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Magnetic-activated cell sorting identifies a unique lung microbiome community

BACKGROUND: The advent of culture-independent, next-generation DNA sequencing has led to the discovery of distinct lung bacterial communities. Studies of lung microbiome taxonomy often reveal only subtle differences between health and disease, but host recognition and response may distinguish the me...

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Autores principales: Dunlap, Daniel G., Yang, Libing, Qin, Shulin, Li, Kelvin, Fitch, Adam, Huang, Laurence, McVerry, Bryan J., Hand, Timothy W., Methé, Barbara A., Morris, Alison
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210470/
https://www.ncbi.nlm.nih.gov/pubmed/37226179
http://dx.doi.org/10.1186/s40168-022-01434-5
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author Dunlap, Daniel G.
Yang, Libing
Qin, Shulin
Li, Kelvin
Fitch, Adam
Huang, Laurence
McVerry, Bryan J.
Hand, Timothy W.
Methé, Barbara A.
Morris, Alison
author_facet Dunlap, Daniel G.
Yang, Libing
Qin, Shulin
Li, Kelvin
Fitch, Adam
Huang, Laurence
McVerry, Bryan J.
Hand, Timothy W.
Methé, Barbara A.
Morris, Alison
author_sort Dunlap, Daniel G.
collection PubMed
description BACKGROUND: The advent of culture-independent, next-generation DNA sequencing has led to the discovery of distinct lung bacterial communities. Studies of lung microbiome taxonomy often reveal only subtle differences between health and disease, but host recognition and response may distinguish the members of similar bacterial communities in different populations. Magnetic-activated cell sorting has been applied to the gut microbiome to identify the numbers and types of bacteria eliciting a humoral response. We adapted this technique to examine the populations of immunoglobulin-bound bacteria in the lung. METHODS: Sixty-four individuals underwent bronchoalveolar lavage (BAL). We separated immunoglobulin G-bound bacteria using magnetic-activated cell sorting and sequenced the 16S rRNA gene on the Illumina MiSeq platform. We compared microbial sequencing data in IgG-bound bacterial communities compared to raw BAL then examined the differences in individuals with and without HIV as a representative disease state. RESULTS: Immunoglobulin G-bound bacteria were identified in all individuals. The community structure differed when compared to raw BAL, and there was a greater abundance of Pseudomonas and fewer oral bacteria in IgG-bound BAL. Examination of IgG-bound communities in individuals with HIV demonstrated the differences in Ig-bound bacteria by HIV status that were not seen in a comparison of raw BAL, and greater numbers of immunoglobulin-bound bacteria were associated with higher pulmonary cytokine levels. CONCLUSIONS: We report a novel application of magnetic-activated cell sorting to identify immunoglobulin G-bound bacteria in the lung. This technique identified distinct bacterial communities which differed in composition from raw bronchoalveolar lavage, revealing the differences not detected by traditional analyses. Cytokine response was also associated with differential immunoglobulin binding of lung bacteria, suggesting the functional importance of these communities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01434-5.
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spelling pubmed-102104702023-05-26 Magnetic-activated cell sorting identifies a unique lung microbiome community Dunlap, Daniel G. Yang, Libing Qin, Shulin Li, Kelvin Fitch, Adam Huang, Laurence McVerry, Bryan J. Hand, Timothy W. Methé, Barbara A. Morris, Alison Microbiome Methodology BACKGROUND: The advent of culture-independent, next-generation DNA sequencing has led to the discovery of distinct lung bacterial communities. Studies of lung microbiome taxonomy often reveal only subtle differences between health and disease, but host recognition and response may distinguish the members of similar bacterial communities in different populations. Magnetic-activated cell sorting has been applied to the gut microbiome to identify the numbers and types of bacteria eliciting a humoral response. We adapted this technique to examine the populations of immunoglobulin-bound bacteria in the lung. METHODS: Sixty-four individuals underwent bronchoalveolar lavage (BAL). We separated immunoglobulin G-bound bacteria using magnetic-activated cell sorting and sequenced the 16S rRNA gene on the Illumina MiSeq platform. We compared microbial sequencing data in IgG-bound bacterial communities compared to raw BAL then examined the differences in individuals with and without HIV as a representative disease state. RESULTS: Immunoglobulin G-bound bacteria were identified in all individuals. The community structure differed when compared to raw BAL, and there was a greater abundance of Pseudomonas and fewer oral bacteria in IgG-bound BAL. Examination of IgG-bound communities in individuals with HIV demonstrated the differences in Ig-bound bacteria by HIV status that were not seen in a comparison of raw BAL, and greater numbers of immunoglobulin-bound bacteria were associated with higher pulmonary cytokine levels. CONCLUSIONS: We report a novel application of magnetic-activated cell sorting to identify immunoglobulin G-bound bacteria in the lung. This technique identified distinct bacterial communities which differed in composition from raw bronchoalveolar lavage, revealing the differences not detected by traditional analyses. Cytokine response was also associated with differential immunoglobulin binding of lung bacteria, suggesting the functional importance of these communities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01434-5. BioMed Central 2023-05-25 /pmc/articles/PMC10210470/ /pubmed/37226179 http://dx.doi.org/10.1186/s40168-022-01434-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Dunlap, Daniel G.
Yang, Libing
Qin, Shulin
Li, Kelvin
Fitch, Adam
Huang, Laurence
McVerry, Bryan J.
Hand, Timothy W.
Methé, Barbara A.
Morris, Alison
Magnetic-activated cell sorting identifies a unique lung microbiome community
title Magnetic-activated cell sorting identifies a unique lung microbiome community
title_full Magnetic-activated cell sorting identifies a unique lung microbiome community
title_fullStr Magnetic-activated cell sorting identifies a unique lung microbiome community
title_full_unstemmed Magnetic-activated cell sorting identifies a unique lung microbiome community
title_short Magnetic-activated cell sorting identifies a unique lung microbiome community
title_sort magnetic-activated cell sorting identifies a unique lung microbiome community
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210470/
https://www.ncbi.nlm.nih.gov/pubmed/37226179
http://dx.doi.org/10.1186/s40168-022-01434-5
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