# Leveraging Adaptive Evolution and High-Throughput Techniques to Dissect the Link Between Biochemical Function and Fitness

> **NIH NIH DP5** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $342,238

## Abstract

PROJECT SUMMARY/ABSTRACT
 Enzymes are the primary functional molecules in cells, providing enormous rate enhancements,
specificity and regulation to the diverse chemical reactions that are necessary for life. Enzymes, like all biological
macromolecules, are the products of evolution: all enzymes have evolved to operate within the complex
environment of the organism/cell in specific environmental niches(s). Thus, an understanding of enzyme function
and evolution is fundamental to biology. Enzymes also have tremendous potential in medicine (e.g., as targets
for anti-cancer, antimicrobial and antiviral drugs and as therapeutics for metabolic disorders) and in industry (e.g.
to make important commodity chemicals and as catalysts for bioremediation). Our central premise is that a
quantitative, mechanistic understanding of enzyme function and its relationship to organism fitness is critically
needed to precisely manipulate enzymes and to deeply understand biology.
 To generate this level of understanding, we need: (1) a quantitative, chemical, and physical knowledge
of enzyme function, and (2) mechanistic data describing how and when these physical principles contribute to
enzyme function within the complex environments where enzymes operate. An enhanced understanding of the
relationships between protein sequence, protein function and cellular/organismal fitness will have profound
impacts across biology and medicine, from improving our ability to predict how mutations will influence the
virulence and drug susceptibility of human pathogens, to enhancing precision medicine by accurately predicting
the consequences of allelic variants, to enabling the design of next-generation protein and cellular therapeutics.
Achieving this understanding requires new tools and a new conceptual paradigm. Enzymes are highly
interconnected, their functions are multifaceted, and their cellular environments are complex. Traditional
biochemistry is enormously powerful, allowing for the intensive study of a few individual enzymes in vitro (10s)
and providing detailed knowledge of their chemical mechanisms. But identifying the many residues that matter
for enzyme function requires investigation of residues beyond the active site at a scale far beyond that of
traditional biochemistry. Furthermore, this biochemical information then needs to be translated to organism
fitness in vivo in a quantitative manner. Here we will overcome these challenges. We will first use evolutionary
sequence information to direct enzyme variant design towards functionally important areas of sequence space.
We will adapt high-throughput microfluidic technologies to quantitively measure the biochemical properties (e.g.,
kcat, Km, Ki, and ∆GFold) of this library of 104 enzyme variants in vitro (Aim 1). Then we will determine how each
of these variants affects organismal fitness in vivo using pooled competition and barcode sequencing assays
(Aim 2). Finally, we will use this sequence-function-fitness map t...

## Key facts

- **NIH application ID:** 10480295
- **Project number:** 1DP5OD033413-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Margaux Pinney
- **Activity code:** DP5 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $342,238
- **Award type:** 1
- **Project period:** 2022-09-13 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10480295

## Citation

> US National Institutes of Health, RePORTER application 10480295, Leveraging Adaptive Evolution and High-Throughput Techniques to Dissect the Link Between Biochemical Function and Fitness (1DP5OD033413-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10480295. Licensed CC0.

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