Journal of Clinical Microbiology最新文献

Accurate detection and monitoring of BK polyomavirus (BKV) infection is of critical importance in the post-transplant period, guiding treatment decisions that balance the anti-rejection effects of immune suppression with host-protective effects of immune defense. Historically, test methods for BKV have been independently developed by laboratories to address this unmet need. However, these assays can suffer from inconsistencies in analytical variability, which in turn have hindered the establishment of commutable and clinically actionable viral load thresholds for clinical management. As a result, the interpretation of viral load quantitation has not been standardized across transplant centers for the purpose of monitoring patients at highest risk for infection-related complications. In this review, we describe challenges that have historically limited widespread adoption of BKV quantitative testing. We then detail how developments in the field, including optimized amplicon selection, the introduction of an international standard, and the availability of Food and Drug Administration (FDA)-cleared methods, have played a role in harmonization of quantitative BKV measurements in the clinical management of transplant recipients.

Mycobacterium ulcerans, a slow-growing nontuberculous mycobacterium, causes Buruli ulcer, a neglected tropical disease. Distinguishing M. ulcerans from related species, including Mycobacterium marinum, poses challenges with respect to making accurate identifications. In this study, we developed a rapid and simple identification method based on mycobacterial lipid profiles and used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the lipid profiles of M. ulcerans (n = 35) and M. marinum (n = 19) isolates. Bacterial colonies pre-cultured on 2% Ogawa egg slants for 2 months were collected, and total lipids were extracted using an MBT Lipid Xtract kit. Spectra were obtained in negative ion mode using a MALDI Biotyper Sirius system, with ClinProTools v3.0 being used to analyze the spectra based on the application of three algorithms (genetic algorithm [GA], supervised neural network [SNN], and quick classifier [QC)]). Cross-validation was performed using a 20% leave-out set randomly selected from the samples. Models generated using GA, SNN, and QC showed cross-validation values of 100%, 100%, and 97.9%, respectively, and all algorithms achieved 100% recognition capability values. Our findings indicate that MALDI-TOF analysis of lipid profiles can accurately differentiate two mycobacterial species (M. ulcerans and M. marinum) that are difficult to distinguish using conventional protein-targeting methods.IMPORTANCEBuruli ulcer, caused by Mycobacterium ulcerans, is a neglected tropical disease. However, distinguishing M. ulcerans from related species, including Mycobacterium marinum, presents certain challenges. In this study, we demonstrate the utility of a rapid yet simple method for differentiating isolates of these mycobacteria based on their lipid profiles using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This new approach can accurately identify species that are otherwise difficult to distinguish using conventional techniques. This represents a significant diagnostic advance for clinical laboratories, in that it enables a more rapid and precise identification, thereby leading to earlier treatment initiation and more appropriate treatment regimens for infections caused by these bacteria.

We report the development of a bench protocol and evaluation of bioinformatics pipelines for the whole genome sequence (WGS) of measles virus (MeV) genotype D8. We established a bench protocol using 1 kb amplicons tiling the MeV WGS. Four different pipeline parameters were assessed based on two basecallers and two quality thresholds: Guppy simplex with Q-score thresholds of 20 and 25 (G20 and G25), and Dorado duplex with Q-score thresholds of 20 and 25 (D20 and D25). Using a reference genome, we determined that complete genomes were obtained down to 10 copies/µL with all four parameters; however, errors began to be detected in the consensus sequence at 100 copies/µL. A panel of specimens from 32 measles cases, for which measles WGS had been obtained by other methods (reference sequences), was used to assess the utility and accuracy of the Oxford Nanopore Technologies (ONT) for the purposes of measles surveillance. We found that a crossing point (Cp) value of 31 (corresponding to approximately 100 copies/µL) or less could be considered a predictor for the generation of accurate and complete WGS. The GQ20 parameter achieved the most complete genomes (75%) and had the most identical sequences (84.4%). Error rates compared with the reference sequences for all parameters were below one nucleotide per whole genome. After assessing the reproducibility, GQ20 had the most identical sequences (97.4%). Finally, we inserted ONT-generated WGS and reference sequences into outbreaks with known epidemiological links, and our results show that the ONT WGS matches the epidemiological data. This evaluation establishes that NGS generated by ONT produces accurate and reliable MeV WGS.IMPORTANCEThe use of ONT-sequencing platforms has the potential to expand the availability of measles sequencing as a result of its relatively lower cost and portability. This study establishes that measles sequences generated by ONT are accurate and reliable. This will enable sequencing in global regions where there is a lack of sequence data (which also tend to be the measles exporting regions) and more timely sequencing in low incidence settings, due also to the lower number of samples needed for the ONT platform. More timely generation of these data enables better investigation of cases, which informs public health response and outbreak management in measles-eliminated countries.

Porcine deltacoronavirus (PDCoV) is an emerging porcine enteric coronavirus causing significant economic losses to the pig farming industry globally. In this study, we expressed the S protein of a highly virulent PDCoV strain in the CHO eukaryotic expression system. After immunizing alpaca with the PDCoV S protein and employing the phage display library technique, a high-affinity and specific nanobody Nb3 against PDCoV S protein was successfully established by three rounds of biopanning and a phage enzyme-linked immunosorbent assay (ELISA). Furthermore, a competitive ELISA (cELISA) was developed based on Nb3 to rapidly and efficiently detect PDCoV antibody levels. The cELISA displayed no cross-reaction with positive sera of porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine rotavirus (PoRV), pseudorabies virus (PRV), classical swine fever virus (CSFV), porcine reproductive and respiratory syndrome virus (PRRSV), or porcine circovirus 2 (PCV2), thereby showing good specificity. The cELISA successfully detected positive sera diluted 1:127 (percentage inhibition ≥ 50.02%), indicating high sensitivity. Both the intra- and inter-batch coefficients of variation were less than 10%, indicating good repeatability. The cELISA had a total coincidence rate of 98.33% with the indirect immunofluorescence assay and a significant positive correlation with the virus neutralization test (r = 0.861, P < 0.001), suggesting that the cELISA can be used to measure the neutralizing antibody titers in serum samples. In conclusion, our nanobody-based cELISA showed good performance indicators and can be used to monitor and evaluate antibody levels following clinical infection of PDCoV or vaccine immunization.

Importance: This study screened out a high-affinity and specific nanobody Nb3 against porcine deltacoronavirus (PDCoV) S protein and established a nanobody-based competitive ELISA (cELISA) for PDCoV antibody detection. This cELISA is a simple, rapid, and specific method that can effectively measure the neutralizing antibody titers in serum samples.