Early life inter-kingdom interactions shape the immunological environment of the airways

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Abstract

Background

There is increasing evidence that the airway microbiome plays a key role in the establishment of respiratory health by interacting with the developing immune system early in life. While it has become clear that bacteria are involved in this process, there is a knowledge gap concerning the role of fungi. Moreover, the inter-kingdom interactions that influence immune development remain unknown. In this prospective exploratory human study, we aimed to determine early post-natal microbial and immunological features of the upper airways in 121 healthy newborns.

Results

We found that the oropharynx and nasal cavity represent distinct ecological niches for bacteria and fungi. Breastfeeding correlated with changes in microbiota composition of oropharyngeal samples with the greatest impact upon the relative abundance of Streptococcus species and Candida. Host transcriptome profiling revealed that genes with the highest expression variation were immunological in nature. Multi-omics factor analysis of host and microbial data revealed unique co-variation patterns.

Conclusion

These data provide evidence of a diverse multi-kingdom microbiota linked with local immunological characteristics in the first week of life that could represent distinct trajectories for future respiratory health.

Trial registration

NHS Health Research Authority, IRAS ID 199053. Registered 5 Oct 2016. https://www.hra.nhs.uk/planning-and-improving-research/application-summaries/research-summaries/breathing-together/

Supplementary Information

The online version contains supplementary material available at 10.1186/s40168-021-01201-y.

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Most cited references 30

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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DADA2: High resolution sample inference from Illumina amplicon data

Benjamin J. Callahan, Paul McMurdie, Michael Rosen … (2016)

We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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Cutadapt removes adapter sequences from high-throughput sequencing reads

Marcel Martin (2011)

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Author and article information

Contributors

Céline Pattaroni:

ORCID: http://orcid.org/0000-0002-9920-1181

celine.pattaroni@monash.edu

Matthew Macowan: matthew.macowan@monash.edu

Roxanne Chatzis: roxanne.chatzis@monash.edu

Carmel Daunt: carmel.daunt@monash.edu

Adnan Custovic: a.custovic@imperial.ac.uk

Michael D. Shields: m.shields@qub.ac.uk

Ultan F. Power: u.power@qub.ac.uk

Jonathan Grigg: j.grigg@qmul.ac.uk

Graham Roberts: g.c.roberts@soton.ac.uk

Peter Ghazal: ghazalp@cardiff.ac.uk

Jürgen Schwarze: jschwarz@ed.ac.uk

Mindy Gore: m.gore@imperial.ac.uk

Steve Turner: s.w.turner@abdn.ac.uk

Andrew Bush: A.Bush@rbht.nhs.uk

Sejal Saglani: s.saglani@imperial.ac.uk

Clare M. Lloyd: c.lloyd@imperial.ac.uk

Benjamin J. Marsland: benjamin.marsland@monash.edu

Journal

Journal ID (nlm-ta): Microbiome

Journal ID (iso-abbrev): Microbiome

Title: Microbiome

Publisher: BioMed Central (London )

ISSN (Electronic): 2049-2618

Publication date (Electronic): 21 February 2022

Publication date PMC-release: 21 February 2022

Publication date Collection: 2022

Volume: 10

Electronic Location Identifier: 34

Affiliations

[1 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, Department of Immunology and Pathology, , Monash University, ; Melbourne, Australia

[2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Imperial Centre for Paediatrics and Child Health, , Imperial College London, ; London, UK

[3 ]GRID grid.4777.3, ISNI 0000 0004 0374 7521, Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Sciences, , Queen’s University Belfast, ; Belfast, UK

[4 ]GRID grid.4868.2, ISNI 0000 0001 2171 1133, Centre for Child Health, Blizard Institute, , Queen Mary University of London, ; London, UK

[5 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Human Development in Health School, , University of Southampton Faculty of Medicine, ; Southampton, UK

[6 ]GRID grid.430506.4, ISNI 0000 0004 0465 4079, NIHR Southampton Biomedical Research Centre, , University Hospital Southampton NHS Foundation Trust, ; Southampton, UK

[7 ]GRID grid.439564.9, David Hide Asthma and Allergy Research Centre, , St Mary’s Hospital, ; Newport, Isle of Wight UK

[8 ]GRID grid.5600.3, ISNI 0000 0001 0807 5670, School of Medicine, Systems Immunity Research Institute, , Cardiff University, ; Cardiff, UK

[9 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Centre for Inflammation Research, Child Life and Health, , The University of Edinburgh, ; Edinburgh, UK

[10 ]GRID grid.7107.1, ISNI 0000 0004 1936 7291, Child Health, , University of Aberdeen, ; Aberdeen, UK

[11 ]GRID grid.411800.c, ISNI 0000 0001 0237 3845, NHS Grampian, ; Aberdeen, UK

[12 ]GRID grid.439338.6, ISNI 0000 0001 1114 4366, Royal Brompton Hospital, ; London, UK

[13 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, National Heart & Lung Institute, , Imperial College London, ; London, UK

Author information

Céline Pattaroni http://orcid.org/0000-0002-9920-1181

Article

Publisher ID: 1201

DOI: 10.1186/s40168-021-01201-y

PMC ID: 8862481

PubMed ID: 35189979

SO-VID: c9b388cd-6209-4ea8-8c69-4a097bbb3fa8

License:

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/. The Creative Commons Public Domain Dedication waiver ( http://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.

History

Date received : 5 October 2021

Date accepted : 12 November 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;

Award ID: 108818

Award Recipient : Andrew Bush

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Early life inter-kingdom interactions shape the immunological environment of the airways

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Abstract

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Trial registration

Supplementary Information

Related collections

Tick microbiome

Most cited references 30

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

DADA2: High resolution sample inference from Illumina amplicon data

Cutadapt removes adapter sequences from high-throughput sequencing reads

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Cited by 14

Most referenced authors 778