Assessing fungal endophyte diversity: a comparative study of three automated metabarcoding pipelines

Lucía Molina; Mario Rajchenberg; M. Catherine Aime; M. Belén Pildain

doi:10.14522/darwiniana.2023.112.1127

Autores/as

Lucía Molina Área de Fitopatología y Microbiología Aplicada, Centro de Investigación y Extensión Forestal Andino Patagónico (CIEFAP), Ruta 259 Km 16.24, 9200 Esquel, Chubut, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina. http://orcid.org/0000-0003-1073-8810
Mario Rajchenberg Área de Fitopatología y Microbiología Aplicada, Centro de Investigación y Extensión Forestal Andino Patagónico (CIEFAP), Ruta 259 Km 16.24, 9200 Esquel, Chubut, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina. https://orcid.org/0000-0001-5031-5148
M. Catherine Aime Department of Botany and Plant Pathology, Purdue University, 915 W State St, West Lafayette, IN 47907, USA. https://orcid.org/0000-0001-8742-6685
M. Belén Pildain Área de Fitopatología y Microbiología Aplicada, Centro de Investigación y Extensión Forestal Andino Patagónico (CIEFAP), Ruta 259 Km 16.24, 9200 Esquel, Chubut, Argentina; Facultad de Ciencias Naturales y Ciencias de la Salud, Universidad Nacional de la Patagonia San Juan Bosco (UNPSJB), Ruta 259 Km 16.4, 9200 Esquel, Chubut, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina. https://orcid.org/0000-0002-0777-8232

DOI:

https://doi.org/10.14522/darwiniana.2023.112.1127

Palabras clave:

ADN ambiental, AMPtk, bosques de Nothofagus, endófitos fúngicos, PIPITS

Resumen

La utilización de la secuenciación de alto rendimiento se ha vuelto frecuente en el estudio de comunidades endófitas. Estas tecnologías han permitido la descripción acumulativa de diversidad fúngica a lo largo de la última década. No obstante, también han implicado nuevos desafíos para los investigadores de las áreas involucradas en términos de la necesidad de contar con herramientas de programación y habilidades desarrolladoras. Hoy en día no existe un consenso sobre las herramientas bioinformáticas más adecuadas para procesar los datos crudos de secuencias que estas tecnologías arrojan. El objetivo de este trabajo fue comparar el rendimiento de tres flujos de trabajo realizados en dos plataformas gratuitas diseñadas para ser amigables con usuarios que no son programadores y desarrolladas específicamente para estudios de hongos: AMPtk y PIPITS. Evaluamos los ensambles de hongos que habitan en la albura de dos especies de Nothofagus de los bosques patagónicos y comparamos el conjunto de datos de metabarcoding del espaciador transcrito interno (ITS) con un conjunto de datos de secuencias existente, obtenido de la prospección de cultivos de los mismos árboles y sitios de estudio. La plataforma AMPtk se desempeñó mejor con respecto a la descripción de la comunidad, en términos de precisión del agrupamiento de taxones, principalmente debido al algoritmo DADA2. El flujo de trabajo PIPITS evidenció una mayor sensibilidad en la detección de taxones conocidos presentes, por lo que es potencialmente útil para futuros estudios que persigan la detección de taxones específicos. Debido a la falta de información que exhiben las bases de datos de referencia sobre el ecosistema en estudio, ambas plataformas tuvieron un desempeño deficiente en cuanto a la asignación de taxonomías. Es imperativo seguir estudiando estos ecosistemas y mejorar las bases de datos para aumentar el potencial explicativo de las nuevas tecnologías.

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