# Molecular determinants of bacterial interactions and maintenance in the Vibrio fischeri-Euprymna scolopes symbiosis

> **NIH NIH R35** · PENNSYLVANIA STATE UNIVERSITY, THE · 2024 · $88,780

## Abstract

PROJECT SUMMARY
The health of animals often depends on their ability to form symbioses with bacteria that are acquired from
environmental reservoirs. Bacteria that express specific traits that increase host fitness, and in many cases,
hosts that lack these beneficial symbionts are at increased risk for developing disease. As part of our long-
term goal to understand how these symbioses are established and maintained, this proposal will investigate
several factors that impact the ability of the beneficial symbiont Vibrio fischeri to colonize and be maintained by
its natural host the Hawaiian bobtail squid Euprymna scolopes. The focus will be on three areas: 1)
interference competition among beneficial symbionts, 2) the role of sulfur metabolism in symbiont physiology,
and 3) evolution of signaling systems in bacterial symbionts. Progress in understanding these areas will
provide new insights into the mechanisms enabling bacterial symbionts to colonize and be maintained by their
hosts. The findings associated with this project may contribute to the strategies employed to improve host
health by manipulating beneficial symbionts.

## Key facts

- **NIH application ID:** 11032061
- **Project number:** 3R35GM152259-01S1
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** Timothy Miyashiro
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $88,780
- **Award type:** 3
- **Project period:** 2024-02-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11032061

## Citation

> US National Institutes of Health, RePORTER application 11032061, Molecular determinants of bacterial interactions and maintenance in the Vibrio fischeri-Euprymna scolopes symbiosis (3R35GM152259-01S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11032061. Licensed CC0.

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