VSRR_12_1

Introduction

Milk is considered a valuable nutritional source as it fulfills the essential dietary requirements for children, pregnant women, and the elderly people (Javaid et al., 2009). However, fresh milk is prone to contamination with various pathogenic bacteria that poses a significant threat to its consumer’s health (Torkar and Teger, 2008). Milk is a perfect growth medium for microorganisms because of its high water, protein, carbohydrate, and fat content (Griffiths, 2010). Various sources act as contamination source including milking equipment, animal feed, soil, manure, and the dairy environment itself (FAO and WHO, 2004). Staphylococcus spp., E. coli, and Salmonella spp. are the most significant pathogenic bacteria found in milk. They can cause serious foodborne illnesses (Oliver et al., 2005).

Staphylococcus spp., being one of the most pathogenic bacteria, when found in milk products, is prone to originate from infected udders and spread as a result of inappropriate handling of udders during milking (Radostits et al., 2006). Conversely, E. coli, which is a normal intestinal inhabitant of animals, when found in milk is assumed to be due to fecal contamination (Oliver et al., 2009). In addition, Salmonella species, particularly Salmonella enterica, may cause life threatening enteric infections upon consumption of contaminated raw milk (Capita et al., 2003).

The growing resistance of bacteria against antibiotics in milk has become a major global health challenge (Devriese et al., 1997). Antibiotic overuse in dairy farming has resulted in decreased treatment efficacy, which is the cause of the rising number of resistant strains (Pant et al., 2013). This resistance develops when sub-therapeutic antibiotic doses eliminate susceptible bacteria while allowing resistant variants to proliferate (Eichner and Gravitz, 2001). Majority of the prior studies on milk borne pathogens in Bangladesh primarily focused on identification of the pathogens based on cultural and biochemical tests. They often examined a single pathogen and mostly lacked advance molecular detection. The present study was taken into account to fill the critical research gap by combining advanced molecular detection along with the traditional method of identification for the three milk-borne pathogens, thus generating a contemporary antibiogram data and highlighting the urgency to intervene in Bangladesh’s dairy sector to control contamination and resistance, which was previously under addressed.

Materials and Methods

Time frame, area of study and sample collection

This study was carried out in the span of six months, July-December 2023, in the Microbiology and Parasitology Laboratory of Sher-e-Bangla Agricultural University. From five randomly selected markets and five dairy farms of Dhaka City, Bangladesh, a total of fifty milk sample were collected aseptically and then transferred to the laboratory maintaining cool chain for further investigation.

Isolation and tentative identification of the isolates

The samples were first enriched in nutrient broth (HiMedia, India) to recover the likelihood of getting low number of bacteria and then cultured into selective media specific for the pathogens. Nutrient agar (HiMedia, India) plate was used first followed by mannitol salt (MS; HiMedia, India) agar for identification of Staphylococcus spp. For E. coli identification, eosin methylene blue (EMB; HiMedia, India) was complemented by McConkey (MC; HiMedia, India) agar media. Salmonella-Shigella (SS; HiMedia, India) agar, Xylose Lysine Deoxycholate agar (XLD; HiMedia, India) agar, and MC agar media were used for Salmonella spp. Gram staining procedure was also performed for morphological confirmation. By hanging drop technique, motility was checked and biochemical characters were ascertained by performing a series of biochemical tests like carbohydrate fermentation, catalase, Methyl Red and Voges-Proskauer (MR-VP), and indole tests (Cheesbrough, 2006).

DNA extraction

By using boiling method, total genomic DNA was extracted from bacterial cultures followed by centrifugation of 1ml of culture 14,000×g for 5 minutes. After getting the pellet, it was washed with sterile water and re-centrifuged. The cells were then re-suspended in 200 µL water, boiled for 10 minutes to lyse them, and immediately chilled on ice. Afterwards, it was centrifuged for one last time for collecting the DNA-containing supernatant followed by storage at -20°C for PCR analysis (Mthembu et al., 2019). This efficient protocol yielded high-quality DNA suitable for downstream applications.

Polymerase chain reaction (PCR) to identify Staphylococcus spp., E. coli, and Salmonella spp.

PCR was used to detect Salmonella (invA gene), Staphylococcus, and E. coli (16S rRNA) (Table 1). Each 25µL reaction containing master mix, primers, water and DNA template extracted from the serovars, they were allowed to thermal cycling conditions. It varied by target: Staphylococcus spp. (30 cycles: 94°C/30s, 60°C/30s, 72°C/45s), E. coli (35 cycles: 94°C/30s, 60°C/30s, 72°C/30s), and Salmonella spp. (30 cycles: 94°C/1min, 64°C/30s, 72°C/30s) (Shome et al., 2018; Tsen et al., 1998; Kaushik et al., 2014). Afterwards, amplified DNA was analyzed on 1.5% agarose gels with DNA ladders. This method provided specific identification of all three pathogens.

Antibiotic sensitivity tests of isolated Staphylococcus spp., E. coli, and Salmonella spp.

The identified isolates were exposed to antibiotic sensitivity test by employing the Kirby-Bauer disk diffusion method against 10 widely used antibiotics (Bauer et al., 1966). Bacterial suspensions maintaining 0.5 McFarland standard, were spread on Mueller-Hinton agar, and antibiotic discs including ampicillin (AMP), 10 μg; amoxicillin (AMX), 30 μg; amoxicillin–clavulanic acid (AMC), 20/10 μg; ceftriaxone (CTR), 30 μg; ciprofloxacin (CIP), 5 μg; nalidixic acid (NA), 30 μg; erythromycin (E), 15 μg; gentamicin (GEN), 10 μg; tetracycline (TE), 30 μg; and meropenem (MEM), 10 μg were applied. After 24h incubation at 37°C, inhibition zones were measured and interpreted using the Clinical and Laboratory Standards Institute (CLSI, 2020) guidelines. Multidrug resistance was defined as resistance against at least one antibiotic from ≥3 antibiotic classes (Magiorakos et al., 2012).

Statistical analysis

Minitab 17 (Minitab Ltd., UK) was used to analyze the study’s data. Pearson’s Chi-square test was used to determine any significant differences between the variables.

Results and Discussion

Isolation and identification of milk borne Staphylococcus, E. coli, and Salmonella spp.

Figure 1 represented the cultural characteristics of isolated bacteria. Mannitol fermentation in MS agar makes it selective for staphylococci and differential for S. aureus, which ferments mannitol, producing a yellow color around the colonies; meanwhile

in nutrient agar, they produce big yellow colonies (McLandsborough, 2005; Cheesbrough, 2006; Foster, 1996). On the other hand, E. coli exhibits distinct cultural characteristics on EMB agar, producing greenish colonies with a metallic sheen (Fesseha, 2020; Nayak et al., 2004) and in MC agar they produce bright pink, lactose-fermenting colonies. Conversely, Salmonella spp. exhibits black-centered colonies (H2S production) in XLD agar, black colonies in (Salmonella-Shigella) SS, and non-lactose fermenter colonies on MC agar (Jones et al., 2008; Buxton and Fraser, 1977). Staphylococcus spp. showed gram positive cocci with grapes like clusters, E. coli showed gram-negative rod-shaped bacteria, while Salmonella spp. showed gram negative coccobacilli on Gram’s staining (Figure 2). Table 2 represented the sugar fermentation patterns and

Table 1: List of primers used in this study.

Target pathogen	Primer sequence (5´→3´)	Amplicon size (bp)	Reference
Staphylococcus spp.	SG16P1(F): GTG ATC GGC CAC ACT GGA	842	Shome et al. (2018)
	SG16P1(R): CAACTTAATGATGGCAACTAAGC
Escherichia coli	16E1(F): GGGAGTAAAGTTAATCCTTTGCTC	584	Tsen et al. (1998)
	16E2(R): TTCCCGAAGGCACATTCT
Salmonella spp.	InvA(F): GTGAAATTATCGCCACGTTCGGGCAA	284	Kaushik et al. (2014)
	InvA(R): TCATCGCACCGTCAAAGGAACC

bp= Base pair

Table 2: Biochemical characteristics of milk-borne Staphylococcus spp., E. coli, and Salmonella spp.

Parameters		Staphylococcus spp.	E. coli	Salmonella spp.
Catalase test		+ve	+ve	+ve
Sugar fermentation tests	Dextrose	A	AG	AG
	Lactose	A	AG	NF
	Sucrose	A	AG	NF
	Maltose	A	AG	AG
	Mannitol	A	AG	AG
Methyl red test		+ve	+ve	+ve
Voges-proskauer test		+ve	–ve	–ve
Indole test		–ve	+ve	–ve

+ve: positive; –ve: negative; A: only acid is produced after fermentation; AG: acid and gas is produced after fermentation; NF: no fermentation occurred.

biochemical characteristics of the isolated bacteria. Staphylococcus spp. fermented all five simple sugars with acid production (Cheesbrough, 2006; OIE, 2000; Freeman, 1985); E. coli demonstrated complete fermentation (Fesseha, 2020; Bedasa et al., 2018; Asmelash, 2015; Giuida and Gohary, 2013); and Salmonella spp. gave positive result in dextrose, glucose, and mannitol fermentation, but were negative in lactose and sucrose fermentations, (Han et al., 2011; Hossain, 2012). Staphylococcus spp. showed positive result in catalase and MR-VP but negative indole reactions (Cheesbrough, 2006; OIE, 2000; Freeman, 1985). E. coli isolates were catalase, MR, and indole positive but VP negative (Zinnah et al., 2007). Salmonella spp. showed MR positive, VP negative, and indole negative results, in agreement with Buxton and Fraser (1977).

Molecular identification of milk-borne Staphylococcus spp., E. coli, and Salmonella spp.

DNA extracted from 14 Staphylococcus spp., 22 E. coli and 10 Salmonella spp. were subjected to PCR amplification, and identified the 842bp, 584bp, and 284bp DNA for Staphylococcus spp., E. coli, and Salmonella spp., respectively (Figures 3) which were in line with Shome et al. (2018), Tsen et al. (1998), and Kaushik et al. (2014), respectively.

Occurrence of Staphylococcus spp., E. coli and Salmonella spp. in farm milk and market milk

The occurrence of Staphylococcus spp. in milk samples (n=50) was 28%, with a higher prevalence in market milk (18%) compared to farm milk (10%) (P >0.05) (Table 3). The total occurrence of E. coli in the samples was 44%, with market milk exhibiting a higher prevalence (26%) than farm milk (18%) (P >0.05) (Table 3). The occurrence of Salmonella spp. was 20%, with market milk showing a slightly higher occurrence (12%) than farm milk (8%) (P >0.05) (Table 3). Although the prevalence of Staphylococcus spp. in this study is lower than that of another study carried out in Australia (60.3%) (Ramezanigardaloud et al., 2025) and Ethiopia (39.3%) (Abebe et al., 2024), it is comparable to that of Borena et al. (2023) (15.6%) in Ethiopia and Regasa et al. (2019) (16.6%) in Uganda. Similarly, E. coli prevalence (44%) is in agreement with Madani et al. (2022), Fesseha (2020), and Yasmin et al. (2015), while high levels were noted in the Czech Republic (Skočková et al., 2018, 92.4%), Iran (Hassani et al., 2022, 78%), and Indonesia (70.4%), while low levels were noted in Ethiopia (Demme and Abegaz, 2015, 9.9%). Salmonella spp. (20%) concurs with Garbaj et al. (2022), Hassani et al. (2022), and Marjan et al. (2014), but contrary to lower prevalence reported by Asefa et al. (2023), Gebeyehu et al. (2022), and Allied (2021). The dissimilarities may have been caused by the climatic conditions, hygiene maintenance and milk handling practices. Overall, these findings highlight the public health impact of drinking contaminated milk and require better hygiene and monitoring along the milk value chain.

Table 3: Occurrence of Staphylococcus spp., E. coli and Salmonella spp. in farm milk and market milk.

Name of Bacteria	No. of sample tested	Occurrence			Chi-square P value
Name of Bacteria	No. of sample tested	Overall No. (%)	Farm milk No. (%)	Market milk No. (%)	Chi-square P value
Staphylococcus spp.	50	14 (28)	5 (10)	9 (18)	0.285
E. coli		22 (44)	9 (18)	13 (26)	0.394
Salmonella spp.		10 (20)	4 (8)	6 (12)	0.527
Chi-square P value	-	0.088	0.311	0.267	-

P value <0.05 was considered as significant differences.

Antimicrobial susceptibility of Staphylococcus spp., E. coli and Salmonella spp. in farm and market milk samples

Figure 4 shows a pattern of susceptibility to antibiotics for isolates of Staphylococcus spp. To ascertain the antibiotic sensitivity pattern, a total of 14 isolates of Staphylococcus spp. were obtained from farm and market milk samples. Out of 14 Staphylococcus spp. positive isolates the highest resistance was noticed against ampicillin and amoxicillin group which was 92.86% and the lowest resistance was found against gentamicin group i.e. 28.57%.

Figure 5 represents the results of susceptibility study and displayed that all the isolates of E. coli (n=22) were 100% resistant against amoxicillin and ampicillin and then followed by tetracycline (90.91%), nalidixic acid (72.73%), erythromycin (72.73%), ceftriaxone (63.64%), ciprofloxacin (63.64%), amoxicillin-clavulanic acid (45.45%), meropenem (36.36%), and gentamicin (13.64%), respectively. However, the highest sensitivity was found for gentamicin (77.27%) and the lowest susceptibility was documented for amoxicillin and ampicillin (0%).

The consequences of vulnerability investigation exposed that all the isolates of Salmonella spp. (n=10) were 100% susceptible to meropenem and then followed by ciprofloxacin (90%), gentamicin (80%), ceftriaxone (50%), amoxicillin-clavulanic acid (40%) and erythromycin (40%), nalidixic acid (30%) and tetracycline (10%) (Figure 6). Conversely, all the isolates of Salmonella spp. (n=10) were 100% resistant against amoxicillin and ampicillin followed by tetracycline (80%).

The present study indicates that ampicillin and amoxicillin are among the most commonly used antibiotics in the Bangladeshi dairy sector, and all three bacterial species examined showed high resistance against these drugs. Among Staphylococcus spp., the highest resistance was observed against ampicillin and amoxicillin, while the highest sensitivity to gentamicin. These findings are consistent with Borena et al. (2023), Gebremedhin et al. (2022), and Hassani et al. (2022), but contrast with Deddefo et al. (2022) and Al-Ashmawy et al. (2016), who reported lower resistance.

For E. coli isolates, resistance was highest against ampicillin and amoxicillin, followed by tetracycline, nalidixic acid, erythromycin, and ceftriaxone, with the highest sensitivity to gentamicin. Similar resistance levels to ampicillin and amoxicillin were reported by Rahman and Ahmed (2022), and Ranjbar et al. (2018), while Hassani et al. (2022)

Table 4: Multidrug-resistant Staphylococcus spp., E. coli, and Salmonella spp.

Name of Isolates	Antimicrobial compounds	Antibiotic classes	No. of MDR isolates (%)	Overall MDR (%)
Staphylococcus spp.	AMX-AMP-TE-AMC-CIP-NA-E-MEM	Pen-Tet-PenB-Flu-Qui-Mac-Carb	2 (20.0)	71.43% (n= 10/14)
	AMX-AMP-TE-AMC-CTR-CIP-NA-E-MEM	Pen-Tet-PenB-Cef-Flu-Qui-Mac-Carb	1 (10.0)
	AMX-AMP-AMC-CTR-CIP-NA-E-GEN-MEM	Pen-PenB-Cef-Flu-Qui-Mac-Ami-Carb	3 (30.0)
	AMX-AMP-TE-E	Pen-Tet-Mac	1 (10.0)
	AMX-AMP-AMC-CTR-CIP-NA-E	Pen-PenB-Cef-Flu-Qui-Mac	2 (20.0)
	AMX-AMP-AMC-CTR-CIP-NA-E-MEM	Pen-PenB-Cef-Flu-Qui-Mac-Carb	1 (10.0)
	Total		10(100.0)
E. coli	AMP-AMX-TE-AMC-CTR-CIP-NA-E-GEN	Pen-Tet-PenB-Cef-Flu-Qui-Mac-Ami	7 (33.33)	95.45% (n=21/22)
	AMP-AMX-CTR-CIP-NA-E-GEN	Pen-Cef-Flu-Qui-Mac-Ami	1 (4.76)
	AMP-AMX-TE-MEM	Pen-Tet-Carb	2 (9.52)
	AMP-AMX-AMC-MEM	Pen-PenB-Carb	1 (4.76)
	AMP-AMX-TE-CTR-CIP-NA-E-GEN	Pen-Tet-Cef-Flu-Qui-Mac-Ami	4 (19.05)
	AMP-AMX-TE-AMC-MEM	Pen-Tet-PenB-Carb	1 (4.76)
	AMP-AMX-TE-AMC-NA-E-GEN	Pen-Tet-PenB-Qui-Mac-Ami	1 (4.76)
	AMP-AMX-TE-CTR-CIP-NA-E-GEN-MEM	Pen-Tet-Cef-Flu-Qui-Mac-Ami-Carb	2 (9.52)
	AMP-AMX-TE-GEN-MEM	Pen-Tet-Ami-Carb	1 (4.76)
	AMP-AMX-TE-NA-E-GEN-MEM	Pen-Tet-Qui-Mac-Ami-Carb	1 (4.76)
	Total		21 (100.0)
Salmonella spp.	AMP-AMX-TE-CIP-NA	Pen-Tet-Flu-Qui	1 (12.50)	80.0% (n=8/10)
	AMP-AMX-AMC-CTR-E	Pen-PenB-Cef-Mac	1 (12.50)
	AMP-AMX-TE-NA-E	Pen-Tet-Qui-Mac	1 (12.50)
	AMP-AMX-TE-NA-GEN	Pen-Tet-Qui-Ami	1 (12.50)
	AMP-AMX-TE-AMC-CTR-E	Pen-Tet-PenB-Cef-Mac	1 (12.50)
	AMP-AMX-TE-AMC-CTR	Pen-Tet-PenB-Cef	1 (12.50)
	AMP-AMX-TE-AMC-NA	Pen-Tet-PenB-Qui	1 (12.50)
	AMP-AMX-TE-AMC-CTR-NA-GEN	Pen-Tet-PenB-Cef-Qui-Ami	1 (12.50)
	Total		8 (100.0)

AMP = Ampicillin, AMX = Amoxicillin, GEN=Gentamicin, TE = Tetracycline, NA = Nalidixic acid, AMC = Amoxycillin/Clavulanic acid, CIP = Ciprofloxacin, CTR = Ceftriaxone, MEM= Meropenem, E= Erythromycin, Pen= Penicillin, Ami=Aminoglycoside, Tet=Tetracycline, Qui= Quinolone, PenB= Penicillin-Beta lactamase inhibitor, Flu=Fluoroquinolone, Cef= Cephalosporins, Carb= Carbapenem, Mac=Macrolide, MDR=Multi-Drug Resistant.

documented lower resistance (70.51%). Salmonella spp. showed complete resistance to ampicillin and amoxicillin, but remained fully susceptible to meropenem, followed by ciprofloxacin and gentamicin. Comparable multidrug resistance (MDR) in Salmonella spp. has been reported by Van Kessel et al. (2013), Gebeyehu et al. (2022), Garbaj et al. (2022), and Rahman and Ahmed (2022), though Hassani et al. (2022) observed lower resistance levels.

Microorganisms that showed resistance to at least one agent in three or more antibiotic classes were considered MDR. Among the MDR isolates of this study, Staphylococcus spp. accounted for 71.43% (10/14), E. coli for 95.45% (21/22), and Salmonella spp. for 80.0% (8/10) isolate(s) (Table 4). The highest (30.0%) MDR pattern for Staphylococcus spp. was “Pen-PenB-Cef-Flu-Qui-Mac-Ami-Carb”. Similarly, 33.33% E. coli showed MRD pattern of “Pen-Tet-PenB-Cef-Flu-Qui-Mac-Ami”; however, Salmonella spp. had eight different MDR pattern with equal percentage of 12.50. Several MDR patterns were observed among the isolates from milk samples indicates the haphazard and non-judicious used of them in animal production and veterinary medicine (Bronzwaer et al., 2002). In Bangladesh, misuse is exacerbated by over-the-counter access, lack of veterinary guidance, and premature discontinuation of treatment courses. Such practices accelerate the development of resistant strains, posing risks to humans and animals. Continuous surveillance of antimicrobial susceptibility patterns is therefore essential for guiding rational antibiotic use and mitigating the threat of AMR.

Conclusion

The existence of pathogenic multidrug-resistant (MDR) bacteria such as Staphylococcus spp. and E. coli and Salmonella spp. in farm and market milk leads to a serious threat to public health. This study supports the need for improvement to hygienic milking, handling, and processing practices, should be accompanied with recommendations for improved farm management and pasteurization of farm milk and market milk. Preventing milk borne transmission of MDR pathogens for the sake of public health requires policy implications and raising awareness among dairy production stakeholders.

Acknowledgement

We acknowledged the Sher-e-Bnagla Agricultural University, Dhaka, Bangladesh.

Novelty Statement

This study detected MDR milk-borne bacteria from both the farm and the market with a molecular basis.

Author’ Contribution

Md. Nasim Hasan Mim and Mahfuzul Islam contributed to the conception and design of the study. Md. Nasim Hasan Mim, M. Rubaiyat Adnan, Md. Abir Hassan Sadi, and Mithium Hussain Loveonnya conducted the field and laboratory work. Md. Nasim Hasan Mim, Md. Kamrul Hassan, Mithium Hussain Loveonnya, Mirza Synthia Sabrin, and Mahfuzul Islam examined the gathered data. Md. Nasim Hasan Mim, Tayeaba Jannat, Md. Rashedul Islam, Nipu Sen, and Mahfuzul Islam performed the data analyses. Md. Kamrul Hassan and Mahfuzul Islam supervised the research work. The manuscript was drafted with the assistance of Md. Nasim Hasan Mim, Tayeaba Jannat, and Mahfuzul Islam. The final manuscript has been revised and approved by all authors.

Generative AI and AI-assisted technology statement

The authors declare that no Genrative AI was used in the creation of this manuscript.

Conflict of interest

The authors have declared no conflict of interest.

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