# Synthetic environmental peptide libraries as a source of novel antibiotics

> **NIH NIH U19** · HACKENSACK UNIVERSITY MEDICAL CENTER · 2021 · $682,686

## Abstract

Project summary:
Bacterial natural products have historically been a very productive source of novel antibiotics. However, it is now
clear that shortcomings in traditional, culture-based, natural product discovery methods have limited our access
to only a small fraction of bacterial biosynthetic diversity in nature. These shortcomings are attributed to the fact
that we are able to culture only a small fraction (<1%) of the bacteria present in most environmental samples
and, furthermore, most biosynthetic gene clusters present in the genomes of this small fraction, comprising the
cultured bacteria, remain silent under laboratory fermentation conditions. The goal of this proposal is to combine
existing next generation sequencing data and novel metagenome cloning methods with bioinformatics-guided,
high-throughput chemical synthesis to develop a rich, new pipeline for identifying new antibiotics, inspired by the
large number of natural product biosynthetic gene clusters that have remained inaccessible to study by
traditional, cultured-based discovery approaches. High-throughput sequencing of bacterial genomic DNA
indicates that nonribosomal peptides biosynthetic gene clusters are likely to be the most common and diverse
natural product biosynthetic systems in bacterial genomes. Nonribosomal peptides identified in culture-based
studies have also proved to be a very productive source of antibiotics. Therefore, gaining access to a larger pool
of nonribosomal peptide synthetase-encoded peptides should be a productive strategy for identifying novel
antibiotics. Nonribosomal peptide biosynthesis is unique in that we understand it well enough that bioinformatic
algorithms have advanced to the point where it is possible to predict the structure of an nonribosomal peptide
from primary sequence data alone. Over the past two decades, a series of increasingly robust models have been
developed for predicting the identity, order, and modification of the amino acids comprising a nonribosomal
peptide, based solely on the primary sequence of its encoding megasynthetase gene. Concurrently, solid-phase
peptide synthesis of structurally diverse peptides has become rapid and economical. Here, I propose to join
nonribosomal peptide structure prediction tools and metagenome sequencing methods with solid-phase peptide
synthesis to provide a simple, high-throughput strategy for rapidly generating a large number of novel,
evolutionarily selected, antibacterial peptides from genomic (Aim 1) and metagenomic (Aim 2) derived gene
clusters data. In Aim 3 I propose a complementary heterologous expression strategy for exploring the most
complex nonribosomal peptide biosynthetic gene clusters that we recover from metagenomic libraries
constructed in Aim 2. Molecules generated in all three aims will be screened against ESKAPE pathogens for
antibacterial activity and the most potent hits will proceed to mechanism of action as well as PK/PD/toxicity
studies. The most promising antibiot...

## Key facts

- **NIH application ID:** 10138986
- **Project number:** 5U19AI142731-03
- **Recipient organization:** HACKENSACK UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** SEAN F BRADY
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $682,686
- **Award type:** 5
- **Project period:** 2019-05-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10138986

## Citation

> US National Institutes of Health, RePORTER application 10138986, Synthetic environmental peptide libraries as a source of novel antibiotics (5U19AI142731-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10138986. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*