# Multisizer 4e - equipment for "Fitness Effects of Beneficial Mutations"

> **NIH NIH R35** · STANFORD UNIVERSITY · 2024 · $83,658

## Abstract

Project Summary/Abstract (from Parent R35 Grant)
 The progression of cancer and infectious disease is an evolutionary process. Pathogens engage in an arms
race with their hosts, and while antibiotics/antivirals have enabled us to skew the outcome of these contests,
these bulwarks against contagion are being steadily eroded. Mutation and natural selection, coupled with rapid
generation times and immense pathogen population sizes, provide pathogens a decisive advantage. To regain
the upper hand, we must better understand the evolutionary process, to aid in the development of novel classes
of antimicrobials and devise therapeutic strategies that take into account how these weapons work and how
pathogens evade them. Until recently, efforts to gain a deep understanding of the adaptive process were stymied,
because adaptive mutations are rare and identifying them is challenging. To solve this, we developed a system
to track the evolutionary process, isolate thousands of adaptive lineages, remeasure the fitness of those lineages
across many environments, and cheaply whole genome sequence hundreds to thousands of such mutants.
 I propose a new phase in my ambitious, integrated research program that takes full advantage of this lineage
tracking system, and our discovery of Pareto fronts, which are indicative of trade-offs. We will pursue two major
goals. First, we will expand our understanding of evolution in the face of abiotic selection pressures, especially
those that produce adaptive trade-offs. Specifically, we will determine the role of historical contingency as it
pertains to trade-offs in adaptation, the potential for trade-offs to force canalization (e.g., trapping lineages into
extreme specialization), the influence that epistasis exerts on the geometry of trait space, and the extent to which
adaptive constraints underlie negative and diminishing returns epistasis. Second, we will expand to contrast
these findings with evolutionary outcomes under biotic selection pressures, using two new systems. To model
genetic conflict and arms race dynamics within species we will use the killer yeast system. Killer yeast secrete a
toxin that destroys sensitive yeast, while retaining an intracellular antitoxin. Toxin and antitoxin are both encoded
by a vertically inherited virus, which itself parasitizes a second virus. We will co-evolve killer and sensitive cells
and determine whether, as theory predicts, there are recurrent periods of selection and whether coevolved
solutions show greater trade-offs than typically observed from abiotic selection pressures. To experimentally
model arms race dynamics between species we will use crAssphage, one of the most prevalent bacteriophages
associated with the human gut microbiome. The aim of these evolution experiments will be to evaluate the
dynamics of phage and its bacterial host co-adaptation over trials of short- and medium-term duration. Overall,
this integrated, multi-level research strategy will yield fundament...

## Key facts

- **NIH application ID:** 11098321
- **Project number:** 3R35GM131824-06S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Gavin J Sherlock
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $83,658
- **Award type:** 3
- **Project period:** 2019-05-01 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11098321

## Citation

> US National Institutes of Health, RePORTER application 11098321, Multisizer 4e - equipment for "Fitness Effects of Beneficial Mutations" (3R35GM131824-06S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11098321. Licensed CC0.

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