Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases DOI Creative Commons
Yu Zhao, Wenhui Zhang, Xin Zhang

et al.

Frontiers in Cellular and Infection Microbiology, Journal Year: 2024, Volume and Issue: 14

Published: Nov. 15, 2024

Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines fundamental principles, workflow, platforms utilized mNGS technology. The methodological backbone involves shotgun total nucleic acids extracted diverse sample types, enabling simultaneous detection bacteria, viruses, fungi, parasites without prior knowledge agent. Key advantages include its capability identify rare, novel, or unculturable pathogens, providing more comprehensive view communities compared traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, need for optimized preparation protocols remain significant hurdles. application across various systemic infections highlights utility. Case studies discussed this illustrate efficacy diagnosing respiratory tract infections, bloodstream central nervous system gastrointestinal others. By rapidly identifying pathogens their genomic characteristics, facilitates timely targeted therapeutic interventions, thereby improving patient outcomes infection control measures. Looking ahead, future disease diagnostics appears promising. Advances bioinformatics tools technologies are anticipated streamline analysis, enhance sensitivity specificity, reduce turnaround times. Integration with decision support systems promises further optimize utilization routine practice. In conclusion, represents paradigm shift field diagnostics, offering unparalleled insights into diversity pathogenesis. While persist, ongoing technological advancements hold immense potential consolidate pivotal tool armamentarium modern medicine, empowering clinicians precise, rapid, pathogen capabilities.

Language: Английский

Recent developments in Aspergillus fumigatus research: diversity, drugs, and disease DOI
Nicole Kordana, Angus Johnson, Karen Quinn

et al.

Microbiology and Molecular Biology Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

SUMMARY Advances in modern medical therapies for many previously intractable human diseases have improved patient outcomes. However, successful disease treatment outcomes are often prevented due to invasive fungal infections caused by the environmental mold Aspergillus fumigatus . As contemporary antifungal not experienced same robust advances as other therapies, defining mechanisms of A. initiation and progression remains a critical research priority. To this end, World Health Organization recently identified priority pathogen Centers Disease Control has highlighted emergence triazole-resistant isolates. The expansion diversity host populations susceptible aspergillosis complex dynamic genotypic phenotypic call reinvigorated assessment pathobiological drug-susceptibility mechanisms. Here, we summarize recent advancements field discuss challenges our understanding heterogeneity its pathogenesis diverse populations.

Language: Английский

Citations

1
Experience of implementing metagenomic next-generation sequencing in patients with suspected pulmonary infection in clinical practice DOI Creative Commons
Yuting Lai,

B Y Chen,

Sida Chen

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 20, 2025

Pulmonary infections remain a leading cause of infectious disease-related hospitalizations. Metagenomic next-generation sequencing (mNGS) has emerged as promising diagnostic tool for identifying pathogens responsible pulmonary infections. However, implementing mNGS in clinical practice presents several challenges. We conducted retrospective analysis 97 patients with suspected who were admitted to our hospital and underwent alongside conventional microbiologic tests (CMT) over the past three years. compared efficacy versus CMT assessed applications challenges associated managing detected 63.9% cases, outperforming (27.8%) showing notable improvements Mycobacterium, fungal species, rare pathogens. Antibiotic regimens adjusted 77.4% positive results, improvement observed 93.5%. Of 138 microbial strains initially identified by possible pathogens, 65 (47.1%) reclassified colonizing organisms upon further evaluation, including bacteria fungi commonly Notably, one patient was diagnosed aspiration pneumonia due oral anaerobes, which had categorized normal flora. In conclusion, serves valuable approach infections, enhancing etiologic precision informing management. Nevertheless, comprehensive interpretation mNGS-identified microorganisms is essential achieve accurate diagnosis.

Language: Английский

Citations

0
New high accuracy diagnostics for avianAspergillus fumigatusinfection using Nanopore methylation sequencing of host cell-free DNA and machine learning prediction DOI Creative Commons
Markus Drag, Christina Hvilsom, Louise Ladefoged Poulsen

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Abstract Avian aspergillosis is a detrimental fungal infection affecting wild and domestic birds yet sensitive antemortem diagnostics for early clinical infections are lacking. Here we present new Aspergillus fumigatus ( Af ) developed from cell-free DNA (cfDNA) methylation markers. Broiler chickens were experimentally infected with either Af, non- agent Escherichia coli or Gallibacterium anatis assigned as controls. Oxford Nanopore (ONT) sequencing was performed on serum cfDNA (n = 124), machine learning (ML) models trained infection-specific Three tests developed: A ‘High Accuracy’ test best performance (sensitivity: 100%, specificity: 89.2%) robustness (ROC-AUC: 0.92) well ‘Fast’- ‘In situ’ rapid turnaround PCR. Diagnostic accuracies 92.3%, 82.7%, 73.1%, respectively. In conclusion, using ML- host markers demonstrated high diagnostic comparable to microbial (mcfDNA) but without concern environmental contamination. Key highlights We three accuracy in that use (cfDNA). Differentially methylated regions (DMRs) detected by used train development of tests. The highest found 83 10 kilobases (KB) the glmnet algorithm ML model, which classified 92.3% blinded samples correctly. Fast designed cheap <1h adaptive sampling could correctly classify 82.7% 22 random forest (rf) model. An situ only four markers, envisioned simple methylation-specific PCR (MSP-PCR) assay, 73.1% samples. Reference values associated probabilities calculated each presented further evaluation.

Language: Английский

Citations

0
Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases DOI Creative Commons
Yu Zhao, Wenhui Zhang, Xin Zhang

et al.

Frontiers in Cellular and Infection Microbiology, Journal Year: 2024, Volume and Issue: 14

Published: Nov. 15, 2024

Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines fundamental principles, workflow, platforms utilized mNGS technology. The methodological backbone involves shotgun total nucleic acids extracted diverse sample types, enabling simultaneous detection bacteria, viruses, fungi, parasites without prior knowledge agent. Key advantages include its capability identify rare, novel, or unculturable pathogens, providing more comprehensive view communities compared traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, need for optimized preparation protocols remain significant hurdles. application across various systemic infections highlights utility. Case studies discussed this illustrate efficacy diagnosing respiratory tract infections, bloodstream central nervous system gastrointestinal others. By rapidly identifying pathogens their genomic characteristics, facilitates timely targeted therapeutic interventions, thereby improving patient outcomes infection control measures. Looking ahead, future disease diagnostics appears promising. Advances bioinformatics tools technologies are anticipated streamline analysis, enhance sensitivity specificity, reduce turnaround times. Integration with decision support systems promises further optimize utilization routine practice. In conclusion, represents paradigm shift field diagnostics, offering unparalleled insights into diversity pathogenesis. While persist, ongoing technological advancements hold immense potential consolidate pivotal tool armamentarium modern medicine, empowering clinicians precise, rapid, pathogen capabilities.

Language: Английский

Citations

3