Abstract

Peristaltic movement of the intestine propels food down the length of the gastrointestinal tract to promote nutrient absorption. Interactions between intestinal macrophages and the enteric nervous system regulate gastrointestinal motility, yet we have an incomplete understanding of the molecular mediators of this crosstalk. Here we identify complement component 1q (C1q) as a macrophage product that regulates gut motility. Macrophages were the predominant source of C1q in the mouse intestine and most extraintestinal tissues. Although C1q mediates complement-mediated killing of bacteria in the bloodstream, we found that C1q was not essential for immune defense of the intestine. Instead, C1q-expressing macrophages were located in the intestinal submucosal and myenteric plexuses where they closely associated with enteric neurons and expressed surface markers characteristic of nerve-adjacent macrophages in other tissues. Mice with a macrophage-specific deletion of C1qa showed changes in enteric neuronal gene expression, increased neurogenic activity of peristalsis, and accelerated intestinal transit. Our findings identify C1q as a key regulator of gastrointestinal motility and provide enhanced insight into the crosstalk between macrophages and the enteric nervous system.

Data availability

16S rRNA gene sequencing data (Figure 3D) and RNA sequencing data (Figure 6A and B; Figure 1 - figure supplement 1; Figure 6 - figure supplement 3) are available from the Sequence Read Archive under BioProject ID PRJNA793870. All mouse strains used are available commercially.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Mihir Pendse

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Haley De Selle

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Nguyen Vo

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Gabriella Quinn

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Chaitanya Dende

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Yun Li

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Cristine N Salinas

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Tarun Srinivasan

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Daniel C Propheter

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Alexander A Crofts

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0811-9199
  11. Eugene Koo

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Brian Hassell

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Kelly A Ruhn

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Prithvi Raj

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Yuuki Obata

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    yuuki.obata@utsouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5461-3521
  16. Lora V Hooper

    Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    lora.hooper@utsouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2759-4641

Funding

National Institutes of Health (R01 DK070855)

  • Lora V Hooper

Welch Foundation Grant (I-1874)

  • Lora V Hooper

Howard Hughes Medical Institute (N/A)

  • Lora V Hooper

National Institutes of Health (T32 AI005284)

  • Mihir Pendse

National Institutes of Health (T32 AI005284)

  • Alexander A Crofts

National Institutes of Health (F32 DK132913)

  • Alexander A Crofts

National Institutes of Health (F31 DK126391)

  • Eugene Koo

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (protocol #2015-101212) of the University of Texas Southwestern Medical Center.

Copyright

© 2023, Pendse et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,346
    views
  • 502
    downloads
  • 11
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Mihir Pendse
  2. Haley De Selle
  3. Nguyen Vo
  4. Gabriella Quinn
  5. Chaitanya Dende
  6. Yun Li
  7. Cristine N Salinas
  8. Tarun Srinivasan
  9. Daniel C Propheter
  10. Alexander A Crofts
  11. Eugene Koo
  12. Brian Hassell
  13. Kelly A Ruhn
  14. Prithvi Raj
  15. Yuuki Obata
  16. Lora V Hooper
(2023)
Macrophages regulate gastrointestinal motility through complement component 1q
eLife 12:e78558.
https://doi.org/10.7554/eLife.78558

Share this article

https://doi.org/10.7554/eLife.78558

Further reading

    1. Immunology and Inflammation
    Eva M García-Cuesta, Pablo Martínez ... Mario Mellado
    Research Article

    CXCR4 is a ubiquitously expressed chemokine receptor that regulates leukocyte trafficking and arrest in both homeostatic and pathological states. It also participates in organogenesis, HIV-1 infection, and tumor development. Despite the potential therapeutic benefit of CXCR4 antagonists, only one, plerixafor (AMD3100), which blocks the ligand-binding site, has reached the clinic. Recent advances in imaging and biophysical techniques have provided a richer understanding of the membrane organization and dynamics of this receptor. Activation of CXCR4 by CXCL12 reduces the number of CXCR4 monomers/dimers at the cell membrane and increases the formation of large nanoclusters, which are largely immobile and are required for correct cell orientation to chemoattractant gradients. Mechanistically, CXCR4 activation involves a structural motif defined by residues in TMV and TMVI. Using this structural motif as a template, we performed in silico molecular modeling followed by in vitro screening of a small compound library to identify negative allosteric modulators of CXCR4 that do not affect CXCL12 binding. We identified AGR1.137, a small molecule that abolishes CXCL12-mediated receptor nanoclustering and dynamics and blocks the ability of cells to sense CXCL12 gradients both in vitro and in vivo while preserving ligand binding and receptor internalization.

    1. Computational and Systems Biology
    2. Immunology and Inflammation
    Jing Sun, Desmond Choy ... Shahram Kordasti
    Tools and Resources

    Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users’ specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling.