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Updated: Jul 23, 2025

Metagenomic Analysis of Silage
Published on: January 13, 2017
Clinical metagenomics-challenges and future prospects
Maliha Batool1, Jessica Galloway-Peña1
1Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States.
Abstract:
Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.
Insights
Metagenomic next-generation sequencing (mNGS) offers a sensitive approach for diagnosing rare infections. However, challenges in sensitivity, cost, and standardization must be addressed for widespread clinical adoption.
Area of Science:
- Infectious Diseases
- Genomics
- Clinical Diagnostics
Background:
- Undiagnosed infections pose significant risks, leading to mortality and long-term health consequences.
- Current diagnostic methods often fail to identify rare, novel, or complex causative pathogens.
- A universal diagnostic strategy is crucial to reduce the burden of undocumented infections.
Purpose of the Study:
- To review the efficacy and limitations of metagenomic next-generation sequencing (mNGS) in diagnosing severe infections.
- To compare mNGS with conventional diagnostic methods.
- To propose strategies for optimizing mNGS as a clinical diagnostic tool.
Main Methods:
- Culture-independent analysis using metagenomic next-generation sequencing (mNGS).
- Review of existing studies and case reports on mNGS in clinical diagnosis.
- Examination of mNGS performance metrics including sensitivity, specificity, and cost-effectiveness.
Main Results:
- mNGS demonstrates high sensitivity in detecting rare, novel, and unexpected pathogens without prior assumptions.
- Studies confirm mNGS's effectiveness in improving clinical diagnosis for various infections.
- Limitations include challenges in sensitivity, specificity, cost, bioinformatic pipeline standardization, and result interpretation.
Conclusions:
- mNGS is a powerful tool for identifying the causes of undiagnosed infections.
- Addressing current limitations is essential for integrating mNGS into routine clinical practice.
- Further development is needed to maximize mNGS's potential in diagnosing severe infections.
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