Dataset Information

Microbiomic Analysis on Low Abundant Respiratory Biomass Samples; Improved Recovery of Microbial DNA From Bronchoalveolar Lavage Fluid.

ABSTRACT: In recent years the study of the commensal microbiota is driving a remarkable paradigm shift in our understanding of human physiology. However, intrinsic technical difficulties associated with investigating the Microbiomics of some body niches are hampering the development of new knowledge. This is particularly the case when investigating the functional role played by the human microbiota in modulating the physiology of key organ systems. A major hurdle in investigating specific Microbiome communities is linked to low bacterial density and susceptibility to bias caused by environmental contamination. To prevent such inaccuracies due to background processing noise, harmonized tools for Microbiomic and bioinformatics practices have been recommended globally. The fact that the impact of this undesirable variability is negatively correlated with the DNA concentration in the sample highlights the necessity to improve existing DNA isolation protocols. In this report, we developed and tested a protocol to more efficiently recover bacterial DNA from low volumes of bronchoalveolar lavage fluid obtained from infants and adults. We have compared the efficiency of the described method with that of a commercially available kit for microbiome analysis in body fluids. We show that this new methodological approach performs better in terms of extraction efficiency. As opposed to commercial kits, the DNA extracts obtained with this new protocol were clearly distinguishable from the negative extraction controls in terms of 16S copy number and Microbiome community profiles. Altogether, we described a cost-efficient protocol that can facilitate microbiome research in low-biomass human niches.

SUBMITTER: Saladie M

PROVIDER: S-EPMC7573210 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Microbiomic Analysis on Low Abundant Respiratory Biomass Samples; Improved Recovery of Microbial DNA From Bronchoalveolar Lavage Fluid.

Saladié Montserrat M Caparrós-Martín Jose Antonio JA Agudelo-Romero Patricia P Wark Peter A B PAB Stick Stephen M SM O'Gara Fergal F

Frontiers in microbiology 20201006

In recent years the study of the commensal microbiota is driving a remarkable paradigm shift in our understanding of human physiology. However, intrinsic technical difficulties associated with investigating the Microbiomics of some body niches are hampering the development of new knowledge. This is particularly the case when investigating the functional role played by the human microbiota in modulating the physiology of key organ systems. A major hurdle in investigating specific Microbiome commu ...[more]

PMID: 33123104

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Project description:BackgroundIt is now possible to comprehensively characterize the microbiota of the lungs using culture-independent, sequencing-based assays. Several sample types have been used to investigate the lung microbiota, each presenting specific challenges for preparation and analysis of microbial communities. Bronchoalveolar lavage fluid (BALF) enables the identification of microbiota specific to the lower lung but commonly has low bacterial density, increasing the risk of false-positive signal from contaminating DNA. The objectives of this study were to investigate the extent of contamination across a range of sample densities representative of BALF and identify features of contaminants that facilitate their removal from sequence data and aid in the interpretation of BALF sample 16S sequencing data.ResultsUsing three mock communities across a range of densities ranging from 8E+?02 to 8E+?09 16S copies/ml, we assessed taxonomic accuracy and precision by 16S rRNA gene sequencing and the proportion of reads arising from contaminants. Sequencing accuracy, precision, and the relative abundance of mock community members decreased with sample input density, with a significant drop-off below 8E+?05 16S copies/ml. Contaminant OTUs were commonly inversely correlated with sample input density or not reproduced between technical replicates. Removal of taxa with these features or physical concentration of samples prior to sequencing improved both sequencing accuracy and precision for samples between 8E+?04 and 8E+?06 16S copies/ml. For the lowest densities, below 8E+?03 16S copies/ml BALF, accuracy and precision could not be significantly improved using these approaches. Using clinical BALF samples across a large density range, we observed that OTUs with features of contaminants identified in mock communities were also evident in low-density BALF samples.ConclusionRelative abundance data and community composition generated by 16S sequencing of BALF samples across the range of density commonly observed in this sample type should be interpreted in the context of input sample density and may be improved by simple pre- and post-sequencing steps for densities above 8E+?04 16S copies/ml.

Dataset Information

Microbiomic Analysis on Low Abundant Respiratory Biomass Samples; Improved Recovery of Microbial DNA From Bronchoalveolar Lavage Fluid.

Publications

Microbiomic Analysis on Low Abundant Respiratory Biomass Samples; Improved Recovery of Microbial DNA From Bronchoalveolar Lavage Fluid.

Similar Datasets

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