Research Interests

Synthetic Biology

The vast majority of commodity and high-value chemicals that society relies on (e.g. medicines, synthetic materials, agrochemicals) are synthesized using petroleum-derived precursors. With the emerging field of synthetic biology, microbial production is now (more than ever) an attractive alternative to generate not only molecules found in nature (“natural product”) but also to expand the chemical diversity of biological systems (1). Among the topics encompassed by synthetic biology (2), we are particularly interested in access to, and engineering and production of complex natural products from terrestrial and aquatic sources.

Polyketide Biosynthesis and Engineering

Polyketides are one of the largest classes of known bacterial natural products. Examples of bacterial polyketides that found applications in biomedicine include antibiotic erythromycin, immunosuppressant FK506, and anticancer epothilone. Classical, bacterial polyketide synthases (PKSs) are giant, multi-modular molecular machines that have been referred to as “molecular lego” (3). Individual catalytic units or domains are organized into modules, with each module being responsible for incorporation and processing of a particular building block in an assembly-line fashion. Structural diversity comes from the combinatorial use of: i) the type and number of building blocks (activated carboxylic acid monomers); ii) the presence or absence of optional catalytic activities; and iii) the action of post-PKS, tailoring enzymes. Modular PKSs are remarkable templates for the production of polyketides, so that one can “read” the PKS domain architecture and deduce the structure of the natural product (to a certain extent) and vice-versa. Another modularity aspect of bacterial natural product biosynthesis is that biosynthetic genes are often clustered in a single locus in the chromosome and genes are frequently organized in regulatory units or operons, facilitating identification of the full set of genes for the biosynthesis of a particular natural product and aiding transfer to other systems. The modularity of polyketide biosynthesis offers tremendous opportunities for engineering further structural diversity and generating chemical novelty. In addition, polyketides are notoriously difficult to obtain synthetically, another argument for producing them by microbial fermentation.
 Polyketide Biosynthesis Figure

Mining Microbial Genomes for Natural Product Drugs

The ability to predict the biosynthetic potential of microorganisms from their genome sequences (“from genes to molecules”) and the ability to predict which genes should code for biosynthesis of a particular natural product (“from molecules to genes”) has the potential to revolutionize drug discovery and development efforts:

1) With the explosion of microbial genome sequences available, it has become clear that the biosynthetic potential of microorganisms is much higher than what you see through fermentation. A typical, natural product-producing bacterium will be known to make a few compounds, but ~30 may be predicted from its genome sequence. Why this discrepancy? Because most biosynthetic genes are silent or not well expressed under laboratory growth conditions. But knowing which genes are there (knowing what the potential is) gives you the chance to activate those genes and get the corresponding compounds.

2) Imagine you have a strain collection of 1,000s to 100,000s of strains. The ability to predict what types of natural products they can potentially make through genome mining, gives you the opportunity to select potentially “talented” strains to be included in the discovery pipeline.

3) Only a small fraction of bacterial strains can be cultured in the laboratory. Genome mining potentially allows access to natural products from uncultured microbes.

genome mining fig

In summary, the concept here is that one can go from genes to molecules and vice-versa. In other words, you can “read” the DNA sequence of an organism using bioinformatics and predict which natural products can be made. The image will be fuzzy, you won’t know the exact structure but you can have a rough idea or at least tell the biosynthetic class. The predictions can then guide you in deciding which strains or environments to focus on. You can also go the other way, if you have a natural product structure, you can predict which type of genes would code for that molecule, which in turn helps you in identifying those genes. Once biosynthetic genes are identified, the respective enzymes can be studied, the strains can be engineered to generate structural modifications or to increase production yields.


1. Keasling, J. D. (2012) Synthetic biology and the development of tools for metabolic engineering. Metab Eng 14, 189-195.
2. ACS Synthetic Biology Author Guidelines.
3. Hertweck, C. (2009) The biosynthetic logic of polyketide diversity. Angew Chem Int Ed Engl 48, 4688-4716.