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Article

Microbiological and Molecular Characterization of Bacterial Communities in Domestic Water Sources in Nabuti Village, Mukono District, Central Uganda

by
Catherine A. Najjembe
1,2,†,
Oluwatoyin M. Aladejana
1,2,†,
Jessica N. Uwanibe
1,2,
Christian T. Happi
1,2 and
Onikepe A. Folarin
1,2,*
1
Department of Biological Sciences, Faculty of Natural Sciences, Redeemer’s University, Oshogbo 232102, Osun State, Nigeria
2
Institute of Genomics and Global Health (IGH), Redeemer’s University, Oshogbo 232102, Osun State, Nigeria
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Microbiol. Res. 2025, 16(5), 99; https://doi.org/10.3390/microbiolres16050099
Submission received: 28 March 2025 / Revised: 13 May 2025 / Accepted: 14 May 2025 / Published: 15 May 2025
Browse Figure
Versions Notes

Abstract

:
Access to clean and safe water is crucial for community well-being. Water samples from storage tank water (STW) and municipal tap water (MTW) were aseptically collected, and total bacterial and coliform counts were determined. Isolates were Gram-stained, and conventional biochemical tests were conducted. Antibiotic susceptibility testing was performed using Kirby–Bauer’s disk diffusion technique. Selected isolates were confirmed through Sanger sequencing of amplified 16S rRNA genes. Polymerase chain reaction and gel electrophoresis techniques were used to determine the presence of quinolone and beta-lactam resistance genes. A total of 50 water samples were analyzed. The mean total coliform counts (TCCs) were 5.75 for STW and 5.5 for MTW. In total, 43 and 13 bacterial isolates were recovered from STW and MTW, respectively, with Gram-negative bacteria being more prevalent 58.14% (25/43) in STW and 81.82% (9/11) in MTW. The isolates appeared to belong to seven different presumptive bacterial genera on biochemical tests. The 16S rRNA gene amplicon Sanger sequencing of 38 isolates revealed 15 different species. A total of 38 isolates tested for resistance genes revealed that 47.37%, 31.58%, 21.05%, 10.53%, 28.95%, and 13.16% harbored gyrB, parC, gyrA, parE, blaSHV, and blaTEM genes, respectively. Antibiotic susceptibility profiling revealed a predominance of multidrug-resistant (MDR) strains among the bacterial isolates from both water sources. Regular monitoring and enhanced water treatment are critical to protect the public health and reduce the spread of potential pathogenic and antibiotic-resistant bacterial strains in household water systems.

1. Introduction

Water quality for domestic purposes in developing countries is frequently compromised due to a variety of contaminants, including chemical and biological pollutants. Pathogenic microorganisms, including bacteria and protozoans, further contribute to the compromised quality of domestic water supplies, posing serious health risks [1]. Globally, the average daily water usage for domestic purposes is estimated at 1.75 L per person, covering activities such as drinking, cleaning, dishwashing, and more [2,3]. Despite municipal water provisions in some developing regions, many households seek additional methods to ensure a reliable and clean water supply. This often involves utilizing alternative water sources, such as shallow or deep wells, boreholes, and various types of storage tanks (steel, plastic, or cement) designed to capture rainwater or store municipal water for future use to meet domestic purposes. These storage solutions provide households with some measure of water security in areas with intermittent or unreliable municipal water services [4].
According to World Health Organization (WHO) guidelines for drinking water quality, water safety requires comprehensive monitoring from the source to the treatment and distribution points [5]. The United Nations (UN) Sustainable Development Goal (SDG) 6.1, introduced in 2015, specifically aims to secure universal access to safe, affordable drinking water by 2030, aligning with broader efforts to improve public health through improved water management. However, as noted in the 2022 SDG report, approximately 2.2 billion people still lack access to safely managed drinking water, highlighting the need for sustained global attention to water access and quality improvement [6].
In developing countries, bacteriological contamination remains a significant challenge in domestic water supplies. The presence of coliform bacteria, in particular, serves as a key indicator of water contamination. WHO guidelines stipulate that coliforms should be absent in every 100 mL of drinking water [5] and that Escherichia coli levels in drinking water should be zero per 100 mL to ensure safety [7]. Contamination can result from numerous sources, including agricultural runoff, untreated industrial or healthcare wastewater, animal and human waste, soil, and even climate change-related temperature shifts, which create conditions favorable for bacterial growth [8,9]. Consuming bacterial contaminated water either by drinking, cooking, or washing food significantly increases the risk of waterborne diseases such as diarrhea, dysentery, typhoid, and cholera, and infections caused by Escherichia coli [10,11]. Diarrheal diseases, which commonly result from water contamination, continue to burden public health systems, particularly in South Asia (e.g., India) and Sub-Saharan Africa (e.g., Uganda, Kenya, Nigeria, and Burundi) [12,13]. Fecal coliforms, including diarrheagenic Escherichia coli, Klebsiella pneumoniae, Citrobacter freundii, and Enterococci, are frequently identified in domestic water sources, alongside other pathogens such as Vibrio cholerae, Salmonella species, and Pseudomonas aeruginosa, which contribute significantly to diarrhea-related illness, especially among children under five and immunocompromised individuals [13,14]. In Uganda, diarrhea is notably prevalent in urban slum areas [15] and in the Northern region, with a reported 29.1% prevalence among children under five [16]. Various bacteria, such as Salmonella typhi, Shigella, Vibrio cholerae, diarrheagenic Escherichia coli, and Campylobacter, are linked to diarrheal illnesses stemming from the consumption of contaminated water [17]. Mortality rates from unsafe water remain disproportionately high in low-income countries, where deaths from waterborne diseases exceed 50 per 100,000 individuals [18].
Despite advances in understanding the bacterial composition of traditional water sources, such as lakes, wells, and rivers [19,20], there remain limited data on the bacterial quality of water from modern sources like storage tanks and municipal tap water systems. Given the need to combat waterborne diseases, continuous surveillance of microbial pathogens in household water sources is essential. Therefore, this study aimed to assess the occurrence and abundance of bacterial life in storage tank water (STW) and municipal tap water (MTW), which are common sources of water for domestic use, isolate the pathogenic bacteria, and conduct antimicrobial susceptibility testing. The presence of resistance genes for quinolones (parE, parC, qnrA, gyrB, and gyrA) and beta-lactams (blaTEM and blaSHV) is also studied, as well as utilizing 16S rRNA gene amplicon sequencing to identify bacterial species among the selected multiple antibiotic-resistant isolates obtained from municipal tap water and storage tank water samples.

2. Materials and Methods

2.1. Study Site

The study site was Nabuti Village, Mukono District, Central Region of Uganda, at an elevation of 1204 m about 0°20′52″ N and 32°44′38″ E. Mukono District spans approximately 2986.47 square kilometers and is bordered by Kampala District to the southwest.
Water samples were collected from household storage tanks and municipal water taps, which are the two primary domestic water sources currently used in Mukono District, Central Uganda.

2.2. Sample Collection

Permission to collect water samples from these sources was obtained from the owners at each residence. Sampling was performed randomly and aseptically, resulting in a collection of 50 samples: 30 from household storage tanks (STW) and 20 from municipal water taps (MTW). Water samples were collected into 15 mL sterile centrifuge tubes, labeled with the date, water source, and a unique identification number. The samples were then placed in an insulated double-walled cooler box with ice packs to maintain a cold chain during temporary storage and transportation. Subsequently, the samples were transported to the Microbiology Laboratory, Department of Biological Sciences at Redeemer’s University for microbial analysis, and molecular analysis was performed at the Institute of Genomics and Global Health (IGH), formerly African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer’s University, Ede, Osun State, Nigeria.

2.3. Plate Count

The pour plate method was used to enumerate the total culturable bacterial and coliform counts in the water samples. For each sample, 1 mL was aseptically transferred into two separately labeled, sterile petri dishes in duplicate. Sterile Plate Count Agar (HiMedia Laboratories Pvt. Ltd., Mumbai, Maharashtra, India) was poured into one set of dishes to quantify total viable bacterial counts, while MacConkey Agar (HiMedia Laboratories Pvt. Ltd., Mumbai, Maharashtra, India) was used in a separate set to assess total coliform counts. The contents of each dish were gently swirled to ensure even mixing before allowing the agar to solidify. The plates were incubated upside down at 37 °C for 24–48 h. The colonies observed were counted and results were expressed in CFU/mL.

2.4. Isolation of Bacteria

Distinct colonies were selected and sub-cultured on sterile nutrient agar plates (HiMedia Laboratories Pvt. Ltd., Mumbai, Maharashtra, India), followed by incubation at 37 °C for 24–48 h. Pure colonies were then transferred onto single-strength nutrient agar slants, incubated at 37 °C for 48 h, and subsequently stored at 4 °C for further analysis.

2.5. Identification of Bacteria Isolates

All bacteria isolates were tested for citrate, catalase, and cytochrome oxidase enzyme production as described by [21], with results recorded as + for a positive reaction and − for a negative reaction. Additionally, substrate fermentation tests were conducted according to [22], with plates incubated at 37 °C for 24–48 h. Observations were based on bacterial growth and color changes on the respective agar media. Gram staining was also performed to determine the Gram reaction of the isolates, as described by [22].

2.6. Antibiotic Susceptibility Test

Antimicrobial susceptibility testing was conducted using the disk diffusion method, as described by [23]. The antibiotic disks used included Tetracycline (30 µg), Ciprofloxacin (5 µg), Chloramphenicol (30 µg), Trimethoprim/sulfamethoxazole (25 µg), Ceftazidime (30 µg), Ceftriaxone (30 µg), Cefotaxime (30 µg), and Aztreonam (30 µg). Results were interpreted according to the 2023 guidelines provided by the Clinical and Laboratory Standards Institute (CLSI) and European Committee on Antimicrobial Susceptibility Testing (EUCAST).

2.7. Extraction of Genomic DNA

For each selected bacterial isolate, 2 loopfuls of pure colonies were incubated on nutrient agar for 18 h at 37 °C and suspended in 400 μL of sterile nuclease-free water in a 2 mL microcentrifuge tube. The bacterial cell suspension was then incubated at 96 °C for 20 min, and DNA extraction from the bacterial isolate cell suspension was performed using QIAamp DNA Mini Kit (Qiagen, Germany) according to the manufacturer’s instructions.

2.8. Amplification of the 16S rRNA Gene

For PCR preparation, a final reaction volume of 25 μL per tube was used with DNA template (5 μL), forward 16SF (5′ GGA ACT GAG ACA CGG TCC AG 3′) and reverse 16SR (5′ CCA GGT AAG GTT CTT CGC GT 3′) primers (0.125 μL each at a concentration of 0.2 uM), 4 μL of FIREPol Master Mix Ready to Load with 12.5 mM MgCl2 (5X), 15.75 μL of nuclease-free water [24]. The mixture was mixed by vortexing and the reaction was carried out in a PCR thermocycler apparatus with initial denaturation at 95 °C for 5 min, followed by 35 cycles, as follows: denaturation was performed at 94 °C for 30 s, annealing at 57 °C for 30 s, elongation at 72 °C for 1 min, and final elongation at 72 °C for 10 min; after which all final PCR products were run through a 2% agarose gel electrophoresis and visualized under ultraviolet light.

2.9. Sanger Sequencing of the 16S rRNA Gene Amplicons

To prepare the 16S rRNA amplicons for sequencing, 10 µL of each PCR product was combined with 4 µL of ExoSAP-IT™ (Thermo Fisher Scientific, Waltham, MA, USA) in a 96-well plate, totaling 14 µL per reaction. The plate was incubated at 37 °C for 15 min to degrade residual primers and nucleotides, followed by inactivation at 80 °C for 15 min. For BigDye™ Terminator (Thermo Fisher Scientific, Waltham, MA, USA) sequencing, 1 µL of 20 µM forward or reverse primer was added to 48 wells each in a new 96-well plate. Each well received 2 µL of BigDye™ Terminator 3.1 Ready Reaction Mix, 3 µL of BigDye™ sequencing buffer, 7 µL of nuclease-free water, and 7 µL of ExoSAP-IT-treated amplicons. After brief vortexing and centrifugation, thermal cycling was conducted as follows: 25 cycles of denaturation at 96 °C for 10 s, annealing at 50 °C for 5 s, and extension at 60 °C for 4 min, with a final hold at 4 °C. For BigDye™ XTerminator purification, 110 µL of a 1:4 mixture of XTerminator and SAM solutions (Thermo Fisher Scientific, Waltham, MA, USA) was added to each well in a new 96-well plate, protected from light, followed by the addition of 5 µL of the sequencing product. The plate was rocked at 300 rpm for 30 min. The final reaction plate was sealed with a sterile septa mat and processed on a 3100/3100-Avant Genetic Analyzer (Thermo Fisher Scientific, Waltham, MA, USA) using standard data collection settings.

2.10. Quinolone and Beta-Lactam Resistance Gene Detection

The quinolone (qnrA, gyrA, parE, parC, and gyrB) and beta-lactam (blaTEM, blaSHV) resistant genes were detected in the isolates using PCR and gel electrophoresis techniques. Multiplex PCR was conducted with quinolone resistant gene (Group 1) and beta-lactam resistant gene (Group 2) primers listed in Table 1. A final reaction volume of 25 μL per tube was used with DNA template (2 μL), forward and reverse primers (1 μL each at a concentration of 0.8 uM), 4 μL of FIREPol Master Mix Ready to Load with 12.5 mM MgCl2 (5X), and nuclease-free water to reach a volume of 25 μL. The mixture was mixed by vortexing and the reaction was carried out in a PCR thermocycler apparatus with initial denaturation at 95 °C for 5 min, followed by 35 cycles, as follows: denaturation was performed at 94 °C for 30 s, annealing at 55 °C for 30 s, elongation at 72 °C for 1 min, and final elongation at 72 °C for 10 min; after which all final PCR products were run through agarose gel electrophoresis and visualized under ultraviolet light.

2.11. Analysis of the 16S rRNA Gene Sequences

The 16S rRNA gene sequences obtained from the bacterial isolates were analyzed using the BLASTn tool (Basic Local Alignment Search Tool) available through the National Center for Biotechnology Information (NCBI). This analysis compared the query sequences to those in the GenBank database to identify the closest matches. Only results showing high sequence identity (97–100%), query coverage of 99–100%, and an E-value of zero indicating strong similarity to reference sequences were considered in this study.

2.12. Statistical Analysis

The data were analyzed using the statistical package SPSS for Windows, version 20. Descriptive statistics were used to describe measures of central tendencies and variation from the mean, including 95% confidence intervals. Data were entered into Microsoft Excel to construct bar charts.

3. Results

3.1. Total Plate Count (TPC) of Bacteria from Water Samples

The TPC was notably higher in storage tank water samples compared to municipal tap water samples, with some storage tank samples exhibiting exceptionally high counts, classifying them as outliers. Despite the differences in variability, the colony count results for both water sources were statistically significant, with p-values of 0.005 for storage tank samples and 0.010 for municipal tap water samples (p < 0.05) (Table 2).

3.2. Total Coliform Counts (TCCs) of Bacteria from Water Samples

The TCCs in both water sources were generally low, with some samples showing no detectable coliforms. Total coliform counts in storage tank water samples were statistically significant (p = 0.003), while those in municipal tap water samples were not (p = 0.121) (p < 0.05) (Table 3).

3.3. Bacterial Isolates Obtained from Water Samples

A total of 56 isolates were obtained; 43 were from STW, and 13 were from MTW samples.

3.3.1. Gram Staining Results of Bacterial Isolates from Water Samples

Of the 43 and 13 isolates obtained from STW and MTW, 25 (58.14%) and 9 (81.82%) respectively were Gram-negative bacteria, while 18 (41.86%) and 4 (36.36%) isolates were Gram-positive bacteria (Supplementary Table S1).

3.3.2. Biochemical Test Results of Bacterial Isolates from Water Samples

Biochemical tests indicated that the isolates likely represent seven different presumptive bacterial genera. The bacterial isolates from storage tank water (STW) were presumptively identified as Klebsiella spp. (9), Pseudomonas spp. (4), Acinetobacter spp. (6), Enterobacter spp. (5), Bacillus spp. (13), Enterococcus spp. (1), and Corynebacterium spp. (5). Similarly, those from municipal tap water (MTW) were presumptively identified as Enterobacter spp. (2), Acinetobacter spp. (4), Corynebacterium spp. (2), Klebsiella spp. (1), Bacillus spp. (3), and Pseudomonas spp. (1) (Supplementary Table S2).

3.4. Antibiotic Susceptibility Profiles of Bacterial Isolates

The antibiotic susceptibility profiles of bacterial isolates from water sources were analyzed based on the diameter of the zone of inhibition (ZOI) for multiple antibiotics. The results, as visualized in the bar chart, (Figure 1) indicate a predominance of multidrug-resistant (MDR) strains among the bacterial isolates.

3.5. Amplification of the 16S rRNA Gene in Bacterial Isolates

The 16S rRNA gene was successfully amplified in 38 (27 from STW, and 11 from MTW) out of the 41 bacterial isolates whose DNA was extracted. This amplification confirmed effective binding between the specific primers and the extracted DNA. The expected amplicon size was approximately 660 bp, as determined by comparison with a 100 bp molecular weight DNA ladder (Supplementary Figures S1 and S2).

3.6. Sanger Sequencing of the 16S rRNA Gene in Isolates from Water Samples

Sanger sequencing of the 16S rRNA gene from 38 successfully amplified isolates (27 from STW, and 11 from MTW) revealed Klebsiella oxytoca (2), Kluyvera georgiana (1), Klebsiella pneumoniae (1), Bacillus altitudinis (3), Acinetobacter junii (1), Comamonas testosteroni (1), Bacillus cereus (4), Acinetobacter pittii (1), Aquitalea magnusonii (1), Bacillus subtilis (1), Stenotrophomonas sp. (1), Pseudomonas putida (1), Acinetobacter parvus (1), Pseudomonas sp. (1), and Enterobacter hormaechei (1) from STW while Comamonas testosteroni (3), Pseudomonas sp. (3), Kluyvera georgiana (1) were detected in MTW (Table 4).

3.7. Prevalence of Quinolone and Beta-Lactam Resistant Genes

Resistance gene detection was successful in only 30 strains. Quinolone resistance genes were detected in 68.42% (26 of 38 isolates) (7 from MTW and 19 from STW). The most common of the genes were gyrB (18/26 isolates) and parC (12/26 isolates). Beta-lactam resistance genes, particularly blaSHV in 28.95% (11 of 38 isolates) (5 from MTW and 6 from STW), and blaTEM in 13.16% (5 of 38 isolates), were less frequently observed in other species but more in Pseudomonas species (Table 5 and Supplementary Figures S3–S6).

4. Discussion

Domestic water sources can be a source of contamination based on storage and sanitation and level of purification processes. This contamination can be of public health significance for disease transmission and spread of antibiotic resistance. This study outlines the presence of bacteria isolates in municipal tap water (MTW) and storage tank water (STW) in Nabuti Village in the Mukono District of Uganda. Most importantly observed is the fact that the bacteria pathogens are mostly observed in immunocompromised individuals, thus causing great concern for effective management of infection in these populations. Of note is the level of resistance observed in these isolates, hence emphasizing the significance of surveillance of antibiotic resistance in water samples in order to curtail the menace of antimicrobial resistance.
The mean total colony count of 54.6 was higher in storage tank samples than in municipal taps, where bacterial distribution was more consistent, reflecting the effectiveness of the National Water and Sewerage Corporation’s (NWSC) water treatment processes, which include coagulation, flocculation, sedimentation, and chlorination. These findings align with previous studies on domestic water quality in Uganda [27,28]. The elevated bacterial counts in storage tanks suggest uneven bacterial loads, likely due to factors such as tank age, material, and inconsistent cleaning practices. Most tanks had not been cleaned in over two years, leading to biofilm accumulation and increased bacterial growth, particularly in older and galvanized steel tanks, as observed in similar studies in Wakiso district [4] and Bolivia [29].
The World Health Organization’s standard for coliform count is zero coliforms per 100 mL of drinking water [30]. The mean coliform count of 5.75 and 5.5 observed in water samples from municipal taps and storage tanks, respectively, was far higher than this standard and this is of great concern to the public health. The variability in coliform counts, particularly in municipal tap water, raises concerns about water quality in Mukono District, which contrasts with lower coliform levels reported in Kampala’s Kawempe division [27]. This increase in Mukono is likely influenced by intermittent water supply systems that are prone to microbial contamination due to low pressure and leaky pipes, as noted in a study by [28]. Such systems can compromise water quality by allowing biofilm formation and pollutant intrusion during low-pressure periods, contributing to microbial and chemical contamination [31,32].
There is notable diversity among the bacterial isolates from both water sources, with a higher proportion of Gram-negative observed in municipal tap water and storage tanks. Gram-negative bacteria are often linked to significant public health concerns, as many are opportunistic pathogens capable of causing infections, particularly in immunocompromised individuals, and are frequently associated with multidrug resistance [33]. For example, Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa have emerged as public health concerns due to their presence in both environmental and hospital settings [34,35,36]. Common Gram-negative rods such as E. coli, Klebsiella, and Pseudomonas are well-known culprits in waterborne diseases [37] that lead to gastrointestinal and wound infections, and in severe cases, systemic infections [38].
The presence of Gram-positive rods also poses a health risk, as species like Bacillus and Clostridium can be problematic, especially if they are spore-forming and resistant to disinfection efforts. The resilience of Bacillus species, including their ability to withstand disinfectants and form spores, underscores their potential pathogenicity in water systems [39,40]. Gram-negative coccobacilli can include species such as Acinetobacter, which are opportunistic pathogens known to cause healthcare-associated infections, respiratory issues, and bloodstream infections, and have well been isolated in domestic water systems [41,42]. In storage tank water, factors such as the sanitary conditions of water entry routes, tank cleanliness, age, material, environmental fluctuations due to climate change, low disinfectant levels, and water stagnation have been associated with microbial contamination [4,28,31].
The colonization of domestic water storage and distribution systems by bacteria belonging to families such as Enterobacteriaceae, Pseudomonadaceae, and Moraxellaceae has been frequently reported [43,44,45,46]. In addition, [47] identified Comamonadaceae as one of the three most dominant families in drinking water tank sediments. The Xanthomonadaceae family, which includes both plant and human opportunistic pathogens, has been associated with biofilms in drinking water distribution pipes [48] and household storage containers [49].
Research differentiates between fecal–oral pathogens and opportunistic pathogens like Klebsiella spp., Pseudomonas spp., Kluyvera spp., Stenotrophomonas spp., Acinetobacter spp., and Bacillus spp., noting that these organisms are normal environmental inhabitants, including water, and their presence does not necessarily indicate fecal contamination [36]. These opportunistic pathogens can thrive in water given the right conditions and temperature, as shown by their metabolic versatility, similar to findings in studies on marine Proteobacteria [50]. Unlike fecal–oral pathogens, opportunistic pathogens have multiple infection routes beyond ingestion, such as through the urinary tract, skin, wounds, eyes, and ears. Their higher infectious dose (typically 105–108 organisms per gram) means that their concentration in water is critical, especially for vulnerable populations such as the elderly, young children, and immunocompromised individuals [40,51,52,53,54]. Opportunistic pathogens identified in this study have also been isolated from human specimens in hospital settings, causing infections such as bacteremia, urinary tract infections, meningitis, pneumonia, endophthalmitis, biliary tract infections, skin and soft tissue infections, and sepsis [53,55,56,57,58,59]. These bacteria are capable of invading various organs and are associated with virulence factors such as toxin production [40,60], biofilm formation, and intrinsic resistance to multiple antibiotics and disinfectants [40,61].
The growing concern regarding antibiotic resistance and the presence of antibiotic resistance genes (ARGs) in bacteria isolated from domestic water sources was also highlighted in this study. Antibiotic susceptibility testing revealed varied resistance patterns, with notable resistance to beta-lactams, particularly aztreonam and third-generation cephalosporins, which is consistent with findings from similar studies [62,63]. Similarly, several Enterobacteriaceae and Acinetobacter species exhibited extensive resistance, particularly to β-lactam antibiotics such as ceftriaxone (CRO), cefotaxime (CTX), ceftazidime (CAZ), and aztreonam (ATM), with minimal or no ZOI recorded. Pseudomonas species also demonstrated a high resistance level to multiple antibiotics, further supporting their intrinsic multidrug-resistant nature.
In contrast, certain isolates, including Comamonas testosteroni, showed greater susceptibility to antibiotics such as ciprofloxacin (CIP) and trimethoprim-sulfamethoxazole (SXT). However, intermediate resistance was observed across multiple bacterial groups, suggesting potential adaptation mechanisms and reduced antibiotic efficacy. The observed resistance patterns underscore the prevalence of multidrug-resistant bacteria in aquatic environments, posing a potential public health risk. These findings emphasize the need for continuous surveillance and the implementation of antimicrobial stewardship programs to mitigate the spread of antibiotic resistance in environmental reservoirs.
Resistance genes such as gyrA, gyrB, parC, and blaSHV were identified in several isolates, suggesting that despite observed susceptibility to ciprofloxacin in antibiotic susceptibility testing (AST), underlying resistance mechanisms may exist. This study found that 65.85% of isolates carried quinolone resistance genes, indicating the potential for emerging resistance under selective pressure [64]. The presence of few isolates carrying blaTEM and blaSHV genes suggests that other beta-lactamase genes like blaCTX-M, blaDHA, or blaCMY could be contributing to the observed resistance, as these genes have been associated with extended-spectrum beta-lactamase (ESBL) production and AmpC beta-lactamase resistance [63,65].
Sanger sequencing of the 16S rRNA gene amplicons from bacterial isolates obtained from the two water sources revealed a diverse range of bacterial families, including Enterobacteriaceae, Comamonadaceae, Pseudomonadaceae, Moraxellaceae, Bacillaceae, Chromobacteriaceae, and Xanthomonadaceae. Isolates from storage tank water exhibited greater diversity of fifteen different species covering seven different families, while those from municipal tap water were limited to three families. Previous studies, such as those by [66,67], have also reported Enterobacteriaceae species in rain harvest tanks and municipal tap water samples within Uganda. However, the broader range of bacterial families identified in this study may be due to the use of a more robust sequencing method, which was not employed in prior studies. The bacterial species identified showed a 16S rRNA gene sequence similarity of 97–100%, with 12 isolates belonging to Proteobacteria and 3 to Firmicutes. The dominance of Proteobacteria in aquatic environments, including drinking water systems, has been well documented [45,68,69]. Studies by [70] demonstrated that the abundance of Proteobacteria increases significantly after chlorine disinfection. Other research works focusing on drinking water distribution systems, molecular techniques like metagenomics, and 16S rRNA gene sequencing have identified bacterial families similar to those found in this study [36,45,71].
The resistance profiles observed in this study align with patterns reported in hospital specimens, further underscoring the public health challenge posed by the transmission of ARGs through water sources. These findings stress the need for continuous monitoring and robust water treatment processes to mitigate the spread of resistant bacteria in domestic water systems. Also as shown in this study, Sanger sequencing offers a broader and more accurate identification of bacterial species compared to conventional biochemical tests.

5. Conclusions

The microbiological analysis of municipal tap and storage tank water in Nabuti Village revealed significant bacterial contamination, with both water sources exceeding the WHO’s coliform count standards. The higher colony counts in storage tanks, coupled with the great diversity of bacteria, present a greater public health risk. The dominance of Gram-negative bacteria, known for their pathogenicity and antibiotic resistance potential, and the presence of antibiotic-resistant, opportunistic bacterial species in these water samples underscores the urgent need for better water treatment and maintenance of domestic water storage systems. The detection of quinolone and beta-lactam resistance genes in isolates from both municipal tap and storage tank water underscores the potential health risks associated with these water sources. Notably, a higher resistance was observed to aztreonam, while ciprofloxacin demonstrated the most effective inhibition. The findings suggest a need for regular monitoring and improved water treatment practices to mitigate the risk of community-acquired infections linked to antibiotic-resistant bacteria in domestic water supplies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microbiolres16050099/s1, Figure S1 and Figure S2: 16S rRNA amplicons; Figure S3 and Figure S4; blaTEM, blaSHV, gyrB and parC gene amplicons; Figure S5: blaTEM, blaSHV, gyrB, parC, gyrA, and parE gene amplicons; Figure S6: qnrA, gyrA and parE gene amplicons; Table S1: Gram stain results and cell shape; Table S2: Biochemical test results and presumptive bacteria.

Author Contributions

Conceptualization, O.A.F. and C.A.N.; Methodology, O.M.A. and J.N.U.; Investigation, O.A.F., C.A.N., O.M.A. and J.N.U.; Data curation, C.A.N. and O.M.A., Writing—original draft preparation, C.A.N., Writing—review and editing, O.A.F. and O.M.A.; Visualization, C.A.N. and J.N.U.; Supervision, O.A.F.; Project administration, O.M.A. and O.A.F.; Funding acquisition, C.T.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the World Bank ACE impact grant (worldbank.org) (ACE—019 project to C.T.H.).

Data Availability Statement

The 16S rRNA gene sequences generated in this study are deposited in the NCBI GenBank under the accession numbers PV643067–PV643095.

Acknowledgments

We extend our sincere appreciation to the community members of Nabuti Village for allowing access to their water sources for sample collection, and to the technical teams at the Microbiology Laboratory, Redeemer’s University, and the Molecular Biology Laboratory, Institute of Genomics and Global Health, for their invaluable technical support.

Conflicts of Interest

The authors declare that there is no conflict of interest.

Abbreviations

The following abbreviations are used in the manuscript:
MTWmunicipal tap water
PCRpolymerase chain reaction
STWstorage tank water
TPCtotal plate count
TCCtotal coliform count

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Microbiolres 16 00099 g001
Figure 1. Antibiotic susceptibility profiles of bacterial isolates from both water sources. The bar chart represents the diameter of the zone of inhibition (ZOI) in millimeters for different bacterial isolates against eight antibiotics: ceftriaxone (CRO), cefotaxime (CTX), ceftazidime (CAZ), aztreonam (ATM), tetracycline (TE), ciprofloxacin (CIP), trimethoprim-sulfamethoxazole (SXT), and chloramphenicol (C). Resistant (ZOI ≤ 14 mm), Intermediate (ZOI 15–19 mm), Susceptible (ZOI ≥ 20 mm), indicating a predominance of multidrug-resistant (MDR) strains.
Figure 1. Antibiotic susceptibility profiles of bacterial isolates from both water sources. The bar chart represents the diameter of the zone of inhibition (ZOI) in millimeters for different bacterial isolates against eight antibiotics: ceftriaxone (CRO), cefotaxime (CTX), ceftazidime (CAZ), aztreonam (ATM), tetracycline (TE), ciprofloxacin (CIP), trimethoprim-sulfamethoxazole (SXT), and chloramphenicol (C). Resistant (ZOI ≤ 14 mm), Intermediate (ZOI 15–19 mm), Susceptible (ZOI ≥ 20 mm), indicating a predominance of multidrug-resistant (MDR) strains.
Microbiolres 16 00099 g001
Table 1. Primers used for the detection of quinolone and beta-lactam resistance genes in the bacteria isolates.
Table 1. Primers used for the detection of quinolone and beta-lactam resistance genes in the bacteria isolates.
Antibiotic TypeResistance GenePrimer Sequence (5′-3′)Reference
QuinolonesQnrAATTTCTCACGCCAGGATTTG[25]
GATCGGCAAAGGTTAGGTCA
GyrAACGTATTGGGCAATGACTGG
GGAGTCGCCGTCAATAGAAC
GyrBCAAACTGGCGACTGTCAGG
AGCCCAGCGCGGTGATCAGC
ParCCGTCTATGCGATGTCAGAGC
TAACAGCAGCTCGGCGTATT
ParEGTCAATGTGCGGCATTTGTT
ATCCCCTTCCACAAGGAACA
Beta-lactamsblaTEMATCAGCAATAAACCAGC[26]
CCCCGAAGAACGTTTTC
blaSHVAGGATTGACTGCCTTTTTG
ATTTGCTGATTTCGCTCG
Table 2. Total plate counts in storage tanks and municipal tap water samples (bacterial count, CFU/mL).
Table 2. Total plate counts in storage tanks and municipal tap water samples (bacterial count, CFU/mL).
Water SuppliesNumber of Samples (N)MeanMdn.Min.Max.SD.95% CI
Storage Tanks3054.615.5144697.43918.216, 90.984
Municipal water Taps2010.35306016.1682.783, 17.917
Table 3. Total coliform counts in storage tanks and municipal tap water samples (bacterial count, CFU/mL).
Table 3. Total coliform counts in storage tanks and municipal tap water samples (bacterial count, CFU/mL).
Water SuppliesNumber of Samples (N)MeanMdn.Min.Max.SD.95% CI
Storage Tanks305.500329.4391.976, 9.024
Municipal water taps205.75007015.824−1.656, 13.156
Table 4. Bacterial isolates identified by 16S rRNA gene amplicon Sanger sequencing.
Table 4. Bacterial isolates identified by 16S rRNA gene amplicon Sanger sequencing.
Isolate CodeOrganism FamilyNCBI % SimilarityGram Stain and Cell Shape
HIAKlebsiella oxytocaEnterobacteriaceae100%Gram-negative (short rods)
H16AKluyvera georgianaEnterobacteriaceae99%Gram-negative (short rods)
H1BKlebsiella oxytocaEnterobacteriaceae100%Gram-negative (short rods)
T6Comamonas testosteroniComamonadaceae98.89%Gram-negative (Short rods)
T3Pseudomonas sp.Pseudomonadaceae99.82%Gram-negative (Short rods)
H10HKlebsiella pneumoniaeEnterobacteriaceae97.69%Gram-negative (short rods)
H3H2Bacillus altitudinisBacillaceae99.67%Gram-positive (Short rods)
H42AAcinetobacter juniiMoraxellaceae98.50%Gram-negative (coccobacilli)
T7AKluyvera georgianaEnterobacteriaceae99.21%Gram-negative (short rods)
H52AAcinetobacter pittiiMoraxellaceae98.89%Gram-negative (coccobacilli)
H59Aquitalea magnusoniiChromobacteriaceae99.51%Gram-negative (short rods)
H40Bacillus cereusBacillaceae99.84%Gram-positive (Long rods)
H3I1Bacillus altitudinisBacillaceae98.84%Gram-positive (short rods)
H34Bacillus subtilisBacillaceae99.51%Gram-positive (Short rods)
H46Stenotrophomonas sp.Xanthomonadaceae98.06%Gram-negative (Short rods)
T12AComamonas testosteroniComamonadaceae98.53%Gram-negative (short rods)
T9APseudomonas sp.Pseudomonadaceae100%Gram-negative (Long rods)
T12BComamonas testosteroniComamonadaceae98.89%Gram-negative (short rods)
H13BPseudomonas putidaPseudomonadaceae98.70%Gram-negative (Short rods)
H9AAcinetobacter parvusMoraxellaceae99.00%Gram-negative (coccobacilli)
H30Bacillus cereusBacillaceae99.84%Gram-positive (Long rods)
H13AComamonas testosteroniComamonadaceae99.54%Gram-negative (Short rods)
H3BBacillus altitudinisBacillaceae99.68%Gram-positive (Long rods)
H19Pseudomonas sp.Pseudomonadaceae99.17%Gram-negative (short rods)
T1Pseudomonas sp.Pseudomonadaceae99.49%Gram-negative (Long rods)
H10-7Enterobacter hormaecheiEnterobacteriaceae99.66%Gram-negative (short rods)
H49Bacillus cereusBacillaceae100%Gram-positive (Long rods)
H8Bacillus cereusBacillaceae99.52%Gram-positive (short rods)
Key: “H” denotes isolates from household storage water tanks. “T” denotes isolates from municipal tap water samples.
Table 5. Bacteria isolates carrying quinolone resistance genes and beta-lactam genes by PCR.
Table 5. Bacteria isolates carrying quinolone resistance genes and beta-lactam genes by PCR.
Isolate CodeBacteriumQuinolone Resistance Genes PresentBeta-Lactam Resistance Genes Present
T6Comamonas testosteroneParCblaSHV
H14ABacillus cereusparC, parEblaSHV
T12AComamonas testosteroneParCblaSHV
H5BUnclassified isolateparC, parE, gyrA, gyrBblaSHV
H46Stenotrophomonas sp.parC, gyrBblaSHV
T7FUnclassified isolateParCblaSHV
H49Bacillus cereusGyrB
H13AComamonas testosteroneParCblaSHV
H2BUnclassified isolateParCblaSHV
H13BPseudomonas putidaGyrB
H1AKlebsiella oxytocagyrB, gyrA
T7AKluyvera georgianagyrB, parC, gyrA
H19AUnclassified isolateGyrB
T14AUnclassified isolategyrB, parEblaSHV
H30Bacillus cereusGyrB
H42AAcinetobacter juniiGyrB
T16AUnclassified isolategyrB, gyrA
H5AUnclassified isolategyrB, parE
H59Aquitalea magnusoniiparC, qnrAblaSHV
H40Bacillus cereusGyrB
H1BKlebsiella oxytocagyrB, gyrA
H10-7Enterobacter hormaecheigyrB, gyrAblaTEM
T13Unclassified isolategyrB, parC
H16AKluyvera georgianagyrB, gyrA
H10HKlebsiella pneumoniaegyrB, gyrA
H9AAcinetobacter modestusParC
T3Pseudomonas sp. blaTEM
T9APseudomonas sp. blaSHV, blaTEM
H19Pseudomonas sp. blaTEM
T1Pseudomonas sp. blaTEM
Key: “H” denotes isolates from household storage water tanks. “T” denotes isolates from municipal tap water samples.
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Najjembe, C.A.; Aladejana, O.M.; Uwanibe, J.N.; Happi, C.T.; Folarin, O.A. Microbiological and Molecular Characterization of Bacterial Communities in Domestic Water Sources in Nabuti Village, Mukono District, Central Uganda. Microbiol. Res. 2025, 16, 99. https://doi.org/10.3390/microbiolres16050099

AMA Style

Najjembe CA, Aladejana OM, Uwanibe JN, Happi CT, Folarin OA. Microbiological and Molecular Characterization of Bacterial Communities in Domestic Water Sources in Nabuti Village, Mukono District, Central Uganda. Microbiology Research. 2025; 16(5):99. https://doi.org/10.3390/microbiolres16050099

Chicago/Turabian Style

Najjembe, Catherine A., Oluwatoyin M. Aladejana, Jessica N. Uwanibe, Christian T. Happi, and Onikepe A. Folarin. 2025. "Microbiological and Molecular Characterization of Bacterial Communities in Domestic Water Sources in Nabuti Village, Mukono District, Central Uganda" Microbiology Research 16, no. 5: 99. https://doi.org/10.3390/microbiolres16050099

APA Style

Najjembe, C. A., Aladejana, O. M., Uwanibe, J. N., Happi, C. T., & Folarin, O. A. (2025). Microbiological and Molecular Characterization of Bacterial Communities in Domestic Water Sources in Nabuti Village, Mukono District, Central Uganda. Microbiology Research, 16(5), 99. https://doi.org/10.3390/microbiolres16050099

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