# C-di-AMP signaling in S. aureus

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2020 · $587,828

## Abstract

Abstract
Staphylococcus aureus is a leading cause of human morbidity and mortality, causing infection of
the skin and soft tissues, post-surgical wounds, and lung infection among influenza and cystic
fibrosis patients. Widespread multi-drug resistance has made eradication of S. aureus
increasingly challenging, necessitating a deeper understanding of the physiology and
pathogenesis associated with these organisms. A key aspect of bacterial survival and adaptation
to altered environmental conditions is the ability to rapidly alter cellular behavior through second
messenger signal transduction. C-di-AMP has recently emerged as a key regulator of bacterial
physiology, pathogenesis, and immune activation. In the context of S. aureus, we believe that c-
di-AMP produced by S. aureus has three important roles; (i) as a signaling molecule that mediates
S. aureus metabolism and antibiotic resistance, (ii) as a bacterial PAMP that promotes
pathological inflammation and host susceptibility to bacterial infection, and (iii) as a mediator of
inter-bacterial signaling that alters the outcome of co-infections. Findings from these studies may
have significant impacts on the course of antibiotic therapy during S. aureus infection and may
uncover a novel target to eradicate recalcitrant S. aureus and the inflammation itpromotes.

## Key facts

- **NIH application ID:** 9858253
- **Project number:** 5R01AI139071-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Joshua Woodward
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $587,828
- **Award type:** 5
- **Project period:** 2019-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9858253

## Citation

> US National Institutes of Health, RePORTER application 9858253, C-di-AMP signaling in S. aureus (5R01AI139071-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9858253. Licensed CC0.

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