Fast detection of bacterial contamination in fresh produce using FTIR and spectral classification.

Screening for microbial contaminants in fresh produce is a lengthy process relative to their short shelf-life. The aim of this study is to develop a comprehensive assay which employs FTIR and spectral classification algorithm for detection of bacterial contamination of fresh produce. The procedure starts by soaking a sample of the fresh produce in broth for 5 h. Then, magnetic nanoparticles are added to capture bacteria which are then collected and prepared for FTIR scanning. The generated FTIR spectra are compared against an in-house database of different bacterial species (n = 6). The ability of the database to discriminate contaminated and uncontaminated samples and to identify the bacterial species was assessed. The compatibility of the FTIR procedures with subsequent DNA extraction and PCR was tested. The developed procedure was applied for assessment of bacterial contamination in fresh produce samples from the market (n = 78). Results were compared to the conventional culture methods. The generated FTIR database coupled to spectral classification was able to detect bacterial contamination with overall accuracy exceeding 90%. The sample processing did not alter the integrity of the bacterial DNA which was suitable for PCR. On application to fresh produce samples collected from the market, the developed method was able to detect bacterial contamination with 94% concordance with the culture method. In conclusion, the developed procedure can be applied for fast detection of microbial contamination in fresh produce with comparable accuracy to conventional microbiological assays and is compatible with subsequent molecular assays.

Detection of Acinetobacter baumannii in fresh produce using modified magnetic nanoparticles and PCR.

Foodborne pathogens represent a major public health concern. In this respect, Acinetobacter baumannii is emerging as multi-drug resistant food pathogen. Screening of A. baumannii in food is a lengthy process. The aim of this study is to develop a fast and efficient protocol for detecting A. baumannii as well as other potential pathogens in fresh food. A. baumannii was collected from strawberry samples (n = 93) and were identified by DNA sequencing and polymerase chain reaction (PCR; recA). Hydrophobic magnetic nanoparticles (OA-MNP) were synthesized and tested for capturing A. baumannii and other bacteria from broth medium. Their ability to immobilize bacteria was assessed and the accuracy of PCR performed on immobilized bacteria was compared against control. A. baumannii (n = 14) was isolated form fresh produce as confirmed by sequencing and PCR. OA-MNPs were able to capture A. baumannii as well as other bacteria from broth medium. Intact DNA was extracted from immobilized bacteria and was successfully recruited for subsequent PCR. In conclusion, OA-MNP can be used for immobilizing food pathogens from broth medium. PCR can be performed using DNA extracted from immobilized bacteria for identification. The proposed analysis procedure may shorten the time required for detection of bacterial contamination in food.