Evidence map›Paper›PMID 42594336›Full record

ArticlePloS one2026

CLR-Seq: A pipeline to identify bacterial microbiota species with immune-relevant glycan moieties through human C-type lectin receptor interaction.

Jasper Mol, Rob van Dalen, Yvonne Pannekoek, Malgorzata E Mnich, Marcel R de Zoete, Mark Davids, Hilde Herrema, Nina M van Sorge

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jasper MolDepartment of Medical Microbiology and Infection Prevention, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.ORCID https://orcid.org/0009-0002-3536-3488
Rob van DalenDepartment of Medical Microbiology and Infection Prevention, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-0436-6048
Yvonne PannekoekDepartment of Medical Microbiology and Infection Prevention, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0003-1154-652X
Malgorzata E MnichDepartment of Medical Microbiology, UMC Utrecht, Utrecht, The Netherlands.ORCID https://orcid.org/0009-0007-5064-2350
Marcel R de ZoeteDepartment of Medical Microbiology, UMC Utrecht, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-6561-5810
Mark DavidsDepartment of Experimental Vascular Medicine, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.
Hilde HerremaDepartment of Experimental Vascular Medicine, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-0112-6348
Nina M van SorgeDepartment of Medical Microbiology and Infection Prevention, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-2695-5863

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial glycans are key components in immune interactions. We lack insight into the diverse glycan landscape present in complex microbial communities since current -omics techniques do not capture this post-translational information. Here we employed C-type lectin receptors (CLRs), which are dedicated innate glycan-sensing receptors, as probes for bacterial cell sorting in combination with 16S rRNA gene sequencing to identify microbiota species with a specific CLR-reactive glycan profile. We established our experimental CLR-sequencing (CLR-seq) pipeline using soluble fluorescently-labeled human macrophage galactose C-type lectin (MGL, CD301) and langerin (CD207). Both receptors identified known langerin- or MGL-interacting Staphylococcus aureus strains in a synthetic microbial community even when present at low abundance. Subsequent application of CLR-seq on fecal microbiota samples from healthy donors identified specific langerin- and MGL-interacting bacterial species that were subsequently validated as monocultures. In summary, CLR-seq is a modular platform that allows identification of human microbiota species based on CLR-interacting glycans with easy expansion to other CLRs or microbiota samples from patients. Given that CLRs are densely expressed on dendrites of antigen-presenting cells, this pathway may play a role in cross-barrier recognition and sampling of the environment during homeostasis.

Indexed as

BacteriaLectins, C-TypeMicrobiotaPolysaccharidesAntigens, CDFecesHumansMannose-Binding LectinsRNA, Ribosomal, 16SStaphylococcus aureusAntigens, CDCD207 protein, humanLectins, C-TypeMannose-Binding LectinsMGL lectin, humanPolysaccharidesRNA, Ribosomal, 16S

Identifiers

PMID42594336
PMCPMC13472642

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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.