# Co-opting Endogenous Pathogen Autolysins as Next Generation Antibiotics

> **NIH NIH R01** · DARTMOUTH COLLEGE · 2021 · $547,683

## Abstract

Summary:
Antibiotic resistance represents one of the greatest threats to human health. In particular, the six so-called
ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter
baumanii, Pseudomonas aeruginosa, and enterobacteriaceae) represent highly drug-resistant bacteria that
exert a tremendous global burden of disease. The potential scope of this crisis was highlighted in a recent
report commissioned by the Wellcome Trust and British Government; the authors projected that, by 2050,
drug-resistant bacterial infections could cost the global economy a cumulative $100 trillion and kill 10 million
people annually. To address this issue, there is a critical need for innovative antibacterial treatments. One
compelling therapeutic strategy leverages recombinant enzymes that degrade cell wall peptidoglycan, thereby
causing bacterial lysis and death. Currently, all such lytic enzyme therapies are trans-acting in nature, i.e., they
are derived from bacteriophage or the immune systems of eukaryotic organisms. This proposal seeks to
establish an entirely new paradigm for developing bacteriolytic enzyme drugs. We hypothesize that a
pathogen's own endogenous cell wall hydrolases (i.e., “autolysins”) can be co-opted to yield potent
antimicrobial agents that are refractory to new resistance phenotypes. To test this hypothesis, we will pursue
initial studies with the high impact pathogen methicillin resistant S. aureus (MRSA), although the strategy
should be broadly applicable to any bacterial pathogen. Here, complementary computational and experimental
approaches will be utilized to identify, isolate, and engineer potent autolysins derived from staphylococcal
proteomes. In aim 1, the sequenced genome of S. aureus and related bacteria will be searched for autolysins
using bioinformatics. Candidate enzymes will be cloned, evaluated, and their activities will be improved via
computationally guided fusion to high performance cell wall targeting domains. In aim 2, a complementary high
throughput screening strategy will be taken to identify autolysins from genomic libraries of pathogenic
staphylococci. The activities of candidate enzymes will be improved via combinatorial chimeragenesis with
high performance cell wall targeting domains, followed by high throughput functional screening of the resultant
chimeric libraries. In aim 3, lead autolysin candidates will be further engineered for potent anti-staphylococcal
activity using a directed evolution strategy. The most promising lead candidates from these studies will be
rigorously evaluated using a panel of clinically relevant in vitro and in vivo assays. Ultimately, this project could
yield both novel anti-staphylococcal agents and an entirely new paradigm for development of antibacterial
biotherapies.

## Key facts

- **NIH application ID:** 10053699
- **Project number:** 5R01AI123372-05
- **Recipient organization:** DARTMOUTH COLLEGE
- **Principal Investigator:** Karl E Griswold
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $547,683
- **Award type:** 5
- **Project period:** 2016-11-18 → 2022-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10053699

## Citation

> US National Institutes of Health, RePORTER application 10053699, Co-opting Endogenous Pathogen Autolysins as Next Generation Antibiotics (5R01AI123372-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10053699. Licensed CC0.

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