Public Abstract

DE-SC0021340: Discovery of Signaling Small Molecules (e.g. quorum sensing molecules) from the Microbiome

Award Status: Expired

Institution: Carnegie Mellon University, Pittsburgh, PA
UEI: U3NKNFLNQ613
DUNS: 052184116

Most Recent Award Date: 09/21/2023
Number of Support Periods: 3
PM: Madupu, Ramana

Current Budget Period: 09/15/2022 - 09/14/2024
Current Project Period: 09/15/2020 - 09/14/2024
PI: Mohimani, Hosein

Supplement Budget Period: N/A

Public Abstract

Microbial communities are regulated through the interactions between their microbial members (microbe-microbe interactions). It is known that most of the signal transduction pathways in the microbiome are modulated through the small molecule products of the microbial biosynthetic gene clusters (BGCs). Advances in 16S and shotgun metagenomics have revolutionized our understanding about the microbial composition of various communities and their BGCs. Preliminary results from our group and others show that environmental metagenomes contain thousands of biosynthetic gene clusters (BGCs) with uncharacterized small molecule products that potentially play roles in signal transduction. The overarching aim of this proposal is to develop computational techniques for discovering these small molecules and characterizing their role in signal transduction. Recent analysis of tens of thousands of public isolated genome / metagenomes has resulted in the identification of over 330,000 BGCs included in the Integrated Microbial Genome Atlas of biosynthetic Gene Clusters (IMG-ABC). However, connecting these BGCs to their molecular products has not kept pace with the speed of microbial genome sequencing (less than 1% of the BGCs from IMG-ABC are connected to their molecular products). Discovering the chemical structure of these BGC products is the first step toward characterizing their activity. Moreover, many of these products might have novel chemistry / modifications, shedding lights on the functionality of biosynthetic enzymes. The overarching goal of this proposal is to develop a high-throughput platform for determining the molecular products of BGCs in IMG-ABC using large mass spectral dataset. The expected outcome is a catalogue of microbial small molecules that play roles in signalling in plant-associated microbial communities, along with their BGCs. We recently developed computational techniques, including Dereplicator and Dereplicator+, for the identification of known small molecules and their variants from tandem mass spectra. Searching billions of mass spectra from the publicly available datasets (e.g. Global Natural Products Social molecular networking infrastructure, GNPS) using these tools has revealed thousands of known small molecules and their novel variants. However, the majority of GNPS spectra remain unannotated. As a step forward, we hypothesize many of these unannotated spectra are the product of BGCs in microbial genomes/metagenomes. Building upon our previous work on developing new computational tools for discovering natural products from mass spectral and genomic data, in this proposal, our immediate plan is to develop new algorithms to elucidate the structure of novel signaling peptide natural products (PNPs) from the microbial communities, and to construct a catalogue of signaling PNPs and their BGCs. We will do this by (i) predicting modification of peptide natural products from their BGCs, (ii) constructing Atlas of hypothetical small molecules by mining microbial genomes and IMG-ABC, (iii) collecting LC-MS-MS data on plant microbial isolates, and discovering PNPs with novel modifications in these spectra using our Atlas. While our computational methods are designed for general discovery of novel PNPs, we will put a special emphasis on the discovery of signaling PNPs from plant-associated microbes. All the data, software, and results developed during the course of this proposal will be available to the researchers through the GNPS infrastructure.

Microbial communities are regulated through the interactions between their microbial members (microbe-microbe interactions). It is known that most of the signal transduction pathways in the microbiome are modulated through the small molecule products of the microbial biosynthetic gene clusters (BGCs). Advances in 16S and shotgun metagenomics have revolutionized our understanding about the microbial composition of various communities and their BGCs. Preliminary results from our group and others show that environmental metagenomes contain thousands of biosynthetic gene clusters (BGCs) with uncharacterized small molecule products that potentially play roles in signal transduction. The overarching aim of this proposal is to develop computational techniques for discovering these small molecules and characterizing their role in signal transduction.

Recent analysis of tens of thousands of public isolated genome / metagenomes has resulted in the identification of over 330,000 BGCs included in the Integrated Microbial Genome Atlas of biosynthetic Gene Clusters (IMG-ABC). However, connecting these BGCs to their molecular products has not kept pace with the speed of microbial genome sequencing (less than 1% of the BGCs from IMG-ABC are connected to their molecular products). Discovering the chemical structure of these BGC products is the first step toward characterizing their activity. Moreover, many of these products might have novel chemistry / modifications, shedding lights on the functionality of biosynthetic enzymes. The overarching goal of this proposal is to develop a high-throughput platform for determining the molecular products of BGCs in IMG-ABC using large mass spectral dataset. The expected outcome is a catalogue of microbial small molecules that play roles in signalling in plant-associated microbial communities, along with their BGCs.

We recently developed computational techniques, including Dereplicator and Dereplicator+, for the identification of known small molecules and their variants from tandem mass spectra. Searching billions of mass spectra from the publicly available datasets (e.g. Global Natural Products Social molecular networking infrastructure, GNPS) using these tools has revealed thousands of known small molecules and their novel variants. However, the majority of GNPS spectra remain unannotated. As a step forward, we hypothesize many of these unannotated spectra are the product of BGCs in microbial genomes/metagenomes. Building upon our previous work on developing new computational tools for discovering natural products from mass spectral and genomic data, in this proposal, our immediate plan is to develop new algorithms to elucidate the structure of novel signaling peptide natural products (PNPs) from the microbial communities, and to construct a catalogue of signaling PNPs and their BGCs. We will do this by (i) predicting modification of peptide natural products from their BGCs, (ii) constructing Atlas of hypothetical small molecules by mining microbial genomes and IMG-ABC, (iii) collecting LC-MS-MS data on plant microbial isolates, and discovering PNPs with novel modifications in these spectra using our Atlas. While our computational methods are designed for general discovery of novel PNPs, we will put a special emphasis on the discovery of signaling PNPs from plant-associated microbes. All the data, software, and results developed during the course of this proposal will be available to the researchers through the GNPS infrastructure.