# Defining mechanisms of Zika-virus associated microcephaly: cell population dynamics and gene expression in infected human cerebral organoids and neural progenitor cells

> **NIH NIH K08** · BOSTON CHILDREN'S HOSPITAL · 2021 · $194,940

## Abstract

PROJECT SUMMARY/ABSTRACT
Zika virus swept across the Americas in 2015-16, and it was during this epidemic that the teratogenic
consequences of congenital Zika infection were first described. Despite extensive research, it remains
unknown how Zika infection causes microcephaly, or whether this pathology is unique to recent strains, Two
new tools will facilitate discovery in this area. First, we and others have shown that the human stem cell
derived cerebral organoid is a tractable neurodevelopmental model in which to study Zika infection. Second,
we have demonstrated that single cell sequencing techniques that enrich for poly-adenylated mRNAs can
identify flavivirus-infected cells – an unexpected result given flavivirus genomes do not have poly(A) tails. The
goal of this study is to determine the mechanisms by which Zika virus disrupts fetal brain development,
building on these technical advances. We will employ single cell RNA-sequencing to identify and compare
cellular populations in organoids over time, in the presence and absence of Zika virus. This will allow us to
distinguish pathogenic disruptions in a) stem cell abundance, b) cell division, and c) differentiation. We will
use single cell RNA-sequencing and ribosome profiling to define gene expression responses to Zika infection
in neural progenitor cells, thought to be the target of Zika virus in the fetal brain. By comparing viruses of
varying pathogenicity in these studies, we will identify differences in host gene expression and viral replication
associated with disease severity. The proposed study will address a major unresolved problem in the field of
Zika virus pathogenesis, contribute broadly to our understanding of cerebral development, and mature cutting
edge technologies for the investigation of questions at the interface of infection and development.
The project will be developed under the mentorship of Dr. Lee Gehrke, a leader and expert in the field of RNA
virology with a background in developmental biology. Additional scientific and career guidance will be provided
by a scientific advisory committee composed of experts in virology, single-cell sequencing, stem-cell derived
tissue models, and pediatric infectious disease pathogenesis. The training program will include coursework
in computational biology, training in molecular and tissue culture techniques, workshops in leadership, and
didactic learning from local seminars as well as national and international conferences. Research and training
will occur at the MIT Institute for Medical Engineering and Science, and at Boston Children’s Hospital at the
Harvard Medical School. Together, MIT and Harvard Medical School afford extensive resources and expertise
in all aspects of the proposed research. Boston Children’s Hospital is a supportive environment committed to
providing 85% protected time for this research, and offers workshops in career development and leadership
to prepare early-stage investigators for independence. The pr...

## Key facts

- **NIH application ID:** 10105573
- **Project number:** 1K08AI156126-01
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Karen Emily Ocwieja
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $194,940
- **Award type:** 1
- **Project period:** 2021-07-23 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10105573

## Citation

> US National Institutes of Health, RePORTER application 10105573, Defining mechanisms of Zika-virus associated microcephaly: cell population dynamics and gene expression in infected human cerebral organoids and neural progenitor cells (1K08AI156126-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10105573. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*