# Spatially Structured Synthetic Consortia of Microbes to Understand and Engineer Cells in 3D Environments

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA-IRVINE · 2024 · $368,307

## Abstract

Project Summary/Abstract
 Microbes in natural habitats mostly exist in groups arranged in the 3D space of biofilms, and spatial
heterogeneity plays a key role in the stabilization, communication, and functions in these multi-species
consortiums. However, a proper platform to build a synthetic community of bacteria and systematically vary the
spatial parameter to deduce key fundamental knowledge in 3D microbial consortia – cellular phenotype,
differentiation, communication, gene expression, and metabolism – is currently lacking. My research program
aims to (1) develop a printing platform to construct 3D microbial consortia with well-defined polymers, (2) study
the physiology of cells confined in these 3D environments, and (3) engineer cells and their 3D arrangement to
yield biomaterials performing useful functions. The outcomes of our research endeavor will be (1) new
fundamental knowledge and understanding of microbial consortia with a 3-dimensional spatial context and (2)
functional biomaterials directly contributing to human health. Our contributions will be significant and have a
long-lasting impact by filling in the critical knowledge gap in our understanding and engineering capability of
microbial consortia relevant to biomedical science.

## Key facts

- **NIH application ID:** 10902087
- **Project number:** 5R35GM150770-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA-IRVINE
- **Principal Investigator:** Seunghyun Sim
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $368,307
- **Award type:** 5
- **Project period:** 2023-08-10 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10902087

## Citation

> US National Institutes of Health, RePORTER application 10902087, Spatially Structured Synthetic Consortia of Microbes to Understand and Engineer Cells in 3D Environments (5R35GM150770-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10902087. Licensed CC0.

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