The ultimate aim of the Blank lab, Chair of Applied Microbiology is to use microbes to the benefit of environment, society and economy. By studying the metabolism of bacteria and fungi we aim to optimize and control a wide array of applications, ranging from the production of platform chemicals to the spoilage of bio diesel.
By using the versatility of life itself, we can convert biological substrates (biomass, CO2, plastics and other underutilized carbon streams) into a wide array of important chemicals. The building blocks for anything from fuel to plastic to medicine can be produced from these renewable carbon sources using bacteria, yeast, and fungi. In this way, whole-cell biocatalysis can offer a cleaner, safer, and environmentally friendlier alternative to traditional chemical synthesis. Conversely, microbes can also degrade a wide range of chemicals. While this can be beneficial for the degradation of pollutants in the environment, it can also cause problems enhancing spoilage and corrosion.
Rational strain development
We can enable microorganisms to produce a wide array of chemicals by genetic engineering. However, for efficient production the metabolism of the organism must be re-routed to enhance product formation. In a process called metabolic engineering, specific reactions in the highly complex metabolic network of the organism are altered, introduced or deleted in order to increase the flux from substrate to product. This can be achieved by adding genetic ‘modules’ to the organism that encode enzymes that perform specific metabolic reactions, or by deleting the corresponding genes in the genome of the organism.
A typical microorganism contains thousands of genes, which encode thousands of proteins, which perform thousands of reactions. This level of complexity makes understanding the effect of even a single perturbation highly complex. Luckily, recent advances in bio-analytics have enabled us to analyze every aspect of the organism. Genome sequencing is increasingly affordable, and the determination of the relative and absolute abundance of transcripts, proteins, metabolites, and even reaction rates in the primary metabolism are becoming ever more accurate and affordable. The large volumes of data produced by such systems-wide analyses can be incorporated into computational metabolic models in order to understand the effect of different alterations. The ultimate aim is rational strain engineering: to be able to predict which genetic alterations in the highly complex organic system will lead to a desired effect.