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nf-core/pacsomatic: a scalable somatic analytic pipeline using PacBio HiFi data.

MOTIVATION: Pacific Biosciences (PacBio) HiFi long-read sequencing enables robust characterization of complex genomic regions, repetitive elements, and structural variants (SVs) that are often inaccessible to short-read technologies. To fully leverage HiFi reads to advance cancer genomics and epigenetics, researchers require an end-to-end, scalable and optimized bioinformatics workflow. The nf-core framework meets this need by providing rigorously tested, community-curated pipelines that ensure reproducibility, transparency, and broad compatibility across computational environments. RESULTS: We present nf-core/pacsomatic, an automated Nextflow DSL2 pipeline designed for comprehensive paired tumor-normal somatic analysis using PacBio HiFi data. The workflow includes steps for read alignments against reference genome, somatic SNV/indel, SV, and CNV calling, CpG methylation profiling and differential methylation region (DMR) detection. Additional downstream modules support functional annotation, mutational signature analysis, tumor purity and ploidy estimation, and homologous recombination deficiency (HRD) assessment. Utilizing nf-core's modular design and containerized execution, nf-core/pacsomatic provides a stable framework for the reproducible discovery of biological insights. AVAILABILITY: nf-core/pacsomatic is available under the MIT License at nf-core (https://nf-co.re/pacsomatic) and github (https://github.com/nf-core/pacsomatic).

Software

Pangenomes aid accurate detection of large insertions and deletions from targeted sequencing: the case of cardiomyopathies.

BACKGROUND: Gene panels represent a widely used strategy for genetic testing in a vast range of Mendelian disorders. While this approach aids reliable bioinformatic detection of short coding variants, it often fails to detect many larger variants. Recent studies have recommended the adoption of pangenome references (as opposed to linear reference genomes like GRCh38) to augment detection of large variants from targeted sequencing, potentially providing diagnostic laboratories with the possibility to streamline diagnostic work-ups and reduce costs. METHODS: Here, we analyze 1969 cardiomyopathy cases and 1805 controls sequenced with the Illumina Trusight Cardio panel using a pangenome-based workflow (GRAF) and five conventional orthogonal methodologies (GATK HaplotypeCaller, GATK-gCNV, ExomeDepth, Manta and Lumpy-SV) to detect variants ≥ 20 bp in size. RESULTS: Following lab-based variant validation by means of PCR and Sanger sequencing, we show that GRAF conjugates higher precision and recall (F1 score 0.86) compared with other methods (F1 0-0.57) in detecting potentially pathogenic variants ≥ 20 bp from short-read panel data. Results were complemented by a comparison of the tools' performance in detecting ground truth variants on reference sample HG002 from Genome In A Bottle, which confirmed GRAF to outperform other tools also on exome sequencing (F1 0.97 vs. 0-0.94). Notably, in the HG002 benchmark dataset, GRAF also showed slightly improved performance compared to GATK HaplotypeCaller in the identification of small variants (1-19 bp; F1 0.975 vs. 0.968). CONCLUSIONS: Our results indicate that pangenome-based workflows aid improved detection of large variants from targeted sequencing data in the clinical context and suggest that they may contribute to more unified variant detection frameworks for all-size genetic variants in the future.

Humans

Characterisation of Bordetella pertussis virulence and macrolide resistance in Australia by targeted culture-independent sequencing: a genomic epidemiology study.

BACKGROUND: Bordetella pertussis continues to circulate globally despite widespread vaccination, with a notable epidemic in 2024. Its resurgence is confounded by the emergence of pertactin-deficient, macrolide-resistant B pertussis strains in Asia and Europe, which are under-recognised by conventional diagnostics. We aimed to apply targeted culture-independent next-generation sequencing (tNGS) of respiratory specimens to improve global B pertussis diagnostic capability and genomic surveillance. METHODS: We did a nationwide genomic epidemiology study of B pertussis RT-PCR-positive respiratory specimens that were retrospectively and prospectively collected by diagnostic and public health laboratories in six of seven states and territories of Australia. Specimens underwent tNGS and macrolide-resistant B pertussis-specific PCR, and an opportunistic subset from New South Wales and Queensland were cultured for confirmatory susceptibility testing and whole-genome sequencing. Sequencing data were analysed for genome recovery, virulence profiles, and macrolide resistance mutations, and were compared with international macrolide-resistant B pertussis genomes and ancestral Australian genomes. The performance of the tNGS approach was assessed with logistic regression relative to RT-PCR cycle threshold values, and sensitivity and specificity values were calculated. FINDINGS: 255 respiratory specimens positive for B pertussis were included in the study. 64 (25%) were retrospectively collected between Jan 12, 2012, and Dec 31, 2023, and 191 (75%) were prospectively collected between Jan 1 and Oct 28, 2024. Of these 255 specimens, 148 (58%) yielded near-complete B pertussis genomes through tNGS. Seven co-circulating lineages of B pertussis were documented, including two associated with macrolide-resistance. Eight epidemiologically unrelated and geographically dispersed cases of macrolide-resistant B pertussis with a 23S rRNA 2037A→G mutation were identified by tNGS and confirmed by whole-genome sequencing. Three of these were further validated by phenotypic testing. The estimated prevalence of macrolide resistance among Australian cases positive for B pertussis was 4% (eight of 188). INTERPRETATION: tNGS can recover near-complete B pertussis genomes directly from clinical specimens, enabling identification of macrolide resistance mutations and high-resolution phylogenetic analysis. These findings show that tNGS complements PCR-based surveillance by providing genome-wide assessment of resistance, virulence, and genomic diversity in a single workflow. FUNDING: NSW Health Prevention Research Support Program.

Macrolides

Semiparametric efficient estimation of small genetic effects in large-scale population cohorts.

Population genetics seeks to quantify DNA variant associations with traits or diseases, as well as interactions among variants and with environmental factors. Computing millions of estimates in large cohorts in which small effect sizes and tight confidence intervals are expected, necessitates minimizing model-misspecification bias to increase power and control false discoveries. We present TarGene, a unified statistical workflow for the semi-parametric efficient and double robust estimation of genetic effects including $ k $-point interactions among categorical variables in the presence of confounding and weak population dependence. $ k $-point interactions, or Average Interaction Effects (AIEs), are a direct generalization of the usual average treatment effect (ATE). We estimate genetic effects with cross-validated and/or weighted versions of Targeted Minimum Loss-based Estimators (TMLE) and One-Step Estimators (OSE). The effect of dependence among data units on variance estimates is corrected by using sieve plateau variance estimators based on genetic relatedness across the units. We present extensive realistic simulations to demonstrate power, coverage, and control of type I error. Our motivating application is the targeted estimation of genetic effects on trait, including two-point and higher-order gene-gene and gene-environment interactions, in large-scale genomic databases such as UK Biobank and All of Us. All cross-validated and/or weighted TMLE and OSE for the AIE $ k $-point interaction, as well as ATEs, conditional ATEs and functions thereof, are implemented in the general purpose Julia package TMLE.jl. For high-throughput applications in population genomics, we provide the open-source Nextflow pipeline and software TarGene which integrates seamlessly with modern high-performance and cloud computing platforms.

Humans

Community-driven updates for comprehensive long-read metagenomics and enhanced binning in nf-core/mag v5.

SUMMARY: nf-core/mag is a reproducible Nextflow pipeline for best-practice metagenomic de novo assembly and binning within the nf-core framework. Here we present a major update that adds support for long-read-only assembly and bin refinement, includes five new binning tools, expands taxonomic classification to viruses and eukaryotes, and improves bin quality evaluation with new tools and latest databases. Through sustained community-driven development spanning seven years and four primary curator teams, nf-core/mag remains actively developed as an open source workflow for metagenomic analysis, benefiting from contributions from across the broader metagenomics, nf-core, and Nextflow ecosystem. AVAILABILITY AND IMPLEMENTATION: The source code of nf-core/mag v5 is available on GitHub (https://github.com/nf-core/mag) under the open source MIT license, with v5.5.0 source code archived on Zenodo (https://zenodo.org/records/21735731). Documentation is viewable on the nf-core website (https://nf-co.re/mag).

Metagenomics

Clinical Variant Interpretation with the Integrative Genomics Viewer (IGV) for Molecular Pathologists.

The integrative genomics viewer (IGV) is a pivotal tool in clinical genomics, enabling the visualization and interpretation of complex sequencing data. Bringing clinical knowledge to bear with visual evaluation of sequencing results is the primary means by which molecular pathologists and other professionals assess and finalize cases. A variety of software tools can assist, but their relationship to the underlying data must be understood and applied systematically. This study includes essential background on next-generation sequencing (NGS) data file types (e.g., FASTQ, BAM, VCF) with a discussion of their format and purpose. We then describe features of IGV that derive nuances from these files. We utilize a series of curated practical cases based on clinical vignettes through which the reader will interact with clinical NGS sequencing data using the IGV software to review various types of clinically relevant variants relative to the human reference genome. These clinical vignettes have been curated to describe examples of some of the complexities of interpretation of genomic data, and how utilizing IGV as part of a routine workflow can provide additional interpretive information for variants beyond routine bioinformatic software algorithm variant calls. The visual inspection of genomic variants utilizing the tools within IGV can unmask subtle contextual cues (i.e., variant allele frequency, strand bias, tissue-specific context) that can influence the interpretation of genomic variants. Although this study focuses on using IGV for the detection and interpretation of somatic variants, the provided applications can be extrapolated for use in the germline setting, including analysis of complex variants and detection of mosaicism.

Humans

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

Integrating Next-Generation Sequencing into von Willebrand Disease Diagnostics: Insights from the PCM-EVW-ES Multicenter Project.

Von Willebrand disease (VWD) is the most common inherited bleeding disorder, caused by quantitative or qualitative defects in von Willebrand factor (VWF). Diagnosis is challenging and requires integrating bleeding history, VWF antigen and activity measurements, FVIII assays, and specialized phenotyping. Genetic testing is increasingly recognized as a key component. Here, we review current concepts in VWD diagnostics and highlight the Spanish Clinical and Molecular Profile of von Willebrand Disease (PCM-EVW-ES) project as a model for genomics-enabled precision medicine. PCM-EVW-ES is a multicenter initiative involving 48 hospitals, centralized phenotypic testing, and next-generation sequencing of the VWF coding region, enabling definitive classification in 730 individuals with VWD to date. Harmonized recruitment criteria and standardized workflows improve subtype assignment, uncover complex genotypes, refine genotype-phenotype correlations, and facilitate the identification of asymptomatic carriers. The PCM-EVW-ES variant spectrum highlights recurrent disease-causing variants in Spain and underscores the value of coordinated national registries for variant curation. Building on these data, we propose a diagnostic algorithm in which bleeding assessment and first-line VWF/FVIII assays, combined with, early VWF molecular testing increases diagnostic accuracy and guides targeted second-line investigations to confirm and refine VWD subtype classification. We also outline persisting challenges, including the interpretation of variants of uncertain significance and patients without identifiable pathogenic VWF variants, and future directions integrating third-generation sequencing, expanded gene panels, functional studies, and artificial-intelligence-driven multiomic approaches. Together, these advances illustrate how robust multicenter studies can bridge the gap between complex diagnostics and clinical practice in VWD.

Humans

Diagnostic and phylogenetic perspectives of the 2023 Murray Valley encephalitis virus outbreak in Australia: an observational study.

BACKGROUND: An outbreak of Murray Valley encephalitis virus (MVEV), the largest since 1974, was observed in Australia between Jan 1 and July 31, 2023. This study aims to characterise the utility of diagnostic platforms, testing algorithms, and genomic characteristics of MVEV to facilitate a comprehensive framework for MVEV testing and surveillance in the outbreak setting. METHODS: In this observational study, we assessed flavivirus diagnostics for all patients with suspected Murray Valley encephalitis in Australia from Jan 1 to July 31, 2023. We included all patients with confirmed Murray Valley encephalitis, probable Murray Valley encephalitis, or acute unspecified flavivirus infection using the Communicable Diseases Network Australia case definition. Cases were excluded if an alternative diagnosis was identified. We collected blood, serum, cerebrospinal fluid, brain tissue, urine, or a combination of these samples, as appropriate and at the discretion of the treating clinician. We conducted multimodal diagnostic testing, which included flavivirus-specific serological and nucleic acid amplification testing. Metagenomic next-generation sequencing, including next-generation deep sequencing, target-enrichment, and targeted amplification, was conducted on human and representative mosquito-derived samples obtained from established mosquito population surveillance programmes for phylogenetic analysis. FINDINGS: 27 patients with encephalitis were assessed for MVEV between Jan 1, 2023, and July 31, 2023, 23 (85%) of whom fulfilled national case definitions for confirmed Murray Valley encephalitis. Patient ages ranged from 6 weeks to 83 years (median 62·0 years [IQR 31·0-67·5]) and patients were mostly male (21 [78%] male patients and six [22%] female patients). Incidence varied widely by geographical region and was highest in the Northern Territory (32·0 per 1 000 000 population). Diagnostic specimen collection generally occurred promptly (median 6·0 days [IQR 4·0-14·5] from symptom onset to diagnostic specimen collection). In seven patients, case assignation relied on convalescent serum samples to assess for seroconversion or an appropriate rise in antibody titre (to four times the initial value or greater), or both. MVEV-specific IgM was detectable in serum samples of 17 (81%) of 21 patients tested by day 7 and MVEV IgG or total antibody (TAb) were detected in 18 (100%) of 18 patients tested by day 30. MVEV-specific IgM (or TAb) and MVEV RNA were detected in cerebrospinal fluid collected within 14 days of symptom onset in nine (39%) of 23 patients and seven (28%) of 25 patients, respectively. Phylogenetic analysis revealed two circulating MVEV genotypes, G1A and G2, in mosquitoes and humans in 2023. In southeast Australia, only G1A was detected and probably introduced from enzootic foci in northern Australia. INTERPRETATION: This study provides a comprehensive overview of the diagnostic workflows and phylogenetic evaluations used during the 2023 MVEV outbreak in Australia, emphasising the importance of a multimodal approach for accurate and timely confirmation of flavivirus infection. Further One Health surveillance for MVEV and other zoonotic flaviviruses is key, given potential expanded ecological niches in the context of episodic climatic events. FUNDING: None.

Humans

TaxTriage: an open-source metagenomic sequencing data analysis pipeline enabling putative pathogen detection.

MOTIVATION: TaxTriage is a comprehensive pathogen identification workflow designed for both short- and long-read untargeted DNA and RNA sequencing data. Combining read classification, mapping, and de novo assembly approaches, putative pathogens are identified through comparisons to curated pathogens and abundance expectations from healthy cohort data. Flexible installation options are enabled using Nextflow™ (NF), including cloud deployment via NF Tower (Seqera Platform) and local installation on a variety of systems, including standalone installations without external internet access. Final analysis summaries are compiled into an Organism Discovery Report, which lists likely pathogens and supporting data, including a custom confidence score. RESULTS: Evaluation of published in silico, clinical, and outbreak datasets identified performance comparable to alternative cloud-based processing pipelines for expected pathogen and co-infection detection with similar sensitivity and increased specificity. To support both public health and veterinary diagnostics communities, customization options have been incorporated to enable improved performance for host species of interest. AVAILABILITY AND IMPLEMENTATION: Source code for TaxTriage is freely available at https://github.com/jhuapl-bio/taxtriage. TaxTriage v2.1.1 has been archived on Zenodo at https://zenodo.org/records/17081354 to permit reproducible analysis as described in this manuscript.

Software

A microcosting and cost consequence analysis from a randomized controlled trial comparing genome sequencing with exome sequencing for genetic diagnosis.

PURPOSE: Diagnosing rare diseases is costly. The objectives were to microcost exome (ES) and genome sequencing (GS) trios and estimate the incremental costs of GS per additional diagnosis from an institutional payer perspective. METHODS: Trios (proband plus biological parents) that are referred for sequencing were randomly assigned to ES or GS. Laboratory workflow and sequencing were microcosted. Total and category cost per trio were estimated probabilistically. Effectiveness was expressed as diagnostic yield (rates of diagnostic or partially diagnostic variants detected). Incremental costs and effectiveness were calculated. RESULTS: The mean total cost per trio was CAD 2888.79 (95% CI 2567.72, 3492.72) for ES (n = 329) and 4364.02 (95% CI 3984.94, 5013.67) for GS (n = 324). Reagents accounted for 34% and 61% of total costs for ES and GS, respectively. The incremental cost of GS was 1475.23. The diagnostic yield was 35.9% for ES and 32.7% for GS with a difference of 0.032 (95% CI: -0.041, 0.104, P value .397). CONCLUSION: GS demonstrated higher costs and a similar diagnostic yield to ES but was limited by technical capabilities at the time of the study. The study provides comprehensive costs for the economic evaluation comparing alternative diagnostic pathways and impetus for further evaluating variants uniquely detectable by GS.

Humans

OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.

MOTIVATION: Structural variants (SVs) influence gene regulation, disease progression, and diagnostics, yet integrating SV calls across platforms remains difficult due to inconsistent annotations, limited merging flexibility, and fragmented workflows. Ambiguous breakend (BND) annotations, which comprise many variant calls, are often discarded or misclassified, hindering variant characterization. Existing tools lack advanced merging operations essential for precise identification of disease-specific or somatic variants across samples or patient groups. Additionally, current SV analysis pipelines require extensive manual intervention and complex parameter tuning, compromising reproducibility and scalability. Addressing these gaps is crucial for improving the accuracy, interpretability, and clinical utility of SV analyses. RESULTS: We developed OctopuSV and TentacleSV to address these long-standing challenges in SV analysis. OctopuSV features a specialized BND correction module that converts ambiguous BND annotations into canonical SV types, recovering important variants that are often overlooked by existing tools. Additionally, it provides advanced set operations (difference, complement, custom-defined) that enable sophisticated variant filtering without programming expertise, critical for identifying tumor-specific SVs or variants unique to specific sample groups. TentacleSV completes our solution by automating the entire SV analysis process from raw sequencing data to high-confidence callsets, ensuring consistency and reproducibility across projects. Benchmarking across short-read and long-read platforms showed superior F1 score, complete SV type consistency compared to existing tools. Our framework enables experimental biologists and clinical researchers to perform sophisticated analyses ranging from cancer subtype-specific SV identification to multi-sample comparative studies without requiring specialized programming skills. AVAILABILITY AND IMPLEMENTATION: All codes are available at https://github.com/ylab-hi/OctopuSV; https://github.com/ylab-hi/TentacleSV.

Software

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.

Circulating Tumor DNA

The diagnostic potential of combined quantitative polymerase chain reaction and next-generation sequencing using the same primers for periprosthetic joint infection.

Next-generation sequencing (NGS) enables the detection of specific pathogens unidentifiable by conventional cultures, but its application in orthopedics remains inconsistent due to background contamination and irreproducible findings. This study evaluated the diagnostic performance of a novel workflow combining broad-range 16S rRNA gene quantitative PCR (qPCR) screening with downstream NGS, focusing on bacterial biomass thresholds. The qPCR assay demonstrated excellent intrarater reliability, with an intraclass correlation coefficient (ICC) of 0.961 (95% confidence interval, 0.881 to 0.997). Based on serially diluted positive controls, a quantitative threshold of 10⁵ CFU/mL was established as the minimum concentration required for the consistent detection of fastidious taxa, such as Escherichia coli. When evaluated against conventional cultures using 95 sonicate fluid and 276 pre/intraoperative tissue samples, the qPCR assay achieved a sensitivity of 80% and a specificity of 72%. Subsequent NGS sequencing of 26 clinical samples and 9 controls showed concordance in 4 of 6 culture-positive infected cases with NGS taxonomy, whereas the remaining discrepancies were likely attributable to culture-based phenotypic misidentification. Notably, among the qPCR-positive cases, three were culture-negative, including two hip prosthesis loosening cases exhibiting polymicrobial profiles, and one post-traumatic osteoarthritis case harboring low-level Staphylococcus. Crucially, this post-traumatic patient developed delayed periprosthetic joint infection (PJI) 2 years post-surgery, with cultures identifying Staphylococcus previously detected by the initial NGS analysis. Integrating qPCR screening with targeted NGS effectively refines pathogen identification, filters environmental artifacts, and overcomes the diagnostic limitations of culture-negative infections in orthopedic practice.IMPORTANCENext-generation sequencing (NGS) enables the detection of specific pathogens in clinical samples that are not identifiable by conventional methods. However, NGS applications in orthopedics have not been quantitatively evaluated, and findings have been inconsistent owing to contaminants and the presence of non-credible causative organisms. These factors primarily stem from the failure to evaluate low-biomass samples and the absence of proper controls, such as negative controls or mock community DNA samples. This study demonstrates that interpreting results from low-biomass samples requires careful consideration because NGS relies on relative bacterial abundances; distinguishing likely pathogens from contaminants is particularly challenging when bacterial loads are low. We demonstrated that combining NGS with quantitative PCR (qPCR) and applying a Cq cutoff can reduce false positives.

Humans

Clinical impact of 16S rRNA RC-PCR NGS on infectious disease management.

16S rRNA metagenomics provides a culture-independent method for diagnosing infections with fastidious or uncultivable organisms, guiding targeted therapy, and detecting polymicrobial communities. This study utilizes reverse complement (RC)-PCR next-generation sequencing (NGS) to accurately identify bacterial pathogens from clinical specimens and assess its impact on clinical decision-making, setting it apart from conventional 16S sequencing approaches. A retrospective analysis of an ISO 15189 accredited 16S RC-PCR NGS diagnostic workflow targeting the V1-6 and V9 regions of the 16S rRNA gene was conducted over a 2-year period, including 390 clinical specimens from 316 patients. 16S RC-PCR NGS results were discussed in a multidisciplinary consultation and subsequently reported to the clinic. In total, 1,283 RC-PCR results were analyzed, of which 517 were from clinical specimens, 284 were negative controls, 66 were positive controls, and 416 were from wet lab and bioinformatic pipeline validation. 16S RC-PCR NGS assay detected bacterial taxa in 179/390 (45.9%) of clinical specimens, while 201/390 (51.5%) were negative, and 10/390 (2.6%) yielded uninterpretable results. The specimen types pus, pleural fluid, and heart valves exhibited the highest positivity rate (68% to 70%). Overall, 16S RC-PCR NGS influenced diagnostic decision making in 145/282 (51.4%) clinical cases and guided therapeutic management in 77/282 (27.3%) cases. Results providing definite evidence for either the presence or absence of bacterial infection were considered clinically valuable. Integration of 16S RC-PCR NGS pathogen detection with multidisciplinary consultation markedly improved clinical management, directly impacting diagnosis and treatment of complex clinical cases in a tertiary care setting. The effect was most pronounced in brain abscess patients, where RC-PCR results guided treatment decisions in 9/13 (69.2%) of cases.IMPORTANCETimely and accurate diagnosis is essential for managing serious infections, yet clinicians often face situations where routine laboratory tests do not provide clear answers. This study demonstrates that next-generation sequencing (NGS) of the bacterial 16S rRNA gene can decisively resolve these uncertainties. By revealing whether bacteria are present in clinical specimens, this approach influenced clinical reasoning and supported treatment decisions across a variety of challenging cases. 16S reverse-complement PCR was especially powerful for brain abscesses and infections where the causative microorganism was unclear, providing clarity that directly improved patient care. These findings show that integrating advanced sequencing with expert clinical interpretation can enhance the management of complex infections and support more confident, evidence-based therapy.

Humans