# An unbiased screen to identify Neisseria gonorrhoeae genes important for survival to neutrophil killing mechanisms

> **NIH NIH R21** · NORTHWESTERN UNIVERSITY · 2021 · $279,125

## Abstract

ABSTRACT
 The human-restricted Neisseria are a collection of related, host-adapted organisms that
show a spectrum of pathogenicity, from true commensals to pathogens. The pathogenic
species, Neisseria gonorrhoeae and Neisseria meningitidis, have the ability to switch from a
more commensal state to produce host damage. Much of the host damage produced by the
pathogenic species is the result of host inflammation, particularly, polymorphonuclear
leukocytes (PMNs), and these bacteria have evolved many ways to avoid the antimicrobial
functions of PMNs. While many studies have identified a number of bacterial genes and gene
products that help the Neisseria resist PMN killing processes, many other bacterial species use
these gene to resist PMN activities. I propose to conduct an unbiased, genetic screen for novel
factors that allow N. gonorrhoeae to resist killing or growth suppression by PMNs to determine
mechanisms that have allowed this pathogenic species to resist control by innate immune
responses. This screen will provide preliminary results to uncover new mechanisms of N.
gonorrhoeae pathogenesis.

## Key facts

- **NIH application ID:** 10197033
- **Project number:** 5R21AI148981-02
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Hank S. SEIFERT
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $279,125
- **Award type:** 5
- **Project period:** 2020-06-17 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10197033

## Citation

> US National Institutes of Health, RePORTER application 10197033, An unbiased screen to identify Neisseria gonorrhoeae genes important for survival to neutrophil killing mechanisms (5R21AI148981-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10197033. Licensed CC0.

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