PROTEOMINING: a novel proteomics-based pipeline for drug and enzyme discovery in filamentous actinomycetes
Can a new proteomics workflow be developed to link genes and gene clusters to bioactive molecules, identify novel compounds and enhance the production in the Streptomyces lividans enzyme?
Streptomycetes are exceptional microorganisms with respect to their lifestyle as mycelium-producing soil bacteria and their ability to produce a vast variety of useful bioactive compounds and enzymes. They are the largest source of antibiotics and therefore important for combating the now rapidly emerging multiple drug-resistant pathogens. Next-generation sequencing technologies now make it feasible to obtain the genome sequence for novel producing organisms, which generates an immense bulk of information that must be narrowed down to the gene(s) of interest. This is not straightforward, as illustrated by the 20 gene clusters for secondary metabolites and the numerous protease genes found in a single streptomycete. Current genome mining strategies fail to deliver high-throughput results and often focus on already known chemistry and enzymatic activity.
Dr. Gubbens proposes to develop a proteomics workflow based on differences in protein expression levels under inducing and non-inducing conditions to link genes and gene clusters to bioactive molecules. This technology will then be applied to identify novel compounds and to understand the changes that lead to enhanced production in the industrial enzyme producer Streptomyces lividans. The key objectives are:
(i) build a new proteomics workflow. For this, available genome sequences will yield a database of protein sequences, which can be used in LC-MS/MS (liquid chromatography coupled to tandem mass spectrometry) to detect proteins that are expressed in the strain of interest;
(ii) compare strains grown under producing and non-producing conditions in a comparative quantitative proteomics workflow based on metabolic labelling with stable isotopes and match the proteins to bioactivity;
(iii) understand the global changes in expression profiles that connect to improved production in an industrial production strain.
The project benefits from the expertise and equipment available at Leiden University and from collaborations with outstanding research groups and companies.