Identification of Potential Biomarkers and Spectral Fingerprinting for Detection of Foodborne Pathogens in Raw Chicken Meat Matrix Using GCMS and FTIR

Abstract

Foodborne illnesses pose a serious threat to public health, with increasing global incidence rates driven by factors such as rising meat consumption. Rapid detection of foodborne pathogens in meat is critical for preventing outbreaks. This study investigates the potential of gas chromatography-mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) for identifying biomarkers and spectral fingerprints indicative of foodborne pathogens in raw chicken meat. Raw broiler chicken meat samples were surface-sterilized and inoculated with foodborne pathogens. The samples were challenge inoculated with the specific pathogen and the physical quality parameters like pH, color, texture, drip loss, and water activity were assessed. GC-MS analysis identified 113 metabolites, including potential biomarkers like ureidopropionic acid, 5-sulfosalicylic acid, 11,14-eicosadienoic acid, methyl ester for E. coli O157:H7; 11-bromoundecanoic acid, neocurdione, glafenin, eicosanoic acid for Salmonella; azepan-1-yl-acetic acid, methyl ester, tramadol, cytarabine, dipipanone for Staphylococcus and cyclopentaneundecanoic acid, phosphonofluoridic acid, î-n-formyl-l-lysine for Pseudomonas. Pathway analysis revealed the involvement of fatty acid metabolism and amino acid degradation pathways. FTIR spectral data showed significant variances between control and spiked samples, particularly in the fatty acid spectral region. The identified metabolites and spectral patterns could serve as biomarkers for developing rapid pathogen detection methods, contributing to enhanced food safety protocols.