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Active Microbiome Structure and Functional Analyses of Freshwater Benthic Biofilm Samples Influenced by RNA Extraction Methods

Advances in high-throughput sequencing technologies have enabled extensive studies of freshwater biofilms and significant breakthroughs in biofilm meta-omics. To date, however, no standardized protocols have been developed for the effective isolation of RNA from freshwater benthic biofilms. In this...

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Detalles Bibliográficos
Autores principales: Yao, Yuan, Rao, Subramanya, Habimana, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085529/
https://www.ncbi.nlm.nih.gov/pubmed/33935982
http://dx.doi.org/10.3389/fmicb.2021.588025
Descripción
Sumario:Advances in high-throughput sequencing technologies have enabled extensive studies of freshwater biofilms and significant breakthroughs in biofilm meta-omics. To date, however, no standardized protocols have been developed for the effective isolation of RNA from freshwater benthic biofilms. In this study, we compared column-based kit RNA extraction with five RNAzol-based extractions, differentiated by various protocol modifications. The RNA products were then evaluated to determine their integrity, purity and yield and were subjected to meta-transcriptomic sequencing and analysis. Significant discrepancies in the relative abundance of active communities and structures of eukaryotic, bacterial, archaebacterial, and viral communities were observed as direct outcomes of the tested RNA extraction methods. The column isolation-based group was characterized by the highest relative abundance of Archaea and Eukaryota, while the organic isolation-based groups commonly had the highest relative abundances of Prokaryota (bacteria). Kit extraction methods provided the best outcomes in terms of high-quality RNA yield and integrity. However, these methods were deemed questionable for studies of active bacterial communities and may contribute a significant degree of bias to the interpretation of downstream meta-transcriptomic analyses.