Coliform bacterial contamination of dairy products and antimicrobial susceptibility patterns of common coliform bacterial isolates in Gondar-Bahir Dar milk shed, Northwest Ethiopia

doi:10.21203/rs.3.rs-3629770/v1

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Coliform bacterial contamination of dairy products and antimicrobial susceptibility patterns of common coliform bacterial isolates in Gondar-Bahir Dar milk shed, Northwest Ethiopia

https://doi.org/10.21203/rs.3.rs-3629770/v1

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Background: Dairy products can be contaminated by pathogenic microorganisms due to unhygienic production and processing practices. Determining the status of the bacteriological contamination is vital to design evidence-based strategies to minimize the risk of infections and to enhance the quality and shelf life of processed products. This study was conducted to determine the status of contamination of dairy products with coliform bacteria and the antimicrobial susceptibility of common coliform bacterial isolates in the Gondar-Bahir Dar milkshed, Northwest Ethiopia.

Methods: In total, 184 dairy product samples (raw milk (97), yoghurt (traditionally fermented milk) (48), buttermilk (9), traditionally prepared soft cheese (11), and pasteurized milk (19)) were collected. Of these, the coliform count was conducted on 146 samples (raw milk (97), yoghurt (6), buttermilk (6), traditionally prepared soft cheese (11), and pasteurized milk (19)) was assessed by coliform counts. Coliform bacteria were isolated from all 184 samples using standard bacteriological techniques and isolates were identified by the Analytical Profile Index (API) E 20 test. The antimicrobial susceptibility of the bacterial isolates was assessed by using the Kirby-Bauer disk diffusion method.

Results: The average coliform count (CC) of samples was 5.6 log CFU/ml (confidence interval (CI)= 5.3 – 6.0). There was a significant (P<0.05) difference in the average CC among sample types, cleanness of the animals and hygiene of the containers. However, the differences in the average CC among sampling sites, farm size, source of water to clean milk containers, availability of cooling facilities, feed source, type of container, farm hygiene, and milker’s hygiene were not statistically significant. Out of examined 184 samples, 40.8, 33.7, 9.2, 12.5, and 1.6% were positive for E. coli, Citrobacter species (spp), Klebsiella spp, Enterobacterspp, and Serratia spp, respectively. Coliform bacteria isolates were more susceptible to third-generation cephalosporins like ceftazidime, ceftriaxone, and cefotaxime. However, they were relatively more resistant to cephalothin and ampicillin.

Conclusion: most of the dairy product samples were highly contaminated by coliform bacteria and the isolates demonstrated a considerable rate of resistance. Therefore, hygienic measures should be enhanced to improve the bacteriological quality of dairy products in the study area, and strategies need to be designed to reduce the proliferation and spread of resistant strains to minimize public health risks.

Antimicrobial resistance

Bacteriological quality

Coliforms

Dairy products

Gondar-Bahir Dar milk shed

Northwest Ethiopia

Milk and other dairy products are important foods for rural and urban communities owing to their high nutritional value. They are good sources of nutrients for infants and children and they are recommended by the World Health Organization (WHO) to cure and prevent stunting of children (Garcia et al., 2019; Haile and Headey, 2023). These products are the source of income that enables families to buy other foodstuffs and significantly contribute to household food security in developing countries like Ethiopia (Gebremedhin et al., 2020; Brown et al., 2022).

Milk is synthesized by specialized cells in the mammary gland and milk from healthy animals contains no or very limited bacteria when secreted into the alveoli of the udder. However, beyond this stage, microorganisms may contaminate the milk at different points of milking and processing as the result of poor preparation of udder to milking, sub-optimal hygiene maintained by milk handlers, uncleaned milking environment, unhygienic ingredients added and storage utensils. Proper hygienic measures during milk production and processing can reduce the bacterial load and improve the safety and quality of dairy products (Reta et al., 2016; Calahorrano-Moreno et al., 2022).

Dairy products can be contaminated with pathogenic microorganisms which may pose serious health risks to the public. In 2010, it was reported that milk-borne diseases account for 20 disability-adjusted life years (DALYs) per 100,000 people which represents about 4% of the global foodborne disease burden and 12% of the animal-source food disease burden in the globe (Grace et al., 2020). Hence, milk-borne diseases have emerged as a major public health concern, particularly for those individuals who still drink raw (untreated or unprocessed) milk (Yohannes, 2018). Since, raw milk is used by many farm families, workers and a growing segment of the general population who believe that some beneficial items can be destroyed during processing. Hence, the utilization of raw dairy products has frequently been associated with foodborne illness (Claeys et al., 2013; Megersa, et al., 2019; Amenu et al., 2020).

Coliform bacteria are among many microorganisms that contaminate dairy products (Martin et al., 2016; Abunna et al., 2019). Coliforms are aerobic or facultatively anaerobic, Gram-negative, non-spore-forming rods and capable of fermenting lactose with the production of acid and gas within 48 hours of incubation at 32–35°C. These include species of Escherichia, Klebsiella, Enterobacter, and Citrobacter which are the members of the Enterobacteriaceae family. They are found in the environment and mammalian intestine as commensal bacteria, and are used as indicators of faecal contamination of food (Martin et al., 2016). Coliforms can also induce urinary tract infections, respiratory tract infections, nosocomial infections, wound infections, meningitis and gastroenteritis. Coliforms can carry resistant traits that are transferable to pathogenic bacteria via horizontal gene transfer (Godziszewska et al., 2018; Liu et al., 2020; Salazar et al., 2020).

There is a worldwide concern about the emergence and spread of antimicrobial resistance (AMR) to commonly used antimicrobials. Antimicrobial resistance has been recognized as one of the most important and top public health threats in the globe. It has been estimated that 4.95 million deaths were associated with bacteria1 AMR in 2019 (Murray et al., 2022). The problem will intensify in the future, especially in developing countries including Ethiopia (O’Neill, 2014; Beyene et al., 2023). The previous reports on AMR were focused on clinical isolates and the dynamic of AMR has been changed due to the COVID-19 pandemic (Virdi et al., 2021). There is a need to generate more data on the susceptibility pattern of isolates from the environmental and food samples (Beyene et al., 2023). Additionally, assessing antimicrobial susceptibility has been recognised as one of the global research agendas to design appropriate interventions and guidelines to prevent and contain the emergence and spread of AMR (WHO, 2023).

Assessment of contamination of dairy products with coliforms helps in determining the microbiological quality of these products so that appropriate hygienic measures can be taken. Food and Agriculture Organization (FAO) and World Health Organization (WHO) guidance on microbial risk assessment indicated that assessing the bacteria composition and load (count) are the essential components of risk analysis and exposure modelling (FAO/WHO, 2021). Such information is very limited in Ethiopia, particularly in the Gondar-Bahir Dar milk shed in Northwest Ethiopia. Thus, this study was designed to estimate the coliform bacteria contamination load and isolate common coliform bacteria from dairy products, and determine their antimicrobial susceptibility in the area.

Study areas

The study was conducted in the Gondar-Bahir Dar milk shed in Amhara Regional State, northwest Ethiopia. The area includes milk-producing areas in and around the big cities (Bahir Dar and Gondar) and other sites in Dembia, and Fogera districts with relatively higher dairy production activities (Fig. 1). The areas are among the highland (1800 to 2850 meters above sea level) places and located in the northwest part of Ethiopia with moderate climatic conditions. Over the year, the temperature typically varies from 11 to 32°C and is rarely below 9°C or above 32°C (Taye et al., 2013). These areas are the main component of Bahir Dar – Gondar milk shed which is one of the nine high milk sheds known in the country (Brandsma et al., 2013).

Figure 1. Map of the study areas (Sketched by ArcGIS maps (https://www.esrij.com/products/arcgis-field-maps/))

Study design and sampling

A cross-sectional study was conducted from June 2022 to February 2023. The sampling sites were selected based on their dairy production activities. First, a list of dairy farmers was obtained from livestock development offices in all selected sites. The dairy farms to collect samples were selected randomly by lottery method. If the selected farm didn’t have milk or dairy products during sample collection, the sample was collected from the nearest farm. The samples represent ready-to-sell or consume pooled cows’ milk and other dairy product samples like traditionally prepared soft cheese, buttermilk, yoghurt and pasteurized milk. For pasteurized milk, as the number of companies pasteurizing milk was limited; there were repetitions of samples from three companies and an attempt was made to purchase different batches.

Sample size determination

The sample size was estimated based on the 12% isolation rate of E. coli (a typical coliform) in bulk (pooled) milk reported by Garedew et al. (2012). The desired sample size for the study was determined by using the formula described by Thrusfield (2007) as follows:

$$n=\frac{{(z}^{2}\left)p\right(1-p)}{{\text{d}}^{2}}$$

Where: n = the required sample size; p = Expected prevalence; d = desired absolute precision (0.05); z = the 95% confidence (1.96). Hence, the estimated sample size was 162. However, coliforms were isolated from 184 samples and from these, coliform count was conducted on 146 samples due to some unenabling situations in the laboratory. The number of samples in each selected site was determined proportionally based on the total number of dairy farms in each site (Levy and Lemeshow, 2013).

Sample collection and transportation

At the selected farm, ~ 50 ml or gram of milk or other dairy product samples were collected using sterile tubes. Then, samples were transported in an icebox to the food safety laboratory of the University of Gondar, Ethiopia, for bacteriological analysis. Pasteurized milk samples were collected as packed and transported similarly in the icebox and opened in the laboratory aseptically. All samples were transported and processed on the day of sample collection.

Assessment of the hygienic practices

Assessment of the hygienic practices was conducted by personal observation using checklists and interviewing the milker about common practices on milk hygiene. Potential factors that may play for the contamination of dairy products (Deddefo et al., 2023) were included during the data collection. The hygienic status of the farm, the milker, the container and the animal were noted and categorized as “poor” if considerable dirt was visible and lack of cleaning or washing was apparent; “medium” if some dirt was visible but appeared to be cleaned infrequently and “good” if no dirt was visible and appeared to be cleaned or washed regularly (Chassagne et al., 2005; Chowdhury et al., 2017; Lopez-Carlos et al., 2023).

Bacteriological quality assessment and isolation of coliforms

The bacteriological quality of the dairy products was assessed by using coliform count. The count was conducted by adding one millilitre or gram of dairy product samples into a sterile test tube having 9 ml sterile buffered peptone water (Bio-Rad Hercules, CA, US). After thorough mixing, the sample was serially diluted up to 10^− 5 and duplicate samples (1ml) were poured-plated on an empty sterile petri dish and about 15 ml of partly cooled (about 45 ^oC) violet red bile agar (VRBA) (Himedia, India) solution was added. Then, the media with the sample was mixed thoroughly by rotating in different directions and the plated petri dish was allowed to solidify and then the plates were incubated at 37 ºC for 24 hours. After incubation, typical coliform colonies were counted and expressed as CFU/ml for milk or CFU/g for the other dairy products (ISO4832, 2006). After counting, the number of bacteria in a millilitre of sample was calculated and the plate counts were expressed as colony-forming units per millilitre (CFU/ml) of the sample. For cheese, a one-gram sample was used and expressed as CFU/g.

The assessment of the hygienic practices at the farm level and coliform count were supplemented by the identification of coliform bacteria in the samples. Escherichia coli and other coliform bacteria were isolated and identified as described in the Bacteriological Analytical Manual (BAM) and ISO7218 (2007). Briefly, ~ 25 ml (g) of the homogenised sample was diluted 1/10 ratio in E. coli broth (Oxoid Ltd, UK) and the mixture was incubated at 42^oC for 36 hours. Subsequently, a loopful of the enriched sample was transferred to MacConkey agar (Oxoid Ltd, UK) and incubated at 37°C for 24 hours. Three to five well-isolated, lactose fermenting colonies were sub-cultured into Levine Eosin Methylene Blue agar (Neogen Corporation, Berkhamsted, UK) and incubated at 37°C for 24 hours. After incubation, the bacteria were sub-cultured onto tryptic soya agar (Sigma-Aldrich Chemie GmbH, Germany) and used for biochemical testing (motility, indole, triple sugar iron and citrate utilization tests). Then, colonies were identified by the analytical profile index (API) 20E (Biomerieux VWR, France) test (Maina et al., 2014).

Antimicrobial susceptibility test

The antimicrobial susceptibility test (AST) was performed using the Kirby-Bauer disk diffusion method (Hudzicki, 2016). Briefly, a bacterial suspension which is equivalent to 0.5 McFarland standard was prepared in 0.85% sterile normal saline solution. The suspensions were uniformly streaked over the entire surface of the Mueller-Hinton agar (Sigma-Aldrich Chemie GmbH, Germany) using sterile cotton swaps. For antimicrobial susceptibility assays, the paper discs impregnated with a fixed concentration of antimicrobials (Oxoid Ltd, UK) were placed on the agar surface and incubated at 37^oc for 18 hours. After incubation, the zone of inhibition was measured in millimetres using a calliper and interpreted as “susceptible”, “intermediate” or “resistant” according to Clinical and Laboratory Standards Institute criteria (CLSI, 2023). Sixteen antimicrobial agents in nine antimicrobial classes were used to determine the antimicrobial susceptibility pattern (supplementary document 1).

Quality control

All bacteriological media were prepared as per the instruction of the manufacturer. The sterility of each batch of the prepared media was checked after autoclaving. The biochemical tests were run with reference standard bacteria like ATCC 700603 (Klebsiella) and ATCC 25922 (E. coli) as controls.

Data analysis

The collected data was analysed by using the Statistical Package for Social Sciences (SPSS) software version 16. Frequencies and percentages were determined using descriptive statistics. Independent t-test, one-way analysis of variance (ANOVA) and chi-square test were used to check the association of potential factors with the contamination status. The association was taken as significant when the P-value was less than 0.05.

Assessment bacteriological quality

A total of 146 raw dairy product samples were assessed for bacterial contamination by determining the coliform count (CC). The average CC was 5.6 log CFU/ml (confidence interval (CI) = 5.3–6.0). There was a significant (P < 0.05) difference in mean CC among dairy product types, cleanness of the animals and hygiene of the container. The largest mean CC was observed in raw milk (6.0 log CFU/ml), poor cleaning status of the animals (6.2 log CFU/ml) and poor hygienic status of the containers (6.3 log CFU/ml). On the contrary, the differences in the mean CC among sampling sites, farm size, source of water to clean milk containers, availability of cooling facilities, feed source, type of container, farm hygiene, and milker’s hygiene were not statistically significant (Table 1).

Table 1

Quality grading of milk based on the coliform count
Factors	Categories	Number assessed	Mean ± SE (log CFU/ml(g))	P-value
Sampling sites (districts)	Gondar	39	4.9 ± 0.4	0.06
	Bahir Dar	41	5.9 ± 0.3
	Fogera	30	6.0 ± 0.3
	Gondar Zuria	14	5.1 ± 0.6
	Dembia	22	6.1 ± 0.4
Type of samples	Raw milk	97	6.0 ± 0.2	0.00
	Yoghurt	13	5.8 ± 0.5
	Buttermilk	6	5.0 ± 1.0
	Traditionally prepared soft Cheese	11	2.6 ± 0.6
	Pasteurized milk	19	5.4 ± 0.7
Farm size*	small (< 20 animals)	103	5.7 ± 0.2	0.41
Farm size*	medium and above (≥ 20 animals)	20	6.0 ± 0.2	0.41
Source of water to clean milk containers	Tap water	98	5.7 ± 0.1	0.77
	River	10	5.9 ± 0.5
	Well /spring water	15	6.0 ± 0.4
Availability of cooling facilities	Yes	35	5.7 ± 0.3	0.73
Availability of cooling facilities	No	88	5.8 ± 0.2	0.73
cleanness of the animals	Poor	66	6.2 ± 0.2	0.02
	Medium	5	5.7 ± 0.5
	Good	52	5.2 ± 0.2
Feed source	Zero grazing (in door)	90	5.8 ± 0.2	0.55
Feed source	Free Grazing	26	5.6 ± 0.3	0.55
Type of container	Aluminum(nickel)	6	5.8 ± 0.2	0.35
	Plastic nonfood grade	88	5.7 ± 0.2
	Plastic food grade	13	6.5 ± 0.5
	Gourd (kil)	16	5.4 ± 0.5
Farm Hygiene	Poor	49	5.8 ± 0.3	0.99
	Medium	21	5.7 ± 0.3
	Good	53	5.7 ± 0.2
Milker’s Hygiene	Poor	27	6.1 ± 0.3	0.33
	Medium	34	5.8 ± 0.3
	Good	62	5.6 ± 0.2
Hygiene of the container	Poor	24	6.3 ± 0.3	0.04
	Medium	39	6.0 ± 0.3
	Good	60	5.4 ± 0.2
Total		146	5.6 ± 0.2
*23 samples counted were purchased from small (retail) shops which was difficult to know about the farm or trace back it, SE = Standard Error

Coliforms were found in all dairy products types including pasteurized milk. The average coliform count in pasteurized milk samples was 5.4 ± 0.7 log CFU/ml, whereas the average counts from companies A, B, and C were 5.8 ± 1.1, 2.3 ± 1.0, and 7.8 ± 0.4 log CFU/ml, respectively. The average coliform counts were significantly (P < 0.05) different among companies.

Ethiopian quality standards classified raw milk as very good, good, bad, and very bad based on the coliform count (ESA, 2009). Based on such classification, the majority (62.9%) of the samples had very bad grade (Fig. 2).

Isolation of coliform bacteria

Out of 184 bacteriologically examined dairy samples, 84.8% were positive for either of the coliforms and 40.8, 33.7, 9.2, 12.5 and 1.6% were positive for E. coli, Citrobacter spp, Klebsiella spp, Enterobacter spp, and Serratia spp, respectively (Table 2). Table 2 also depicts the isolation rate of coliform bacteria from different districts and types of samples. The positivity rates of coliforms were significantly (P < 0.05) different among sampling sites and types of samples. All samples collected from Fogera and all buttermilk samples were positive for coliform bacteria (Table 2). A higher proportion of E. coli was observed in samples from Gondar Zuria (52.4%) and Yoghurt samples (52.1%). The detection rate of Citrobacter spp was higher in samples from Fogera (62.9%) and Dembia (63.6%). However, there was no significant difference in the detection rate of other coliforms from sampling sites and type of samples.

Table 2

Isolation rate of coliform bacteria from different sources and types of samples
Variables	Category	Number of the samples	Over all Coliforms (n (%))	E. coli (n (%))	Citrobacter spp (n (%))	Klebsiella spp (n(%))	Enterobacter spp (n(%))	Serratia spp (n(%))
Districts	Gondar	45	36 (80)	21 (46.7)	6 (13.3)	3 (6.7)	6 (13.3)	0(0.0)
	Bahir Dar	50	36 (72)	25 (50.0)	6 (12.0)	7 (14.0)	4 (8.0)	1(2.0)
	Fogera	35	35 (100.0)	8 (22.9)	22 (62.9)	5 (14.3)	8 (22.9)	2(5.7)
	Gondar Zuria	21	18 (85.7)	11 (52.4)	7 (33.3)	2 (9.5)	0 (0.0)	0(0.0)
	Dembia	33	31 (93.9)	10 (30.3)	21 (63.6)	0 (0.0)	5 (15.2)	0(0.0)
Sample type	Raw milk	97	89 (91.8)	37 (38.1)	41 (42.3)	11 (11.3)	12 (12.4)	1 (1.0)
	Yoghurt	48	40 (83.3)	25 (52.1)	14 (29.2)	3 (6.2)	4 (8.3)	0 (0.0)
	Butter milk	9	9 (100.0)	4 (44.4)	4 (44.4)	0 (0.0)	3 (33.3)	1 (11.1)
	Soft Cheese	11	6 (54.5)	1 (9.1)	2 (18.2)	2 (18.2)	2 (18.2)	0 (0.0)
	Pasteurized milk	19	12 (63.2)	8 (42.1)	1 (5.3)	1 (5.3)	2 (10.5)	1 (5.3)
Total		184	156 (84.8)	75(40.8)	62 (33.7)	17(9.2)	23 (12.5)	3 (1.6)

Antimicrobial susceptibility patterns of coliform isolates

Escherichia coli isolates were 100% susceptible to ceftazidime, ceftriaxone, cefotaxime and azithromycin. However, these isolates were relatively more resistant to cephalothin (60.5%). Citrobacter spp were 100% susceptible to chloramphenicol, norfloxacin and ciprofloxacin however, they were more resistant to ampicillin (74.2%) and cephalothin (60.5%). High susceptibility (100%) to amoxicillin-clavulanic acid, ceftazidime, ceftriaxone, cefotaxime, chloramphenicol, tetracycline, doxycycline and norfloxacin and more resistant to ampicillin (66.7%) were observed among Klebsiella spp. On the other hand, Enterobacter spp showed 100% susceptibility to ceftazidime and norfloxacin. However, they were relatively more resistant to ampicillin (75.0%) and cephalothin (83.3%) (Fig. 3).

Figure 4 shows representative examples of isolates which were susceptible to many AMAs (left) and resistant to more than two pf groups antimicrobial agents (right).

Milk and other dairy products are very valuable food items, however, they can be easily contaminated by pathogenic agents. Coliform bacteria are the common contaminants of these products. They are indicators of contamination, can induce opportunistic infections, and carry resistant genes which can be potentially transferred to other pathogenic bacteria. In this study, bacterial contamination status was assessed by conducting coliform count, isolation and characterization of the bacterial isolates. The overall mean coliform count (CC) of all samples was 5.6 log CFU/ml which was very close to the report (5.86 logcfu/ml) in Eastern Ethiopia (Amentie et al., 2016). However, it was higher than the value reported (3.7 log CFU/ml) in Mersa, Ethiopia (Oumer et al., 2017), in Addis Ababa, Ethiopia, (4.8 log cfu/ml) (Abunna et al., 2019), and lower than the report from Hawassa, Ethiopia (6.6 log CFU/ml) (Korma et al., 2018). These differences in coliform count might be due to the difference in the hygienic status of the farms, the animals, the milkers, the milk containers and the milking environment (Deddefo et al., 2023). The finding of this study showed that coliform count was significantly (P < 0.05) different among sample types, cleanness of the animals and hygiene of the container. In line with this, Deddefo et al. (2023) also reported the association between coliform count and cow cleanliness as well as milk utensil hygiene.

It is recommended to use clean water to wash utensils for milking and milk containers to reduce milk contamination. In this study, the source of water to clean equipment was not statistically significant. This may be related to the multiple sources of milk contamination and the hygienic status of the tap water distributed by the municipalities. Previous to this study, it had been reported that even tap water had poor bacteriological quality in the country (Wolde et al., 2020; Sitotaw and Nigus, 2021).

In this study, coliform bacteria were detected from all types of samples including the pasteurized milk. The overall average coliform count from pasteurized milk in this study was 5.4 log CFU/ml which was higher than the Ethiopian standard (ESA, 2009), East African standards and the average coliform count reported by Mikru et al. (2009) (3.2 log CFU/ml) in Ethiopia and (Hasan et al., 2015) (2.2 log CFU/ml) in Bangladesh. However, the result of this study was very close to the coliform count (4.5 log CFU/ml) of pasteurized milk reported in Kathmandu Valley, Nepal (Acharya et al. 2017). The presence of excess coliform in the pasteurized milk may be related to the bacteria load of raw milk, faults in the pasteurization process, post-pasteurization contamination, packaging, and/or storage conditions after pasteurization. It may also be related to the extent of applying good manufacturing practices by milk processing companies (Dhanashekar et al., 2012; Hasan et al., 2015).

The majority (62.9%) of the raw milk samples in this study had very bad grades based on the standard authority of Ethiopia (SAE) (ESA, 2009) which might be due to the contamination of the milk through the udder, milkers, milk containers and milking environment. The presence of high numbers of coliforms in milk indicates that the milk has been contaminated with faecal materials and it is an index of hygienic standards used in the production of milk, as unclean udder and teats can contribute to the presence of coliforms from a variety of sources like the use of improperly washed milking equipment, unsanitary milking practices, contaminated water and cows with subclinical coliform mastitis (Oumer et al., 2017).

In this study, E. coli was detected in 40.3% of samples which was very close to the isolation rate (42%) of E. coli reported in Bishoftu Town, Central Ethiopia (Megersa et al., 2019). However, it was higher than the report (25%) from Mekelle (Yohanis 2018) and reported (33.9%) from Asosa town, Western Ethiopia (Disassa et al., 2017). On the other hand, the isolation rate found in this study was lower than the reports (49.6%) in Addis Ababa, Ethiopia (Abunna et al., 2019) and in Eastern Ethiopia (58%) (Reta et al., 2016). The variation in the isolation rate of E. coli may be due to differences in the hygienic practices in the dairy farms and/or agroclimatic conditions (Philipsborn et al., 2021; Disassa et al., 2017).

Citrobacter spp are bacteria that are also found in the intestinal tract of both humans and animals and they can induce opportunistic infections in the intestine or beyond. They can be isolated from fecal samples, farm environment or contaminated milk or other food products, wound, and hospital environment (Hidayatullah et al., 2020; Chelkeba et al., 2021). In this study, Citrobacter spp were detected in 33.7% of the samples. This finding was higher than previous reports on dairy products in Ethiopia. Garedew et al. (2012) reported a 7.4% prevalence from critical control points of raw and pasteurized cow milk consumed at Gondar town. The difference may be related to the type of samples. Since, in this study, dairy products were sampled.

Klebsiella spp are another type of coliform bacteria that can also be found in the gut of both humans and animals. They can induce localized infections like mastitis or systemic opportunistic infections and are the common cause of nosocomial and some community-acquired infections (Calderon-Gonzalez et al., 2023; Song et al., 2023). In this study, Klebsiella spp was detected in 9.2% of milk and dairy products. This is in agreement with the study report from Debre Birhan town in Ethiopia which was 11.3% in milk and yoghurt samples (Asfaw et al., 2023).

Enterobacter spp are also lactose fermenting members of the Enterobacteriaceae which can cause nosocomial infections, and some community-acquired infections (Sanders and Sanders, 1997). The isolation rate in this study was 12.5%. In contrary to this, 20 and 30% isolation rates were reported by Yilma et al. (2007) in dairy products in Ethiopia and Elutade et al. (2023) in raw milk in Nigeria, respectively. The difference may be related to the hygeinic status and climatic differences in the study areas.

The development of AMR among coliform bacteria poses a serious public health concern. The effectiveness of treatments and the ability to control infectious diseases in both animals and humans may be severely hampered (Yohannes, 2018). Coliform bacteria can also act as the reservoir of resistant genes and share them with other bacteria (Godziszewska et al., 2018; Liu et al., 2020). Coliform bacteria like E. coli are indicators of not only contamination but also the extent of AMR in a given area (Anjum et al., 2021). In this study, E. coli isolates were 100% susceptible to third-generation cephalosporins (ceftazidime, ceftriaxone, cefotaxime) and azithromycin. However, they were relatively resistant to cephalothin (60.5%), tetracycline (44.7%) and ampicillin (36.8%). Tuem et al. (2018), conducted a meta-analysis study on drug resistance patterns of E. coli isolates in Ethiopia. They reported that the pooled prevalence of cephalothin resistance was 56. 7% which was very close to the finding of this study. The resistance of tetracycline and amplicin may be related to their frequent use in animals in the country (Tufa et al., 2018).

In this study, Citrobacter spp isolates were highly susceptible to chloramphenicol, norfloxacin and ciprofloxacin. However, they were resistant to cephalothin (64.5%), and ampicillin (74.2%). A higher rate of resistance of Citrobacter spp to ampicillin was also reported by Tiruneh et al. (2014). Klebsiella spp isolates were highly susceptibility to amoxicillin-clavulanic acid, ceftazidime, ceftriaxone, cefotaxime, chloramphenicol, tetracycline, doxycycline and norfloxacin and more resistant to ampicillin (66.7%). High susceptibility of Klebsiella spp to norfloxacin and high resistance to ampicillin were also reported by Chelkeba et al. (2021).

In Ethiopia and other parts of the world, susceptibility patterns of bacterial isolates were more frequently reported from clinical specimens (Chelkeba et al., 2021; Beyene et al., 2023). In addition, Shawky et al., (2021) reported that the bacterial isolates from clinical specimens appeared more resistant than non-clinicals. However, our findings indicated that a considerable proportion of resistant bacteria can be found in food products like milk and other dairy products.

The bacteriological quality analysis indicated that the majority of dairy products supplied to the consumer in the study area were highly contaminated by coliform bacteria which can be the potential source of milk-borne diseases to the community. Additionally, considerable proportions of isolates were resistant to antimicrobial agents. Therefore, dairy farmers should enhance hygienic practices and raw products should be heat treated before consumption. The AMR mitigation strategies like rational use of antimicrobial, awareness creation and infection prevention and control activities should be implemented.

Ethics approval and consent to participate

The proposal for the study was submitted and approved by the University of Gondar, Department of Medical Microbiology and ethical clearance was obtained from the Institutional Ethical Board of the University of Gondar, Ethiopia. Selected farmers were visited in person and the objective(s) and study procedures were explained to the owner or manager of the farms verbally and data were collected when a consensus was reached.

Consent for publication

Not applicable

Availability of data and material

All data generated or analysed during this study were included in this published article and its supplementary information files. Alternatively, the data can also be obtained from the corresponding author upon request.

Competing interests

The authors declare the absence of either financial or non-financial competing interest from anybody or institute. We also want to assure that we did not receive any technical assistant in developing the research concept or preparation of the manuscript.

Funding

Research materials (media and reagents) were obtained from TARTARE project, University of Gondar and colleagues. Otherwise, there was no direct fund allocated for the research activities.

Authors’ contributions

AMB carried out the conception of the research concept and designed the methodology, data analysis, interpretation and preparation of the manuscript for publication. AMB, ZJ and HH carried out the sample collection and laboratory work. AY, MG and BG critically revised the proposal and reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Some of the media used in this study were obtained from TARTARE project hence authors would like to thank for the material support. The authors are also like to acknowledge the dairy farmers and experts in each sampling sites for their support during sample collection.

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No competing interests reported.

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Coliform bacterial contamination of dairy products and antimicrobial susceptibility patterns of common coliform bacterial isolates in Gondar-Bahir Dar milk shed, Northwest Ethiopia

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Abstract

Figures

Introduction

Methods

Study areas

Study design and sampling

Sample size determination

Sample collection and transportation

Assessment of the hygienic practices

Bacteriological quality assessment and isolation of coliforms

Antimicrobial susceptibility test

Quality control

Data analysis

Results

Assessment bacteriological quality

Isolation of coliform bacteria

Antimicrobial susceptibility patterns of coliform isolates

Discussion

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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