Journal of Clinical Microbiology最新文献

{"title":"Comparison of the Filamentous Fungi Library v4.0 MALDI Biotyper Platform vs MSI-2 performance for identifying filamentous fungi from liquid cultures.","authors":"María F Gonzalez-Lara, Carla M Román-Montes, Paulette Díaz-Lomelí, Winston Hernández-Ceballos, Lizeth Morales-Camilo, Axel Cervantes-Sánchez, Andrea Cordero-Rangel, Jazmín Tejeda-Olán, Alexandro Bonifaz-Trujillo, Alfredo Ponce-de-León, Areli Martínez-Gamboa","doi":"10.1128/jcm.01371-24","DOIUrl":"10.1128/jcm.01371-24","url":null,"abstract":"<p><p>Correct, rapid, and reliable filamentous fungi identification is crucial for timely diagnosis and therapy. We compared the performance of the FFLv4.0 MALDI Biotyper and MSI-2 to identify filamentous fungi from clinical isolates. We analyzed 307 clinical isolates of <i>Aspergillus</i> spp.<i>, Fusarium</i> spp.<i>,</i> and <i>Mucorales</i> and compared them to sequencing as the reference standard. The overall identification rates to genus (<i>Mucorales</i>), section (<i>Aspergillus</i>), and species complex (<i>Fusarium</i>) level were 96% (296/307) for FFLv4.0 and 78.5% (241/307) for MSI-2. By each genus, correct species identification was achieved by FFLv4.0 and MSI-2 as follows: 72.4% (165/228) and 55.3% (126/228) for <i>Aspergillus</i> species, 17.6% (6/34) and 38.2% (13/34) for <i>Fusarium</i> species, and 88.9% (40/45) and 55.5% (25/45) for the <i>Mucorales</i>. The rates of non-identification by FFLv4.0 and MSI-2, respectively, were 4% (9/228) and 18% (41/228) for <i>Aspergillus</i> spp., 0% and 17.6% (6/34) for <i>Fusarium</i> spp. and 4.4% (2/45) and 42.2% (19/45%) for the <i>Mucorales</i>. Misidentification rates by FFLv4.0 and MSI-2, respectively, were 16.2% (37/228) and 6.1% (14/228) for <i>Aspergillus</i> species, 67.6% (23/34) and 14.7% (5/34) for <i>Fusarium</i> spp., and 0% and 2.2% (1/45) for the <i>Mucorales</i>. The FFLv4.0 MALDI Biotyper outperformed MSI-2 in identifying filamentous fungi from liquid culture spectra.</p>","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0137124"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143065888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An overview of the laboratory diagnosis of <i>Pneumocystis jirovecii</i> pneumonia.","authors":"Alexis Jaramillo Cartagena, Osaretin Emmanuel Asowata, Dianna Ng, N Esther Babady","doi":"10.1128/jcm.00361-24","DOIUrl":"10.1128/jcm.00361-24","url":null,"abstract":"<p><p><i>Pneumocystis jirovecii</i> (<i>P. jirovecii</i>) is a fungal pathogen associated with significant morbidity in immunocompromised patients, including both HIV- and non-HIV-infected patients. The nonspecific clinical and radiological presentation makes clinical diagnostic challenging, emphasizing the need for accurate laboratory diagnostic tests. However, <i>P. jirovecii</i> does not grow in routine culture media, which presents diagnostic challenges in the laboratory as well. Recent publications from the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium continue to rely on direct detection of <i>P. jirovecii</i> organisms in tissues and respiratory samples to define proven <i>P. jirovecii</i> pneumonia (PCP) even as the sensitivity of these methods are lower. Novel, standardized methods are needed to improve the clinical and laboratory diagnosis and management of PCP. This minireview provides an overview of current diagnostic tests for PCP and emerging applications that aim at filling existing diagnostic gaps and providing more accurate and less invasive diagnoses for this significant disease.</p>","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0036124"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143080214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel framework for the automated characterization of Gram-stained blood culture slides using a large-scale vision transformer.","authors":"Jack McMahon, Naofumi Tomita, Elizabeth S Tatishev, Adrienne A Workman, Cristina R Costales, Niaz Banaei, Isabella W Martin, Saeed Hassanpour","doi":"10.1128/jcm.01514-24","DOIUrl":"10.1128/jcm.01514-24","url":null,"abstract":"<p><p>This study introduces a new framework for the artificial intelligence-based characterization of Gram-stained whole-slide images (WSIs). As a test for the diagnosis of bloodstream infections, Gram stains provide critical early data to inform patient treatment in conjunction with data from rapid molecular tests. In this work, we developed a novel transformer-based model for Gram-stained WSI classification, which is more scalable to large data sets than previous convolutional neural network-based methods as it does not require patch-level manual annotations. We also introduce a large Gram stain data set from Dartmouth-Hitchcock Medical Center (Lebanon, New Hampshire, USA) to evaluate our model, exploring the classification of five major categories of Gram-stained WSIs: gram-positive cocci in clusters, gram-positive cocci in pairs/chains, gram-positive rods, gram-negative rods, and slides with no bacteria. Our model achieves a classification accuracy of 0.858 (95% CI: 0.805, 0.905) and an area under the receiver operating characteristic curve (AUC) of 0.952 (95% CI: 0.922, 0.976) using fivefold nested cross-validation on our 475-slide data set, demonstrating the potential of large-scale transformer models for Gram stain classification. Results were measured against the final clinical laboratory Gram stain report after growth of organism in culture. We further demonstrate the generalizability of our trained model by applying it without additional fine-tuning on a second 27-slide external data set from Stanford Health (Palo Alto, California, USA) where it achieves a binary classification accuracy of 0.926 (95% CI: 0.885, 0.960) and an AUC of 0.8651 (95% CI: 0.6337, 0.9917) while distinguishing gram-positive from gram-negative bacteria.</p><p><strong>Importance: </strong>This study introduces a scalable transformer-based deep learning model for automating Gram-stained whole-slide image classification. It surpasses previous methods by eliminating the need for manual annotations and demonstrates high accuracy and generalizability across multiple data sets, enhancing the speed and reliability of Gram stain analysis.</p>","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0151424"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field evaluation of nanopore targeted next-generation sequencing to predict drug-resistant tuberculosis from native sputum in South Africa and Zambia.","authors":"Tiana C Schwab, Lavania Joseph, Andrew Moono, Pauline C Göller, Mamello Motsei, Guy Muula, Denise Evans, Stefan Neuenschwander, Gunar Günther, Carolyn Bolton, Peter M Keller, Alban Ramette, Matthias Egger, Shaheed V Omar, Lukas Fenner","doi":"10.1128/jcm.01390-24","DOIUrl":"10.1128/jcm.01390-24","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Rapid and comprehensive drug susceptibility testing (DST) is essential for diagnosing and treating drug-resistant tuberculosis effectively, and next-generation sequencing can be an effective genotypic DST method. We implemented and evaluated the performance of a nanopore targeted sequencing assay, called the Tuberculosis Drug Resistance Test (TBDR, Oxford Nanopore Diagnostics, Ltd., United Kingdom), which predicts drug resistance to 16 TB drugs, at a South African reference laboratory and a district diagnostic laboratory in Zambia. We compared the sequencing success rates between unprocessed and decontaminated sputum samples and determined the diagnostic accuracy against local DST (Xpert MTB/RIF Ultra, Xpert MTB/XDR, and BD BACTEC MGIT phenotypic DST). We prospectively sequenced 236 samples and have 148 samples with sequencing results from unprocessed and decontaminated sputum. We obtained successful sequencing results from 66.4% (94/148) unprocessed sputum samples and 75% (111/148) decontaminated samples. Sequencing success rates at the two sites differed, with 50.7% (36/71) successful sequencing results from unprocessed sputum in Zambia and 75.3% (58/77) in South Africa. Samples with \"low\" bacterial load, measured by Xpert MTB/RIF Ultra, tended to produce fewer successful sequencing results. TBDR sequencing predicted resistances in 48 samples, detecting resistance for rifampicin (&lt;i&gt;n&lt;/i&gt; = 41) and isoniazid (&lt;i&gt;n&lt;/i&gt; = 20), as well as 10 second-line drugs (&lt;i&gt;n&lt;/i&gt; = 15). Sensitivity was variable compared to phenotypic DST, ranging from 33 (ethionamide) to 94% (rifampicin), while specificity remained above 90% for all drugs, except clofazimine. The TBDR assay can provide rapid, comprehensive genotypic DST. Technical and operational challenges need to be addressed for its broader implementation in high tuberculosis-burden settings.IMPORTANCEThis study illustrates the use of the Tuberculosis Drug Resistance Test (TBDR, Oxford Nanopore Diagnostics, Ltd., United Kingdom) as a rapid drug susceptibility testing (DST) approach for diagnosing drug-resistant TB in the high TB-burden countries of South Africa and Zambia. The TBDR assay predicts resistance to 16 TB drugs, including first- and second-line treatments. By implementing the TBDR assay in a national reference laboratory in South Africa and a district diagnostic laboratory in Zambia, we demonstrate how this technology can provide faster diagnostic results (days) compared to traditional phenotypic DST methods (~2 months), with adequate sensitivity. Missed resistances compared to phenotypic DST indicate that technical improvements are needed. Successful sequencing from unprocessed and decontaminated sputum samples at different sites suggests feasibility in diverse settings, though operational challenges remain. Implementing this rapid, comprehensive DST approach could enhance drug-resistant tuberculosis diagnosis and treatment, ultimately improving patient outcomes and helping to combat tub","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0139024"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143399425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2025 American Society for Microbiology Awards and Prize Program: honorees from clinical microbiology.","authors":"Erik Munson","doi":"10.1128/jcm.00001-25","DOIUrl":"https://doi.org/10.1128/jcm.00001-25","url":null,"abstract":"","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":"63 3","pages":"e0000125"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Brief Case: Cutaneous ulceration associated with acalabrutinib treatment.","authors":"Victor Luzarraga, Céline Nourrisson, Florence Anglade, Carole Chevenet, Philippe Poirier, Maxime Moniot","doi":"10.1128/jcm.01583-24","DOIUrl":"10.1128/jcm.01583-24","url":null,"abstract":"","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":"63 3","pages":"e0158324"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum for Snyder et al., \"Performance of the LifeScale automated rapid phenotypic antimicrobial susceptibility testing on Gram-negative rods directly from positive blood cultures\".","authors":"James W Snyder, Nadia Chaudhry, Wesley Hoffmann","doi":"10.1128/jcm.00156-25","DOIUrl":"10.1128/jcm.00156-25","url":null,"abstract":"","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0015625"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143399422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photo Quiz: Hematuria in a pediatric patient.","authors":"Víctor Antón Berenguer, Sara Ruiz González, Francisco Jesús Merino Fernández, José Miguel Rubio Muñoz, Sara Gómez de Frutos, María Delmans Flores-Chavez","doi":"10.1128/jcm.00241-24","DOIUrl":"10.1128/jcm.00241-24","url":null,"abstract":"","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":"63 3","pages":"e0024124"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of FDA-cleared molecular solutions for BK polyomavirus quantitation.","authors":"Bijal A Parikh, Neil W Anderson","doi":"10.1128/jcm.00348-24","DOIUrl":"10.1128/jcm.00348-24","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0034824"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143006406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A rapid and simple MALDI-TOF MS lipid profiling method for differentiating <i>Mycobacterium ulcerans</i> from <i>Mycobacterium marinum</i>.","authors":"Takeshi Komine, Hanako Fukano, Mitsunori Yoshida, Yuji Miyamoto, Makoto Nakaya, Azumi Fujinaga, Kohei Doke, Yoshihiko Hoshino","doi":"10.1128/jcm.01400-24","DOIUrl":"10.1128/jcm.01400-24","url":null,"abstract":"<p><p><i>Mycobacterium ulcerans</i>, a slow-growing nontuberculous mycobacterium, causes Buruli ulcer, a neglected tropical disease. Distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, 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 <i>M. ulcerans</i> (<i>n</i> = 35) and <i>M. marinum</i> (<i>n</i> = 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 (<i>M. ulcerans</i> and <i>M. marinum</i>) that are difficult to distinguish using conventional protein-targeting methods.IMPORTANCEBuruli ulcer, caused by <i>Mycobacterium ulcerans</i>, is a neglected tropical disease. However, distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, 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.</p>","PeriodicalId":15511,"journal":{"name":"Journal of Clinical Microbiology","volume":" ","pages":"e0140024"},"PeriodicalIF":6.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898672/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}