Optimized DNA extraction and purification method for characterization of bacterial and fungal communities in lung tissue samples

Author:

Pérez-Brocal Vicente,Magne Fabien,Ruiz-Ruiz Susana,Ponce Carolina A.,Bustamante Rebeca,Martin Viviana San,Gutierrez Mireya,Gatti Gianna,Vargas Sergio L.,Moya Andrés

Abstract

AbstractHuman lungs harbor a scarce microbial community, requiring to develop methods to enhance the recovery of nucleic acids from bacteria and fungi, leading to a more efficient analysis of the lung tissue microbiota. Here we describe five extraction protocols including pre-treatment, bead-beating and/or Phenol:Chloroform:Isoamyl alcohol steps, applied to lung tissue samples from autopsied individuals. The resulting total DNA yield and quality, bacterial and fungal DNA amount and the microbial community structure were analyzed by qPCR and Illumina sequencing of bacterial 16S rRNA and fungal ITS genes. Bioinformatic modeling revealed that a large part of microbiome from lung tissue is composed of microbial contaminants, although our controls clustered separately from biological samples. After removal of contaminant sequences, the effects of extraction protocols on the microbiota were assessed. The major differences among samples could be attributed to inter-individual variations rather than DNA extraction protocols. However, inclusion of the bead-beater and Phenol:Chloroform:Isoamyl alcohol steps resulted in changes in the relative abundance of some bacterial/fungal taxa. Furthermore, inclusion of a pre-treatment step increased microbial DNA concentration but not diversity and it may contribute to eliminate DNA fragments from dead microorganisms in lung tissue samples, making the microbial profile closer to the actual one.

Funder

Fondo Nacional de Desarrollo Científico y Tecnológico,Chile

ERANet LAC

Fondo Nacional de Desarrollo Científico y Tecnológico

Spanish Ministry of Economy and Competitiveness

Instituto de Salud Carlos III

Fundación Científica Asociación Española Contra el Cáncer

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3