# Transcriptional Control of Human Cytomegalovirus Latency

> **NIH NIH R01** · UNIVERSITY OF WISCONSIN-MADISON · 2024 · $453,180

## Abstract

Abstract
HCMV encodes multiple proteins that suppress lytic phase immediate early (IE) transcription during latency.
These include Us28 and UL138. We identified a new repressor of the MIEP during latency: the Pentamer.
The Pentamer is a five-member glycoprotein complex consisting of gH, gL, UL128, UL130, and UL131 that
is required for entry into epithelial and endothelial cells. We determined the Pentamer represses the MIEP
during both lytic and latent infections. Provocatively, we determined at least two different Pentamer alleles
exist, one that strongly represses the MIEP, and one that weakly represses the MIEP. We hypothesize that
HCMV uses unique Pentamer alleles to create different sub-sets of virions pre-programmed to either
initiate a lytic infection or to establish latency. To test this hypothesis, in Aim 1 we will create genetically
matched virus strains (laboratory and clinical) with pro-lytic or pro-latency Pentamer alleles and test them for
their propensity to initiate lytic infection in fibroblasts, epithelial and endothelial cells, to select against
Pentamer function during fibroblast propagation, and to establish latency in primary CD34+ cells. In Aim 2
we will determine the mechanism through which the Pentamer represses the MIEP.

## Key facts

- **NIH application ID:** 10979013
- **Project number:** 2R01AI130089-06
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** ROBERT F KALEJTA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $453,180
- **Award type:** 2
- **Project period:** 2018-04-11 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10979013

## Citation

> US National Institutes of Health, RePORTER application 10979013, Transcriptional Control of Human Cytomegalovirus Latency (2R01AI130089-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10979013. Licensed CC0.

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