Transcription Profiling for Natural Product Antibiotic Discovery


Most antibiotics were discovered by screening soil actinomycetes, but the efficiency of the platform collapsed in the 60s due to its success: more than 3,000 antibiotics have been described, and the majority of effort is spent on rediscovery of knowns, making the approach impractical. The last marketed antibiotic to be discovered was daptomycin (1985), and before then, linezolid (1962). The current state of the art in anti-infective is a non-existent pipeline in the absence of a discovery platform. The result is the emergence of pan-resistant pathogens. The current practice in dealing with the problem of the background of known compounds is to use chemical dereplication of extracts to assess the relative novelty of a compound it contains. Dereplication typically requires scale-up, extraction, and often fractionation before an accurate mass can be produced by MS analysis in combination with 2D NMR. Every extract becomes a separate project, incompatible with high-throughput screening. The value of information chemical dereplication produces is also modest, it tells us nothing about the potential value of the compound is it a useful lead, or a nuisance compound with non-specific mode of action, or an inhibitor of central metabolism? We propose to transform antimicrobial drug discovery by introducing transcriptome analysis as a rapid tool to identify promising compounds of producing organisms. Compounds affecting the same target produce distinct transcription profiles that cluster together. Nuisance compounds such as detergents, general metabolism inhibitors or DNA intercalators produce their own distinct profiles. Creating a large database of transcription profiles of known antibiotics will then allow one to automatically interrogate a profile produced by an active extract and classify compounds as known; novel hitting a known target; novel hitting a new valuable target; hitting an undesirable target; or a nuisance compound lacking specificity. This efficient determination will eliminate background and will essentially return us to the golden age of antibiotic discovery. The aim of this pilot study is to compare transcription profiles obtained by challenging S. aureus with antibiotics to the profiles from cells incubated with extracts from strains producing the same antibiotics. A reasonably good correlation is expected, which will provide the basis for producing a larger database of drug profiles, and for using transcription profiling in conjunction with screening natural products. Cells of S. aureus HG003 will be grown to mid-log (O.D.600=~0.5) in TSB broth. Antibacterial compounds will be added at 1x MIC (as determined by MIC culture determination) and incubated with cells for 30 minutes. The MIC of extracts will be first determined, and they will be added at 1x MIC as well. The 30-minute time point was determined by previously generated data by Drs. Jones and Lewis. Compounds and extracts used include: Valinomycin, Penicillin, Chloramphenicol, X4251, B26P7, Erythromycin, Actinomycin, Bacitracin, Rifampin and Novobiocin. Cells were exposed to 2% DMSO as a negative control for comparison/reference.

Investigators and Collaborators

Karen Nelson, PhD

President, Professor, J.Craig Venter Institute

Marcus Jones, PhD

Assistant Professor, J.Craig Venter Institute

Kim Lewis

Northeastern University