Targeted discovery of antibiotics from cave bacteria

点击翻译按钮获取中文摘要

 DESCRIPTION (provided by applicant): The increasing prevalence of bacterial pathogens that are resistant to most of the clinically approved antibiotics is an alarming situation that has spurred renewed interest in antibiotic discovery programs. Since most antibiotics are derived from natural products produced by microorganisms, there is now intense interest in using new methods to screen genetically and chemically diverse collections of bacteria. However, identifying new molecules from bacterial extracts is confounded by the overwhelming presence of previously identified molecules as well as the fact that most of the biosynthetic potential of a organism is typically not expressed under laboratory growth conditions. We have characterized a unique collection of microbes obtained from deep within four different caves of New Mexico. Since these bacteria were isolated from remote, underexplored locations that are only just beginning to be mined for antibiotics, there is an increased probability of identifying molecules with unique chemical structures and new modes of action. The goal of this project is to use two new powerful platforms to identify and purify molecules active against multidrug resistant (MDR) bacteria from this diverse collection of cave bacteria. First, we will use our recently developed bacterial cytological profiling (BCP) approach to identify natural products with antibacterial activities in crude organic extracts or directly on plates. BCP uses quantitative fluorescence microscopy to measure the effects of antibiotic treatment on individual cells. Antibiotics that target different cellular pathways and different steps within a pathway generate unique cytological profiles, allowing identification of the likely cellular target of newly isolated compounds in a few hours. BCP works in complex crude extracts and subsequent fractions, allowing it to be used to guide natural product purification. We will sequence strains producing antibiotics and then use target directed genome mining (TDGM) and heterologous biosynthetic gene cluster (BGC) overproduction to identify novel antibacterial producing BGCs. Heterologous overexpression of normally silent BGCs will allow us to identify molecules missed by traditional screening.