Journal of Clinical Microbiology

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.

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.

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.

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.

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.

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.

Background Oropouche virus (OROV) is an emerging vector-borne virus with rapidly expanding geographic range, increasing case counts, and growing evidence of severe outcomes including neuroinvasive disease and vertical transmission. Because OROV infection presents with nonspecific febrile illness that overlaps clinically with other viruses including dengue, zika, and chikungunya, accurate molecular diagnostics are essential for patient care and surveillance. Yet existing assays rely on single genomic targets and are vulnerable to detection failure as the virus evolves and reassorts. Methodology/Principal Findings To support diagnostic capacity, we developed and clinically validated a multiplexed qPCR assay targeting three regions of the OROV S segment, incorporating redundancy to preserve sensitivity across viral diversity while enabling robust clinical interpretation. The multiplex also includes an assay targeting RNaseP as an internal sample control to ensure adequate sample processing. We evaluated assay performance using both historical and contemporary OROV strains and validated the assay on contrived serum, plasma, and cerebrospinal fluid samples, assessing linearity, limit of detection (LOD), accuracy, specificity, precision, and sample stability. The assay met or exceeded all predefined acceptance criteria for clinical testing and achieved an LOD as low as 6 copies per reaction for contemporary outbreak strains. We further implemented a logic-based interpretation matrix that reduced false-positive risk while maintaining sensitivity near the analytical LOD. Conclusions/Significance Our assay sensitively and specifically detects OROV RNA in serum, plasma, and cerebrospinal fluid while incorporating safeguards against viral evolution and reassortment. The assay has been approved for use by CLIA at Nexus Medical Labs in 49 U.S. states, expanding access to timely OROV diagnostics in the United States and providing a durable framework for molecular detection of reassorting, rapidly evolving viruses as OROV continues to spread into new regions.

Species-level Candida identification can inform antifungal management, but reliable identification platforms remain inaccessible in many clinical microbiology laboratories, whereas phase contrast microscopy -- a common feature of routine laboratory microscopes -- is widely available. We asked whether this ubiquitous optical tool, combined with a consumer smartphone and deep transfer learning, could provide a feasible low-cost approach for preliminary Candida species discrimination. Fifteen clinical isolates of four species (C. albicans, C. glabrata, C. tropicalis, C. krusei) were collected from a single clinical microbiology laboratory and imaged using a consumer-grade smartphone coupled to a standard phase contrast microscope. Suspensions in human serum were imaged immediately after preparation (T0) and after 2-hour incubation at 37{degrees}C (T2). Pretrained vision backbone architectures were evaluated as fixed feature extractors under strict Leave-One-Strain-Out cross-validation. The best-performing model -- EfficientNet-B0 embeddings with a Linear Support Vector Machine applied to T2 images -- achieved an apparent internally cross-validated strain-level balanced accuracy of 0.833 and an overall strain accuracy of 86.7% (13/15 strains correctly classified). C. albicans, C. glabrata, and C. tropicalis were each identified with 100% recall. Both misclassified strains belonged to C. krusei -- the species with the smallest panel representation (n=3 strains) -- with misclassification attributable to limited strain diversity and suboptimal image quality. These findings demonstrate promising feasibility for preliminary image-based Candida species discrimination from smartphone-acquired phase contrast microscopy images, and support further evaluation in larger, externally validated strain collections.

In the United States, gay, bisexual, and other men who have sex with men (MSM) experience a disproportionate burden of sexually transmitted infections (STIs), with notable racial/ethnic disparities. Doxycycline post-exposure prophylaxis (doxy-PEP) has emerged as a promising strategy to prevent bacterial STIs. This study analyzed 2023 National HIV Behavioral Surveillance data to examine doxy-PEP awareness, use, and intent to use among MSM in New York City (NYC), in a predominantly Hispanic/Latino sample. Among 134 participants, awareness and prior use were low (38.8% and 9.0%, respectively), but intent to use was high (75.4%). In Poisson regression models, intent was higher among participants reporting non-injection drug use and 2-10 partners in the past 12 months, while marginally lower among those above the Federal Poverty Level and recent migrants. Findings suggest doxy-PEP is acceptable for MSM in NYC, but addressing barriers among low-income groups and recent migrants is critical to reducing disparities.

Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Whole-genome sequencing (WGS) offers a more rapid and comprehensive method for AMR characterization compared to conventional antimicrobial susceptibility testing (AST), supporting antimicrobial therapy and surveillance efforts. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype- phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) MIC modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.4%) in S. Enteritidis without identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate, comprehensive AMR characterization, offering direct identification of AMR determinants and minimizing misclassification due to breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing.

Trichophyton mentagrophytes genotype VII (TmVII) is an emerging sexually transmitted dermatophyte that causes skin infections characterized by inflammatory, erythematous-squamous, painful, and persistent lesions. This genotype is part of the T. interdigitale/T. mentagrophytes Species Complex (TiTmSC), which comprises 28 genotypes. To enable rapid and specific differentiation of TmVII from other genotypes, a real-time polymerase chain reaction (rt-PCR) assay was developed targeting three unique single-nucleotide polymorphisms in the ITS1 region of TmVII. Assay specificity was further improved by introducing an additional mismatch at the 3 ends of both forward and reverse primers. The rt-PCR assay demonstrated high sensitivity, with a detection limit of 0.0002 ng of TmVII genomic DNA. The assay was highly specific, with no cross-reactivity observed with either closely or distantly related fungal pathogens when a cycle threshold (Ct) cutoff of 37 was applied. Among 497 mold isolates tested, 47 were confirmed as TmVII by rt-PCR, and the results were fully concordant with conventional ITS-PCR/Sanger sequencing. The rt-PCR assay demonstrated high sensitivity, specificity, reproducibility, and speed, with a turnaround time of one day after DNA extraction, compared with seven to ten days for Sanger sequencing. The first rapid molecular assay developed using TaqMan chemistry for TmVII identification is expected to enhance patient care and support infection control measures.

First documented detection of Vibrio paracholerae in a Costa Rican foodborne outbreak. Genomic analysis confirmed species identity, revealing limitations of conventional PCR and MALDI methods. Findings underscore the need for genomic surveillance to accurately characterize emerging enteropathogens and support public health systems.

Effective filtration and concentration of stool specimens is an essential pre-analytical step for reducing fecal debris and improving organism recovery using microscopy-based ova and parasite (O&P) examination. This study evaluated three commercially available fecal sedimentation-based filtration/concentration systems, ParaPak SpinCon (Meridian Bioscience), Mini Parasep SF (Apacor), and the newly-available ParadeviceReingenuity), for qualitative parasite detection and workflow logistics using conventional and artificial intelligence (AI)-assisted microscopy. Forty clinical stool specimens (20 parasite-positive and 20 parasite-negative) were processed with the 3 devices, and the resultant 120 wet mount and 120 trichrome stained smear preparations were examined using conventional microscopy. Trichrome-stained slides were also scanned at 40x magnification using a Hamamatsu NanoZoomerS360 flatbed digital slide scanner and images were analyzed using the Techcyte Fusion Human Fecal Trichrome AI algorithm. Positive and indeterminate digital findings were confirmed by conventional glass slide microscopy. Slides and digital images were reviewed in a blinded manner. Concordance was assessed among the 360 initial evaluations (microscopy and AI-assisted), and discrepant parasitology results were resolved through re-review and specimen reprocessing as needed. Final qualitative agreement across slide/image evaluations using all three concentration systems was 100%. Minor discrepancies in protozoan and white/red blood cell detection/identification were noted in 5 and 7 cases, respectively, and likely reflected sampling and observer variability. While the three concentration systems produced equivalent qualitative results, the Paradevice and Mini Parasep SF offered the most streamlined workflows. These findings support the Paradevice and Mini Parasep SF as efficient, analytically equivalent systems that are compatible with traditional and AI-assisted O&P workflows.

Background Microbiological confirmation of paediatric pulmonary tuberculosis is frequently unattainable, rendering chest radiography a critical yet underutilised diagnostic tool. Methods We conducted a retrospective diagnostic accuracy study of the qXR version 4.2.1 (Qure.ai), a paediatric optimized computer-aided detection (CAD) algorithm, for pulmonary tuberculosis. Diagnostic performance was assessed against microbiological (MRS) and clinical reference standards (ClRS). Bayesian latent class analysis (LCA) was applied to address the imperfection of both reference standards in children. Performance was quantified using area under the receiver operating characteristic curve (AUROC) and estimates of sensitivity and specificity. Results We included digital chest radiographs of 932 Gambian children (< 15 years) comprising 80 (9%) children with confirmed tuberculosis, 163 (17%) with unconfirmed tuberculosis, and 689 (74%) classified as unlikely tuberculosis. Against MRS, qXR demonstrated AUROC, sensitivity and specificity of 0.68 (95% CI, 0.61 to 0.75), 54% (95% CI, 43 to 64%), and 82% (95% CI, 79 to 84%), respectively. Against ClRS, the AUROC, sensitivity and specificity were 0.73 (95% CI, 0.69 to 0.77), 41% (95% CI, 34 to 49%), and 87% (95% CI, 84 to 89%), respectively. Bayesian LCA, assuming conditional independence, estimated sensitivity of 79% (95% CrI, 65 to 89%) and specificity of 82% (95% CrI, 79 to 84%). Assuming conditional dependence between qXR and expert radiologist, and between culture and Xpert, estimated sensitivity increased to 89% (95% CrI, 71 to 98%), with specificity remaining at 82% (95% CrI, 79 to 84%). Conclusions Paediatric optimized qXR algorithm provides a valuable complementary tool for diagnosis of paediatric pulmonary tuberculosis. Conventional reference standards likely underestimate the true diagnostic performance of CAD systems in children.

Shigella sonnei is a human-adapted enteric pathogen with a very low infectious dose and increasing antimicrobial resistance. In high-income settings, transmission is multimodal including sporadic cases/outbreaks associated with food and travel, as well as sustained transmission among sexual networks of men who have sex with men (MSM). Whole-genome sequencing (WGS) now underpins national shigellosis surveillance in the United Kingdom. Hence, consistent, communicable genotyping is essential for case linkage and trend detection across heterogeneous transmission modes. Here, we evaluate the performance of WGS genotyping approaches for granulating outbreaks of S. sonnei shigellosis, particularly considering differential performance in dense sexual transmission where highly clonal MSM-associated sublineages pose distinct clustering challenges. Specifically, we compare performance of the current practice approach (10 SNP-distance clustering based on SNP address [t10]), allele-based methods (EnteroBase cgMLST/HierCC [HC5]), a pathogen-specific genotyping scheme (sonneityper), and two k-mer based approaches (PopPUNK and KPop), on a bona fide UK surveillance dataset (n = 3,639 isolates from between 2016 and 2022), and stratify analyses by demographics (i.e. presumptive MSM [pMSM] versus non-pMSM). Comparison metrics indicate that t10 clustering method groups data more broadly than HC5, and k-mer-based methods may capture genetic variation independent from SNP or allele-based approaches. Clusters derived from k-mer-based methods offer similar resolution to HC5 and reflect different demographics, but had unconvincing utility for this pathogen. These findings suggest a transmission context-aware surveillance workflow for shigellosis in high income settings: anchor routine communication on a portable allele-based backbone and augment with more granular, complementary methods (e.g., k-mer-based micro-partitioning or phylogenetic analysis) in comparatively low genomic-density regions of population structure (e.g., pMSM transmission lineages) to stabilise clusters and reduce artefactual chaining.

The 16S rRNA gene is the most widely used genetic marker for microbial community profiling, but its limited sequence divergence often prevents species-level identification. The RNA polymerase {beta}-subunit gene (rpoB) offers higher sequence variability, single-copy occurrence, and stronger phylogenetic consistency, yet its adoption in metataxonomic studies has been constrained by the lack of universal primer sets. Here, we present a novel universal primer pair that amplifies an [~]1,800 bp rpoB region (rpoB_MV) compatible with long-read sequencing platforms. In silico evaluation across 17683 bacterial reference genomes demonstrated high universality, with over 86% of genomes predicted to amplify. Compared with full-length and partial 16S rRNA gene markers, the rpoB_MV amplicon exhibited significantly greater inter-species sequence divergence and improved phylogenetic concordance with core-genome trees. Sequencing of two complementary mock communities confirmed superior species-level identification accuracy, with misclassification rates below 0.01% and no reads assigned to unresolved species clusters. These results establish rpoB_MV as a robust alternative to 16S rRNA gene-based profiling for high-resolution metataxonomic applications. IMPORTANCEMicrobial community studies increasingly require species-level resolution because species within the same genus can differ substantially in pathogenicity, ecological function, and metabolic capacity. Current 16S rRNA gene-based methods frequently fail to distinguish closely related species, collapsing biologically distinct organisms into the same taxonomic assignment and obscuring community differences that matter for clinical diagnostics, food safety, and environmental monitoring. The rpoB_MV primer pair presented here overcomes this limitation by targeting a longer, more variable region of the rpoB gene, enabling accurate species-level identification across diverse bacterial phyla. Combined with advances in long-read sequencing, this approach provides researchers with a practical tool to resolve microbial communities at the species-level.

Measles virus remains a significant global health threat, and despite the availability of an effective vaccine, measles cases continue to increase worldwide in recent years. Genomic surveillance has become an essential tool for monitoring virus circulation and investigating outbreaks. Here, we describe a wet-laboratory method for whole-genome sequencing of measles virus using a tiled amplicon approach and Illumina sequencing technology. A previously published Oxford Nanopore-based tiled primer scheme was adapted to include both circulating measles genotypes and for use on the Illumina platform. Two Illumina library preparation kits, Illumina DNA Prep (IDP) and Nextera XT (XT), were evaluated for performance. The IDP kit demonstrated more complete genomes and consistent genome coverage compared with XT. Using quantified reference genomes, the limit of detection was determined to be 10,000 genome copies for genotype B3 and D8. Sequence accuracy was evaluated using previously characterized clinical samples and showed high concordance. This method provides a reliable and sensitive approach for measles virus whole-genome sequencing using Illumina platforms and is suitable for genomic surveillance applications.

Introduction: Viral load (VL) monitoring is the gold standard for antiretroviral therapy (ART) monitoring. Still, due to limited funds and infrastructure, many people living with HIV (PLHIV) in low- and middle-income countries do not receive timely VL testing. We evaluated the clinical performance and end-user acceptability of a prototype interferon gamma-induced protein 10 (IP-10) point-of-care (POC) test as a rule-out triage tool to identify individuals unlikely to have unsuppressed VL in PLHIV in Mozambique. Methods: A mixed-methods study was conducted between November 2023 and November 2024 at two primary healthcare facilities in Maputo Province. We enrolled 1,057 PLHIV on ART from stable and specialized risk clinics. Clinical performance of the IP-10 POC test (index test) was compared against plasma HIV VL (reference test; unsuppressed defined as >1000 copies/mL). Socio-demographic and clinical predictors of false-positive results were identified using multivariable logistic regression. Immediate acceptability was assessed through exit interviews on a subset of 43 PLHIV. Results: Among participants (71.7% female; median age 41.4 years), 12.0% had unsuppressed VL. The IP-10 POC test demonstrated high sensitivity (90.6%) and moderate specificity (35.6%). Specificity was higher in clinics treating stable patients (44.5% 95%CI: 39.7-49.3) compared to specialized risk clinics (26.5% 95%CI: 21.1-28.9). The proportion of false-positive results was also higher in patients attending specialized risk clinics. Independent predictors of false positivity included enrolment in a one-stop TB/HIV clinic (aOR=2.99 95%CI: 1.09-8.15), cotrimoxazole use (aOR=2.16, 95% CI: 1.13-4.13), and obesity (aOR=3.47 95%CI: 1.74-6.93). Acceptability was high: 70% of participants appreciated the test simplicity and rapid results, and 95.3% expressed interest in future testing. Most patients preferred finger-prick collection over venous draws. Conclusions: The IP-10 POC test is a highly sensitive triage tool, demonstrating superior performance among stable PLHIV enrolled in differentiated service delivery models like six-month multi-month dispensing. While factors associated with co-infections can reduce specificity, the test's high acceptability and potential to reduce confirmatory VL test demand suggests it could serve as a viable triage strategy for optimizing resources particularly in stable care pathways with a lower prevalence of inflammatory comorbidities. This could enable health systems to reallocate intensive monitoring toward higher-risk populations.

In July 2021, the California Code of Regulations Title 17 required all laboratories performing SARS-CoV-2 whole genome sequencing (WGS) to report their sequencing results to the California Department of Public Health (CDPH). These viral genomic data and patient metadata were compiled into the Integrated Genomic Epidemiology Database (IGED). Linking anonymized viral sequences with patient-level information enabled monitoring of infectiousness, pathogenicity, transmission dynamics, evolution, and vaccine evasion among emerging SARS-CoV-2 lineages. Laboratories performing SARS-CoV-2 WGS transmitted sequencing results to CDPH through Electronic Laboratory Reporting (ELR) and non-ELR pathways. CDPH applied uniform reporting requirements but allowed flexibility in specific data formats to accommodate diverse data systems. To preserve data quality and interoperability across heterogeneous sources, CDPH implemented standardization, validation, and deduplication protocols. Snowflake, a cloud-based data storage and analytics platform, and Posit Connect, a cloud deployment and automation platform, supported the management, processing, and integration of data within the IGED. The IGED established links between SARS-CoV-2 WGS data and epidemiologic metadata for 801,418 sequences, representing 81.7% of all sequences reported in California. Lineages reported to the IGED showed strong concordance with lineage proportions in GISAID. Sequences reported to the IGED had average turnaround times longer than one month, and the majority of sequencing was performed in Southern California and Los Angeles. The IGED enhanced genomic surveillance through predictive modeling and monitoring concerning evolutionary trends such as recombination and saltations in persistent infections. Development of the IGED highlighted the need for standardized data requirements, sustained funding for sequencing, incentives for data submission, and interdisciplinary collaboration to build an effective genomic surveillance system. This framework for linking genomic and epidemiologic data has not only generated critical insights for SARS-CoV-2 but also provided the foundation for CDPH and other public health organizations to develop similar IGED-like systems for other priority pathogens as genomic surveillance expands.

Tuberculosis (TB) remains one of the deadliest infectious diseases, with over a million deaths annually and a growing threat from multidrug-resistant strains (MDR-TB). A major bottleneck in controlling TB is the lack of truly portable, rapid, and user-friendly diagnostic systems that can operate effectively in decentralized, resource-constrained settings. Here, we present a first-of-its-kind, portable nucleic-acid-based diagnostic platform that enables both primary TB screening and detection of drug resistance within the same unified framework, without any change in the operative embodiment. The system integrates loop-mediated isothermal amplification (LAMP) targeting dual Mycobacterium tuberculosis markers (IS6110 and IS1081) with a compact, AI-enabled device and smartphone-based readout, delivering rapid and reliable results at the point-of-care. Clinical evaluation across 105 samples demonstrated high sensitivity and specificity. Further validation through real-world deployment in a primary healthcare setting, using a single-gene (IS6110) configuration operated by minimally trained personnel, yielded 95.60% sensitivity and 100% specificity, benchmarked against GeneXpert. Critically, the same platform architecture, without modification, extends seamlessly to drug-resistance profiling, demonstrated here through a probe-free, allele-specific LAMP approach for identifying key mutations associated with rifampicin (rpoB) and isoniazid (katG) resistance. By combining robust molecular diagnostics with AI-driven automation in a compact and accessible format, this work represents a significant medical advancement toward democratizing TB care. The platform thus holds strong potential to enable early screening, guide timely treatment decisions, reduce transmission, and substantially strengthen global TB elimination efforts, particularly in high-burden, low-resource settings.