Application of MALDI-TOF MS Profiling Coupled With Functionalized Magnetic Enrichment for Rapid Identification of Pathogens in a Patient With Open Fracture

A novel diagnostic method for a rare fungus: FcMBL facilitates Wickerhamomyces anomalus identification in an immunocompromised neonate

Fungemia negatively impacts patient outcomes, current diagnostics lack sensitivity to identify emerging rare mycoses, and fungal infections are increasing in prevalence, variety, and resistance. We report a case of Wickerhamomyces anomalus in an immunocompromised neonate in which FcMBL bead-based matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) resulted in species identification roughly 30 hours before standard pathogen identification methods. Deploying FcMBL bead-based MALDI-TOF MS may improve the speed and accuracy of identification, and therefore treatment, of rare pathogens.

MALDI-TOF MS Is an Effective Technique To Classify Specific Microbiota

MALDI-TOF MS is well-recognized for single microbial identification and widely used in research and clinical fields due to its specificity, speed of analysis, and low cost of consumables. Multiple commercial platforms have been developed and approved by the U.S. Food and Drug Administration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has been used for microbial identification. However, microbes can present as a specific microbiota, and detection and classification remain a challenge. Here, we constructed several specific microbiotas and tried to classify them using MALDI-TOF MS. Different concentrations of nine bacterial strains (belonging to eight genera) constituted 20 specific microbiotas. Using MALDI-TOF MS, the overlap spectrum of each microbiota (MS spectra of nine bacterial strains with component percentages) could be classified by hierarchical clustering analysis (HCA). However, the real MS spectrum of a specific microbiota was different than that of the overlap spectrum of component bacteria. The MS spectra of specific microbiota showed excellent repeatability and were easier to classify by HCA, with an accuracy close to 90%. These results indicate that the widely used MALDI-TOF MS identification method for individual bacteria can be expanded to classification of microbiota. IMPORTANCE MALDI-TOF MS can be used to classify specific model microbiota. The actual MS spectrum of the model microbiota was not a simple superposition of every single bacterium in a certain proportion but had a specific spectral fingerprint. The specificity of this fingerprint can enhance the accuracy of microbiota classification.

Rapid Pathogen Identification in Aqueous Humor Samples by Combining Fc-MBL@Fe3O4 Enrichment and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Profiling

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.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.