The new era in industrial biotech and in particular fermentation-based production processes is increasingly driven by the emerging ultra-fast sequencing technologies applying a broad utilization of genotyping studies. It is generally recognized that the current major bottleneck is the systematic handling of the large data volumes produced by next-gen sequencers and the interpretation of the genotype data across complex ancestries of production strains.

The design of improved production strains is of major interest to Evonik Degussa, a leading producer of L-amino acids by microbial production strains derived from C. glutamicum and E. coli. Here, we present next-gen sequencing data comparing 25 proprietary strains, resulting from random mutagenesis campaigns and directed strain engineering strategies. We have used the Genedata Phylosopher to systematically process and annotate these strains including automated identification and categorization of point mutations into their genetic and biological context. This process is assisted by tailored viewers to drill down to the sequencing data, predicting the mutations’ influences on gene products (e.g. by modifying an enzyme’s active site) or on the gene regulation (e.g., by altering a transcription factor’s DNA binding site). The software also provides tools for investigating downstream effects on the metabolic, signaling and regulatory level.

This study demonstrates how next-gen sequencing data, if appropriately processed and analyzed, can be capitalized upon to guide rational genomic design strategies to improve strains for increasing yields like L-amino acids or different products such as vitamins or enzymes.