# Regulation of Gammaherpesviral Late Gene Expression

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2022 · $388,435

## Abstract

ABSTRACT
Herpesviruses are endemic within the human population, and cause a wide range of life-threatening diseases.
Members of the betaherpesvirus and gammaherpesvirus subfamilies are extremely problematic in
immunocompromised individuals, leading to severe congenital disorders and a variety of cancers. This
proposal will define how a critical class of herpesviral genes are expressed late in the lifecycle of Kaposi's
sarcoma-associated herpesvirus (KSHV) through a mechanism that involves a novel transcription complex,
which combines both viral mimicry and co-option of select host machinery. The set of viral proteins required for
late gene activation are broadly conserved among the beta- and gammaherpesviruses, indicating that
information gained herein for KSHV will likely be applicable for Epstein-Barr virus and human cytomegalovirus
as well. The focus of this grant is to define the composition and regulation of this novel gene expression
complex, and reveal how its function is linked to viral genome replication. Given that even subtle mutations in
this late gene transcription complex effectively `kill' the virus, an understanding of its composition and
regulation is anticipated to reveal new targets for antiviral strategies.

## Key facts

- **NIH application ID:** 10368981
- **Project number:** 5R01AI122528-07
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Britt A Glaunsinger
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $388,435
- **Award type:** 5
- **Project period:** 2015-11-13 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10368981

## Citation

> US National Institutes of Health, RePORTER application 10368981, Regulation of Gammaherpesviral Late Gene Expression (5R01AI122528-07). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10368981. Licensed CC0.

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