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Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical Samples.

作者信息

Afonso Claudio L, Afonso Anna M

机构信息

BASE2BIO, 1945 Arlington Drive, Oshkosh, WI 54904, USA.

Independent Researcher, Athens, GA 30601, USA.

出版信息

Vet Sci. 2023 Dec 4;10(12):690. doi: 10.3390/vetsci10120690.


DOI:10.3390/vetsci10120690
PMID:38133241
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10747646/
Abstract

Direct-targeted next-generation sequencing (tNGS), with its undoubtedly superior diagnostic capacity over real-time PCR (RT-PCR), and direct-non-targeted NGS (ntNGS), with its higher capacity to identify and characterize multiple agents, are both likely to become diagnostic methods of choice in the future. tNGS is a rapid and sensitive method for precise characterization of suspected agents. ntNGS, also known as agnostic diagnosis, does not require a hypothesis and has been used to identify unsuspected infections in clinical samples. Implemented in the form of multiplexed total DNA metagenomics or as total RNA sequencing, the approach produces comprehensive and actionable reports that allow semi-quantitative identification of most of the agents present in respiratory, cloacal, and tissue samples. The diagnostic benefits of the use of direct tNGS and ntNGS are high specificity, compatibility with different types of clinical samples (fresh, frozen, FTA cards, and paraffin-embedded), production of nearly complete infection profiles (viruses, bacteria, fungus, and parasites), production of "semi-quantitative" information, direct agent genotyping, and infectious agent mutational information. The achievements of NGS in terms of diagnosing poultry problems are described here, along with future applications. Multiplexing, development of standard operating procedures, robotics, sequencing kits, automated bioinformatics, cloud computing, and artificial intelligence (AI) are disciplines converging toward the use of this technology for active surveillance in poultry farms. Other advances in human and veterinary NGS sequencing are likely to be adaptable to avian species in the future.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bca0/10747646/8045e36b9d49/vetsci-10-00690-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bca0/10747646/8045e36b9d49/vetsci-10-00690-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bca0/10747646/8045e36b9d49/vetsci-10-00690-g001.jpg

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本文引用的文献

[1]
Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

J Biomol Struct Dyn. 2024-7

[2]
Complete Genome Sequences of Avian Metapneumovirus Subtype B Vaccine Strains from Brazil.

Microbiol Resour Announc. 2023-6-20

[3]
Comparable outcomes from long and short read random sequencing of total RNA for detection of pathogens in chicken respiratory samples.

Front Vet Sci. 2022-12-1

[4]
Detection and Genome Sequence Analysis of Avian Metapneumovirus Subtype A Viruses Circulating in Commercial Chicken Flocks in Mexico.

Vet Sci. 2022-10-19

[5]
Genome Sequence Variations of Infectious Bronchitis Virus Serotypes From Commercial Chickens in Mexico.

Front Vet Sci. 2022-7-12

[6]
Non-target RNA depletion strategy to improve sensitivity of next-generation sequencing for the detection of RNA viruses in poultry.

J Vet Diagn Invest. 2022-7

[7]
Integrated Bioinformatics and Clinical Correlation Analysis of Key Genes, Pathways, and Potential Therapeutic Agents Related to Diabetic Nephropathy.

Dis Markers. 2022

[8]
Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections.

J Adv Res. 2022-5

[9]
Machine Learning and Deep Learning Applications in Metagenomic Taxonomy and Functional Annotation.

Front Microbiol. 2022-3-14

[10]
A Step Towards Validation of High-Throughput Sequencing for the Identification of Plant Pathogenic Oomycetes.

Phytopathology. 2022-9

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