Journal of Clinical Microbiology最新文献

The aim of this study was to identify parameters influencing DNA extraction and PCR amplification efficiencies in an attempt to standardize Mucorales qPCR. The Fungal PCR Initiative Mucorales Laboratory Working Group distributed two panels of simulated samples to 26 laboratories: Panel A (six sera spiked with Mucorales DNA and one negative control serum) and Panel B (six Mucorales DNA extracts). Panel A underwent DNA extraction in each laboratory according to the local procedure and were sent to a central laboratory for testing using three different qPCR techniques: one in-house qPCR assay and two commercial assays (MucorGenius and Fungiplex). Panel B DNA extracts were PCR amplified in each laboratory using local procedures: nine in-house qPCR assays and two commercial kits (MucorGenius and MycoGENIE). All data were compiled and anonymously analyzed at the central laboratory. For Panel A, a total of six different automated platforms and five manual extraction methods were used. Positive rates were 64%, 70%, and 89%, for the MucorGenius, Fungiplex, and the in-house qPCR assay, respectively. Using a large volume of serum for DNA extraction provided the highest analytical sensitivity (82.5% for 1 mL compared with 62.7% for smaller volumes, P < 0.01). For Panel B, five in-house qPCR assays and two commercial kits had >78% positivity. Using larger PCR input volumes (≥7 µL) was associated with the highest sensitivity at 95.5% compared to 58.3% when lower input volumes were used (P < 0.01). Using larger sample volumes for nucleic acid extraction and DNA template volumes for PCR amplification significantly improves the performance of Mucorales qPCR when testing serum.

Importance: Mucormycosis is a life-threatening mold infection affecting immunosuppressed patients but also other patients with diabetes or trauma. Better survival is linked to shorter delays in diagnosis and treatment initiation. Detection of Mucorales-free DNA in serum or plasma using quantitative PCR allows a prompt diagnosis and earlier treatment. Several techniques and protocols of quantitative Mucorales PCR are used in Europe, and improving performance remains a common objective of laboratories participating in the fungal PCR Initiative Working Group. This study, which combined results from 26 laboratories in Europe, showed that the main parameters underpinning sensitivity are the preanalytical variables (volume of serum used for DNA extraction and DNA template volume), irrespective of the extraction platforms and qPCR assay/platform.

Rapid and accurate identification of cultured molds is important to determine clinical significance and therapeutic decision-making. Conventional mold identification uses phenotypic macroscopic and microscopic characterization; however, this can take days or weeks for colony maturity and definitive microscopic structure formation, be limited to genus-level identification, and be misidentified due to morphologic mimics or similarities between closely related species. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) revolutionized bacterial and yeast identification but remains uncommon for molds in part because of limited reference libraries. Here, a retrospective 5-year review at a large teaching hospital found that 88.6% of identified molds were in the Bruker Filamentous Fungi Library 3.0 and 91.5% in the VITEK Knowledge Base Library 3.2.0. A prospective evaluation was also performed on early growth from 205 consecutive, working clinical isolates. Each mold was processed using the VITEK chemical extraction method and modified NIH chemical plus bead-beating extraction method; both extractions were tested on both systems. When compared to conventional identification, more molds were identified using VITEK extractions over NIH extractions using the VITEK (65 and 59%) and Bruker (56 and 54%) systems, respectively, using the ≥1.5 log Bruker threshold. VITEK MS identified more molds, regardless of the extraction method. Isolates without consensus agreement (n = 116) underwent sequence-based identification, which demonstrated that conventional identification had the highest genus-level (84%) but lowest species-level (3%) identification rates compared to VITEK (59 and 52%, respectively) and Bruker (52 and 36%) using VITEK extractions. Taken together, our findings suggest both MALDI-TOF systems can supplement conventional mold identification to optimize identification rates with species-level distinction.

Importance: Mold identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) remains uncommon in clinical laboratories. Contributing concerns include limited genus/species spectra in the MALDI-TOF MS libraries, varying success rates in the literature regarding extraction methods and instrumentation, and the lack of practical performance evaluations using early mold colony growth, which would be used in a clinical mycology laboratory. This study used multiple approaches to improve our understanding of the clinical utility and performance of MALDI-TOF MS mold identification.

This study addresses the use of other echinocandins as surrogate markers to predict the susceptibility of rezafungin against the six most common Candida spp. The Clinical Laboratory Standards Institute (CLSI) reference broth microdilution method was performed to test 5,720 clinical isolates of six different Candida species. Species-specific interpretative criteria by CLSI breakpoints or epidemiological cutoff values were applied. Essential agreement was 100% within two doubling dilutions for all species and comparisons. The categorical agreement of rezafungin using anidulafungin against all Candida spp. was 97.6% (2.9% very major errors [VMEs], 0.2% major errors [MEs], and 2.2% minor errors [miEs]); for caspofungin, it was 99.6% (11.4% VME, 0.09% ME, and 0.19% miE); and for micafungin, it was 99.6% (14.3% VME, 0.15% ME, and 0.17% miE). There were species-specific differences that led to unacceptably high VME for Candida dubliniensis with all agents and for Candida parapsilosis when caspofungin or micafungin but not anidulafungin was used as the comparator. Genetic analysis showed rezafungin nonsusceptibility correlated well with FKS hotspot mutations. The best-performing surrogate was anidulafungin, which can be used to predict rezafungin susceptible or nonsusceptible in Candida albicans, Candida glabrata, Candida parapsilosis, Candida tropicalis, and Candida krusei with low error rates and ≥90% essential and categorical agreement. Micafungin or caspofungin can also be used as a surrogate marker for predicting rezafungin susceptible or nonsusceptible in C. albicans, C. glabrata, C. tropicalis, and C. krusei. No surrogate performs appropriately to determine rezafungin susceptibility for C. dubliniensis.

Early use of infection control methods is critical for preventing the spread of antimicrobial resistance. Whole-genome sequencing (WGS) is considered the gold standard for investigating outbreaks; however, the turnaround time is usually too long for clinical decision-making and the method is also costly. The aim of this study was to evaluate the performance of Fourier transform infrared (FTIR) and artificial intelligence tools as a first-line typing tool for typing carbapenemase-producing Klebsiella pneumoniae (CPK) in the hospital setting. For this purpose, we analyzed 365 CPK isolates from two tertiary hospitals in Spain in parallel by applying unsupervised principal component analysis (PCA) and supervised algorithms (artificial neural network [ANN], support vector machine [SVM] linear, SVM radial basis function in the IR Biotyper software, and random forest in the Clover MSDAS software). Concordance with FTIR clustering considering the sequence type (ST) and the clonal cluster, obtained by cgMLST for reference purposes, was measured using the adjusted Wallace index (AWI), yielding values of 0.611 and 0.652, respectively. Different regions of the spectra were studied in relation to repeatability and reproducibility, and the polysaccharides region proved the best for FTIR differential analysis. The best results for accuracy were obtained using the ANN algorithm in the IR Biotyper software, with 80.5% of correct prediction. Regarding accuracy, the poorest results were obtained for isolates belonging to ST392 (55.5%) and the best results for ST307 (94.4%). The findings demonstrate the utility of the FTIR method as a rapid, inexpensive, first-line typing tool for detecting CPK, preserving WGS for confirmation and further characterization.

Bovine reproductive failure, which includes infertility, abortion, and stillbirth in cattle, leads to significant economic losses for beef and milk producers. Diagnosing the infectious causes of bovine reproductive failure is challenging as there are multiple pathogens associated with it. The traditional stepwise approach to diagnostic testing is time-consuming and can cause significant delays. In this study, we have developed a syndromic next-generation sequencing panel (BovReproSeq) for the simultaneous detection of 17 pathogens (bacteria, virus, and protozoa) associated with bovine reproductive failure. This targeted approach involves amplifying multiple pathogen-specific targets using ultra-multiplex PCR, followed by sequencing with the Oxford Nanopore platform and subsequent analysis of the data using a custom bioinformatic pipeline to determine the presence or absence of pathogens. We tested 116 clinical samples and found that BovReproSeq results matched with current diagnostic methods for 93% of the samples, and most of the disagreements occurring in samples with very low pathogen loads (Ct >35). At the optimal read-count threshold of 10 reads (minimum number of reads to classify the sample as positive), the clinical sensitivity of the assay was approximately 82%, while clinical specificity was 100%. The overall accuracy of the assay was 98.8%. Matthews correlation coefficient (correlation coefficient of binary classification) was approximately 0.90 and F1 score (harmonic mean of precision and recall) was 0.90, indicating excellent overall performance. Our study presents a significant advancement in detecting the infectious agents associated with bovine reproductive failure and the BovReproSeq panel's ability to detect 17 pathogens makes it a promising tool for veterinary diagnostics.IMPORTANCEBovine reproductive failure causes substantial economic losses to beef and milk producers, and infectious disease contributes significantly to this syndrome. Etiologic diagnosis is complicated since multiple pathogens can be involved and infections with some pathogens are asymptomatic or cause similar clinical signs. A stepwise approach to diagnostic testing is time-consuming and increases the risk of missing the correct diagnosis. BovReproSeq is a next-generation sequencing-based diagnostic panel that allows detection of 17 reproductive failure pathogens simultaneously.