# R01 Supplement for Undergraduate Summer Research 2020

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $14,084

## Abstract

Summary of the parent project: In recent years, the field of bacterial cell-size control has received broad
attention due to the discovery of the “adder” principle by Christine Jacobs-Wagner’s lab and my lab. This
phenomenological principle states that cells add constant size between birth and division regardless of cell size
at birth. Until now, the vast majority of bacteria, budding yeast, and even some mammalian cell lines have been
shown to follow the adder principle. This directly refutes the 50-year old checkpoint-based paradigm of cell-size
control that cells should divide when they reach a fixed size. The goal of the funded parent award is to
understand the mechanisms underlying the adder principle. So far, our research has revealed that the adder
phenotype requires two general principles in biology (Si et al. 2019): (1) accumulation of division proteins (such
as FtsZ in bacteria) to their threshold number (2) their balanced biosynthesis during cell elongation. Therefore,
the adder principle is naturally robust to static growth inhibition, and these mechanistic principles further
allowed us to “reprogram” cell-size homeostasis in a quantitatively predictive manner in both Gram-negative
Escherichia coli and Gram-positive Bacillus subtilis.

## Key facts

- **NIH application ID:** 10146096
- **Project number:** 3R01GM118565-05S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Suckjoon Jun
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $14,084
- **Award type:** 3
- **Project period:** 2016-04-01 → 2021-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10146096

## Citation

> US National Institutes of Health, RePORTER application 10146096, R01 Supplement for Undergraduate Summer Research 2020 (3R01GM118565-05S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10146096. Licensed CC0.

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