# Genome-Scale Models of Stress Response for E. coli

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $418,740

## Abstract

The genomic sequence of Escherichia coli appeared in 1997. Since 1998, this R01 program has systematically
built genome-scale models of E. coli, culminating with models of Metabolism and protein Expression (ME models)
that compute up to 80% of the proteome by mass in rapidly growing cells [1]. The models generated under this
program have deepened our understanding of how to read genomes, computationally model the physiological
processes they encode, and to guide design of interventions. These genome-scale models have enabled
hundreds, possibly over a thousand, systems biology studies of bacteria.
Half of the unmodeled proteome represents stress functions that provide responses to oxidative, thermal, and
acid stresses. The human immune system uses these stresses to eradicate pathogens, but no mechanistic
model can currently compute how these stresses perturb key cellular processes on a genome-scale. Therefore,
new modeling methods are needed. Our preliminary data strongly indicate that the underlying molecular
mechanisms can be modeled by extending the ME modeling approach. Our laboratory has also developed
Adaptive Laboratory Evolution (ALE) technology capable of generating hundreds of evolved strains and high
precision DNA assembly protocols to find all mutations occurring during ALE. We can thus computationally
model, experimentally evolve, molecularly profile and mechanistically determine the genetic basis of stress
tolerance.
We propose an iterative three-step process that will 1) EVOLVE E. coli under various stress conditions, 2)
ANALYZE the resulting phenotypes through data analytics and mechanistic modeling, and 3) VALIDATE model-
driven hypotheses. This iterative workflow takes advantage of our ALE technology, extensive mutational and
RNA-Seq databases with accompanying data analytics, and genome-scale modeling capabilities to elucidate
cellular responses to oxidative, thermal, and acid stresses.
A major outcome of the proposed program is an experimentally-validated genome-scale model that employs
novel methodologies to describe stress responses, metabolism and protein expression (called the StressME
model) that increase computational coverage of the E. coli proteome up to 90% of proteome mass. In particular,
the three stresses that we propose to study are critical for a deep systems-level understanding of the tolerance
that pathogens have against the stresses imposed by the immune system and certain types of antimicrobials.
The genetic basis revealed can be compared to characteristics of wild type strains isolated from patients. Thus,
these new models will facilitate future translational studies that investigate infectious disease.

## Key facts

- **NIH application ID:** 10202633
- **Project number:** 5R01GM057089-20
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** BERNHARD O PALSSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $418,740
- **Award type:** 5
- **Project period:** 1998-08-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10202633

## Citation

> US National Institutes of Health, RePORTER application 10202633, Genome-Scale Models of Stress Response for E. coli (5R01GM057089-20). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10202633. Licensed CC0.

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