Journal of Clinical Microbiology最新文献

Tuberculosis (TB) remains a leading global infectious killer, yet traditional diagnostic methods are inadequate. Acid-fast staining suffers from low sensitivity, and mycobacterial culture requires prolonged incubation because of the slow growth of Mycobacterium tuberculosis. PCR-based molecular assays allow rapid detection, but their capacity for resistance profiling is limited to a narrow set of mutations. Metagenomic next-generation sequencing (mNGS) has emerged as a promising culture-independent tool for TB detection, enabling broad-spectrum pathogen identification and offering added value in complex scenarios including extra-pulmonary disease, mixed infections, and infections in immunocompromised or pediatric populations. Clinical studies indicate that mNGS achieves moderate to high sensitivity and excellent specificity in the diagnosis of tuberculosis. However, its diagnostic performance is often constrained by low mycobacterial read counts, interference from abundant host nucleic acids, and the inability to distinguish active from latent infection. In addition, the accuracy of drug resistance prediction using mNGS remains limited, and the World Health Organization currently endorses targeted NGS as the preferred sequencing-based approach for resistance profiling. Despite these challenges, mNGS has facilitated novel diagnostic strategies that combine pathogen detection with host-response data, thereby broadening its potential clinical utility. Nevertheless, practical barriers such as high cost, complex laboratory workflows, and difficulties in data interpretation continue to restrict widespread adoption in routine practice. Future efforts should prioritize technical optimization, standardized protocols, and integration with conventional diagnostics to establish cost-effective and clinically meaningful roles for mNGS in TB diagnosis and management.

Historic detection methods for diarrheal pathogens are time-consuming, laborious, and may lack specificity and sensitivity. Multiplexed molecular panels for enteric pathogens are widely used for rapid and accurate results. We evaluated the performance of the investigational use only (IUO) Hologic Panther Fusion GI Bacterial and Expanded Bacterial assays (Fusion GI Bac), the Verigene Enteric Pathogens (EP), and BioFire FilmArray Gastrointestinal (BioFire GI) panels for the detection of primary bacterial causes of gastrointestinal infection. We conducted a multi-platform evaluation for the detection of Salmonella, Shigella/Enteroinvasive Escherichia coli, Campylobacter, Shiga toxin-producing E. coli, Vibrio, and Yersinia enterocolitica. Limited analysis of Plesiomonas shigelloides and E. coli O157 was also performed. A total of 591 stool specimens underwent complete analysis: 263 frozen positive specimens and 328 freshly collected samples. We used a 2-out-of-3 consensus as the reference for assay performance. Positive and negative percent agreement (PPA and NPA) were high for most pathogen/assay pairs. Individual false-positive (FP) or false-negative (FN) results were seen for all pathogens and assays. PPAs below 95% in the retrospective samples were seen for Shiga toxin (Verigene EP, 89.3%) and Y. enterocolitica (Verigene EP, 88.9% and Fusion GI Bac, 72.2%). There were 12 FP results for Vibrio affecting all assays. Factors contributing to erroneous results, including freeze/thaw effects, are discussed. Overall, the IUO Panther Fusion GI Bacterial and Expanded Bacterial assays were comparable to two commercially available GI panels with a straightforward workflow using a high-throughput instrument.

Importance: Bacterial causes of diarrhea lead to significant morbidity and mortality around the world. Historic testing methods, for example, antigens and culture. For these reasons, molecular testing for enteric bacterial pathogens has become widely used, but there are limited numbers of commercially available tests on the market, especially those suitable for higher-throughput testing. We show that the high-throughput, random- access investigational use only Hologic Panther Fusion Gastrointestinal (GI) Bacterial assay and Panther Fusion GI Expanded Bacterial assay perform comparably to existing assays.

Biofilms are structured communities of microorganisms encased in a self-produced polymeric matrix that typically adhere to surfaces. Recent research, however, has revealed that non-attached aggregates share many common traits with the surface-dependent biofilms. This mode of bacterial growth provides enhanced protection against antibiotics and resistance to host immune defenses. Biofilms require higher antibiotic concentrations than those needed to inhibit planktonic bacteria, necessitating prolonged high-dose and combination therapies to achieve effective eradication. This increased resistance is attributed to multiple factors, including the protective extracellular matrix, reduced metabolic activity of bacteria within the biofilm, and also the ability of bacterial genomes to rapidly adjust in response to environmental changes. Diagnostic modalities such as sonication, tissue culture, and polymerase chain reaction-based assays currently dominate clinical diagnostics of biofilm infections due to their practicality, cost-effectiveness, and proven reliability. Recent research has led to innovative treatment strategies that target biofilm structure, enhance drug delivery, and modulate host-pathogen interactions. This review summarizes our current knowledge of biofilm formation, explores the current techniques for detecting microbial biofilms, and discusses future perspectives for advancing diagnostic and therapeutic strategies.

Matrix-assisted laser desorption-ionization-time of flight (MALDI-TOF) mass spectra can be used to predict antimicrobial resistance (AMR) using machine learning (ML). This study aimed to validate the performance of ML models for AMR prediction using own and publicly available MALDI-TOF data and to test how these models perform over time. Mass spectra of Escherichia coli (n = 7,897), Klebsiella pneumoniae (n = 2,444), and Staphylococcus aureus (n = 4,664) from routine diagnostics (Germany) and the DRIAMS-A database (Switzerland) were used. Six classification models were benchmarked for AMR prediction using cross-validation (regularized logistic regressions [LR], multilayer perceptrons [MLP], support vector machines [SVM], random forests [RF], gradient boosting machines [LGBM, XGB]). Performance was prospectively observed for 18 months after training. The performance of AMR prediction evaluated by the mean area under the receiver operating characteristic curve (AUROC) was comparable between the DRIAMS-A data set and own data. The best predictive performance (classifier, AUROC) on own data was achieved for oxacillin resistance in S. aureus (RF, 0.85), ciprofloxacin resistance in E. coli (XGB, 0.83), and piperacillin-tazobactam resistance in K. pneumoniae (XGB, 0.81). ML performance was poor if training and test data were unrelated in terms of location and time. Performance (change in AUROC) decreased within 18 months after training for S. aureus (oxacillin resistance, RF: -0.10), E. coli (ciprofloxacin, XGB: -0.19), and K. pneumoniae (piperacillin-tazobactam, XGB: -0.25). The performance of ML for the prediction of AMR based on MALDI-TOF data is good (AUROC ≥ 0.8) but classifiers need to be trained on local data and retrained regularly to maintain the performance level.

Importance: MALDI-TOF mass spectrometry can be used not only for bacterial species identification but also for the prediction of antimicrobial resistance (AMR) using machine learning (ML). Such an approach would provide antimicrobial susceptibility test results one day earlier than conventional routine diagnostics. This is essential for an early targeted treatment to reduce mortality of severe infections. We show that the performance of ML for the prediction of AMR based on MALDI-TOF data is good (AUROC ≥ 0.8). However, the ML models need to be trained on local data and retrained regularly to maintain a good performance.

The LIAISON PLEX Respiratory Flex Assay is a customizable syndromic molecular assay for the qualitative detection of nucleic acids from 14 viral and 5 bacterial respiratory pathogens in nasopharyngeal swabs (NPS). This study evaluated its clinical performance in comparison to established FDA-cleared and standard-of-care molecular diagnostic platforms. A total of 2,099 NPS specimens were prospectively and retrospectively collected. Positive Percent Agreement (PPA), Negative Percent Agreement (NPA), and diagnostic accuracy were calculated across 19 targets. The assay was benchmarked against SOC assays, including Cepheid Xpert Xpress CoV-2/Flu/RSV Plus, Abbott Alinity m Resp-4-Plex, and BioFire RP 2.1 panel. Agreement metrics, kappa coefficients, and discordance analysis were used to assess the comparative performance. For bacterial targets, PPA ranged from 92.3% to 100%, with NPA exceeding 99%, and diagnostic accuracy above 99.7%. Viral targets showed PPA from 90.3% to 100% and NPA from 95.8% to 100%. Adenovirus, Influenza A, and Influenza B achieved 100% PPA. RSV and SARS-CoV-2 demonstrated diagnostic accuracies of 99.7% and 99.0%, respectively. Agreement with SOC assays was high (PPA up to 97.1%; kappa 0.81-0.97). Discordance analyses identified differences in pathogen detection, with the Respiratory Flex Assay detecting analytes missed by SOC assays. The LIAISON PLEX Respiratory Flex Assay demonstrated high accuracy, reliability, and strong diagnostic agreement with SOC assays. Its robust performance across respiratory pathogens supports its use as a comprehensive diagnostic tool for respiratory infection management.

Importance: Fast and accurate detection of respiratory pathogens helps guide treatment, lower healthcare costs, and support disease monitoring. The LIAISON PLEX Respiratory Flex Assay was evaluated for respiratory pathogen detection by comparing its performance to FDA-cleared molecular respiratory pathogen detection methods, PCR followed by bi-directional sequencing (PCR/BDS) for bacterial pathogens, and standard-of-care (SOC) molecular respiratory assays, including targeted and multiplex syndromic PCR panels. The study assessed its ability to identify pathogens associated with respiratory tract infections, measure agreement with SOC assays, and determine its accuracy in clinical settings. The findings provide data on the assay's diagnostic performance, testing flexibility, and applicability in laboratory workflows.

Invasive fungal infections (IFIs), including aspergillosis and mucormycosis, are serious complications in cancer patients. Reliable detection of etiologic agents is challenging but important for optimal patient management. In a prospective multicenter study, we compared fungal detection by culture, specific and unspecific qPCRs, and fluorescence in situ hybridization (FISH) targeting Aspergillus and Mucorales in bronchoalveolar lavage fluid (BALF) and serum of adult cancer patients with suspected fungal pneumonia. In subgroups of patients, fungal DNA was amplified from serum. We evaluated 210 IFI episodes (proven: 3, probable: 72, possible: 107, unclassifiable: 28). Broad-range fungal PCR from BALF was terminated early due to frequent amplification of colonizing yeasts. Specific qPCR assays targeting molds (Aspergillus, Mucorales) were superior for mold detection (26%) compared to FISH (15%) and culture (8%). Detection of fungi by FISH predicted subsequent fungal culture positivity. In proven/probable IFI episodes, detection of Aspergillus DNA was more likely in BALF than in serum (35/75 [47%] vs 11/66 [17%]; P = 0.0002) in contrast to Mucorales DNA (7/75 [9%] vs 5/66 [8%]; P = 0.73). Mucorales DNA was detected together with Aspergillus DNA in 6 of 7 BALF samples but not in serum. Specific qPCRs targeting Aspergillus and Mucorales from BALF are the most sensitive means to identify molds in adult cancer patients with suspected fungal pneumonia. BALF qPCRs suggest frequent fungal coinfection, while viruses were rarely detected. Fungal detection by FISH may predict subsequent positive fungal cultures.IMPORTANCEMold pneumonia is a serious complication in cancer patients. Reliable detection of etiologic agents is critical for patient care, but optimal testing strategies are undefined. We performed a prospective study comparing molecular tests (specific and unspecific qPCR and FISH) and culture on bronchoalveolar lavage fluid (BALF) and serum, focusing on aspergillosis and mucormycosis to gain insights into mold detection in high-risk patients. We demonstrate that FISH visualizes fungal elements in BALF, predominantly conidia, suggesting recent fungal exposure or failure to clear inhaled conidia at the time of diagnostic testing. We find that specific qPCRs from BALF are the most sensitive method to detect Aspergillus and Mucorales, superior to broad-range qPCR, culture, and testing of serum. Importantly, Mucorales DNA is mostly co-detected with Aspergillus, suggesting co-infections. Although DNA detection in serum is more likely in mucormycosis than in aspergillosis, sole serum testing may miss mucormycosis, precluding optimal patient care.

The resurgence of whooping cough in regions utilizing acellular pertussis vaccines underscores emerging public health challenges. Here, we characterized 178 Bordetella pertussis isolates collected from patients across all age groups in Shanghai (2018-2024) to assess genomic evolution and antibiotic susceptibility. Macrolide resistance to erythromycin, azithromycin, and clarithromycin escalated from ≤50% (pre-2020) to nearly 100% (post-2020), mechanistically linked to the 23S rRNA A2047G mutation. Genome-based analysis identified a genotype MT28-ptxP3-MRBP rapidly dominated post-2020, exhibiting significantly higher prevalence in adults than in other age groups. Phylogenetic analysis of 178 Shanghai and 1,596 global genomes revealed two major lineages corresponding to ptxP1 and ptxP3 alleles. MT28-ptxP3-MRBP cluster was identified in France, Japan, and the United States in 2024, indicating potential cross-border transmission. These findings advocate for integrated surveillance spanning all ages and international borders to contain the global spread of macrolide-resistant B. pertussis.

Importance: In recent years, despite high coverage of acellular pertussis vaccines in China, pertussis cases have increased substantially. Drawing on 178 Bordetella pertussis isolates obtained through age-inclusive active surveillance in Shanghai (2018-2024), we found that macrolide resistance rose from ≤50% before 2020 to nearly 100% thereafter, with all resistant isolates harboring the 23S rRNA A2047G mutation. A resistant MT28-ptxP3 lineage became dominant after 2020 (61.7%) and was disproportionately represented among older age groups; the primary affected population shifted from children ≤36 months toward those aged 37 months to 18 years. Incorporating NCBI public genome data, we further observed that this resistant lineage is not confined locally, suggesting a risk of cross-border spread. These findings provide an early warning of the expansion of macrolide-resistant pertussis and underscore the need for age-inclusive, cross-regional genomic surveillance and re-evaluation of diagnostic workflows, antimicrobial stewardship, and immunization strategies.

Diagnosing pulmonary tuberculosis (TB) and monitoring treatment remain challenging. New tools such as the PATHFAST TB LAM assay (PHC Corporation, formerly LSI Medience Corporation, Tokyo, Japan; distributed by BioSynex, France; PF-LAM) may complement microscopy, culture, and NAAT. PF-LAM is an immunoassay quantifying lipoarabinomannan (LAM), a mycobacterial cell wall component, in sputum within 1 hour using an automated chemiluminescent reader. Diagnostic performance was first assessed on 100 sputum samples: 40 culture-positive for Mycobacterium tuberculosis complex (MTBC), 40 culture-positive for nontuberculous mycobacteria (NTM), and 20 culture-negative for both. We then tested 61 longitudinal sputum samples from 19 pulmonary TB patients under treatment. Four additional samples from one patient with NTM pulmonary disease (NTM-PD) were also tested. PF-LAM showed 75% sensitivity for MTBC detection, with a strong correlation between LAM concentration and culture time-to-positivity (Spearman ρ = 0.915, P < 0.0001). Specificity was 95% on culture-negative specimens. The test was also positive for 26/40 (65%) NTM-culture-positive samples. Notably, 19 of these 26 samples were obtained from NTM-PD patients, yielding 73% sensitivity for NTM-PD detection. The assay's potential for treatment monitoring was demonstrated by significant negative correlations between LAM concentration and (a) treatment duration (ρ=-0.434, P = 0.0012) and (b) time to positive culture (ρ=-0.665, P < 0.0001). PF-LAM is a rapid and easy-to-use test for diagnosing pulmonary TB. While NTM cross-reactivity reduces specificity, it may provide diagnostic value for NTM-PD. Results on monitoring TB treatment are promising as no test is currently available for this indication.

Importance: Effective monitoring of the treatment response is essential for successful tuberculosis (TB) management as prolonged therapies require accurate evaluation to prevent relapse, treatment failure, or drug resistance. This study highlights the diagnostic and treatment-monitoring potential of the PATHFAST TB LAM Ag assay, which quantifies lipoarabinomannan (LAM) concentrations in sputum samples and correlates with bacterial load. For the first time, we also demonstrate the assay's applicability for detecting and monitoring nontuberculous mycobacterial (NTM) pulmonary diseases, which are increasingly prevalent in industrialized countries. The semi-automated, rapid format (<17 minutes) of the PATHFAST TB LAM Ag assay provides a simple and reliable approach for assessing bacillary load during treatment, representing a promising tool for improving patient management and diagnostic efficiency in both TB and NTM-PD.