Frequency and Antimicrobial Resistance Patterns of Foodborne Pathogens in Ready-to-Eat Foods: An Evolving Public Health Challenge

Food products that are ready-to-eat have become increasingly popular in recent years due to their efficiency, affordability, and convenience. However, there are concerns about public health because certain products, particularly animal products, may contain antibiotic-resistant bacteria. This study aimed to quickly and accurately identify foodborne pathogens, such as Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), in samples of shawarma and chicken burgers using peptide mass fingerprinting (PMF) technology. Additionally, the prevalence and levels of antibiotic resistance in the pathogens were determined. The study utilized 300 samples obtained from fast food restaurants in Al Qassim, Saudi Arabia. A variety of methods were used to identify foodborne pathogens, including culture on specific media, bacterial counts by numerical dilutions of homogenized samples, and proteome identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The Kirby–Bauer method was applied to detect the susceptibility and resistance of the bacteria to various antibiotics. PCR was utilized to identify antimicrobial resistance genes such as blaTEM, tet(A), blaZ, and mecA in S. aureus and E. coli isolates. The percentage of E. coli, S. aureus, Salmonella, Listeria monocytogenes (L. monocytogenes), Acinetobacter baumannii (A. baumannii), and Hafnia alevei (H. alevei) was 34%, 31%, 10.67%, 7.33%, 6.67%, and 4%, respectively. Shawarma samples were found to contain the highest levels of pathogens, compared with chicken burger samples. According to the MBT Compass Flex Series Version 1.3 software, all isolates were identified with 100% accuracy. The log score for MBT identification ranged from 2.00 to 2.56. Among E. coli isolates, ampicillin, and penicillin had the highest resistance rate (100%), followed by tetracycline (35.29%). A number of antibiotics were reported to be resistant to S. aureus, including nalidixic acid (100%), followed by penicillin (96.77%), piperacillin (45.16%), and norfloxacin (32.26%). Some E. coli isolates were susceptible to tetracycline (49.02%), nalidixic acid (47.06%), and piperacillin (43.14%), whereas amikacin was the only drug that was effective against 32.72% of S. aureus isolates. The proportions of the blaTEM and tet(A) genes in E. coli isolates were 55.89% and 45.1%, respectively, whereas S. aureus strains did not possess either of these genes. However, 21.5% and 47.31% of blaz and mecA genes were present among various isolates of S. aureus, respectively. In contrast, E. coli strains did not possess either of these genes. In conclusion, the fast identification and antimicrobial profiles of the foodborne pathogens were useful in identifying which restaurants and fast food outlets may need to improve their food safety practices. Ultimately, our results will be used to devise targeted strategies to control foodborne pathogens.