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El uso de la inteligencia artificial para documentar la virusfera de ARN oculto
1National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, State Key Laboratory for Biocontrol, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China.
Cell
|October 10, 2024
Resumen
Una nueva herramienta de aprendizaje profundo, LucaProt, identifica virus de ARN altamente divergentes mediante el análisis de secuencias de ARN polimerasa dependientes de ARN. Este descubrimiento amplía nuestra comprensión de la virósfera global y la diversidad de virus en los ecosistemas.
Área de la Ciencia:
- Virología
- La bioinformática
- La genómica
Sus antecedentes:
- Las herramientas metagenómicas a menudo no logran detectar virus de ARN altamente divergentes.
- La ARN polimerasa dependiente del ARN (RdRP) es una enzima clave para la replicación del virus del ARN.
Objetivo del estudio:
- Desarrollar una nueva herramienta computacional para descubrir secuencias de virus de ARN altamente divergentes.
- Caracterizar la diversidad y distribución de nuevos virus de ARN en varios ecosistemas globales.
Principales métodos:
- Desarrollo de LucaProt, un algoritmo de aprendizaje profundo que integra información secuencial y estructural.
- Análisis de 10.487 metatranscriptomas de diversos entornos del mundo.
- Validación de nuevas secuencias virales mediante RT-PCR y secuenciación de ARN/ADN.
Principales resultados:
- Identificación de 161,979 especies potenciales de virus de ARN y 180 supergrupos de virus de ARN.
- Descubrimiento de genomas de virus de ARN excepcionalmente largos (hasta 47.250 nucleótidos) y estructuras genómicas complejas.
- Detección de nuevos virus de ARN en diversos entornos como el aire, las aguas termales y las fuentes hidrotermales.
Conclusiones:
- LucaProt mejora significativamente el descubrimiento de virus de ARN divergentes.
- El estudio revela la vasta escala de la virósfera global de ARN y su distribución ecológica.
- Las herramientas computacionales son cruciales para la documentación completa del viroma de ARN global.
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