School of Medicine and Health Sciences Poster Presentations

Different Sequencing Platforms Give Distinct Measures of Alpha Diversity of the Pulmonary Microbiome Detected in Cystic Fibrosis

Poster Number

260

Document Type

Poster

Publication Date

3-2016

Abstract

Introduction: Cystic fibrosis (CF) is an autosomal recessive disorder that causes abnormal salt and water transport across epithelia due to a mutation in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR). Mutations in CFTR cause thick mucus to collect in airways, clogging them and making breathing difficult. Cilia cannot remove pathogens in the respiratory tract, resulting in recurrent and chronic bacterial infections. Currently, bacteria are identified by culturing on media. There are diverse species that grow in a patient’s lung, so it can be hard to identify all pathogens. A noveler method of bacterial identification involves next generation sequencing (NGS) of the bacterial 16S rRNA gene. Prior studies using NGS have identified a large number of bacteria present in the CF lung, and that a loss of bacterial diversity is associated with disease progression. Two state-of-the-art platforms that can sequence the CF lung microbiome are MiSeq and PacBio RS II. Our goal was to determine whether MiSeq, with shorter reads, can still identify the dominant pathogen and a similar measure of alpha diversity compared to PacBio in CF sputum samples.

Methods: The bacterial DNA from the sputum of 10 de-identified subjects with CF was extracted to make 16 samples. MiSeq was used to sequence V3/V4 with read lengths of 250 base pairs. Identification of bacteria was done using BaseSpace (Illumina). PacBio sequenced the full 16S rRNA gene (~ 1450 base pairs) using ≥16 passes via circular consensus sequencing. Software from the ChunLab was used for bacterial identification. The Shannon Index (SI) was used to calculate alpha diversity.

Results: 13 matched samples were sequenced on both platforms. 609 (±132) OTUs were identified with MiSeq, compared to 88 (±59) with PacBio (p <0.001). The Shannon Index for MiSeq was calculated to be 1.916 (±0.517) and 2.005 (±0.656) for PacBio (p =0.018). The agreement of the dominant pathogen was 92% between the two platforms.

Discussion/Conclusions: Although the dominant pathogen was identified by both platforms, MiSeq identified a larger number of operational taxonomic units (OTUs), which is observed in the measures of alpha diversity. Only 49.4% of the MiSeq OTUs were classified to the genus level, compared to 99.3% of PacBio OTUs. PacBio was able to more accurately identify the taxa of the OTUs, but MiSeq was able to find rare OTUs not identified by PacBio. Determining the strengths and weaknesses of each platform will help choose the correct platform for future studies.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Open Access

1

Comments

Presented at: GW Research Days 2016

This document is currently not available here.

Share

COinS
 

Different Sequencing Platforms Give Distinct Measures of Alpha Diversity of the Pulmonary Microbiome Detected in Cystic Fibrosis

Introduction: Cystic fibrosis (CF) is an autosomal recessive disorder that causes abnormal salt and water transport across epithelia due to a mutation in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR). Mutations in CFTR cause thick mucus to collect in airways, clogging them and making breathing difficult. Cilia cannot remove pathogens in the respiratory tract, resulting in recurrent and chronic bacterial infections. Currently, bacteria are identified by culturing on media. There are diverse species that grow in a patient’s lung, so it can be hard to identify all pathogens. A noveler method of bacterial identification involves next generation sequencing (NGS) of the bacterial 16S rRNA gene. Prior studies using NGS have identified a large number of bacteria present in the CF lung, and that a loss of bacterial diversity is associated with disease progression. Two state-of-the-art platforms that can sequence the CF lung microbiome are MiSeq and PacBio RS II. Our goal was to determine whether MiSeq, with shorter reads, can still identify the dominant pathogen and a similar measure of alpha diversity compared to PacBio in CF sputum samples.

Methods: The bacterial DNA from the sputum of 10 de-identified subjects with CF was extracted to make 16 samples. MiSeq was used to sequence V3/V4 with read lengths of 250 base pairs. Identification of bacteria was done using BaseSpace (Illumina). PacBio sequenced the full 16S rRNA gene (~ 1450 base pairs) using ≥16 passes via circular consensus sequencing. Software from the ChunLab was used for bacterial identification. The Shannon Index (SI) was used to calculate alpha diversity.

Results: 13 matched samples were sequenced on both platforms. 609 (±132) OTUs were identified with MiSeq, compared to 88 (±59) with PacBio (p <0.001). The Shannon Index for MiSeq was calculated to be 1.916 (±0.517) and 2.005 (±0.656) for PacBio (p =0.018). The agreement of the dominant pathogen was 92% between the two platforms.

Discussion/Conclusions: Although the dominant pathogen was identified by both platforms, MiSeq identified a larger number of operational taxonomic units (OTUs), which is observed in the measures of alpha diversity. Only 49.4% of the MiSeq OTUs were classified to the genus level, compared to 99.3% of PacBio OTUs. PacBio was able to more accurately identify the taxa of the OTUs, but MiSeq was able to find rare OTUs not identified by PacBio. Determining the strengths and weaknesses of each platform will help choose the correct platform for future studies.