Abstract
Prompt clinical diagnosis and antimicrobial therapy are key to managing infective endophthalmitis. The small volume of aqueous humor, low bacterial counts, and empirical medication by physicians make existing diagnostic methods time-consuming and imprecise. Here, we investigated the feasibility of combining Fc-containing mannose-binding lectin-coated Fe3O4 (Fc-MBL@Fe3O4) enrichment with matrix-assisted laser desorption-ionization time of flight mass spectrometry (MALDI-TOF MS) profiling to identify pathogens in aqueous humor. Aqueous humor aspirated from freshly enucleated porcine eyes was treated with different inocula of Staphylococcus aureus, Staphylococcus epidermidis, and Klebsiella pneumoniae. We performed identification directly in aqueous humor samples and after short-term culture of micro-LB broth. Aqueous humor endophthalmitis samples were enriched with Fc-MBL@Fe3O4 and analyzed using MALDI-TOF MS. The identification time and minimum bacterial concentration required for identification were determined. The enrichment efficiency of Fc-MBL@Fe3O4 for different bacteria was greater than (87.5 ± 5.0)%. The objects of direct identification include live bacteria and bacteria treated with antibiotics, which can be completed within 1.5 h. The minimum number of bacteria needed for positive identification was 2.20 × 106 CFU. For micro-LB broth culture, the identification of bacteria can be completed within 6.5 to 9.5 h for aqueous humor samples with an initial bacterial count of tens to hundreds. IMPORTANCE Fc-MBL@Fe3O4 capture not only live bacteria in aqueous humor but also bacteria inactivated by antibiotics. Fc-MBL@Fe3O4 combined with micro-LB broth culture significantly reduced the turnaround time (TAT) by more than half a day by shortening the time required for bacterial identification. Our findings demonstrate that combining Fc-MBL@Fe3O4 enrichment with MALDI-TOF MS identification is a fast, sensitive, and efficient analytical method with great potential for identifying pathogens in aqueous humor samples.