Amirreza Sharif ¹ Ramin Bagheri Nejad ² Alireza Ghassempour ^1*

• ¹ Shahid Beheshti University, Tehran, Iran
• ² Razi Vaccine and Serum Research Institute, Karaj, Alborz, Iran

Frequently two factors impede accurate bacterial identification using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS): inadequate bacterial abundance in real samples and bacterial combinations. For MALDI-TOF MS analysis and libraries for bacterial identification, time-consuming culture procedures are necessary to achieve sufficient concentration and isolation of a single bacterium. When dealing with hazardous bacteria like Brucella, which are more difficult to handle and cure, this problem becomes even more crucial. To overcome these obstacles, Fe3O4 magnetic nanoparticles (MNPs) linked with Brucella-specific antibodies and MALDI-TOF MS analysis have been used to create a quick and accurate technique for direct bacterial separation and identification in complex samples. This method allows MNPs to immune-selectively collect Brucella cells, which are then deactivated and ready for MALDI-TOF MS analysis by a formic acid/acetonitrile wash.Rabbits were used to manufacture brucella antibodies, which have effectively adsorbed onto the MNPs-Protein A. Any particular Brucella bacteria found in the media might be absorbed by this MNPs-Protein A antibody immunoprobe. The concentration of Brucella bacterial cells increases the protein spectrum's visibility by a factor of 10 3 , making it possible to quickly identify Brucella spp. without first growing them in cultural conditions. This method has been successfully used to achieve a limit of detection (LOD) of 50 CFU/mL in an aqueous medium and genuine sample; milk. The diagnostic time for this harmful bacterium is greatly decreased because the entire procedure from bacterial isolation to species identification is finished in less than 60 minutes. High sensitivity and specificity are demonstrated by the immunoassay-MS approach, as the spectral pattern it produces matches well-known databases like SPECLUST and Ribopeaks.