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PubMed2026

CRISPRessoSea: streamlined analysis and comparison of pooled amplicon CRISPR screens.

BACKGROUND: CRISPR genome editing enables precise modification of genomic targets but may also induce unintended edits at off-target sites with similar sequences. Pooled amplicon sequencing can assess on- and off-target editing across many samples, yet analyzing, aggregating, and visualizing results from multiple pooled experiments remains challenging. Tools to simplify and standardize these analyses are needed to provide reproducible and comparable interpretation of editing data. RESULTS: We developed CRISPRessoSea, a software package that processes, compares, and visualizes genome editing rates from pooled amplicon sequencing experiments. The tool provides standardized workflows for analyzing editing across multiple targets and samples, supports both nuclease- and base-editing modalities, and generates clear, data-rich summaries suitable for downstream interpretation. CONCLUSIONS: CRISPRessoSea facilitates reproducible, scalable analysis of CRISPR editing outcomes across diverse experimental designs, enabling more efficient and transparent assessment of genome editing specificity. The software is freely available at https://github.com/clementlab/CRISPRessoSea .

Software↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2025

Deep clinical and genetic analysis of 17p13.3 region: 38 pediatric patients diagnosed using next-generation sequencing and literature review.

BACKGROUND: Chromosome 17p13.3 is a region of genomic instability associated with different neurodevelopmental diseases. The malformation spectrum of 17p13.3 microdeletions ranges from an isolated lissencephaly sequence to Miller-Dieker syndrome, while 17p13.3 microduplications result in autism, learning disabilities, microcephaly and other brain malformations. This study aims to provide a more comprehensive delineation of the clinical and genetic characteristics associated with 17p13.3 alterations. METHODS: We retrospectively analyzed the next-generation sequencing (NGS) data of more than 40 thousand patients from January 2016 to December 2021 and identified 38 pediatric patients with copy-number variations (CNVs) or single-nucleotide variations (SNVs) in 17p13.3 region. Published patients with CNVs in the 17p13.3 region were also collected and we performed a Chi-square test to compare the phenotype spectrum of microdeletions and microduplications. RESULTS: Among the 27 CNV patients, 20 patients with microdeletions and 7 patients with microduplications were found. PAFAH1B1 was the most frequently deleted gene and CRK was the most frequently duplicated gene. Affected genes in 11 SNV patients included PAFAH1B1 and PRPF8. Developmental delay was the most common abnormality detected in the 38 patients (29/38, 76.3%). Of note, Case 10 presented omphalocele and Case 23 presented scoliosis, webbed neck and bone cyst, all of which were unusual variant phenotypes in this region. The Chi-square test revealed that epilepsy, lissencephaly and short stature were statistically significant with microdeletions, while behavioral abnormalities and hand and foot abnormalities were significant with microduplications (p < 0.01). CONCLUSIONS: While PAFAH1B1, YWHAE and CRK are associated with major phenotypes of 17p13.3, RTN4RL1 may be involved in white matter changes and HIC1 might contribute to the occurrence of omphalocele. This study provided a comprehensive understanding of genetic information and phenotype spectrum of the 17p13.3 region.

Humans↗

PubMed2026

Clinically actionable stratification of uncommon MET fusions: a precision oncology framework.

BACKGROUND: MET fusions represent emerging therapeutic targets in solid tumors; however, functional interpretation of non-canonical variants remains poorly understood, posing a major challenge for precision oncology. METHODS: We conducted a multicenter, pan-cancer study analyzing 23,299 clinical samples using DNA-based next-generation sequencing (NGS) to profile MET fusions. Transcriptional validation was performed using RNA-based NGS on available samples. Preliminary clinical outcomes were assessed in four patients with advanced malignancies harboring uncommon MET fusions who received MET tyrosine kinase inhibitor therapy. RESULTS: We identified 116 MET fusions (incidence: 0.5%), with 55.2% (64/116) classified as uncommon fusions. These uncommon fusions were stratified into: Group A (5’-retained, n = 12), Group B (intergenic/exonic breakpoints, n = 19), Group C (rare partners, n = 23), and Group D (dual fusions, n = 10). RNA validation revealed an overall low transcriptional consistency of 43.8% (14/32) for uncommon fusions, versus 100% for canonical fusions (PTPRZ1::MET, CAPZA2::MET). Notably, most 5’-retained fusions were transcriptionally silent, while some intergenic fusions resolved into expressed canonical partners (e.g. PTPRZ1::MET). Therapeutically, all four MET inhibitor-treated patients achieved partial responses, including pediatric diffuse midline gliomas (DMG) (median OS: 11.2 months) and lung adenocarcinoma (median OS: 34 months), demonstrating preliminary clinical activity. CONCLUSIONS: uncommon MET fusions are heterogeneous at genomic and transcriptional levels. DNA-level findings often do not predict functional transcripts, underscoring the necessity of RNA-based confirmation for clinical interpretation. Despite low overall consistency, a subset retains therapeutic potential. We propose a refined diagnostic framework integrating DNA-based stratification and RNA validation to guide the management of MET-altered cancers in precision oncology workflows.

Humans↗

PubMed2026

An open-source clinical bioinformatics pipeline for real-world NGS implementation: translating genomic variants into actionable treatment strategies in oncology.

BACKGROUND: Next-Generation Sequencing (NGS) has become a cornerstone technology in clinical practice, yet its adoption presents significant challenges. Physicians and oncologists must manage vast amounts of genome-scale data and transform it into actionable insights for complex decision-making. While commercial systems exist to synthesize data from NGS experiments into clinical reports, many are hindered by limitations such as closed-source designs that restrict transparency and customization. Additionally, some fail to leverage publicly available genomic databases, missing opportunities to integrate valuable external data. Furthermore, the rigidity of many tools in accommodating diverse NGS panels limits their applicability across varied clinical scenarios. METHODS: To address these limitations, we developed OncoReport, an open-source tool that generates comprehensive reports from NGS analyses. By integrating publicly accessible databases, OncoReport provides a robust, user-friendly environment equipped with essential tools for NGS analysis. This design aims to enhance data interpretation and support informed clinical decision-making. RESULTS: Rigorous testing has demonstrated OncoReport’s effectiveness in producing detailed, actionable reports that are clear and easy to use. By automating key aspects of the workflow, the tool significantly reduces manual effort and expedites the synthesis and interpretation of NGS results, making genomic insights more accessible to clinicians. CONCLUSION: OncoReport offers a transparent, flexible, and efficient framework for clinicians to analyze and apply genomic data in patient care. By streamlining workflows and leveraging open-source principles, it empowers healthcare professionals to make informed, data-driven decisions. OncoReport is freely available at https://oncoreport.atlas.dmi.unict.it, with source code and issue tracking on GitHub: https://github.com/knowmics-lab/oncoreport .

Humans↗

PubMed2026

Metagenomic next-generation sequencing of cerebrospinal fluid reveals pathogen spectrum and mortality predictors among patients with advanced HIV-1 disease at a tertiary hospital in China.

BACKGROUND: Central nervous system (CNS) infections remain the major causes of morbidity and mortality among people living with HIV-1 (PLWH), particularly in resource-limited settings. However, the clinical characteristics and prognostic indicators of PLWH with suspected CNS infections are not well defined. In this study, we aim to characterize the spectrum of CNS pathogens, clinical characteristics, in-hospital mortality, and factors associated with death among people with advanced HIV-1 disease (AHD) in Guangxi, China. METHODS: Metagenomic next-generation sequencing (mNGS) was performed to analyze types of infection in cerebrospinal fluid (CSF) from 61 treatment-naive PLWH with suspected CNS infections. Clinical data, routine laboratory tests, and biochemical tests were collected and analyzed. RESULTS: Among the 61 CSF samples, primarily with AHD, a total of 206 pathogens were identified. Viral pathogens predominated, with Epstein-Barr virus being the most frequently identified, followed by cytomegalovirus. Compared with patients with single-pathogen infection, those with multiple infections (viral, bacterial, and fungal) exhibited significantly lower CD4 T cell counts, higher C-reactive protein levels, and markedly reduced lipid metabolism parameters. However, infection types were not significantly associated with in-hospital death. Multivariate logistic regression analysis identified plasma low density lipoprotein (LDL) and CSF lactate dehydrogenase (LDH) as independent predictors of in-hospital death. CONCLUSION: In PLWH with AHD and suspected CNS infections, multiple pathogens frequently coexist in the CSF. Plasma LDL and CSF LDH levels were independent predictors of death, indicating their potential value as early risk stratification in AHD.

Humans↗

PubMed2025

Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite.

Nucleotide recoding RNA sequencing methods (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.) are powerful approaches for assaying transcript population dynamics. In addition, these methods have been extended to probe a host of regulated steps in the RNA life cycle. Current bioinformatic tools significantly constrain analyses of NR-seq data. To address this limitation, we developed EZbakR (https://github.com/isaacvock/EZbakR), an R package to facilitate a more comprehensive set of NR-seq analyses, and fastq2EZbakR (https://github.com/isaacvock/fastq2EZbakR), a Snakemake pipeline for flexible preprocessing of NR-seq datasets, collectively referred to as the EZbakR suite. Together, these tools generalize many aspects of the NR-seq analysis workflow. The fastq2EZbakR pipeline can assign reads to a diverse set of genomic features (e.g., genes, exons, splice junctions), and EZbakR can perform analyses on any combination of these features. EZbakR extends standard NR-seq mutational modeling to support multi-label analyses (e.g., s4U and s6G dual labeling), and implements an improved hierarchical model to better account for transcript-to-transcript variance in metabolic label incorporation. EZbakR also generalizes dynamical systems modeling of NR-seq data to support analyses of premature mRNA processing and flow between subcellular compartments. Finally, EZbakR implements flexible and well-powered comparative analyses of all estimated parameters via design matrix-specified generalized linear modeling. The EZbakR suite will thus allow researchers to make full, effective use of NR-seq data.

Software↗

PubMed2025

NextVir: Enabling classification of tumor-causing viruses with genomic foundation models.

MOTIVATION: Oncoviruses, pathogens known to cause or increase the risk of cancer, include both common viruses such as human papillomaviruses and rarer pathogens such as human T-lymphotropic viruses. Computational methods for detecting viral DNA from data acquired by modern DNA sequencing technologies have enabled studies of the association between oncoviruses and cancers. Those studies are rendered particularly challenging when multiple species of oncovirus are present in a tumor sample. In such scenarios, merely detecting the presence of a sequencing read of viral origin is insufficiently informative-instead, a more precise characterization of the viral content in the sample is required. RESULTS: We address this need with NextVir, to our knowledge the first multi-class viral classification framework that adapts genomic foundation models to detecting and classifying sequencing reads of oncoviral origin. Specifically, NextVir explores several foundation models-DNABERT-S, Nucelotide Transformer, and HyenaDNA-and efficiently fine-tunes them to enable accurate identification of the sequencing reads' origin. The results demonstrate superior performance of the proposed framework over existing deep learning methods and suggest downstream potential for foundational models in genomics.

Humans↗

PubMed2025

MRDtarget: A heuristic Gaussian approach for optimizing targeted capture regions to enhance Minimal Residual Disease detection.

Molecular residual disease (MRD) detection, initially developed for hematologic malignancies, has become a critical biomarker for monitoring solid tumors. MRD detection primarily relies on circulating tumor DNA (ctDNA) analysis using next-generation sequencing, offering high sensitivity and broad genomic coverage. However, challenges remain in designing cost-effective panels that maximize mutation detection while maintaining biological relevance. Fixed panels often lack sufficient patient-specific mutation coverage, while WES-based personalized MRD assays, despite their high sensitivity, are costly and less accessible. We developed a tumor comprehensive genomic profiling (CGP)-informed personalized MRD assay to detect tumor-derived mutations, which allowed us to design patient-specific personalized panels and meanwhile, provide a cost-effective alternative to whole exome sequencing (WES). To address these limitations, we developed MRDtarget, a heuristic multivariate Gaussian model-based targeted capture region selection method. By expanding beyond traditional hotspot regions, MRDtarget optimizes variant tracking for MRD detection, significantly improving sensitivity. Using a Bayesian inference-based heuristic approach, MRDtarget integrates multi-feature informativeness rates to identify optimal genomic regions for capture. Experimental results demonstrate that MRDtarget enables the detection of more variants per patient. This study underscores the importance of rational panel design to improve MRD sensitivity and provides a novel approach to enhance precision diagnostics and treatment for solid tumor patients.

Humans↗

PubMed2026

Characteristics of p53 and Smad4 immunohistochemistry in pancreatic ductal adenocarcinoma and validation by next-generation sequencing.

BACKGROUND: Mutations in four major driver genes -KRAS, CDKN2A, TP53, and SMAD4- are central to the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) and critically inform diagnosis, therapeutic decision-making, and prognostic assessment. Although next-generation sequencing (NGS) is widely regarded as the gold standard for detecting these mutations, its clinical application is often limited by suboptimal analytical efficiency and substantial economic cost. Among these genes, immunohistochemical (IHC) staining for the proteins encoded by TP53 and SMAD4 has been extensively adopted in routine pathology practice. However, standardized IHC pattern classification schemes and rigorous validation of their predictive accuracy for underlying genomic alterations remain lacking in PDAC. METHODS: We retrospectively enrolled 63 PDAC patients and systematically characterized the typical IHC expression patterns of p53 and Smad4. Targeted NGS was subsequently performed on all available tumor specimens, and the resulting mutational profiles were correlated with corresponding IHC findings. Diagnostic performance including sensitivity, specificity and accuracy of p53 IHC for predicting TP53 mutations and of Smad4 IHC for predicting SMAD4 mutations was rigorously evaluated. RESULTS: Among the four canonical driver genes, co-occurring double- or triple-gene mutations were prevalent; within TP53 and SMAD4, missense mutations constituted the most frequent variant type. Using NGS as the reference standard, we validated the diagnostic utility of a three-tiered p53 IHC classification system, particularly in fine-needle biopsy (FNB) specimens. Furthermore, we proposed a novel, refined Smad4 IHC pattern classification that incorporates an "intermediate" category, thereby expanding upon conventional binary interpretation. This new scheme achieved markedly improved mutation prediction accuracy (0.76) compared with traditional approaches (0.57). CONCLUSION: Our study highlights the complementary diagnostic value of p53 and Smad4 IHC relative to molecular testing in PDAC, especially when tissue is limited, as commonly encountered in FNB specimens. The newly established Smad4 IHC classification system, which integrates an intermediate expression category into the conventional two-tier framework, demonstrates superior clinical utility and enhances predictive accuracy for SMAD4 genomic alterations.

Humans↗

PubMed2026

MET Exon 14 Skipping Mutation in NSCLC: From Genomic Discovery to Biomarker-Guided Therapeutic Innovation.

INTRODUCTION: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the MET exon 14 skipping mutation is a key oncogenic driver, which promotes tumor progression and provides a new direction for precision therapy. METHODS: A systematic search of English-language literature and clinical trial data related to the MET exon 14 skipping mutation from 2020-2025 was performed to summarize the role of the mutation and therapeutic advances. RESULTS: DNA-based next-generation sequencing (NGS), RNA-based NGS, and RT-qPCR were employed as the main detection methods. Preclinical models confirmed that mutations promote tumor progression by activating the RAS/MAPK pathway. Clinical trials have reported objective remission rates (ORR) of 46-68% for first-line treatment with MET inhibitors in NSCLC patients harboring MET exon 14 skipping mutations. DISCUSSION: MET exon 14 skipping mutation as a therapeutic target for NSCLC has made significant progress, and MET inhibitors are more advantageous than chemotherapy and immunotherapy, and have been recommended by national and international guidelines as a first-line treatment option. Additionally, NGS technology has the potential to dynamically monitor tumor evolution and drugresistant mutations, thereby helping to realize precision medicine. CONCLUSION: The MET exon 14 skipping mutation is an important target for the precision treatment of NSCLC, and MET-TKIs have remarkable efficacy but a prominent problem with drug resistance. The construction of a precision medicine system encompassing diagnosis, treatment, and drug resistance management through multi-omics research, technological innovation, and international collaboration is a key direction for improving prognosis.

Humans↗

PubMed2014

Combinatorial approaches for the identification of brain drug delivery targets.

The blood-brain barrier (BBB) represents a large obstacle for the treatment of central nervous system diseases. Targeting endogenous nutrient transporters that transcytose the BBB is one promising approach to selectively and noninvasively deliver a drug payload to the brain. The main limitations of the currently employed transcytosing receptors are their ubiquitous expression in the peripheral vasculature and the inherent low levels of transcytosis mediated by such systems. In this review, approaches designed to increase the repertoire of transcytosing receptors which can be targeted for the purpose of drug delivery are discussed. In particular, combinatorial protein libraries can be screened on BBB cells in vitro or in vivo to isolate targeting peptides or antibodies that can trigger transcytosis. Once these targeting reagents are discovered, the cognate BBB transcytosis system can be identified using techniques such as expression cloning or immunoprecipitation coupled with mass spectrometry. Continued technological advances in BBB genomics and proteomics, membrane protein manipulation, and in vitro BBB technology promise to further advance the capability to identify and optimize peptides and antibodies capable of mediating drug transport across the BBB.

Animals↗

PubMed2026

Tumor Mutational Landscape and Its Correlation With Histopathological Characteristics in Breast Cancer.

BACKGROUND/AIM: In breast cancer, knowledge of the associations between clinicopathologic characteristics, genetic changes, and subtype-specific patterns is expanding. This study investigated how pathological and clinical variables affect the actionability of Next Generation Sequencing (NGS)-based tumor molecular data. MATERIALS AND METHODS: 227 breast cancer patients referred to Genekor's laboratory for tumor molecular profile analysis were included in the study. Pathology records were used to assess critical clinicopathological features, including HER2, ER, PR, Ki67, grade, metastatic site, and age. A 1021-gene NGS-based multigene panel was utilized to assess tumor biology alongside tumor mutational burden (TMB) and microsatellite instability (MSI). RESULTS: Comprehensive genomic profiling revealed that 95.6% of the patients harbored at least one oncogenic or likely oncogenic alteration, highlighting the high diagnostic yield of NGS-based testing. Distinct subtype-specific patterns were observed: HR+/HER2- tumors were enriched for PIK3CA and ESR1 gene alterations, whereas triple-negative breast cancer (TNBC) was dominated by TP53 alterations. Clinically actionable alterations were most common in HR+/HER2- tumors (~60% on-label), whereas TNBC more often harbored off-label or trial-associated targets. The inclusion of tumor-agnostic biomarkers (TMB/MSI) increased on-label actionability up to 64.5% in HR+/HER2- tumors, primarily driven by TMB-high cases. Median TMB values were low, and age was the only independent predictor. Furthermore, the presence of actionable alterations was significantly higher in metastatic tumors, and TP53 alterations were associated with aggressive tumor characteristics. CONCLUSION: Comprehensive NGS-based genomic profiling identifies clinically actionable alterations in over half of breast cancer patients, with substantial variability across molecular subtypes. The HR+/HER2- subtype demonstrates the highest prevalence of on-label actionable biomarkers. These findings support the routine implementation of comprehensive genomic profiling, especially in metastatic HER2-negative breast cancer, to guide precision oncology strategies and enable enrollment in biomarker-driven clinical trials.

Humans↗

PubMed2026

Targeted Next-Generation Sequencing for Improved Clinical Outcomes in People Living With Rare Diseases in Global South: Protocol for a Systematic Review and Meta-Synthesis.

BACKGROUND: Rare diseases affect many individuals and pose major challenges in diagnosis and treatment, especially in Global South countries where health care resources are limited. Targeted next-generation sequencing (NGS) has significantly advanced diagnostic accuracy and clinical care for rare diseases globally; however, its implementation and impact within the Global South context remain insufficiently studied. OBJECTIVE: This study aims to evaluate the use, clinical benefits, challenges, and implementation outcomes of targeted NGS for diagnosing and managing rare diseases in Global South populations. Specifically, it seeks to quantify the diagnostic yield of NGS, examine its influence on subsequent clinical decision-making, and identify principal barriers to, and facilitators of, the implementation of targeted NGS approaches in these contexts. METHODS: This protocol follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We will systematically search PubMed, Scopus, and Web of Science for studies published between 2005 and 2025 that report on the use of targeted NGS in Global South population with rare diseases. Two reviewers will independently perform study selection, data extraction, quality assessment, and evaluation of risk of bias by using QUADAS-2 for diagnostic accuracy studies and the risk of bias assessment tool for nonrandomized studies. Meta-analyses will be conducted to estimate pooled outcomes for diagnostic yield, with heterogeneity assessed using random effects models. Heterogeneity will be further examined through visual inspection of forest plots and by evaluating the chi-square test and I² statistic. RESULTS: The protocol has been registered with PROSPERO (CRD420251078455). Database search or screening, data extraction, and data synthesis are planned to commence in June 2026 and conclude by September 2026. Study findings will synthesize the diagnostic yield, clinical impact, and contextual determinants influencing the implementation of targeted NGS in Global South health care settings. CONCLUSIONS: This review will provide evidence on the application, advantages, limitations, and clinical outcomes of targeted NGS for individuals affected by rare diseases in countries of the Global South. The finding will identify priorities for capacity strengthening, policy development, and future genomic research. TRIAL REGISTRATION: PROSPERO CRD420251078455; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251078455. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/85150.

Rare Diseases↗

PubMed2026

The Rh blood group system: RHCE update.

While the previous review encompassed the Rh blood group system (Chou ST, Westhoff CM. The Rh and RhAG blood group systems. Immunohematology. 2010;26:178-86), this update focusses on the RHCE gene and its variants. Four new antigens- PARG, CEVF, CEWA, and CETW (RH60 to RH63)-were reported since the last update. RHCE*cEMI (RHCE*03.31) was amended from a null allele to an allele encoding very weak antigen expression. The following topics are discussed: cross-reactive alleles [such as RHCE*ceHAR (*01.22.01) and RHCE*ceCF (*01.20.06) which may type D+ with some monoclonal anti-D reagents], issues with hybrid alleles and allele dropout, common haplotypes (association between RHCE alleles and specific RHD alleles), and clinical considerations. While the detailed description of new Rh antigens has become rare, many RHCE alleles have been reported since the previous review, a result of increased adoption of DNAbased testing for red blood cell antigens in immunohematology laboratories. The Rh blood group system has fascinated generations of immunohematologists and is likely to continue to do so for decades to come.

Rh-Hr Blood-Group System↗

PubMed2026

Differentiating tuberculous pleurisy from pulmonary tuberculosis using mNGS: a multicenter cohort analysis.

BACKGROUND: Tuberculous pleurisy (TBP), a major extrapulmonary form of tuberculosis, is characterized by a paucibacillary state that makes diagnosis challenging. Metagenomic next-generation sequencing (mNGS) has emerged as a promising approach for MTB detection; however, its discriminatory value between TBP and pulmonary tuberculosis (PTB) among mNGS-confirmed cases, and its integration with clinical features for differential diagnosis, remain insufficiently defined. METHODS: This multicenter retrospective cohort included hospitalized patients with MTB-positive mNGS results from January 2020 to January 2025. As only mNGS-positive cases were included, overall mNGS diagnostic sensitivity cannot be estimated. Twelve TBP patients were matched 1:2 with twenty-four PTB patients by age and sex; patients with immunosuppressive conditions were excluded prior to matching. Clinical, laboratory, mNGS, and conventional TB test data were collected. Logistic regression and ROC analyses were performed. RESULTS: Conventional tests showed limited sensitivity in TBP despite universal mNGS positivity. MTB read counts were similar between groups (median 1976.5 vs. 990.0, P = 0.920). Pleural-derived specimens predominated in TBP (41.7% vs. 4.2%, P = 0.007). CRP demonstrated the highest individual discriminatory value (AUC = 0.658, P = 0.131), though no single predictor reached significance. A combined model (cough, fever, CRP, WBC) showed modest non-significant improvement (AUC = 0.722, overall P = 0.359; sensitivity 66.7%, specificity 83.3%). Given EPV ≈ 3, all findings are exploratory only. No significant prognostic predictors were identified in TBP; a non-significant trend toward lower lymphocyte counts was observed in patients with unfavorable outcomes (0.60 vs. 1.10 ×109/L, P = 0.115). CONCLUSIONS: Among mNGS-confirmed cases, MTB read counts were comparable between TBP and PTB. No single parameter reliably distinguished the two; a combined clinical model showed modest improvement but requires prospective validation in larger cohorts. Integrating mNGS with systematic clinical evaluation remains essential for accurate TB diagnosis.

Humans↗

PubMed2026

Genomic characterization of avian metapneumovirus subtypes A and B in United States poultry by targeted amplicon sequencing.

Avian metapneumovirus (aMPV) subtypes A and B emerged in United States poultry in late 2023 and early 2024, prompting genome-scale surveillance from clinical samples. Here, we developed and optimized targeted amplicon sequencing (TAS) assays for both subtypes and applied them to 104 subtype-positive clinical samples collected from chicken and turkey farms across nine US states between early 2024 and early 2026. TAS recovered 91 genomes suitable for comparative analysis, including 44 aMPV-A and 47 aMPV-B sequences, with successful recovery extending to Ct values of 34.6 for aMPV-A and 31.2 for aMPV-B. Recovered genomes showed near-complete breadth and high mapping efficiency. Phylogenetic analyses of both G-gene and whole-genome datasets showed that US aMPV-A field strains formed a distinct monophyletic lineage within group IV and resolved into three closely related clusters. Cluster 2, first recognized in North Carolina and later detected in Ohio, spread across 30 turkey and chicken farms. Cluster 2 genomes were defined by a concentrated G-protein hotspot within residues 209-275, and most North Carolina Cluster 2 genomes carried 10-11 nonsynonymous substitutions in this region, including multiple proline substitutions suggestive of local structural change. Missouri Cluster 3 remained cohesive but distinct from both Cluster 1 and Cluster 2 in the G-gene and whole-genome trees. In contrast, US aMPV-B field strains remained highly homogeneous across hosts and states, with more than 99% nucleotide identity by both G-gene and WGS analyses. We also identified 12 vaccine-derived genomes on both vaccinated and nonvaccinated farms. These included six genomes related to aMPV-A vaccine and six related to aMPV-B vaccines (VCO3/50 and 1062), all of which retained vaccine-defining markers together with additional substitutions consistent with continued circulation after vaccine use in the field. Selection analyses showed that the G gene had the highest gene-wise dN/dS ratio in both subtypes. Additional elevated signal was observed in SH and M2, and candidate positively or episodically selected codons were concentrated in the subtype A Cluster 2 G-gene hotspot. These findings show that TAS supports direct-from-sample aMPV genomic surveillance and provides genomic context for field clusters, vaccine-derived lineages, and continued adaptive change in aMPV in US poultry.

Animals↗

PubMed2026

Integrating metagenomic next-generation sequencing into a multimodal diagnostic framework for spinal infection: enhancing etiological identification and clinical prediction.

BACKGROUND: Spinal infection (SI) remains diagnostically challenging because of heterogeneous etiologies, nonspecific clinical manifestations, and the limited sensitivity of conventional microbiological approaches, particularly following empirical antimicrobial exposure. Although metagenomic next-generation sequencing (mNGS) enables unbiased pathogen detection, its incremental clinical value beyond pathogen identification and its role within integrated diagnostic strategies remain incompletely established. METHODS: We retrospectively analyzed 208 consecutive patients with suspected SI between August 2022 and August 2025. Final diagnoses were established using a multidisciplinary-adjudicated composite reference standard incorporating clinical, radiological, microbiological, and histopathological evidence. The diagnostic performance of mNGS was compared with conventional culture and histopathology. Furthermore, multimodal predictive models integrating clinical variables and microbiological information were developed using L1-regularized logistic regression. RESULTS: In the comparative cohort, mNGS achieved a significantly higher diagnostic yield than culture (66.5% vs. 27.41%, P < 0.001). Among confirmed SI cases, mNGS demonstrated higher sensitivity than conventional culture (91.67% vs. 40.15%, P < 0.001). mNGS identified a substantially broader pathogen spectrum, ranging from fastidious organisms such as Mycobacterium tuberculosis and Brucella to rare pathogens including Talaromyces marneffei and Coxiella burnetii, and maintained robust sensitivity (98.2%) despite prior antibiotic exposure. While an integrated clinical model achieved an AUC of 0.916, mNGS as a standalone modality provided superior discriminative power (AUC = 0.889) compared to histopathology (AUC = 0.836), the Conventional Biomarker Model (AUC = 0.742), and culture (AUC = 0.693). CONCLUSIONS: mNGS is a high-yield diagnostic tool for spinal infection, particularly in culture-negative and antibiotic-pretreated scenarios. Integrating mNGS into a multimodal clinical framework facilitates etiological clarity and precision antimicrobial therapy.

Humans↗