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African swine fever virus biotype identification tool
Mark Dinhobl1,2, Edward Spinard1,2, Hillary Birtlery3
1Foreign Animal Disease Research Unit, National Bio and Agro-Defense Facility, U.S. Department of Agriculture, Agricultural Research Service, Manhattan, Kansas, USA.
Microbiology Resource Announcements
|December 19, 2024
Summary
African swine fever virus (ASFV) biotyping classifies isolates using proteome analysis and machine learning. This new tool identifies ASFV biotypes by comparing viral genomes, offering a freely available implementation.
Area of Science:
- Virology
- Bioinformatics
- Genomics
Background:
- African swine fever virus (ASFV) poses a significant threat to global swine populations.
- Accurate classification of ASFV isolates is crucial for epidemiological surveillance and control strategies.
- Current classification methods are being enhanced by genomic and proteomic approaches.
Purpose of the Study:
- To introduce a computational tool for classifying African swine fever virus (ASFV) isolates.
- To enable the determination of ASFV biotypes based on genomic data.
- To provide a freely accessible implementation for ASFV biotyping.
Main Methods:
- The study utilizes unsupervised machine learning algorithms to compare viral proteomes.
- ASFV genomes are analyzed to identify proteomic similarities and differences.
- A standalone software implementation was developed for the biotyping tool.
Main Results:
- The developed tool accurately analyzes ASFV genomes.
- It identifies the closest genomic matches for a given ASFV isolate.
- The tool reports the corresponding ASFV biotype for each analyzed genome.
Conclusions:
- The described implementation provides a practical method for ASFV biotyping.
- This tool facilitates the classification of ASFV isolates based on their encoded proteomes.
- The freely downloadable software supports ASFV research and diagnostics.
