1Department of Biological Sciences; Faculty of Science,

2Centre of Excellence in Bionanoscience,

 3Princess Dr. Najla Bint Saud Al-Saud Centre for Excellence Research in Biotechnology; Faculty of Science, Department of
Biology, Taif University, Taif, Saudi Arabia,  King Abdulaziz University, Jeddah-21589, Saudi Arabia.

Article Publishing History

Received: 25/03/2026

Accepted After Revision: 12/06/2026

ABSTRACT:

Beef meat is a major source of human dietary protein; however, it can be contaminated microbially by various means. In this study, we isolated bacterial strains from meat grinders, cutting boards, knives, and refrigerated meats at four stores located in Makkah, and identified them based on their biochemical characteristics and 16S rRNA gene sequencing. A total of 30 strains were isolated in this study, where 11 isolates were Gram-positive and 19 isolates were Gram-negative bacteria. Gram staining, oxidase and catalase tests were performed with all isolated strains. 16S rRNA gene phylogeny showed that the bacteria belonged to a wide range of genera including Staphylococcus, Psychrobacter, Acinetobacter, Macrococcus, Lactococcus, Bacillus, Pseudomonas, Enterobacter, Raoultella, Hafnia, Lysinibacillus, Brevibacillus, Klebsiella, Escherichia, Ochrobactrum, Chryseobacterium and Citrobacter. The response of bacterial isolates was different to various tested antibiotics; however, some isolates showed resistance to the most commonly used antibiotics. Overall, the present study showed that beef meat in the studied area could be contaminated at different stages of meat processing sites, and therefore, it is important to investigate stores regularly for potential microbial contamination to ensure food safety. In addition, this study also evaluated the susceptibility of the isolated Gram-positive and Gram-negative strains to eleven and twelve antibiotics, respectively. The A1B3 strain was found resistant to the highest number (eleven) of antibiotics tested.

KEYWORDS:

Beef Meat, Bacterial Contamination, Antibiotic, Antibiotic Resistance, 16S Rrna Gene And Sequencing.

Download this article as: Copy the following to cite this article:

Jeddawi A, Albiheyri R, Gado E. A, Abo-Aba S. E. M. Detection And Identification of Pathogenic Bacterial Species Using Culture-Based and Molecular Methods from Retail Meat Shops and Local Markets of Makkah, Saudi Arabia. Biosc.Biotech.Res.Comm. 2026;19(2).

Copy the following to cite this URL:

Jeddawi A, Albiheyri R, Gado E. A, Abo-Aba S. E. M. Detection And Identification of Pathogenic Bacterial Species Using Culture-Based and Molecular Methods from Retail Meat Shops and Local Markets of Makkah, Saudi Arabia. Biosc.Biotech.Res.Comm. 2026;19(2). Available from: <ahref=”https://shorturl.at/M54er“>https://shorturl.at/M54er</a>

INTRODUCTION

Meat is one of the primary sources of proteins in the human diet. Beef, veal, pig, poultry, and sheep are the major sources of meat and meat products (Thomson and Kotula, 1959). As beef meat consists of several amino acids, it is regarded as a major source of high-quality proteins in human diet. Also, during the digestion process, meat proteins break down into various peptides that are known to play important biological as well as health-promoting functions (Bauchart et al., 2007; Udenigwe and Howard, 2013). With time, the global demand for beef meat is increasing. During the past 50 years, meat production has risen exponentially around the world, while the total production has more than quadrupled since 1961 (Weis, 2013). During 1961 to 2018 period, the production of beef meat increased to about 40,000 tons in Saudi Arabia (Al-Thubaiti et al., 2021).

Saudi Arabia is the GCC’s largest consumer of red meat. In Saudi Arabia, various meat products, for example, sausages, beef burgers, luncheons, etc., are also gaining popularity (Reyad et al., 2016). These data clearly indicate that research on beef meat and meat products is significant for ensuring public health, and global as well as regional economy. In recent years, ensuring the safety of meat and meat products has been at the forefront of public concerns. Various foodborne diseases are one of the major sources of anxiety and stress in human lives (Wilcock et al., 2004).

Various microorganisms can grow on meat and meat products upon suitable environment for their growth. Several microorganisms including bacteria are responsible for meat spoilage, food poisoning, and carcass condemnation that negatively affects the economy of both farmers and sellers. Different infectious diseases, namely, anthrax, clostridiosis, leptospirosis, Q-fever listeriosis, erysipelas, glanders, brucellosis, salmonellosis, streptococcosis, and yersiniosis may develop because of  improper handling of meat and meat products. Microorganisms like Brochothrix thermosphacta and Pseudomonas spp. can spoil meat and meat products if they grow at high levels (Koutsoumanis et al., 2005). Bacterial species such as Aeromonas hydrophila, Bacillus cereus, Campylobacter jejuni, Clostridium perfringens, Escherichia coli, Listeria monocytogenes, Salmonella spp., Staphylococcus aureus and Yersinia enterocolitica may also be found in meat and meat products, and cause several diseases, either by multiplying in the human body (food infection), by generating toxins (food poisoning), or by multiplying and releasing toxins in the body (food toxicity) (Ismail et al., 2013).

Therefore, it is important to have elaborate and updated information about microbial populations in meat and meat products along with its surrounding environment. Throughout the mid-20th century, antibiotics were used as the ‘wonder drug’. To counter diseases or bacteria, antibiotics are undeniably a gift to human civilisation, which has saved millions of lives (Zaman et al., 2017). Millions of metric tons of newer antibiotic groups have been developed since their inception in the last 60 years. Due to the massive and reckless use of antibiotics, the advent of antibiotic-resistant strains has increased significantly (Saha and Sarkar 2021).

Microbiological studies have provided a limited platform for studying microbial flora due to its limitations of conventional enrichment approaches and pure culture techniques. Molecular methods based on polymerase chain reaction (PCR) offer a fast and sensitive alternative to traditional techniques. With the advent of high- throughput DNA sequencing technology, the comparison of 16S rRNA gene sequences has been considered as a powerful tool for the identification of microorganisms and inferring phylogenetic as well as the evolutionary relationship among diverse microorganisms (Weisburg et al., 1991). Most of the works that reported microbial communities of beef meat and meat products is dedicated to detecting the presence of bacterial pathogens, primarily Salmonella and Campylobacter, using conventional methods (Rouger et al., 2017).

Regular screening of the stores for the detection of microbial contamination at different stages of meat processing is required to ensure public health safety. Also, reports on molecular identification of bacterial communities present in beef meat and meat products using high-throughput sequencing technologies are still limited in Saudi Arabia. The present study was conducted to isolate various bacterial strains from different sources inside four retail stores located in Makkah, Saudi Arabia, identify them based on their biochemical and 16S rRNA gene phylogeny, and characterise their antibiotic sensitivity.

MATERIALS AND METHODS

Collection of samples and isolation of bacteria: Bacterial strains were isolated from four different sources, namely beef meat cutting boards, knives used to cut the meats, meat grinders, and the meat stored in the refrigerators inside four different retail stores located in Makkah, Saudi Arabia. Bacterial isolates were grown on nutrient agar (NA) plates and incubated at 37 °C for 24 h. Purified bacterial strains were grown in nutrient broth (NB) (Salfinger and Tortorello, 2015), and preserved in 20% glycerol solution at -20 °C for subsequent use.

Identification of bacteria

Biochemical characterisation: To determine various biochemical features of bacteria, gram staining, oxidase and catalase tests were performed according to Vincent and Humphrey (1970), Shekhawat et al. (1992), and Hayward (1960).

Molecular characterisation: Bacterial genomic DNA was extracted using the QIAGEN Kit, Germany as described in the manufacturer’s guidelines. The 16S rRNA gene was amplified using the universal primers, 27F (5ʹ-AGAGTTTGATCCTGGCTCAG-3ʹ) and 1492R (5ʹ-AAGGAGGTGATCCAGCCGCA-3ʹ). Amplified products were purified and Sanger-sequenced at Macrogen, South Korea. The sequences were then manually edited by Snap Gene Viewer software version 3.3.3 and compared with the GenBank database of NCBI (http://www.ncbi.nlm.nih.gov) using the BLAST search. Phylogenetic trees were constructed using MEGA available on the NCBI website.

Antibiotic susceptibility test of bacterial isolates: Bacterial antibiotic susceptibility test was conducted following Kirby-Bauer disk diffusion method on NA (Bauer et al., 1966). Eighteen (18) antibiotic discs, namely, ampicillin (10 μg), augmentin (30 μg), gentamicin (10 μg), cefoxitin (30 μg), cephalothin (30 μg), cotrimoxazole (25 μg), vancomycin (30 μg), fucidic acid (10 μg), chloramphenicol (30 μg), methicillin (5 μg), cefepime (30 μg), penicillin G (10 units), erythromycin (15 μg), clindamycin (2 μg), amikacine (30 μg), ticarcillin (75 μg), piperacillin (100 μg), and imipenem (10 μg) were purchased from  Mast Group Ltd, Merseyside, UK, Six discs were distributed on each plate.. Bacterial isolates were spread over the plates using cotton swab following an incubation period of  48h. at 37 ºC. The zone of inhibition was measured using a meter scale, and the isolates were grouped into resistant, intermediate, and sensitive.

RESULTS

Isolation and identification of the bacteria: A total of thirty bacterial strains were isolated from beef meat cutting boards, knives, meat grinders and refrigerated beef meat from four different stores located in Makkah region. Different appeared colonies purified by re-culturing on nutrient agar (NA) medium. The highest number of bacteria was isolated from store 3 (ten strains) followed by store 4 (eight strains), store 2 (seven strains) and store 1 (five strains), respectively. The maximum number of bacteria was isolated from the meat grinder of store 4 (five strains), indicating poor hygiene practices during the grinding process in the respective store. Gram reaction test showed that among thirty bacteria, eleven isolates were Gram-positive and nineteen isolates were Gram-negative bacteria. Out of these isolated bacteria, a total of thirteen isolates showed oxidase and twenty-seven isolates exhibited catalase activity (Table 1).

The BLAST search at the NCBI showed that 16S rRNA gene sequences of the isolates A2B6, B2A1 and B2B2 showed 16S rDNA similarity to Staphylococcus epidermidis (99.71%), S. sciuri (98.98%) and S. saprophyticus (99.2%). Isolates A1B3, C3A2, and C4B1 showed 16S rDNA homology with Psychrobacter sp. (100%), P. piechaudii (99.27%) and P. sanguinis (99.79%). Isolates B3B4, D1B4 and D3B3 showed 16S rDNA similarity to Acinetobacter lactucae (92.62%), A. baumannii (98.38%) and A. variabilis (99.20%).

According to analysis of 16S rRNA gene sequences and NCBI search results of the isolated bacteria showed that isolated bacteria were belong to seventeen genera including Staphylococcus, Psychrobacter, Acinetobater, Macrococcus, Lactococcus, Bacillus, Pseudomonas, Enterobacter, Raoultella, Hafnia, Lysinibacillus, Brevibacillus, Klebsiella, Escherichia, Ochrobactrum, Chryseobacterium and Citrobacter (Table 1). However, Staphylococcus, Psychrobacter and Acinetobater were the most prevalent genera having three species each.

Table 1. Source of isolation, biochemical and molecular features of the isolated bacteria.

Table 1a

Isolates No. Source of isolation Biochemical features Molecular features Gram reaction Oxida se Catalase Closest species from  NCBI Accession number of the closest species from

NCBI

16S rDNA

similar ity (%)

A1A1 Meat – – + Enterobacter MT18423 99.73 Grinder, hormaechei 5.1 % Store 4 A1B1 Meat Grinder,

Store 4

+ + + Macrococcus epidermidis NR_15909 5.1 99.81

%

A1B3 Meat

Grinder, Store 4

– + + Psychrobacter sp NR_11783 3.1 100.00

%

A1B5 Meat – + – Pseudomonas MH28175 99.61 Grinder, luteola 1.1 % Store 4 A1B6 Meat

Grinder, Store 4

+ – – Lactococcus garvieae NR_11326 8.1 99.38

%

A2B6 Meat + – + Staphylococcu NR_03690 99.71 cutting s epidermidis 4.1 % tools Store 4 A3B3 Meat in + + + Macrococcus NR_11926 99.91 the caseolyticus 2.1 % refrigera tor Store 4 A4B1 Meat – – + Klebsiella CP052181 99.73 cutting pneumonia .1 % board Store 4

Table 1b

B1A1 Meat

Grinder, Store 3

– – + Raoultella

ornithinolytic a

NR_04479

9.1

99.64

%

B1A3 Meat

Grinder, Store 3

– – + Hafnia alvei NR_11298

5.1

99.73

%

B1B2 Meat Grinder, Store 3 + – – Lactococcus garvieae NR_11326 8.1 97.86

%

B2A1 Meat

cutting board Store 3

+ + + Staphylococcu

s sciuri

NR_02552

0.1

98.98

%

B2B1 Meat

cutting board Store 3

– + + Ochrobactru

m endophyticum

NR_14636

2.2

97.40

%

B2B2 Meat

cutting board Store 3

+ – + Staphylococcu

s saprophyticus

KF228927

.1

99.20

%

B3B1 Meat in

the refrigera tor Store 3

– + + Pseudomonas

deceptionensi s

NR_11755

2.1

99.49

%

B3B3 Meat in the refrigera tor Store 3 – – + Escherichia marmotae NR_13647 2.1 99.29

%

B3B4 Meat in

the refrigera tor Store

3

– – + Acinetobacter

lactucae

NR_15200

4.1

92.62

%

Table 1c

B4B1 Meat

cutting tools Store 3

+ + + Lysinibacillus

boronitoleran s

NR_11420

7.1

99.73

%

 

C1A2

 

Meat cutting board Store 2

 

–

 

–

 

+

Hafnia paralvei NR_11689 8.1 99.11

%

C1B3 Meat

cutting board Store 2

+ + + Bacillus

sfensis

NR_11394

5.1

99.64

%

C2A3 Meat

cutting tools Store 2

– – + Citrobacter

freundii

NR_11775

2.1

98.93

%

C3A2 Meat

Grinder, Store 2

+ + + Psychrobacter

piechaudii

NR_15798

9.1

99.27

%

C4A2 Meat in the refrigera tor Store 2 – – + Raoultella ornithinolytic a NR_04479 9.1 99.64

%

C4B1 Meat in

the refrigera tor Store 2

– + + Psychrobacter

sanguinis

NR_11783

3.1

99.79

%

C4B3 Meat in the refrigera tor Store 2 – + + Chryseobacte rium carnis NR_12625 5.1 99.64

%

D1B1 Meat

cutting board

Store 1

+ – + Brevibacillus

borstelensis

NR_11379

9.1

99.47

%

Table 1d

D1B2 Meat cutting board

Store 1

+ + + Bacillus piscis NR_16568 5.1 99.81

%

D1B4 Meat cutting board

Store 1

– – + Acinetobacter baumannii NR_11767 7.1 98.38

%

 

D3B3

Meat in the refrigera

tor Store 1

 

–

 

–

 

+

Acinetobacter variabilis NR_13468 5.1 99.20

%

D4B1 Meat cutting tools Store 1 – – + Enterobacter hormaechei subsp.

Xiangfangensi s

NR_12620 8.1 99.82

%

“+” indicates positive and “-” indicates negative response.

Antibiotic susceptibility test: In the present study, all the eleven gram positive bacterial isolates were tested against eleven different antibiotics, namely, ampicillin (10 μg), augmentin (30 μg), gentamicin (10 μg), cefoxitin (30 μg), cephalothin (30 μg), cotrimoxazole (25 μg), vancomycin (30 μg), fucidic acid (10 μg), chloramphenicol (30 μg), methicillin (5 μg) and cefepime (30 μg) to examine their antibiotic sensitivity (Table 2). All the eleven isolates exhibited resistance to at least one of the antibiotics tested (Table 2). The isolate A1B6 showed resistance to highest number of antibiotics (nine) (Figure 1)  and (Table 2). The isolates A1B1 and D1B1 exhibited resistance to lowest number of antibiotics (only one) (Table 2). Among the tested antibiotics, gentamicin was found as the most effective as all isolates were susceptible to it (Table 2).

Figure 1: Response of the isolate A1B6 to eleven antibiotics.

Table 2. Antibiotic susceptibility test of the isolated gram-positive bacteria.

Bacterial isolates  Used antibiotics AP AUG GM FOX KF TS VA FC C MT CPM A2B6 R R S R R R S S S R R A1B1 S S S S S S S S S R S A3B3 S S S S S S S S S R R A1B6 R R S R S R R R R R R B2B2 S S S S S S S S S R R B4B1 S S S S S S S S S R R B1B2 R R S R S R S S S R R B2A1 S S S S S S S S S R R C1B3 R S S S R R R R R R R D1B1 S S S S S S S S S R S D1B2 S S S S S S S S S R R

‘S’ indicates sensitive and ‘R’ indicates resistant to the tested antibiotics.
*AP (Ampicillin, 10 μg), AUG (Augmentin, 30 μg), GM (Gentamicin, 10 μg), FOX (Cefoxitin, 30 μg), KF (Cephalothin, 30 μg), TS (Cotrimoxazole, 25 μg), VA (Vancomycin 30 μg), FC (Fucidic acid, 10 μg), C (Chloramphenicol, 30 μg), MT (Methicillin, 5 μg) and CPM (Cefepime, 30 μg).

On the other hand, all the nineteen gram negative bacteria were tested against twelve different antibiotics, namely, penicillin G (10 units), erythromycin (15 μg), cefoxitin (30 μg), cephalothin (30 μg), clindamycin (2 μg), cotrimoxazole (25 μg),

amikacine (30 μg), gentamicin (10 μg), cefepime (30 μg), ticarcillin (75 μg), piperacillin (100 μg), and imipenem (10 μg) (Table 3). Out of nineteen isolates, seventeen isolates showed resistance to at least one antibiotics tested. The isolate A1B3 was found resistant against maximum (eleven) antibiotics tested (Figure 2) (Table 3). Two isolates, namely B3B4 and C4B3 were susceptible against all the twelve antibiotics tested. Amikacine and imipenm were the most effective antibiotics against the gram negative isolates as both antibiotics were observed effective in suppressing the growth of all but two isolates (Table 3).

Figure 2: Response of the isolate A1B3 to twelve antibiotics.

Table 3. Antibiotic susceptibility test of the isolated gram-negative bacteria.

Bacterial isolates Used antibiotics PG E FOX KF CD TS AK GM CPM TC PRL IMI A1B5 R S R R R R S S S S S S A1A1 R R R R R S S S S S S S A4B1 R R S R R R S S R R R S A1B3 R S R R R R R R R R R R B3B3 R S S R R R S S S S S S B2B1 R R R R R R S S R R R S B3B4 S S S S S S S S S S S S B1A1 R R S S R S S S S S S S B3B1 R R R R R S S S S S S S B1A3 R R S R R S S S S S S S C4B3 S S S S S S S S S S S S C1A2 R R S R R R S S S S S S C3A2 S S S S R R S S S S S S C4A2 R R S S R S S S S R S S C2A3 R R R R R S S S S S S S C4B1 R R R R R S R R S R R R D4B1 R R R R R S S S S S S S D3B3 R S R R R S S S S S S S D1B4 S S S S R S S S S S S S

‘S’ indicates sensitive and ‘R’ indicates resistant to the tested antibiotics.
* PG (Penicillin G, 10 units), E (Erythromycin, 15 μg), FOX (Cefoxitin, 30 μg), KF (Cephalothin, 30 μg), CD (Clindamycin, 2 μg), TS (Cotrimoxazole, 25 μg), AK (Amikacine, 30 μg), GM (Gentamicin, 10 μg), CPM (cefepime, 30 μg), TC (Ticarcillin, 75 μg), PRL (Piperacillin, 100 μg) and IMI (Imipenem (10 μg).

DISCUSSION

Beef meat is one of the major sources of human dietary protein. It can be contaminated in several ways, and thus threatens consumers’ health. In this study, we isolated thirty bacterial strains from meat grinders, cutting boards, knives, and refrigerated meats at four stores located in Makkah. Most bacteria were isolated from the meat grinder of store 4 (five strains), indicating poor hygiene practices during the grinding process in the respective store. The biochemical and 16S rRNA gene phylogeny of the isolated bacteria showed that these bacteria belonged to seventeen genera including Staphylococcus, Psychrobacter, Acinetobacter, Macrococcus, Lactococcus, Bacillus, Pseudomonas, Enterobacter, Raoultella, Hafnia, Lysinibacillus, Brevibacillus, Klebsiella, Escherichia, Ochrobactrum, Chryseobacterium and Citrobacter. Staphylococcus, Psychrobacter and Acinetobater were the most prevalent genera, having three species each.

Bacterial antibiotic resistance has been documented since the beginning of antibiotic era. A number of studies reported resistance to several antibiotics in a wide range of bacteria isolated from beef meat and its surrounding environment (Hiroi et al., 2012; Cameron and McAllister, 2016; Jaja et al., 2019). However, the  underlying mechanism of antibiotic resistance in bacteria was beyond the scope of the present study.

In this study, varied response of bacterial isolates to various antibiotics tested was also observed. Among the gram-positive isolates, isolate A1B6 (Lactococcus garvieae) showed resistance to maximum number of antibiotics tested, whereas isolate A1B3 (Psychrobacter sp.) showed resistance to maximum antibiotics among gram-negative isolates. Resistance to several commonly used antibiotics in Lactococcus garvieae and Psychrobacter strains has been reported by Raissy and Ansari (2011) and González-Aravena et al. (2016), respectively.

Meat can be contaminated at different stages of the supply chain including production, packaging, transport, and storage (Rather et al., 2017; Reyad et al., 2016). Salmonella spp., Bacillus cereus, Campylobacter spp., Clostridium perfringens, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, Yersinia enterocolitica, and Vibrio parahaemolyticus are the most commonly detected bacterial species reported to contaminate beef meat and meat products (Biswas, 2011). It has been reported that Compylobacter spp., Escherichia coli and Salmonella spp. are frequently found in fresh meat and poultry (Zhao et al., 2001).

CONCLUSION 

The present study did not investigate the potential of the isolated bacteria to be opportunistic human pathogens. In addition, the mechanism of antibiotic resistance in the isolated bacteria was out of the scope of the study. Therefore, further investigation is recommended to examine pathogenicity and elucidate the antibiotic resistance mechanism in the isolated strains. In conclusion, the present study isolated and identified thirty bacterial isolates from four different sources inside four stores located in the Makkah region. In addition, this study also evaluated the susceptibility of the isolated Gram-positive and Gram-negative strains to eleven and twelve antibiotics, respectively. The A1B3 strain was found resistant to the highest number (eleven) of antibiotics tested.

ACKNOWLEDGEMENT

This project was funded by the Deanship of Scientific Research (DSR) AT  King Abdulaziz University, Jeddah, under Grant No. (G: 588-130-1441). The authors, therefore, acknowledge with thanks DSR for technical and financial support.

Conflict of interest: The authors do not have any conflict of interest to declare.

Data Availability: Data are available with the corresponding author on reasonable request.

REFERENCES

Al-Thubaiti  E. H., Omar A. M.S., , El-Omri A., Al-Matary M., Al-Mwallad A..H. and Eldeeb S. M. (2021) Safety of Commercially Available Beef Burger in Saudi Arabia. Coatings,  11, 686.

Bauchart C., Morzel M., Chambon C., Mirand P. P., Reynès C., Buffière C., and Rémond D. (2007) Peptides reproducibly released by in vivo digestion of beef meat and trout flesh in pigs. British Journal of Nutrition, 98(6), 1187–1195.

Biswas A.J., Kondaiah N., Anjaneyulu A.S.R. and Mandal, P.K. (2011) Cause, concern, consequences, and control of microbial contaminants in meat- A Review. International Journal of Meat Science 1: 27–35.

Cameron A., and McAllister T.A. (2016) Antimicrobial usage and resistance in beef production. Journal of Animal Science and Biotechnology. 7: 68.

González-Aravena M., Urtubia R., Del Campo K., Lavín P., Wong C., Cárdenas C., and González-Rocha G.( 2016) Antibiotic and metal resistance of cultivable bacteria in the Antarctic sea urchin. Antarctic Science, 28:261-268.

Hiroi    M., Kawamori    F., Harada    T., Sano    Y., Miwa    N., Sugiyama     K.     et al. (2012) Antibiotic resistance in bacterial pathogens from retail raw meats and food‐producing animals in Japan. Journal of Food Protection. 75: 1774–1782.

Ismail S.A., Shehata A.A., and El-Diasty E.M. (2013) Microbiological quality of some meat products in local markets with special reference to mycotoxins. Global Veterinaria. 10: 577–584.

Jaja I.F., Bhembe N.L., Green E., Oguttu J., and Muchenje V. (2019.) Molecular characterisation of antibiotic‐resistant Salmonella enterica isolates recovered from meat in South Africa. Acta Tropica. 190: 129–136.

Outsoumanis K. P, Geornaras I., and Sofos J.N. (2005) Microbiology of land muscle foods. Handbook of Food Science, Technology, and Engineering. 4: 955–997.

Raissy M., Ansari M. (2011) Antibiotic susceptibility of Lactococcus garvieae isolated from rainbow trout (Oncorhynchus mykiss) in Iran fish farms. African Journal of Biotechnology. 10:1473-1476.

Rather IA  Koh W. Y., Paek W. K. and Lim J. (2017) The sources of chemical contaminants in food and their health implications. Frontiers in Pharmacology. 8: 830.

Reyad R, Shawish Naser A, Al-Humam. 2016. Contamination of beef products with staphylococcal classical enterotoxins in Egypt and Saudi Arabia. GMS Hygiene and Infection Control .11: 2196-5226

Rouger A., Tresse O., and Zagorec M. (2017) Bacterial contaminants of poultry meat: sources, species, and dynamics. Microorganisms. 5: 50.

 Saha, M and Sarkar A. (2021) Review on Multiple Facets of Drug Resistance: A Rising Challenge in the 21st Century. J. Xenobiot.13;11(4):197–21.

Salfinger Y., and Tortorello M..L, (2015) Compendium of Methods for the Microbiological Examination of Foods, 5th Ed., American Public Health Association, Washington, D.C.

Thomson J.E., and Kotula A.W. (1959) Contamination of the air sac areas of chicken carcasses and its relationship to scalding and method of killing. Poultry Science. 38: 1433–1437.

Udenigwe C.C., and Howard A. (2013) Meat proteome as source of functional biopeptides. Food Research International. 54: 1021–1032.

Weis T. (2013.) The meat of the global food crisis. Journal of Peasant Studies. 40: 65–85.

Weisburg W.G., Barns S.M., Pelletier D.A., and Lane D.J. (1991) 16S ribosomal DNA amplification for phylogenetic study. Journal of Bacteriology 173: 697-703.

Wilcock A., Pun M., Khanana J. and Aung M. (2004) Consumer attitudes, knowledge and behaviour: A review of food safety issues. Trends in Food Science and Technology. 15: 56–66.

Zaman S.B., Hussain A., and Hossain N. (2017) Antibiotic resistance : a tragedy of the commons.  J. of Food Microbiology 1: 7–9.

Zhao C., Ge B., DeVillena J., Sudler R., Yeh E., White D.G., Wagner D. and Meng J. (2001) Prevalence of Campylobacter spp., Escherichia coli, and Bacillus cereus serovars in retail chicken, turkey, pork, and beef from the Greater Washington, D.C., area. Journal of Applied Environmental Microbiology. 67: 5431-5436.