Investigating the Unfavored Factors That Interfere MALDI-TOF Based AI in Predicting Antibiotic Resistance

Combining Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility test (AST) of S. aureus. Based on the AI predictive probability, the cases with probabilities between low and high cut-offs are defined as “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. A total 479 S. aureus isolates were collected, analyzed by MALDI-TOF, and AST prediction, standard AST were obtained in a tertiary medical center. The predictions were categorized into the correct prediction group, wrong prediction group, and grey zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For MRSA, larger cefoxitin zone size was found in the wrong prediction group. MLST of the MRSA isolates in the grey zone group revealed that uncommon strain types composed 80%. Amid MSSA isolates in the grey zone group, the majority (60%) was composed of over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity would contribute to suboptimal predictive performance.

Validation of a novel fluorescent lateral flow assay for rapid qualitative and quantitative assessment of total anti-SARS-CoV-2 S-RBD binding antibody units (BAU) from plasma or fingerstick whole-blood of COVID-19 vaccinees

Background: Limited commercial LFA assays are available to provide a reliable quantitative measurement of the total binding antibody units (BAU/mL) against the receptor-binding domain of the SARS-CoV-2 spike protein (S-RBD). Aim: To evaluate the performance of FinecareTM2019-nCoV S-RBD LFA and its fluorescent reader (FinecareTM-FIA Meter) against the following reference methods (i) The FDA-approved Genscript surrogate virus-neutralizing assay (sVNT), and (ii) three highly performing automated immunoassays: BioMerieux VIDAS, Ortho VITROS, and Mindray CL-900i. Methods: Plasma from 488 vaccinees were tested by all aforementioned assays. Fingerstick whole-blood samples from 156 vaccinees were also tested by FinecareTM. Results and conclusions: FinecareTM showed 100% specificity as none of the pre-pandemic samples tested positive. Equivalent FinecareTM results were observed among the samples taken from fingerstick or plasma (Pearson correlation r=0.9, p<0.0001), suggesting that fingerstick samples are sufficient to quantitate the S-RBD BAU/mL. A moderate correlation was observed between FinecareTM and sVNT (r=0.5, p<0.0001), indicating that FinecareTM can be used for rapid prediction of the neutralization antibody post-vaccination. FinecareTM BAU results showed strong correlation with VIDAS (r=0.6, p<0.0001), and moderate correlation with VITROS (r=0.5, p<0.0001), and CL-900 (r=0.4, p<0.0001), suggesting that FinecareTM be used as a surrogate for the advanced automated assays to measure S-RBD BAU/mL.