanes 1–9 are samples, where lanes 1, 2, 4, 5 and 8 are positives located at 554 bp. Lanes 10 and 11 are negative and positive controls, respectively. (c): PCR amplification of bla SHV and bla TEM resistance genes. M is a 100 bp marker and lanes 1–5, 8–10 are samples, where lanes 1–5 are positive for the bla SHV resistance gene located at 862 bp, lanes 6 and 7 are negative and positive controls for bla SHV, respectively, lanes 8–10 are positives for the bla TEM resistant gene located at 858 bp, and lanes 11 and 12 are negative and positive controls for bla TEM, respectively.
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Figure 6. Neighbor-joining phylogenetic trees based on 16S rRNA gene partial sequences of Escherichia coli, Klebsiella ssp., and Pseudomonas ssp. (Bolded) obtained from this study clustered together with the closely related genera of the family Enterobacteriaceae retrieved from GenBank database. Bootstrap values (expressed as percentages of 1000 replications) are shown at branch points. Rickettsia species was used as an outgroup to root up the tree.
Figure 6. Neighbor-joining phylogenetic trees based on 16S rRNA gene partial sequences of Escherichia coli, Klebsiella ssp., and Pseudomonas ssp. (Bolded) obtained from this study clustered together with the closely related genera of the family Enterobacteriaceae retrieved from GenBank database. Bootstrap values (expressed as percentages of 1000 replications) are shown at branch points. Rickettsia species was used as an outgroup to root up the tree.
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Table 1. Primers’ names and sequences used in the present study.
Table 1. Primers’ names and sequences used in the present study.
Primer NameSequenceExpected Band (bp)Annealing Temp.Reference
Sul1 F
Sul1 R		CGGCGTGGGCTACCTGAACG
GCCGATCGCGTGAAGGTTCCG 		450 bp55 °C[64]
Sul2 F
Sul2 R		GCGCTCAAGGCAGATGGCATT
GCGTTTGATACCGGCACCCGT		625 bp58 °C[64]
bla SHV F
bla SHV R		ATGCGTTATATTCGCCTGTG
AGCGTTGGCCAGTGCTCGATC		862 bp58 °C[65]
bla CTXM F
bla CTXM R		SCSATGTGCAGYACCAGTAA
CCCGCRATATGRTTGGTGGTGGTG		554 bp58 °C[66]
bla TEM F
bla TEM R		ATGAGTATTCMCATTTCCG
CCMTGCTTMTCAGTGAGG		858 bp50 °C[65]
16s rDNA F
16s rDNA R		AGAGTTTGATTCATGGCTCAG
TACGGYTACCTTGTTACGACTT 		1500 bp58 °C[64]
Table 2. Antibiotic-resistant genes on bacterial isolates.
Table 2. Antibiotic-resistant genes on bacterial isolates.
Bacterial ssp.Number
(N)		Sul1
(n)		Sul2
(n)		SHV
(n)		CTXM
(n)		TEM
(n)		MDR Genes (%)
Pseudomonas ssp.43030135
Klebsiella ssp.41115040
E. coli ssp. 40110220
Resistance genes (%) 3317424225
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Karungamye, P.; Rugaika, A.; Mtei, K.; Machunda, R. Antibiotic Resistance Patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa Isolated from Hospital Wastewater. Appl. Microbiol. 2023, 3, 867-882. https://doi.org/10.3390/applmicrobiol3030060

AMA Style

Karungamye P, Rugaika A, Mtei K, Machunda R. Antibiotic Resistance Patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa Isolated from Hospital Wastewater. Applied Microbiology. 2023; 3(3):867-882. https://doi.org/10.3390/applmicrobiol3030060

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Karungamye, Petro, Anita Rugaika, Kelvin Mtei, and Revocatus Machunda. 2023. "Antibiotic Resistance Patterns of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa Isolated from Hospital Wastewater" Applied Microbiology 3, no. 3: 867-882. https://doi.org/10.3390/applmicrobiol3030060

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