Journal of Clinical Microbiology

BackgroundLower respiratory tract infections (LRTIs) remain diagnostically challenging when culture and molecular assays are negative or delayed. We evaluated ONETest Pathogenome (OT), an automated hybrid-capture metagenomic assay with core-genome enrichment probes, for direct pathogen detection in bronchoalveolar lavage (BAL). MethodsAnalytical performance (LoD, precision, continuity) was assessed using whole-cell spike-ins into culture-negative BAL fluid. Technical performance was assessed in 119 specimens profiled by OT and whole-metagenome shotgun sequencing (WmGS, cohort 1). Clinical accuracy was evaluated in 360 specimens (cohort 2) benchmarked against routine bacterial and acid-fast bacillus (AFB) culture. Laboratory-developed test (LDT) validation included 43 specimens (cohort 3) benchmarked to bacterial and AFB culture. ResultsOT uses 6.2 million probes covering core genomes across 50 microbial families (>250 respiratory pathogens). In BAL specimens, OT increased normalized on-target microbial abundance 26-fold versus that of WmGS while preserving within-sample microbial diversity. In cohort 2, OT achieved species-level sensitivity of 80% and specificity of 99% across culture-confirmed isolates and detected [&ge;]1 culture-confirmed organism in 100/115 culture-positive specimens (87%), while applying species-specific background baselines to mitigate overcalling. Additive yield was 21% (76/360), with 7.5% (27/360) of specimens having [&ge;]1 additional finding supported by orthogonal testing. In LDT validation, OT identified [&ge;]1 culture-confirmed organism in 34/40 culture-positive specimens (85%) with one OT-positive/culture-negative specimen. ConclusionsOT is an assay with a turnaround time <24 h complementary to culture that improves pathogen detection and expands microbiologic findings through additional detections and co-detections, including slow-growing organisms that may require prolonged incubation by conventional methods.

BackgroundMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is pivotal in clinical microbiology. The VITEK MS Research Use Only (RUO) database offers broader species coverage, yet its clinical adoption is hindered by insufficient performance validation against the approved in vitro diagnostic (IVD) database and inefficient manual operational workflows. ObjectiveThis two-phase study first aimed to develop and evaluate an automated integrated workflow to enhance laboratory efficiency and diagnostic capability. MethodsThe RUO databases two-tier identification architecture was utilized and in-house automated relay software was developed to parse IVD results and fully automate RUO reanalysis. Phase 1 (Mar 2021-Jun 2022) involved parallel manual testing of 2,432 isolates with both databases to analyze concordance and supplementary performance. Phase 2 (Jul-Nov 2022) prospectively incorporated 3,954 isolates to implement and assess the "IVD screening - automated RUO reanalysis" workflow. ResultsPhase 1 demonstrated high RUO-IVD concordance (95.7% species/genus agreement). The RUO database correctly identified 98.9% of isolates and provided valid supplementary identification for 84.4% (108/128) of IVD-failed cases, with Tier 2 contributing 28.9%. Phase 2 revealed that the integrated workflow increased the overall identification rate from 95.5% to 98.7%, with Tier 2 contributing an additional 14.5%. The automated software reduced reanalysis turnaround time by > 75%, saving consumables and labor. ConclusionThe VITEK MS RUO database is a reliable and complementary tool to the IVD database. Integration with automated software creates an efficient, compliant clinical workflow, providing a practical model to enhance pathogen identification for infectious disease management. IMPORTANCEThe present study bridges the validation-to-application gap for the VITEK MS RUO database. We confirm its high concordance (95.7%) and complementary value to the IVD database, quantify the impact of manual workflow inefficiency and introduce an automated software solution. The strategy highlights the key role of Reference Spectra (Tier 2) in expanding coverage and simultaneously improves diagnostic efficacy ([~]99% ID rate), operational efficiency (> 75% time saved) and cost-effectiveness, offering a practical model to accelerate pathogen reporting and to guide therapy.

To evaluate the diagnostic performance of clinical shotgun metagenomic sequencing (SMg) for detecting medically relevant fungi and parasites compared with standard of care (SoC), and to define read-based thresholds for interpretation, we retrospectively analyzed 198 clinical samples from 187 patients across four university hospitals (2018-2022): blood (n=37), faeces (n=63), respiratory fluids (n=54), other biological fluids (n=24), and tissue biopsies (n=20). Total nucleic acids were sequenced ([&ge;]10 million reads per library) and processed with MetaMIC v2.2.1. Data were normalized as reads per million (RPM). Receiver operating characteristic analyses were used to derive optimal RPM thresholds by sample type. SoC identified microorganisms in 152/198 samples (76.8%). All 46 SoC-negative samples were also negative by SMg. At the genus level, SoC identified 187 taxa and SMg 175. Of these, 147 (78.6%) were detected by both methods, 40 (21.4%) by SoC only, and 28 (14.9%) by SMg only. The overall genus-level F1-score was 0.84. Quantification cycle (Cq) values (n=57) correlated inversely with RPM (p<0.001), and no false negatives occurred with Cq<28.6. Optimal thresholds were 0.06 RPM for faeces (AUC 0.89), 0.07 for respiratory fluids (AUC 0.93; sensitivity 88.9%, specificity 90.7%), 0.09 for blood (AUC 0.99), 0.19 for other fluids (AUC 0.94), and 0.57 for biopsies (AUC 0.89). A global threshold of 0.06 RPM yielded an AUC of 0.92 (sensitivity 88.9%, specificity 88.5%). A pragmatic uniform 0.1 RPM threshold maintained performance, while sample-type specific thresholds further improved accuracy, supporting standardized implementation of clinical metagenomics for fungal and parasitic diagnostics.

Illumina sequencing of primary MGIT cultures is an established workflow in several reference mycobacteriology laboratories. Oxford Nanopore Technologies (ONT) provides real-time genetic sequencing yielding long reads which help resolve repetitive genomes and is being explored for in-house implementation within diagnostic laboratories. However, low DNA yields from primary MGIT cultures frequently limit the application of ONT workflows, due to high minimum DNA input requirements for library preparation. We evaluated a modified ONT workflow combining rapid, semi-automated DNA extraction from MGIT cultures with PCR-based whole-genome amplification, and compared its performance with Illumina sequencing for species identification and Mycobacterium tuberculosis complex (MTBC) single-nucleotide polymorphism (SNP) detection. A platformagnostic analysis pipeline enabled consistent human read removal, taxonomic assignment, and MTBC genomic characterisation. ONT sequencing data was subsampled at 1 h, 6 h, and 72 h to determine the earliest time point for reliable species identification. The concordance between sequencing platforms of species classification and MTBC lineage assignment was 95%. SNP agreement was high, with a mean of 1.0 and a median of 0 SNP differences between sequencing platforms after masking. These findings demonstrate the feasibility of PCR-amplified ONT sequencing as a reliable alternative for routine genomic characterisation of MGIT cultures. IMPORTANCERapid genomic characterisation of mycobacteria from primary MGIT cultures is valuable for timely and accurate clinical diagnosis. Although Illumina sequencing provides high sequence accuracy, its longer turnaround time and workflow complexity limit the rapid delivery of actionable results. Oxford Nanopore Technologies (ONT) sequencing enables continuous data generation and analysis, allowing real-time species identification and genomic characterisation. However, low DNA yield from primary MGIT cultures has limited the reliable application of ONT sequencing using standard extraction and PCR-free rapid library preparation methods. This study shows that combining semi-automated DNA extraction with PCR-based wholegenome amplification substantially improves ONT sequencing performance from primary MGIT cultures. The resulting increase in data yield enables more samples to be multiplexed and shorter sequencing run times while retaining comprehensive diagnostic information from a single whole-genome sequencing assay. Together, these improvements enable the practical implementation of ONT sequencing for routine mycobacterial diagnostics and may reduce both turnaround time and sequencing costs in clinical laboratories.

Bacillus paranthracis was formally defined as a species in 2017, after decades of carrying the name "emetic B. cereus" based on cereulide production and clustering within B. cereus sensu lato phylogenetic group III. Commonly associated with foodborne intoxication, reports rarely link B. paranthracis to non-foodborne clinical illness. As such, the new taxonomy and close resemblance of the name to the biothreat pathogen Bacillus anthracis cause confusion in diagnostic and public health settings. To address this issue, B. paranthracis clinical strains (n=20) from the CDC collection were tested with microbiological methods used for identification of B. anthracis and antimicrobial susceptibility testing. Some B. paranthracis phenotypes were similar to B. anthracis, however others were inconsistent across strains. Like B. anthracis: 3 strains tested capsule positive, 5 were non-hemolytic on blood agar, and 9 non-motile. All B. paranthracis strains were resistant to gamma phage lysis, which differentiated them from B. anthracis. Treatment regimens for B. paranthracis infections are not well established, as antimicrobial therapy is not indicated for emetic intoxication caused by B. paranthracis. Notably, six B. paranthracis strains had elevated minimal inhibitory concentrations to anthrax-recommended antibiotics: one for ciprofloxacin, three for doxycycline and tetracycline, and two for clindamycin. Rapid MinION sequencing was assessed for antimicrobial resistance detection prediction but had limited value when using PiMA v.1. These microbiological observations and susceptibility profiles of B. paranthracis expand our understanding of this pathogen, strengthening our ability to differentiate this bacterium from B. anthracis to improve diagnosis and patient outcomes. IMPORTANCEThis study describes in vitro characterization of 20 archived clinical strains of B. paranthracis, an opportunistic pathogen identified more frequently in recent reports. Our findings highlight phenotypic differences and similarities between B. paranthracis and B. anthracis using standard microbiological methods and drug susceptibility profiling. We also assess a rapid B. anthracis specific MinION long read genome sequencing workflow with B. paranthracis. This report highlights the overlapping morphological features shared by B. paranthracis and B. anthracis to improve future laboratory diagnosis and strengthen anthrax preparedness. This article will effectively reach an audience of public health professionals and microbiologists strengthening anthrax preparedness.

Respiratory syncytial virus (RSV), an approximately 15.2 kb negative sense RNA virus, causes acute respiratory infections in infants and older adults. Its two subtypes, RSV/A and RSV/B, evolve rapidly, making ongoing monitoring of circulating strains essential. The Georgia Public Health Laboratory (GPHL) developed and evaluated an amplicon-based whole-genome sequencing (WGS) assay for RSV surveillance. A total of 214 deidentified remnant clinical specimens (102 RSV/A; 112 RSV/B) with RT PCR Ct values <31 were included. RSV genomes were amplified using ARTIC style and custom primer sets, with the ARTIC set showing superior performance. Libraries were prepared using a modified Illumina COVIDSeq protocol, sequenced on NextSeq 1000/2000 instruments, and analyzed using the GPHL-RSV-PIPE bioinformatics pipeline. Among genomes meeting validation criteria, sequencing depth was slightly higher for RSV/A (median 53,433x; mean 51,076x) than RSV/B (median 49,699x; mean 46,945x), whereas genomic coverage was slightly lower for RSV/A (median 97.5%; mean 96.6%) than RSV/B (median 98.3%; mean 97.6%). Predominant lineages were A.D.3.1 and A.D.5.2 for RSV/A and B.D.E.1 for RSV/B. For RSV/A, the assay showed 92.8% accuracy, 96.2% sensitivity, 87.2% specificity, 92.6% positive predictive value, and 93.2% negative predictive value. Intra and inter run precision assessed using 16 and 53-57 genomes, respectively, showed nearly 100% consensus genome identity with 0 to 5 nucleotide differences. Specificity testing of 31 non-RSV specimens produced no false-positive detections. These results demonstrate that the ARTIC-based RSV WGS assay enables near real time surveillance and strengthens data driven public health responses to future outbreaks.

Clostridioides difficile (C. diff) is a leading cause of hospital-acquired infections with severity ranging from mild diarrhea to fulminant colitis and death. Current antigen tests lack adequate sensitivity and DNA-based nucleic acid amplification tests (DNA-NAATs) exhibit limited specificity for active infection, leading to either underdiagnosis or inappropriate treatment of colonized individuals. Unlike DNA, mRNA is expressed only by metabolically active bacteria and is rapidly hydrolyzed, providing natural advantages to distinguish active infection from colonization. In this study, we developed and evaluated a novel multiplexed reverse-transcriptase PCR assay (RNA-NAAT) targeting C. diff-specific sequences. No cross-reactivity was observed with other gastrointestinal pathogens, commensal enteric flora, or closely-related Clostridioides or Clostridium species. Toxin gene RNA expression was detected only in samples spiked with metabolically active C. diff at a limit of detection 30-to-50-fold less than current diagnostic methods. Sequential clinical samples (n=260) were collected in proprietary RNA-preservative solution from patients receiving standard of care C. diff diagnostic testing. All samples were evaluated with RNA-NAAT, Alere GDH/toxin EIA, Solana DNA-NAAT, and both forward- and reverse-2-Step Algorithms (2-SA). Samples yielding valid results on all platforms (n=239) with discordant test results (n=14) were adjudicated via toxigenic culture and blinded chart review by infectious disease physicians. RNA-NAAT outperformed all comparator test strategies, simultaneously exhibiting higher sensitivity and specificity, including a higher specificity for active infection than the specific toxin EIA (99.5% vs 98.2%) and a higher sensitivity for organism identification than the sensitive DNA-NAAT (100% vs 88.2%), with significantly reduced false positive test results (1 vs 7). One Sentence SummaryA novel RNA diagnostic distinguishes clinically-relevant C. difficile infection from toxigenic carrier states, improving sensitivity and specificity.

BackgroundShort-read genetic sequencing technologies (mainly Illumina) have been extensively used for around a decade for Mycobacterium tuberculosis complex (MTBC) outbreak analysis and genomic drug susceptibility testing (gDST) with the result that Illumina has become the de facto gold standard. Long-read sequencing, as exemplified by Oxford Nanopore Technologies (ONT), offer the prospect of faster, simpler, and portable sequencing. In this work, we carry out the largest to date comparison of how well Illumina and ONT technologies sequence MTBC samples, making use of R10.4 ONT flowcells, updated basecalling models and deep-learning variant calling. MethodsA total of 508 samples were sequenced using both short and long-read platforms. All samples originated from South Africa or Vietnam and were over-selected for drug resistance and also included several local outbreaks and a range of lineages. The South African and Vietnamese samples had already been Illumina sequenced. Samples with [&ge;]50 read depth by Illumina were selected for sequencing by ONT using one of the GridION or PromethION platforms. Bioinformatics processing was done using a modified online cloud platform which included reference-based variant calling, catalogue-based gDST and identified related samples via SNP counting to inform outbreak detection. The lineages and gDST predictions obtained by short-and long-sequencing were compared for all samples as were all putative clusters identified via SNP counting. For convenience Illumina was used as the reference method. FindingsOf the 508 samples, 425 (83.7%) had sufficient read depths to permit comparison between the two sequencing technologies. The assigned lineages were identical for 407/425 (95.8%) samples and all discordances were due to mixed lineages being identified by one technology. Evidence of non-tuberculous mycobacterium (NTM) subpopulations were found in nine samples. Using Illumina as the reference method, the very major error (VME) rate of ONT for predicting resistance to all 15 drugs is 1.0% (0.6-1.5%) whilst the major error (ME) rate is 1.7% (1.3-2.2%) with an unclassified rate of 6.9% (6.3-7.5%). This is below the thresholds specified by the CLSI. Considering each of the 15 drugs individually they had VME and ME point estimates below [&le;]3% in 29/30 cases; and most 25/30 below [&le;]1.5%. Filtering out all samples containing mixtures left 382 isolates. By appropriate masking of the reference genome we were able to obtain a mean SNP distance between the two platforms of 0.13 (median of zero) for the same sample and for 376/382 samples (98.4%, CI:96.6-99.4%) the difference was [&le;]1 SNPs. The high concordance in SNP identification ensured that few differences in the 43 putative clusters among 172 isolates were observed. InterpretationThe differences between the two sequencing platforms for the key clinical outputs is so small that it is now within the tolerances set by regulatory agencies. Provided the sequencing is of sufficient quality, we have therefore reached a threshold whereby sequencing data from long-and short-read platforms can be aggregated. This will enable large scale analyses by national and international public health agencies whilst allowing the MTBC community to take advantage of the portability and speed of long-read sequencing. FundingThe NIHR Health Protection Research Unit: Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford (NIHR200915), a partnership between the UK Health Security Agency (UKHSA) and the University of Oxford, the National Institute for Health and Care Research Biomedical Research Centre: Oxford (BRC) and the Ellison Institute of Technology, Oxford Ltd. The CRyPTIC project was funded by Wellcome [214560/Z/18/Z], a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z); and the Bill & Melinda Gates Foundation Trust (OPP1133541). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe conducted a PubMed Central full text search for "tuberculosis" AND ("drug resistance prediction" OR "drug susceptibility prediction") AND ("genome" OR "genomic" OR "geno-typic") AND ("ont" OR "oxford nanopore") between 2022 and 2026 (conducted 1 April 2026). This returned 62 papers; of which, six used both Illumina and ONT sequencing. One of these, published in 2023, directly compared the performance of the two platforms on 151 M. tuberculosis isolates oversampled for resistance. The investigation yielded comparative results for the earlier generation ONT flow cell (R9{middle dot}4{middle dot}1) and base-caller (guppy version 5{middle dot}0{middle dot}16). Another, published in 2026, investigated a targeted next-generation sequencing panel of 20 amplicons using ONT sequencing on R10.4.1 flow cells with guppy 6{middle dot}4{middle dot}6. They compared the results on 71 isolates against phenotypic data and Illumina whole genome sequencing (for 53 isolates) but had low rates of resistance, with all drugs but isoniazid being limited to under five resistant isolates. Two other small studies (10 and 13 samples, respectively) conducted feasibility studies comparing ONT with Illumina, also using earlier generation flow cells and base-calling technology from ONT. Two further studies compared Illumina with ONT for direct sputum sequencing and did not investigate the comparative performance of the two platforms for variant call accuracy, resistance prediction, and outbreak detection. Illumina sequencing technology is widely used for genomic sequence analysis in research, and clinical and public health contexts. Consequently, it has become the de facto reference standard for generating whole genome sequence data. Whilst previous studies established the promise and limitations of long-read (ONT) sequencing as an alternative to short-read sequencing (mainly Illumina), the enhanced performance arising from newer flowcells (e.g. R10.4.1), V14 chemistry, and the latest basecallers (dorado v4.3.0/5.0.0) has not been analysed. Neither has any ONT analysis incorporating the new deep-learning variant callers been evaluated in a large-scale comparative study. Thus, it is currently unclear whether data generated by either platform can be used safely in aggregated analyses for research and clinical or public health service. Added value of this studyWe compared how well short-(Illumina) and long-read (ONT) sequencing platforms identify the genetic variants in M. tuberculosis, predict antituberculous drug resistance and recog-nise outbreaks. The long-reads were generated using the latest generation ONT R10.4.1 flows cells, V14 chemistry, super high accuracy basecalling (dorado v4.3.0/5.0.0) and a bioinformatics analysis pipeline built using the Clair3 deep-learning based variant caller. A total of 508 clinical samples were sequenced using both technologies, substantially more than previous studies. The sampling frame was much larger than previously investigations and included a large proportion of isolates with resistance to first-line and second-line antibiotics as well as bedaquiline. Thus, providing greater statistical power for resistance prediction than before. In particular, the inclusion of bedaquiline resistance provided evidence useful for predicting resistance to this newly deployed drug for treating multi-drug resistant (MDR) TB. We find that the differences between technologies are small meaning that either technology can be used alone safely, and services using both technologies can confidently aggregate the data for analysis. Implications of all the available evidenceThis will be a benefit to local, regional and international organisations, particularly public health agencies, which often have a mix of the two main sequencing technologies for characterising TB whole genome sequences. It also opens up the sequence based diagnostic market to greater competition, particularly if the observed performance can be replicated for other pathogen species.

Abstract Background Timely diagnosis of tuberculosis and drug resistance remains a cornerstone of effective disease control. Multiplex open molecular platforms capable of simultaneously detecting Mycobacterium tuberculosis complex (MTBc), non-tuberculous mycobacteria (NTM), and resistance to first-line anti-tuberculosis drugs could streamline diagnostic pathways. Methods We conducted a laboratory-based evaluation of two multiplex real-time PCR assays (MTBc/NTM R-Gene and MTB-RIF/INH R-Gene) using 300 well-characterized samples, including 150 MTBc-positive culture isolates (including rifampicin-resistant, isoniazid-resistant, and drug-susceptible strains) and 150 MTBc-negative samples (50 NTM isolates and 100 mycobacteria-negative specimens). Composite reference standards included culture, MPT64 antigen testing, and line probe assay corroborated by phenotypic drug susceptibility testing for resistance profiling, with NTM speciation performed using a dedicated line probe assay. DNA extraction was performed using the QIAamp DNA Mini Kit (QIAGEN, Germany), followed by amplification on a real-time PCR platform according to manufacturer instructions. The diagnostic performance was assessed against composite reference standards. Results The analytical performance for detecting MTBc demonstrated 100% sensitivity and specificity (150/150). NTM detection showed 70.0% sensitivity (35/50) and a specificity of 100%, highlighting limitations in coverage of NTM species. Rifampicin resistance was detected with a sensitivity of 96.0% (48/50) and specificity of 100%, whereas isoniazid resistance detection was 100% sensitive and specific (50/50). Agreement with established reference standards was high ({kappa}=0.76-1.00) within this analytical context. Interpretation This analytical validation demonstrates that multiplex open real-time PCR assays can accurately and simultaneously detect MTBc, NTM, and rifampicin and isoniazid resistance using culture isolates. While these platforms offer potential advantages in flexibility and expanded resistance profiling, additional studies on clinical diagnostic accuracy, cost-effectiveness analyses, and operational feasibility are required to determine their practical utility and programmatic impact in high-burden settings

BackgroundClinical metagenomics (CMg) offers high-throughput respiratory pathogen detection with a wider range than targeted, probe-dependent diagnostics. Sequencing cost and the challenges of high host biomass in non-invasive samples are barriers to the use of CMg in high-throughput respiratory pathogen detection. MethodsWe optimised a long-read sequencing workflow to detect RNA viruses in nasopharyngeal swabs, employing pathogen enrichment and ONT sequencing. As a pre-requisite for agnostic pathogen detection, we first derived quality control (QC) criteria and diagnostic thresholds against a gold-standard comprising 23 pathogen targets detected by routine multiplex PCR. We validated this workflow using 344 prospectively collected upper respiratory tract samples submitted for routine testing. FindingsUsing pre-defined QC and positivity criteria, the workflows sensitivity versus PCR was 51% (95%CI: 45%-57%) (133/260 positive targets detected) (ranging from 19%-85% across pathogens with >20 gold-standard detections), and specificity 99.8% (95%CI: 99.6%-99.9%) (3836/3845 negative targets not detected). Sensitivity improved to 58% using post-hoc optimised thresholds, 61% only considering RNA pathogens, 70% excluding rhinovirus/enterovirus and 83% excluding samples with qPCR Ct values [&ge;]35. Read crossover from multiplex sequencing contributed most (7/9) false-positives: only 2 plausible additional pathogens were identified (rhinovirus and coronavirus OC43). 41 respiratory syncytial virus (RSV), 13 influenza A and 10 rhinovirus/enterovirus were successfully sub-typed by sequencing. Multiplexed nanopore sequencing costs were {pound}112/sample. InterpretationAlthough CMg has substantial diagnostic potential, this validation study demonstrates the technical limitations of current metagenomic sequencing methods applied to viral detection in upper respiratory tract samples with high host and low pathogen biomass. Its greater sensitivity at higher viral loads demonstrates the importance of identifying the most appropriate use cases to maximise its utility and value. FundingNational Institute for Health and Care Research Oxford Biomedical Research Centre. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSClinical metagenomics (CMg) provides the potential for rapid respiratory pathogen detection with a wider range than targeted, probe-dependent diagnostics. Searching PubMed for studies published between Jan 1 2018 and December 1 2025 using the terms respiratory tract infection AND metagenomics AND diagnosis, with no language restrictions yielded 734 items. We identified 15 clinical studies assessing the diagnostic performance of a metagenomic workflow for respiratory samples. Only 3 of these included upper respiratory tract samples (nasopharyngeal swabs); the remaining studies exclusively investigated invasive samples from the lower respiratory tract (bronchioalveolar lavage fluid). One of the three relevant studies assessed detection of viral pathogens in 83 specimens from critical care patients as part of pan-microbial nanopore sequencing metagenomic assay; only 2 samples included were nasopharyngeal samples. The second validated a high-depth short-read CMg workflow in 191 samples (85% nasopharyngeal), reporting 93.6% sensitivity and 98.8% specificity across eight respiratory pathogens detected by respiratory PCR. This workflow required substantial equipment and sequencing costs. A third study validated a nanopore sequencing CMg workflow, with lower laboratory footprint and sequencing costs than the second study. In 359 nasopharyngeal samples, they reported 61% sensitivity and 100% specificity against four respiratory viral targets detected by PCR. The costs of CMg mean that routine deployment as a high-throughput test with broad use will require demonstrating good performance across a range of common respiratory pathogens (such as can be assayed with commercially available extended multiplex PCR testing) and in upper respiratory tract samples. Added value of this studyThis prospective study is the first to evaluate nanopore sequencing for detecting a broad range of common respiratory viruses in nasopharyngeal samples. We validated a CMg workflow employing a modernised SISPA step for viral amplification, in 344 prospectively collected non-invasive samples, from which 19 different respiratory pathogens were detected by routine PCR testing. Using pre-defined bioinformatic thresholds overall sensitivity was 51% compared with PCR. This could be improved to 83% by limiting analysis to RNA viruses with Ct <35 and using post-hoc exploratory bioinformatic criteria. Sequencing costs were 45% lower than short-read sequencing. Implications of all the available evidenceOur results demonstrate rigorous bioinformatic thresholds are essential in multiplexed CMg sequencing to reduce false-positive detections, a particular danger with imperfect barcode de-multiplexing. However these thresholds impair true-positive detection in samples with a high ratio of host-to-pathogen biomass. Further research should focus on identifying in which samples and clinical settings CMg can offer greater value in patient care.

Conventional diagnostic methods (CDM) for Legionella preferentially detect L. pneumophila and frequently fail to identify non-pneumophila species (NPLS), obscuring the full clinical spectrum of infection and limiting surveillance accuracy. We analyzed plasma microbial cell-free DNA (mcfDNA) sequencing detections of Legionella spp. from a large clinical cohort tested between 2018 and 2024 and compared species distributions with culture and PCR confirmed cases reported in the most recent national surveillance datasets (2018-2021). To contextualize the clinical impact, we reviewed published reports in which mcfDNA sequencing was used to diagnose legionellosis (2021-2025) and evaluated real-world performance data from a hospital contributing 8.9% of detections within the cohort (Hospital A). mcfDNA sequencing identified proportionally fewer L. pneumophila, more NPLS, and fewer unresolved species than the CDC reports (all p<0.001). Among 15 publications describing 19 U.S. patients, 74% were immunocompromised and 79% had NPLS infections. Concordance between mcfDNA and CDM occurred in 31.6% of cases. At Hospital A with 36 detections, diagnosis was established by CDM alone in none, by both CDM and mcfDNA in 23.5%, and by mcfDNA alone in 76.5%, yielding an additive diagnostic value of 56.8% These findings suggest that plasma mcfDNA sequencing may improve detection of NPLS particularly in high-risk or diagnostically challenging patients and provide complementary data for both clinical diagnosis and epidemiologic surveillance.

ObjectiveThe rapid availability of phenotypic antimicrobial susceptibility results is crucial for the timely detection of multidrug-resistant Gram-negative organisms and for guiding optimized treatment strategies. Recently, novel methods have been introduced that enable direct antimicrobial susceptibility testing (AST) from positive blood cultures. However, their performance has not yet been systematically compared in head-to-head evaluations. This study aimed to assess the analytical performance of two rapid AST approaches--the agar diffusion-based EUCAST rapid AST (RAST) method and the automated QuickMIC system--using a challenging collection of highly resistant Gram-negative organisms. MethodsA total of 101 Gram-negative bacteria (Escherichia coli, n = 24; Klebsiella pneumoniae, n = 22; Acinetobacter baumannii, n = 30; Pseudomonas aeruginosa, n = 25) were spiked into blood cultures and processed according to the respective AST workflows. Broth microdilution (BMD) was performed from pure cultures as the reference method. Time to result (TTR), categorical agreement (CA), and essential agreement (EA) with BMD were evaluated. Boruta analysis was applied to identify genetic determinants associated with AST errors. ResultsOverall TTR for QuickMIC was 3 h 44 min with a CA of 86.2%, an EA of 92.3 % for Enterobacteriaceae and 97.0 % for non-fermenters. Overall CA of RAST ranged from 90.7%-93.7% across reading time points. Overall, very major discrepancy rates were low (QuickMIC n=0.7%, RAST n=0.1%). Presence of NDM-5 and KPC was most frequently associated with errors for QuickMIC and EUCAST RAST, respectively. ConclusionsBoth rapid AST approaches yielded robust results in this diverse and highly resistant bacterial study population, directly from positive blood cultures, with a short turnaround time. These findings underscore the potential of rapid AST methods to facilitate timely optimization of antimicrobial therapy in bloodstream infections, even in the context of extensively drug-resistant pathogens. ImportanceAccurate antimicrobial susceptibility testing (AST) is essential for stewardship and effective therapy, especially as rising antimicrobial resistance increases the risk of empiric treatment failure. Traditional AST methods are limited by slow turnaround times, creating a need for rapid alternatives. This study evaluated the diagnostic accuracy of two rapid AST methods--EUCAST RAST and QuickMIC--using 101 genetically characterized, carbapenem-resistant Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii tested directly from positive blood cultures. Broth microdilution served as the reference. Both rapid assays provided results within 3.5-6 hours and demonstrated high categorical and essential agreement with few very major discrepancies. Incorrect results were more common in isolates harboring NDM-5 and KPC carbapenemases. Overall, the findings support EUCAST RAST and QuickMIC as reliable tools for challenging resistant pathogens and highlight their potential to enable earlier detection of carbapenem-resistant phenotypes and more timely initiation of appropriate, last-resort antimicrobial therapy.

1.Etiological diagnosis of lower respiratory tract infections (LRTIs) relies on sputum or bronchoalveolar lavage (BAL), which may be difficult to obtain or invasive. Exhaled breath aerosol (XBA) sampling offers a non-invasive alternative for pathogen detection. We evaluated the performance of the AveloMask, a face mask-based device designed to capture XBAs for molecular testing. In this prospective paired-sample study, hospitalized adults with pneumonia at three hospitals in Switzerland and Georgia provided an XBA sample using the AveloMask and a lower respiratory tract (LRT) specimen (sputum or BAL). XBA samples were analyzed by multiplex PCR using the Roche LightMix(R) panel and LRT samples were tested using the BioFire(R) FilmArray(R) Pneumonia Panel. Concordance between XBA and LRT samples was assessed using positive percent agreement (PPA), negative percent agreement (NPA), and overall percent agreement (OPA). Ninety-three participants were enrolled and 63 participants provided paired samples. AveloMask sampling identified the dominant pathogen (lowest Ct value in the LRT sample) in 40/47 LRT-positive cases (85.1%). Across all targets, PPA was 61% (95%CI, 50-72%), NPA was 100% (95%CI, 99-100%), and OPA was 95% (95% CI, 92-96%). PPA was higher for bacteria than for viruses and lower PPA was largely driven by reduced detection of low-abundance or co-infecting pathogens. In a subset analysis, AveloMask results showed substantial overlap with standard-of-care testing and could have supported antimicrobial de-escalation. Breath aerosol sampling using the AveloMask enabled non-invasive molecular detection of LRT pathogens in pneumonia cases and may complement conventional standard-of-care testing, particularly when sputum is unavailable.

Invasive fungal infections are a global threat; early diagnosis is critical for patient outcomes, but current diagnostic measures remain notoriously slow. Here we extend our multiplexed, hybridization-based rRNA-targeted strategy for rapid, sensitive pathogen identification, previously designed for diverse bacteria and Candida species, to identify diverse fungal pathogens. We created a set of 91 probes targeting 86 medically relevant fungal species, designed to recognize regions of differential conservation across taxonomic groupings, from class- to species-specific probes. We assessed assay performance across a Training Set of 93 clinical isolates spanning 32 species of common fungal pathogens across 18 genera, with Pearson correlations of probeset reactivity profiles (PSRPs) identifying the pathogen at the species, genus, and family level with 83%, 94%, and 95% accuracy, respectively, in a leave-one-out analysis. We developed a more sophisticated classifier on this Training Set, using taxonomic categories to select progressively more informative probes at each taxonomic level. After optimization, we assessed performance on an independent Validation Set of 54 clinical isolates spanning the same species as the Training Set, with 91%, 94%, and 98% at the species, genus, and family levels, respectively. We piloted our assay on formalin-fixed paraffin-embedded (FFPE) tissue, demonstrating rapid, culture-independent fungal identification from this high-value clinical sample type, often the sole specimen available. The assay requires <30 minutes hands-on time (or <65 minutes from FFPE tissue), returning results in <8 hours from cultured specimen or FFPE tissue to answer on an RNA detection platform available in clinical laboratories. ImportanceTimely identification of fungal pathogens is critical for patient outcomes. A multiplexed hybridization-based assay targeting rRNA enables accurate identification of >50 species of pathogenic fungi from crude lysates of cultured clinical isolates.

PurposeDiphtheria is caused by toxigenic strains of the Corynebacterium diphtheriae complex, mainly Corynebacterium diphtheriae and C. ulcerans. The diagnosis of diphtheria relies on detecting the diphtheria toxin (DT), for which Englers method of Eleks immunoprecipitation test is the gold standard. A recent optimization of Englers method was proposed by Melnikov and colleagues, showing higher sensitivity for C. ulcerans. The goal of our study was to test and adapt this optimized method, and to re-analyze apparent non-toxigenic tox gene bearing (NTTB) isolates from our collection. MethodsWe included 48 C. ulcerans, C. ramonii and C. diphtheriae isolates previously categorized as NTTB but for which no genetic explanation was found for the lack of DT expression. DT production was tested using Melnikovs method with further modifications made by us: i) increasing the antitoxin concentration; ii) using 5{degrees}C as the incubation temperature after 24h; and iii) modifying the layout of control and test strains on agar plates. Results35 of 38 C. ulcerans, 3 C. ramonii and 8 of 10 C. diphtheriae were found to be toxigenic. No genetic explanation was found regarding two non-toxigenic isolates (1 C. diphtheriae and 1 C. ulcerans), whereas for one C. diphtheriae, IS1132 was detected upstream of the tox gene. ConclusionOur modified implementation of Melnikovs Elek test improved our ability to detect diphtheria toxin production. Most isolates previously considered as NTTB but with no genetic explanation, were shown to be toxigenic using the novel method.

BackgroundMpox has spread to 35 countries in Africa, yet many face challenges achieving nationwide PCR-based testing due to cost and limited access in remote and rural areas. Point-of-care antigen-based rapid diagnostic tests (AgRDTs) may help improve diagnostic access. ObjectivesTo evaluate the diagnostic accuracy of five mpox AgRDTs manufactured by Beijing Hotgen Biotech (China), Contipharma (Belgium), Hangzhou Testsea Biotechnology (China), Guangdong Wesail Biotech (China), and NG Biotech (France). MethodsDiagnostic accuracy was assessed using 190 lesion swabs from suspected mpox cases in the Democratic Republic of the Congo, with results compared against the RADI FAST Mpox PCR assay (KH Medical, South Korea). Analytical sensitivity was evaluated using a clade Ib MPXV isolate from the WHO Biohub held by the Geneva University Hospitals, Switzerland. ResultsThe best-performing assay, the Monkeypox Virus Ag Test Kit (Guangdong Wesail Biotech), demonstrated a sensitivity of 77.3% (95% CI: 68.0-84.5) and specificity of 93.5% (95% CI: 86.6-97.0). The Hangzhou Testsea assay showed comparable performance (sensitivity 72.2%, specificity 93.5%). Beijing Hotgen and Contipharma assays exhibited moderate sensitivity (59.8% and 50.5%, respectively) with high specificity (96.8% and 95.7% respectively), while the NG Biotech assay showed the lowest sensitivity (39.2%) but similarly high specificity (96.8%). Analytical testing revealed no major differences across assays, though Guangdong Wesail demonstrated the highest analytical sensitivity, detecting clade Ib virus at a Ct of 28.3. ConclusionSeveral AgRDTs show high positive predictive values for mpox screening in high-prevalence settings, where positive test results may support confirmation but negative results cannot rule out infection. Further multicentre prospective studies are needed to define appropriate use cases as countries transition to sustainable mpox control. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAccess to decentralized mpox diagnostics remains limited in many African countries due to the cost, infrastructure, and turnaround time associated with PCR, particularly in remote settings. Antigen-based rapid diagnostic tests (AgRDTs) could expand access to point-of-care testing, but data supporting their clinical performance has been limited. We searched PubMed and medRxiv on Dec 31, 2025, using the following search string: (mpox OR monkeypox) AND (diagnostic* OR point of care OR lateral flow assay OR rapid antigen test OR AgRDT). Early evaluations of mpox AgRDTs reported very low sensitivity. A large prospective, multicentre field study in Uganda and the Democratic Republic of the Congo (DRC) evaluating a single mpox AgRDT for research use only using lesion swabs reported an overall sensitivity of 70.4%, with substantial variation by country (81.9% in Uganda vs 55.1% in DR Congo), age, and viral load, and specificity of 89.3%. Independent comparative evaluations of multiple commercially available AgRDTs with regulatory approval--particularly in clade I-endemic African settings--have been lacking. Added value of this studyThis study provides the first head-to-head clinical and analytical evaluation of five commercially available mpox AgRDTs using skin or mucosal lesion swab specimens from suspected cases in DRC. By assessing all assays against a molecular reference test under identical conditions and incorporating analytical testing with a clade Ib reference virus isolate, we demonstrate substantial variability in performance between manufacturers tests kits. Two assays achieved sensitivity against PCR of above 70% with moderate specificity (93.5%), comparable to or exceeding results reported in prior field studies, while others showed moderate to poor sensitivity. Analytical testing identified meaningful differences in detection limits, with the best-performing assay detecting clade Ib virus at viral loads corresponding to a Ct value of 28.3. These findings provide critical data to inform further field-based validation projects, assay selection and procurement decisions for use of such AgRDTs in endemic settings. Implications of all the available evidenceAcross studies, mpox AgRDTs consistently demonstrate high specificity but variable and often insufficient sensitivity to function as standalone diagnostic tools. Prior studies have provided evidence that sensitivity is highest for samples with Ct values 25 or lower, and the present comparative evaluation show that positive AgRDT results may be able to reliably confirm mpox infection in high-prevalence settings, whereas negative results cannot safely exclude disease. The heterogeneity in performance between assays underscores the need for field-based independent evaluations of most promising tests before their large-scale deployment, and cautions against treating AgRDTs as a uniform diagnostic test category. As countries transition from emergency response to sustainable mpox control, AgRDTs may have a complementary role in decentralized screening, outbreak confirmation, and triage, provided confirmatory PCR remains available. Further multi-centre prospective studies and continued assay optimization are essential to ensure antigen-based diagnostics can be used to meaningfully strengthen mpox surveillance, preparedness and outbreak response.

Antimicrobial resistance (AMR) presents a pressing need to ensure that the right antimicrobials are used to target the right microbes at the right time. Ideally, the appropriate antimicrobial is selected after patient samples have been cultured and assessed with antimicrobial sensitivity testing (AST). However, the time needed for culture-based diagnosis leads to immediate empirical treatment, often with broad-spectrum and/or high-tier antimicrobials. Direct nanopore metagenomic whole genome sequencing to identify pathogens and predict their antimicrobial resistance is a rapid and patient-side alternative. A limitation of this approach is potential inconsistencies in in silico predicted AMR phenotypes. Here, we benchmarked the current performance of in silico AMR prediction strategies for nanopore-generated long read data. Using nanopore data paired with AST phenotyping for 201 samples, we assessed the impact of basecalling mode, data volume, and assembly strategy, and compared the performance of eight in silico AMR prediction tools with seven AMR databases. We found that basecalling accuracy mode does not affect the overall accuracy of in silico AMR predictions, but assembly strategy and data volume both do. Prediction tools using the ResFinder database scored best for balanced accuracy (0.80 {+/-} 0.02 for both ResFinder and ABRicate), whilst DeepARG scored best for sensitivity (0.65 {+/-} 0.03). However, even the best performing in silico AMR prediction strategy missed some resistance identified by lab-based AST. In silico AMR prediction can therefore supplement lab-based AST, but cannot yet replace it. Impact statementAntimicrobial resistance (AMR) is threatening modern standards of human and veterinary healthcare. Rapid and patient-side diagnostic tests are needed to diagnose bacterial infections and allow clinicians to select effective antibiotics. Current tests based on bacterial cultures take several days, which may delay diagnosis and treatment, or lead to inappropriate "just in case" treatment while waiting for the results. In contrast, nanopore metagenomic whole genome sequencing can identify bacterial infections and predict which antibiotics will be effective in minutes to hours. However, the accuracy of these tests is uncertain. We therefore compared the performance of eight AMR prediction tools and seven databases of AMR determinants, using 201 bacterial samples with known antibiotic susceptibility and resistance. We found that the sensitivity (i.e. false negative rate), specificity (i.e. false positive rare) and overall accuracy of the tools and databases varied. In particular, even the best performing AMR prediction methods missed some AMR. Therefore, while these tools are useful for rapid and patient-side diagnosis and treatment decisions, they still have limitations and should be used alongside bacterial cultures and antibiotic sensitivity testing. Data summarySequencing data for the samples sequenced for this study are available at the NCBI under BioProject ID PRJNA1292816 (SRA accessions for all datasets used here are available in Supplementary Table S1). All commands and code used can be found at: https://github.com/nataliering/nanopore_AMR_tools/ The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

Campylobacter jejuni is a leading cause of foodborne gastroenteritis globally and is classified by the CDC as a serious public health threat due to increasing resistance to fluoroquinolones and macrolides. This study used whole-genome sequencing to characterize the virulence and antimicrobial resistance profiles of 2,783 clinical C. jejuni isolates collected from Minnesota residents from 2018 through 2021. More than 90% of the isolates had genes related to stress defense (rpoN and htrB), cytolethal distending toxin (cdtA, cdtB, and cdtC), and cell adhesion and invasion (ciaB, cadF, and flaC). A diverse array of antimicrobial resistance genes was detected, with beta-lactam resistance genes having a particularly high prevalence. The gyrA point mutation associated with quinolone resistance was present in 29% of isolates. To evaluate the correlation between genotypic and phenotypic antimicrobial resistance profiles, the antimicrobial susceptibility testing results from a subset of isolates were compared with genotypic resistance profiles. Results showed a strong overall correlation, particularly for tetracycline and quinolones, though 24 discrepancies were detected. In the majority of discrepancies (n=21), genomic antimicrobial resistance markers were absent in isolates that were phenotypically resistant, suggesting possible unknown resistance mechanisms or limitations in current sequencing methods. The remaining three discrepancies occurred in isolates that had the tet(O) resistance gene but were susceptible to tetracycline phenotypically. These findings highlight the value of whole genome sequencing in improving antimicrobial resistance surveillance and understanding virulence factors in C. jejuni, supporting its integration into routine monitoring practices to better manage and understand antimicrobial resistance in foodborne pathogens.

BackgroundStool-based molecular tests are a noninvasive option for pediatric tuberculosis (TB) diagnosis, but have lower sensitivity compared to sputum-based tests. Untargeted metagenomic sequencing (mNGS) on stool could improve sensitivity and identify new gene targets for molecular testing. MethodsWe performed shotgun mNGS on DNA isolated from stool samples of children undergoing assessment for pulmonary TB in Uganda. We defined the performance of mNGS to identify Mycobacterium tuberculosis (Mtb) against a microbiological reference standard (MRS, TB if sputum Xpert Ultra or culture positive) and a composite reference standard (TB if confirmed or unconfirmed TB). We also compared accuracy of mNGS against the stool-based Xpert Ultra test. Finally, we identified enriched genomic loci among Mtb classified reads. ResultsWe analyzed 176 stool samples of children with a median age of 3.6 years (IQR, 1-6 years). !"#$%&()*(+,-. ()*(&*%&$$/$$*&(01(234-(5$)(60&$$/*(78(9*1$%*9(as [&ge;] 1, 2, or 5 sequence fragments were 35.5% (95% CI 19%:;;<=.(>;?@<(AB>< : 45%), and 19.4% (13%-25%) respectively, and specificities 92.64% (87%-96%), 97% (93%-99%), and 99.3% (96%-100%). Stool Xpert Ultra had similar sensitivity (22.6%) to stool mNGS considering all samples tested. In a head-to-head comparison, stool mNGS had lower sensitivity than stool Xpert Ultra (38.5% vs. 53.8%, difference -15.3%, 95% CI 14-68 to 25-81). mNGS utilized rRNA, virulence proteins and membrane proteins not targeted in current PCR-based platforms. ConclusionsMetagenomic sequencing of stool DNA did not increase sensitivity of TB detection, but identified novel targets for molecular testing that may support development of more sensitive tests.

The Klebsiella pneumoniae species complex (KpSC) is a clinically important group of closely related pathogens associated with invasive infections. The complex comprises seven closely related members, which are often reported as K. pneumoniae, particularly in resource-limited settings. Accurate differentiation of KpSC members remains challenging because routine laboratory methods lack sufficient resolution, and approaches like mass spectrometry and whole genome sequencing (WGS) are not widely available. Consequently, the epidemiology and clinical significance of non-K. pneumoniae members of the KpSC remain underrecognized. We developed a conventional multiplex mismatch amplification mutation assay (MAMA) PCR targeting species- and subspecies-specific single-nucleotide polymorphisms in the housekeeping gene rpoB, with six primer sets for differentiation of common KpSC members. The assay was validated against 49 genomically characterized clinical isolates, after which 179 wastewater-derived isolates provisionally identified as Klebsiella spp. by standard microbiological methods were tested. Of these, 174 were assigned to specific KpSC members by the assay, while 5 produced inconclusive amplification patterns. A subset of 16 environmental isolates was selected for WGS, including four of the five inconclusive isolates. All environmental isolates with interpretable MAMA PCR patterns were concordant with WGS. The four inconclusive environmental isolates were identified as Enterobacter spp. Overall, comparison of MAMA PCR with WGS showed 100% sensitivity and 100% specificity for all tested targets, and the total cost was approximately US$1. This rpoB-based multiplex MAMA PCR provides a simple, accurate, and low-cost approach for differentiation of KpSC members in routine laboratories and may support improved identification and surveillance in resource-limited settings. ImportanceThe Klebsiella pneumoniae species complex (KpSC) has seven members but is often reported as a single organism in routine laboratories, masking clinically and epidemiologically important diversity. As a result, the contribution of non-K. pneumoniae KpSC members to human and environmental microbiology remains poorly defined, especially in low-resource settings. We developed a conventional multiplex mismatch amplification mutation assay (MAMA) PCR based on discriminatory rpoB single nucleotide polymorphisms for differentiation of common KpSC members using standard PCR and agarose gel electrophoresis. The assay demonstrated 100% sensitivity and 100% specificity against whole-genome sequencing and excluded non-Klebsiella environmental isolates initially identified as Klebsiella pneumoniae using standard microbiological procedures. With an estimated per-test cost of about US$1, this method offers an affordable and scalable option for laboratories seeking more accurate KpSC identification and improved surveillance.