Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases
-
Published:2024-05-26
Issue:6
Volume:11
Page:239
-
ISSN:2306-7381
-
Container-title:Veterinary Sciences
-
language:en
-
Short-container-title:Veterinary Sciences
Author:
Spatz Stephen1, Afonso Claudio L.2ORCID
Affiliation:
1. Southeast Poultry Research Laboratory, Agricultural Research Service, United States Department of Agriculture, 934 College Station Road, Athens, GA 30605, USA 2. BASE2BIO, 1945 Arlington Drive, Oshkosh, WI 54904, USA
Abstract
Metagenomics offers the potential to replace and simplify classical methods used in the clinical diagnosis of human and veterinary infectious diseases. Metagenomics boasts a high pathogen discovery rate and high specificity, advantages absent in most classical approaches. However, its widespread adoption in clinical settings is still pending, with a slow transition from research to routine use. While longer turnaround times and higher costs were once concerns, these issues are currently being addressed by automation, better chemistries, improved sequencing platforms, better databases, and automated bioinformatics analysis. However, many technical options and steps, each producing highly variable outcomes, have reduced the technology’s operational value, discouraging its implementation in diagnostic labs. We present a case for utilizing non-targeted RNA sequencing (NT-RNA-seq) as an ideal metagenomics method for the detection of infectious disease-causing agents in humans and animals. Additionally, to create operational value, we propose to identify best practices for the “core” of steps that are invariably shared among many human and veterinary protocols. Reference materials, sequencing procedures, and bioinformatics standards should accelerate the validation processes necessary for the widespread adoption of this technology. Best practices could be determined through “implementation research” by a consortium of interested institutions working on common samples.
Reference130 articles.
1. Shi, Y., Wang, G., Lau, H.C.H., and Yu, J. (2022). Metagenomic Sequencing for Microbial DNA in Human Samples: Emerging Technological Advances. Int. J. Mol. Sci., 23. 2. Itokawa, K., Sekizuka, T., Hashino, M., Tanaka, R., and Kuroda, M. (2020). Disentangling Primer Interactions Improves SARS-CoV-2 Genome Sequencing by Multiplex Tiling PCR. PLoS ONE, 15. 3. Arana, C., Liang, C., Brock, M., Zhang, B., Zhou, J., Chen, L., Cantarel, B., SoRelle, J., Hooper, L.V., and Raj, P. (2022). A Short plus Long-Amplicon Based Sequencing Approach Improves Genomic Coverage and Variant Detection in the SARS-CoV-2 Genome. PLoS ONE, 17. 4. DNA Pipelines R&D, Farr, B., Rajan, D., Betteridge, E., Shirley, L., Quail, M., Park, N., Redshaw, N., Bronner, I., and Aigrain, L. (2020). COVID-19 ARTIC v3 Illumina Library Construction and Sequencing Protocol. PLoS Glob. Public Health. 5. Use of Diagnostic Metagenomics in the Clinical Microbiology Laboratory;Mitchell;Am. Soc. Clin. Lab. Sci.,2019
|
|