# Quality Control of Antibody Responses by the Innate Signaling Adaptor MAVS

> **NIH NIH R21** · UNIVERSITY OF ARIZONA · 2021 · $191,875

## Abstract

ABSTRACT
 Innate immune recognition of microbial compounds by pattern recognition receptors (PRRs) represents a
central regulatory checkpoint in the control of adaptive immune responses. Rig-I-like receptors (RLRs) comprise
a PRR family that includes the RNA helicases RIG-I and MDA-5. RLRs recognize microbial RNA species in the
cytosol and rely on the essential signaling adaptor MAVS for the induction of the cellular response. RLRs are
important mediators of innate immunity to multiple viral infections. However, the role of RLRs in the regulation of
adaptive immunity is still poorly understood. MAVS-deficient mice infected with West Nile Virus (WNV) fail to
develop an effective virus-specific neutralizing antibody response, suggesting an important role for MAVS
signaling in the control of humoral immunity. Here, we will employ a single-round-of-infection mutant of WNV to
probe the central hypothesis that RLRs regulate the quality control of the antibody response. Our study will
therefore address fundamental mechanistic questions about the role of RLRs in the adaptive immune response
to WNV and other RNA viruses. Such insights will advance the development of novel vaccine strategies against
WNV and related flaviviruses.

## Key facts

- **NIH application ID:** 10114197
- **Project number:** 5R21AI146388-02
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** DOMINIK SCHENTEN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $191,875
- **Award type:** 5
- **Project period:** 2020-03-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10114197

## Citation

> US National Institutes of Health, RePORTER application 10114197, Quality Control of Antibody Responses by the Innate Signaling Adaptor MAVS (5R21AI146388-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10114197. Licensed CC0.

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