# Project 2: Use of 2D cultures and 3D organoids to identify candidate antiviral compounds; to use genetic approaches to identify host genes that promote or protect against flavivirus infection

> **NIH NIH U19** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2021 · $543,548

## Abstract

To address a critical need for improved human tissue models to study infectious diseases, we propose to form 
the MIT Center for Human Tissues and Infectious Diseases (MIT.HTMID). The MIT.HTMID Center will study 
viral infections of the human brain and central nervous system by using biologically relevant two dimensional 
(2D) human neural cells and three dimensional (3D) human cerebral organoids. The cells are homogeneous 
preparations of human neuronal progenitors, neurons, oligodendrocytes, astrocytes, and microglia, derived 
from embryonic stem (ES) cells or induced pluripotent stem cells (iPS cells), and will be produced in the 
MIT.HTMID Human Cell and Tissue Core. Prior work has demonstrated that these cells and the organoids 
formed are near-physiological in their biological functions, thereby representing an experimental system that is 
superior to rodent models. MIT.HTMID Project 2 will focus on the applied use of the 2D and 3D tissue models 
for the purposes of a) testing a panel of published antiviral compounds for efficacy in blocking virus infections, 
and b) studying the genetics of infectious disease by performing CRISPR-Cas9 gene knockouts to identify host 
dependency genes that regulate virus infections or are regulated by virus infections. Project 2 Aim 2A will test 
a panel of published antiviral compounds for efficacy in blocking virus infections. The approaches will couple 
the cells and organoids with infections using two types of viruses, produced in the MIT.HTMID Virology Core. 
First, we will study flaviviruses, including Dengue Fever Virus, West Nile Virus, and Zika Virus. Indeed, an 
important motivation for studying human brain tissue and viruses is to understand the pathogenesis of Zika 
virus infections, which are causing microcephaly and Guillain-Barre syndrome worldwide. Second, we will use 
pseudotyped vesicular stomatitis viruses (VSV) to study entry of several encephalitic viruses, including Eastern 
Equine Encephalitis Virus (EEEV), Western Equine Encephalitis Virus (WEEV) and Venezuelan Equine 
Encephalitis Virus (VEEV). By replacing the VSV viral envelope with that of EEEV, WEEV, or VEEV, we are 
able to study virus entry of select (i.e. highly dangerous with potential application in biowarfare) agents in the 
2D cells and 3D organoids. Using pseudotyped select viruses and multiple relevant cell types will allow us to 
study virus tropism, pathology, and potential therapeutic targets. Project 2 Aim 2A is not a high throughput 
screen; rather, the goal is to test the efficacy of a panel of published antivirals in blocking infections of the 2D 
neural cells and 3D organoids. Project 2 Aim 2B.i and 2B.ii will focus on performing and validating CRISPR- 
Cas9 screens that couple the neural cell types with infections by Zika virus or pseudotyped VSV. These 
screens will identify host dependency factors (HDF) that are required for the viral replication cycle, and may 
identify targets for therapeutic intervention. ...

## Key facts

- **NIH application ID:** 10141199
- **Project number:** 5U19AI131135-05
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Lee Gehrke
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $543,548
- **Award type:** 5
- **Project period:** 2017-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10141199

## Citation

> US National Institutes of Health, RePORTER application 10141199, Project 2: Use of 2D cultures and 3D organoids to identify candidate antiviral compounds; to use genetic approaches to identify host genes that promote or protect against flavivirus infection (5U19AI131135-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10141199. Licensed CC0.

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