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.

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.

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.

The Burkholderia cepacia complex (BCC) is comprised of 24 species of Gram-negative bacteria that cause opportunistic infections. While antimicrobial susceptibility testing (AST) has historically been used to guide treatment for BCC infections, recent work highlighting problems with AST for these organisms led the Clinical and Laboratory Sciences Institute (CLSI) to remove disk diffusion (DD) and minimal inhibitory concentration (MIC) breakpoints for BCC from its M100 standards document. Epidemiological cut-off values (ECVs) may be helpful to clinicians in the absence of breakpoints, as they may be used to determine whether an isolate has a wild-type or non-wild-type phenotype. Here we present an analysis of BCC ECVs for ceftazidime (CAZ), levofloxacin (LVX), meropenem (MEM), minocycline (MIN), and trimethoprim-sulfamethoxazole (TMP-SMX). ECVs were calculated using MIC data from 3 previous studies and 3 independent laboratories for 1,896 BCC isolates. ECVs were 16 g/ml for CAZ, 8 g/ml for LVX, 16 g/ml for MEM, and 8 g/ml for MIN. The ECV for TMP-SMX varied depending on the analysis from 2 g/ml, 8 g/ml, and 16 g/ml and therefore could not be reliably established. Challenges with establishing ECVs for BCC include limitations with the pooled MIC dataset, broad MIC distributions, and high ECVs that are above the obsolete susceptible MIC breakpoints. These challenges limit the clinical utility of ECVs for these organisms and supported removal of ECVs from the CLSI M100 standards document. IMPORTANCEThe Burkholderia cepacia complex is a group of bacterial species that cause difficult-to-treat opportunistic infections. Recently, clinical breakpoints, which are used to determine whether organisms are susceptible to certain antimicrobials, were removed from Clinical and Laboratory Standards Institute (CLSI) standards for these organisms due to problems with antimicrobial susceptibility testing performance. Clinicians are now faced with the challenge of how to treat these complex infections without clinical breakpoints. Here we determine epidemiological cut-off values (ECVs) for relevant antimicrobials for the B. cepacia complex. While we established ECVs for four antimicrobials, we encountered significant challenges in our analyses, including limitations with data for these organisms and high ECVs that are not clinically useful. These challenges limit the practical use of these ECVs in helping guide clinicians on treatment and supported the eventual removal of ECVs from the CLSI M100 standards document.

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.

ObjectivesListeria monocytogenes is an opportunistic pathogen, associated with foodborne infections that disproportionately affect newborns, elderly and immunocompromised patients. L. monocytogenes can be classified on the antigenic and related structural variation of cell-associated wall teichoic acid (WTA) molecules through conventional serotyping techniques. The WTA structure of serovars (SV) 1/2, 1/2*, 3 and 7 consists of a linear poly-ribitolphosphate (RboP) polymer either with or without decoration with rhamnose (Rha) and/or N-acetylglucosamine (GlcNAc). Of these four SVs, SV1/2 (WTA with GlcNAc and Rha) causes [~] 99% of all listeriosis cases. However, conventional serotyping cannot accurately discriminate between these four SVs, particularly SVs1/2* (WTA with Rha). MethodsHere we applied two identified monoclonal antibodies (mAb), with specificity for the RboP backbone or GlcNAc modification to develop a discriminatory serotyping scheme for SV1/2, 1/2*, 3 and 7. Isogenic mutants for the different SVs were created in L. monocytogenes SV1/2 strain EGD-e. The typing scheme was then adapted to an immnoblot assay and applied to a collection of 317 previously classified listeriosis isolates from the Netherlands Reference Laboratory for Bacterial Meningitis. ResultsBinding of the RboP-specific mAb was limited to EGD-e wild type (SV1/2), but increased significantly for isogenic EGD-e mutants representing SV1/2*, 3 and 7. In contrast, the GlcNAc-specific mAb only recognized EGD-e mutants representing SVs 1/2 and 3. The combined staining profiles of the two mAbs allowed accurate discrimination of the four SVs as verified on clinical isolates. Applying this typing scheme to 317 listeriosis isolates previously typed as SV1/2, we confirmed SV designation in >90% of isolates, but also identified SV1/2* (5.4%), SV3 (0.6%) and SV7 (0.3%) isolates. SV1/2* isolates were also identified among meningitis patients. ConclusionThe increased discriminatory capacity of L. monocytogenes serotyping provides a more detailed insight of the epidemiological landscape and the critical factors for L. monocytogenes infections.

BackgroundTimely 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. MethodsWe conducted a laboratory-based evaluation of two multiplex real-time PCR assays (MTBc/NTM R-Gene(R) and MTB-RIF/INH R-Gene(R)) 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. ResultsThe analytical performance for detecting MTBc demonstrated 100% sensitivity and specificity (150/150). NTM detection showed 70{middle dot}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{middle dot}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{middle dot}76-1{middle dot}00) within this analytical context. InterpretationThis 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

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.

Cryptococcus neoformans is the leading cause of fungal meningitis with limited treatment options, making early and accurate diagnosis critical for improved patient outcome. Current diagnostic methods for cryptococcosis rely largely on capsule antigen detection and fungal culture, which are time-consuming and unable to identify mutation-driven antifungal heteroresistance. In this study, we have developed a SuperSelective primer-based PCR (SSP-PCR) platform for the rapid and specific detection of azole resistance-associated single-nucleotide polymorphisms (SNPs). We demonstrate that SSP-PCR reliably detected a single copy mutant allele in the presence of excess wild-type (WT) DNA, with sensitivity reaching a 1:104 mutant-to-WT ratio. Incorporating molecular beacon (MB) probes with our SSP-PCR platform further enhanced amplification specificity, enabling selective detection of the ERG11 Y145F (A434T) mutation that is known to cause high azole resistance. Using genomic DNA from in vitro cultures and mouse lung tissues infected with either WT strain H99 strain or a fluconazole-hyper-resistant mrl1 clinical isolate that carries the ERG11(A434T) mutation, or both strains, we successfully detected the A434T mutant allele in both settings. Moreover, our SSP-PCR simultaneously identified ERG11(A434T) and the multi-azole resistance-associated ERG11(G1885A) mutant alleles in a single-tube duplex reaction. Collectively, the SSP-PCR platform provides a robust and ultrasensitive molecular approach for the detection of azole resistance and heteroresistance in C. neoformans, with strong potential for high-throughput clinical screening applications. ImportanceInvasive fungal infections are a growing public health threat, causing over 1.5 million deaths annually, with cryptococcal meningitis accounting for over 15% HIV/AIDS related mortality. The problem is aggravated by limited treatment options and emerging of drug resistance. Long-term use of fungistatic azoles like fluconazole promotes the emergence of azole heteroresistance, contributing to clinical treatment failure. Current diagnostic assays often fail to detect resistance-associated mutations within heterogeneous fungal populations, limiting their clinical utility. In this study, we developed a SuperSelective primer-based PCR (SSP-PCR) platform for the rapid and ultrasensitive detection of azole resistance associated single-nucleotide polymorphisms (SNPs) in Cryptococcus neoformans. By integrating molecular beacon probes, this assay achieves high specificity and enables simultaneously detection of multiple SNP mutations in a single reaction. Our SSP-PCR platform offers a powerful molecular approach for identifying azole resistance and heteroresistance, with strong potential to improve diagnostic precision and guide antifungal therapy in clinical settings.

Molecular syndromic panels such as the BioFire FilmArray Gastrointestinal Panel (BF-GIP) have been widely adopted for gastrointestinal illness diagnosis due to their fast turnaround times and broad pathogen coverage. Recently, the BF-GIP demonstrated increased rates of norovirus false-positive detections, prompting a Class II recall of more than two million tests in February 2024. We examined the prevalence of BF-GIP norovirus false positives across four hospitals from December 2024 to June 2025. Among 185 BF-GIP norovirus-positive results confirmed with the BD MAX Enteric Viral Panel, the false discovery rate ranged from 31 to 74% across sites, with the highest rate seen at a specialized cancer care hospital. Deep sequencing of BF-GIP pouches (n=42) confirmed the Noro-1 assay as the primary source of off-target amplification, identifying 78 off-target species, predominantly commensal stool bacteria, compared to only two species for the Noro-2 assay. Off-target species amplified by the Noro-1 assay were recovered from both false-positive and true-negative pouches, suggesting no single species accounted for the false-positive results. Partial primer complementarity at off-target loci and amplicon Tm values within the acceptable range support mispriming of gut microbiota as the underlying cause. False-positive pouches exhibited significantly higher Cp values than true positives for both assays (Noro-1: 26.6 vs. 11.1, p=0.013; Noro-2: 30.0 vs. 13.1, p<0.001), consistent with low-level off-target amplification. These findings highlight the high false discovery rate of the Noro-1 assay, identify bacterial species involved in mispriming, and demonstrate the need to redesign this assay to ensure reliable testing and improved patient care.

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.

BackgroundTuberculous meningitis (TBM) is the most sinister form of extrapulmonary tuberculosis (EPTB), associated with high mortality due to delayed diagnosis and limited sensitivity of conventional and molecular tests. Current study evaluated the diagnostic utility of Lipoarabinomannan antigen (LAM) detection in CSF and urine and explored host inflammatory biomarkers for diagnosis and prognosis of TBM. MethodsThis prospective observational study enrolled 80 patients with presumptive TBM at a tertiary care centre. CSF samples were subjected to AFB microscopy, liquid culture(MGIT-960), GeneXpert MTB/RIF (GX), and LAM lateral flow assay. Urine LAM was performed at baseline. Serum and CSF levels of IL-1{beta}, IL-6, TNF-, IFN-{gamma}, IL-17A, and IP-10 were measured at baseline and after 1 month treatment. ResultsAmong 80 participants, 23 (28.7%) had definite TBM and 46 (57.5%) had probable TBM. CSF LAM sensitivity and specificity against microbiological reference standards was 43.5% and 80.7%, while urine LAM sensitivity (60.9%) and specificity 82.5% was higher. Against composite reference standards, both CSF and urine LAM showed reduced sensitivity but achieved 100% specificity. Serum IL-1{beta} showed the best diagnostic performance (AUC 0.943; sensitivity 88.9%, specificity 90.9%). Elevated serum and CSF IP-10 levels were associated with poor outcomes, whereas declining IL-6 and TNF- levels correlated with treatment response. ConclusionLAM detection in CSF and urine may serve as a highly specific, rapid rule-in test for TBM. Host inflammatory biomarkers, especially IL-1{beta} and IP-10, show additional diagnostic and prognostic value. Combining LAM testing with cytokine biomarkers may improve early diagnosis and efficient clinical management of TBM.

Direct genome sequencing of Mycoplasma genitalium from clinical specimens is challenging due to the organisms low bacterial load. We developed and compared two DNA enrichment strategies--amplicon-based and hybridisation capture-based--coupled with next-generation sequencing, and assessed the suitability of DNA capture for whole-genome sequencing and high-resolution molecular typing. The enrichment approaches, RNA bait hybridisation and targeted sequence amplification, were combined with paired-end sequencing on the Illumina iSeq 100. Method performance was evaluated in 89 M. genitalium-positive specimens across five genomic loci: 23S and 16S rRNA, and parC and gyrA for macrolide, tetracycline, and fluoroquinolone resistance, respectively, and mgpB for phylogenetic analysis. Regarding antimicrobial resistance (AMR) determinants, the multiplex amplicon sequencing method demonstrated the highest sensitivity, at 93.3-98.9%. Although < 50% of samples were characterised using DNA capture, concordance between the two methods was excellent. Using DNA capture, 24.7% of specimens achieved a minimum coverage of 95% at 1x depth. Sequencing success was inversely correlated with human DNA contamination and the presence of low-quality reads. Whole-genome single-nucleotide polymorphism analysis provided higher discriminatory power than multi-locus sequence typing schemes and confirmed the clonality of multidrug-resistant M. genitalium strains belonging to the mgpB genotype 159. In conclusion, targeted amplicon-based enrichment is the most accurate and reliable approach for epidemiological studies focused on AMR and mgpB typing, whereas DNA capture is valuable for generating comprehensive genomic data from selected M. genitalium-positive specimens. Impact statementCulturing Mycoplasma genitalium from clinical specimens is challenging; consequently, epidemiological studies rely on molecular techniques. Whole-genome sequences have been obtained from a few M. genitalium clinical isolates, and direct sequencing from clinical specimens requires enrichment strategies to overcome the organisms low bacterial load. Consequently, published data on antimicrobial resistance (AMR) mechanisms and phylogenetic relationships among circulating strains remain incomplete. We demonstrated that targeted amplicon-based enrichment provided high-resolution AMR detection and highly sensitive mgpB genotyping, enabling the identification of minority variants. In contrast, hybridisation capture-based enrichment showed lower sensitivity but permitted successful WGS in a subset of M. genitalium-positive specimens and supported the development of new typing schemes. Although amplicon-based enrichment remains a reliable approach for epidemiological studies, strategic application of DNA capture facilitates the generation of comprehensive genomic data even though performance is reduced in the context of low bacterial loads, high host DNA contamination or suboptimal DNA quality.

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.

IntroductionHerpes simplex virus type 1 (HSV-1) is highly prevalent worldwide, making accurate serological testing essential for both clinical diagnosis and epidemiological surveillance. Automated chemiluminescent immunoassays (CLIAs) offer operational advantages over enzyme-linked immunosorbent assays (ELISAs); however, their diagnostic performance relative to Western blot (WB) confirmation in high-prevalence settings remains insufficiently characterized. Hypothesis/Gap StatementThe comparative diagnostic accuracy of CLIA- and ELISA-based assays for HSV-1 IgG detection, when benchmarked against a WB reference standard in endemic populations, remains unclear. AimThis study aimed to evaluate HSV-1 IgG seroprevalence and diagnostic performance of one CLIA and two ELISA platforms using Western blot as the reference method. MethodologyFour hundred archived serum samples from adult male craft and manual workers in Qatar were tested using the Mindray CL-900i CLIA, HerpeSelect ELISA, NovaLisa ELISA, and Euroimmun Western blot. Seroprevalence, diagnostic accuracy, and interassay agreement were assessed using WB as the reference standard, with equivocal and indeterminate results excluded from analysis. ResultsHSV-1 IgG seroprevalence estimates were comparable across assays: HerpeSelect 72.5%, Mindray 70.5%, NovaLisa 66.3%, and Western blot 66.5%, with no statistically significant differences (all p > 0.05). The Mindray CLIA demonstrated the highest diagnostic performance (sensitivity 95.7%, specificity 88.9%, accuracy 93.4%) and strong agreement with Western blot ({kappa} = 0.85). HerpeSelect showed substantial agreement ({kappa} = 0.81), while NovaLisa exhibited lower specificity. ConclusionCLIA- and ELISA-based assays produced comparable HSV-1 seroprevalence estimates in this high-prevalence population; however, diagnostic accuracy varied across platforms. The CLIA platform demonstrated the strongest agreement with Western blot, supporting its use in high-throughput settings, while confirmatory testing remains important to minimize misclassification. Key PointsO_LIWhat is known: HSV-1 serological diagnosis relies mainly on ELISA assays, while automated CLIA platforms are increasingly used in high-throughput laboratories but remain insufficiently evaluated against Western blot confirmation. C_LIO_LIWhat is new: This study provides a large head-to-head comparison of CLIA and ELISA platforms for HSV-1 IgG detection using Western blot as the reference standard in a high-prevalence population. C_LIO_LIClinical implications: Automated CLIA systems demonstrated strong diagnostic accuracy and may represent reliable high-throughput alternatives for HSV-1 serological screening in clinical laboratories. C_LI Impact StatementAccurate serological diagnosis of herpes simplex virus type 1 (HSV-1) is essential for clinical management, epidemiological surveillance, and public health decision-making, particularly in populations where infection is highly prevalent. This study adds to the existing literature by providing a large, head-to-head comparison of automated chemiluminescent immunoassay (CLIA) and enzyme-linked immunosorbent assay (ELISA) platforms for HSV-1 IgG detection, benchmarked against Western blot confirmation in a real-world, high-prevalence setting. By demonstrating that different serological platforms can yield similar population-level seroprevalence estimates yet differ in diagnostic accuracy and specificity, this work highlights the risk of misclassification when confirmatory testing is not considered. The findings are of broad relevance to clinical microbiology laboratories, diagnostic services, and public health surveillance programs that rely on serological assays for HSV-1 screening. The study represents an incremental but important step in refining assay selection and interpretation, supporting more reliable laboratory diagnostics and improved understanding of HSV-1 infection burden in endemic populations. Data Availability StatementThe data that support the findings of this study are available from the corresponding author upon reasonable request.

Nasopharyngeal (NP) swabs remain the dominant gold standard for respiratory infection diagnostics. While there has been increased use of alternative sample types since the COVID-19 pandemic, guidance on their use for detecting respiratory viruses is not yet definitive, especially for children. In this systematic review and meta-analysis, we aimed to compare the diagnostic accuracy and tolerability of multiple respiratory specimen types for detecting respiratory viruses in pediatric populations. Searches were conducted on July 17, 2025 in MEDLINE, Embase, Web of Science, and Scopus, with screening and data extraction performed in Covidence. English-language primary research articles published since 2000 comparing respiratory virus detection rates in children, using nucleic acid amplification tests between paired respiratory specimens, were included. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies criteria. We calculated pooled sensitivities and specificities of index specimens: nasopharyngeal aspirates (NPA), mid-turbinate swabs (MT), anterior nasal swabs (ANS), oropharyngeal swabs (OP), and bronchoalveolar lavage fluid (BAL), as compared to the reference, NP swabs, using random-effects modeling, firstly without discrimination by virus. Index specimens were then grouped by sample collection site as nasal, oral, and lower respiratory tract (LRT) specimens for virus-specific analyses. Overall performance and statistical validity were evaluated by hierarchical summary receiver operating characteristic (HSROC) analysis. Data regarding sampling tolerability was also assessed. We screened 2,448 studies and identified 36 publications (total N participants = 10,687) that reported diagnostic test accuracy using paired index-reference data in children. Of these, 18 (total N participants = 4,310) used NP specimens as the reference and were included in the diagnostic test accuracy analysis. Virus-agnostic pooled sensitivity estimates indicated that MT (0.92%) performed most similarly to NP, though sensitivities of ANS (0.79%) and OP (0.70%) were also moderately high for detection of any respiratory virus. BAL sensitivity was the lowest (0.37%). All sample types demonstrated high specificity (0.98%-0.99%). Group estimates and HSROC statistics found that nasal specimens, when grouped, had the highest sensitivity and accuracy for all examined viruses, including for influenza (92%) and RSV (90%). By comparison, oral and LRT specimens performed less well, with more variability, though both showed moderately high sensitivities for RSV (78%, 76%, respectively) and influenza (82%, 80%, respectively), and LRT samples showed high sensitivity for HMPV (82%). Analysis of sample tolerability found that NP swabs consistently ranked as the least comfortable and least preferred, while nasal swabs and saliva both performed well. Datasets for LRT and oral specimens were sparser than for nasal, and this contributed to greater variability, underscoring the need for further diagnostic accuracy studies on alternatives to NP sampling. These data support the viability of nasal and oral alternatives to NP swabs and affirm their application in pediatric care, particularly in outpatient settings. Such alternatives could greatly improve sampling tolerability and increase global access, including in resource-limited settings, to accurate diagnostic methods for respiratory infections.

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.

Tuberculosis (TB) remains a leading cause of infectious disease mortality, and the continued emergence of drug-resistant Mycobacterium tuberculosis (MTB) strains threatens the effectiveness of standard treatment regimens. Culture-based antibiotic susceptibility testing (AST) remains the clinical reference standard for resistance determination but typically requires six to eight weeks, delaying initiation of optimized therapy for patients with drug-resistant disease. Whole-genome sequencing (WGS)-based approaches provide a rapid alternative for predicting antimicrobial resistance directly from genomic data and are increasingly being incorporated into diagnostic workflows. This survey reviews computational approaches for genomic resistance prediction in MTB, focusing on two major classes of methods: catalog-based tools that identify established resistance-conferring variants, and de novo machine learning approaches that infer resistance from genome-wide sequence features. We examine the strengths and limitations of these approaches with respect to interpretability, scalability, computational requirements, and concordance with phenotypic testing. We further discuss emerging directions in quantitative minimum inhibitory concentration (MIC) prediction, challenges in pyrazinamide susceptibility testing, and the limited availability of resistant isolates for newer and repurposed drugs used in multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) treatment regimens. Continued expansion of paired phenotypic and genomic datasets, standardized MIC testing protocols, and rigorous lineage-aware evaluation frameworks will be essential for improving the clinical reliability and global deployment of genomic resistance prediction for tuberculosis diagnostics.

2.Streptococcus pneumoniae is the leading cause of empyema and pneumonia in children, and monitoring of effectiveness of polyvalent pneumococcal vaccines has been essential for controlling invasive pneumococcal disease (IPD) in children and elderly adults. Conventional serotyping of pneumococci has relied on Quellung reaction following laboratory culture, however more recently whole genome sequencing (WGS) has been implemented in many reference laboratories to enhance traditional typing. Pleural fluid samples from cases with empyema are often culture negative, limiting the utility of WGS and requiring polymerase chain reaction (PCR) or 16S rRNA sequencing to detect S. pneumoniae. These molecular methods have limited sensitivity and capacity to characterise pneumococcus in clinical samples, especially in specimens with a low pathogen abundance. This study applied capture-based enrichment (tNGS) to identify and characterise S. pneumoniae directly from pleural fluid samples. A total of 51 pleural fluid samples were subjected to tNGS with a custom probe panel, for 39 known positive fluids collected from IPD cases between 2018-2025 in New South Wales, Australia. tNGS results were benchmarked against molecular-based serotyping. Our tNGS achieved 100% sensitivity and specificity in detecting S. pneumoniae. Serotyping results were concordant with PCR and 95% (37/39) of S. pneumoniae PCR positive pleural fluid cases could be serotyped using tNGS. Standard molecular methods however could only determine serotype in 56% (22/39) of samples. This tNGS enabled 39% improvement in ability to directly identify and serotype IPD-associated serotypes of S. pneumoniae in difficult-to-culture pleural fluids can significantly enhance laboratory surveillance of IPD as well as our understanding of vaccine effectiveness. 3. Impact statementThere is currently a gap in understanding the pneumococcus serotype diversity causing infection within the pleural fluid space. The gold-standard Quellung method to determine serotype relies on culturing the pneumococci first. However, pleural fluids often remain culture-negative, and cases of pneumococcal empyema have been a historical blind spot in pneumococcal surveillance. This study offers a new methodology to close this gap and allow serotyping of previously untypable cases. The study demonstrated a targeted next generation sequencing (tNGS) approach to determine serotype without the need to first culture the bacteria. This novel use of tNGS targets part of the cps gene cluster, which determines serotype. To the best of our knowledge this is the first panel to do so. We have successfully serotyped 95% of pleural fluid S.pneumoniae PCR positive samples, where previously only 56% could be determined using conventional PCR typing methods. This demonstrates for the first time a novel tNGS method capable of determining the full serotype landscape causing pleural fluid infection. This development will enhance the understanding of vaccine effectiveness and contribute to the prevention of invasive pneumococcal disease. 4. Data summarySupplementary data containing reference cpsB genomes are available within this article. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. 1.5 RepositoriesENA project accession number PRJEB111154. All supporting data has been provided within the article or in supplementary data files. One supplementary data file is available with the online version of this article.