# Antigen-specific B cell tolerance in the gut-associated lymphoid tissue (GALT)

> **NIH NIH R01** · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · 2020 · $487,500

## Abstract

   
DESCRIPTION (provided by applicant): Pathogens and dietary factors are transported across the gut epithelium. This poses a challenge of discriminating innocuous versus harmful antigens by innate and adaptive immune mechanisms. How B cells contribute to these processes is poorly understood. Moreover, recent studies indicate that B cells also undergo BCR diversification in the GALT, indicating that tolerance mechanisms need to be in place to eliminate newly arising autoreactive B cells. In the proposed work, we will use the conditional expression of a neo-self antigen to investigate B cell tolerance to epithelia-associated antigens in the GALT. This mouse model mimics the situation in some ulcerative colitis patients who produce auto-antibodies to antigens on epithelial cells of the colon. Proof-of-concept for the proposed studies is provided by our preliminary findings, showing that antigens expressed on the gut epithelia can efficiently eliminate self-reactive B cells. Here we will determine how and where these negative selection events take place, and how these processes are affected by a breach in the gut epithelial barrier as it relates to infection and inflammatory bowel disease.

## Key facts

- **NIH application ID:** 9828744
- **Project number:** 5R01AI122344-05
- **Recipient organization:** SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE
- **Principal Investigator:** John R Apgar
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $487,500
- **Award type:** 5
- **Project period:** 2015-12-01 → 2020-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9828744

## Citation

> US National Institutes of Health, RePORTER application 9828744, Antigen-specific B cell tolerance in the gut-associated lymphoid tissue (GALT) (5R01AI122344-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9828744. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*