ARSCP: An antimicrobial residue surveillance cloud platform for animal-derived foods.

Antibiotics have been widely used for improving human and animal health and well-being for many decades. However, the enormous antibiotic usage in agriculture especially for livestock leads to considerable quantities of antibiotic residues in associated food products and can reach potentially hazardous levels for consumers. Therefore, timely detection and systematical surveillance on residual antibiotics in food materials are of significance to minimize the negative impact caused by such unwanted antibiotic leftovers. To this end, we constructed a cloud-platform-based system (ARSCP) for comprehensive surveillance of antibiotic residues in food materials. With the system, we collected 126,560 samples from 68 chicken farms across China and detected the antibiotic residues using a rapid detection colorimetric commercial (Explorer 2.0) kit and UPLC-MS/MS. Only 108 (0.085 %) of the samples contained residual antibiotics exceeding the MRLs and all data were subjected to ARSCP system to provide a landscape of antibiotic residues in China. As a proof-of-concept, we provided an overview of residual antibiotics based on data from China, but the system is generally applicable to track and monitor the antibiotic residues globally when the data from other countries are incorporated. We used the combined Explorer 2.0 and MS data to construct ARSCP, an antimicrobial residue surveillance cloud platform for raw chicken samples. ARSCP can be used for rapid detection and real-time monitoring of antibiotic residues in animal food and provides both data management and risk warning functions. This system provides a solution to improve the management of facilities that must monitor antibiotic MRLs in food animal products that can reduce the pollution of antibiotics to the environment.

MALDI-TOF MS for rapid detection and differentiation between Tet(X)-producers and non-Tet(X)-producing tetracycline-resistant Gram-negative bacteria.

The extensive use of tetracycline antibiotics has led to the widespread presence of tetracycline-resistance genes in Gram-negative bacteria and this poses serious threats to human and animal health. In our previous study, we reported a method for rapid detection of Tet(X)-producers using MALDI-TOF MS. However, there have been multiple machineries involved in tetracycline resistance including efflux pump, and ribosomal protection protein. Our previous demonstrated the limitation in probing the non-Tet(X)-producing tetracycline-resistant strains. In this regard, we further developed a MALDI-TOF MS method to detect and differentiate Tet(X)-producers and non-Tet(X)-producing tetracycline-resistant strains. Test strains were incubated with tigecycline and oxytetracycline in separate tubes for 3 h and then analyzed spectral peaks of tigecycline, oxytetracycline, and their metabolite. Strains were distinguished using MS ratio for [metabolite/(metabolite+ tigecycline or oxytetracycline)]. Four control strains and 319 test strains were analyzed and the sensitivity was 98.90% and specificity was 98.34%. This was consistent with the results obtained from LC-MS/MS analysis. Interestingly, we also found that the reactive oxygen species (ROS) produced by tetracycline-susceptible strains were able to promote the degradation of oxytetracycline. Overall, the MALDITet(X)-plus test represents a rapid and reliable method to detect Tet(X)-producers, non-Tet(X)-producing tetracycline-resistant strains, and tetracycline-susceptible strains.