Evidence map›Paper›PMID 33516266›Full record

ArticleMicrobiome2021

Accurate identification and quantification of commensal microbiota bound by host immunoglobulins.

Matthew A Jackson, Claire Pearson, Nicholas E Ilott, Kelsey E Huus, Ahmed N Hegazy, Jonathan Webber, B Brett Finlay, Andrew J Macpherson, Fiona Powrie, Lilian H Lam

Abstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

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  12. Profiling Antibody Reactivity to Gut Microbes in ME/CFS Patients.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Matthew A JacksonKennedy Institute of Rheumatology, University of Oxford, Oxford, UK. matthew.jackson@kennedy.ox.ac.uk.ORCID 0000-0002-7891-6217
Claire PearsonKennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
Nicholas E IlottKennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
Kelsey E HuusMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Ahmed N HegazyKennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
Jonathan WebberKennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
B Brett FinlayMichael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Andrew J MacphersonMaurice Müller Laboratories, Department of Biomedical Research, University of Bern, 3008, Bern, Switzerland.
Fiona PowrieKennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
Lilian H LamKennedy Institute of Rheumatology, University of Oxford, Oxford, UK. lilian.lam@kennedy.ox.ac.uk.

Funding

CIHRVersus Arthritis 21226Wellcome TrustWellcome Trust 212240/Z/18/Z
6 · The paper itself

Abstract

backgroundIdentifying which taxa are targeted by immunoglobulins can uncover important host-microbe interactions. Immunoglobulin binding of commensal taxa can be assayed by sorting bound bacteria from samples and using amplicon sequencing to determine their taxonomy, a technique most widely applied to study Immunoglobulin A (IgA-Seq). Previous experiments have scored taxon binding in IgA-Seq datasets by comparing abundances in the IgA bound and unbound sorted fractions. However, as these are relative abundances, such scores are influenced by the levels of the other taxa present and represent an abstract combination of these effects. Diversity in the practical approaches of prior studies also warrants benchmarking of the individual stages involved. Here, we provide a detailed description of the design strategy for an optimised IgA-Seq protocol. Combined with a novel scoring method for IgA-Seq datasets that accounts for the aforementioned effects, this platform enables accurate identification and quantification of commensal gut microbiota targeted by host immunoglobulins.

resultsUsing germ-free and Rag1

conclusionsWe provide a detailed IgA-Seq protocol to accurately isolate IgA-bound taxa from intestinal samples. Using simulated and experimental data, we demonstrate novel probability-based scores that adjust for the compositional nature of relative abundance data to accurately quantify taxon-level IgA binding. All scoring approaches are made available in the IgAScores R package. These methods should improve the generation and interpretation of IgA-Seq datasets and could be applied to study other immunoglobulins and sample types. Video abstract.

Indexed as

SymbiosisAnimalsBacteriaDatasets as TopicFemaleGastrointestinal MicrobiomeImmunoglobulin AIntestinesMaleMiceMice, Inbred C57BLImmunoglobulin AGastrointestinalIgAIgA-SeqImmunoglobulinImmunologyMicrobiome

Identifiers

PMID33516266
PMCPMC7847592

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.