INSIGHTS
Genomics accelerates food innovation Gene-trait
matching enables NIZO food research to predict functional properties of starter and probiotic cultures and to optimize fermentation conditions. Fermented foods constitute a large part of the human diet. Examples are products like cheese, yoghurt, bread, wine, beer and soy sauce. In order to obtain specific product characteristics, microorganisms such as bacteria, yeasts and molds are added to milk, fruits, cereals, soy and other food substrates. Well-known examples of bacteria used in this way are Lactococcus lactis, Lactobacillus plantarum and Streptococcus thermophilus. Enzymes of these microorganisms, particularly amylases, proteases, and lipases, hydrolyze polysaccharides, proteins, and lipids into nontoxic products with flavors, aromas, and textures that consumers find appealing. Modern genomics technologies offer unprecedented options for optimization of fermentation conditions. NIZO food research, an independent contract research company working on tasty, healthy, sustainable, affordable and safe foods, is at the forefront of this development.
Predicting functional properties
Genomics has matured into a powerful technique for analyzing microbial activity. Next-generation sequencing techniques have made it possible to determine the genetics of microorganisms quickly and relatively cheaply. Much information about the genetic code of industrially employed microorganisms is currently becoming available. The datasets obtained through “omics” technologies offer interesting strategies for the delivery of tasty, safe and healthy food products. NIZO food research has
developed various analytical and predictive bioinformatic tools that can help food companies optimize their fermentation processes. One of these techniques is referred to as genotype-phenotype-matching analysis, or gene-trait matching. Gene-trait matching makes it possible to predict the behavior and functionalities of a microorganism in a given fermentation, based on the microorganism’s genetic code. “Application of our tools can optimize fermentation processes in various ways, for example with the respect to the growth of a bacterial strain on certain sugars, for instance, or related to production of specific compounds such as flavors and vitamins,” said Dr Sacha van Hijum, principal scientist bioinformatics at NIZO food research and group leader of the Radboud umc bacterial (meta) genomics group. Gene-trait matching may also lead to identification of factors contributing to quality and shelf-life survival of the food product in a knowledgebased manner. If research data on the robustness/ resistance of spoilage strains to cleaning protocols (high temperatures, types of detergents) can be associated with specific genes responsible for this resistance, this could lead to new ways of combating these spoilage organisms. Also, if spoilage of a specific product could be linked to one or several genes (functionalities), and an anti-microbial treatment can be devised based on this knowledge, adjusting the product composition in a certain way might reduce the chance of spoilage considerably.
Variants
Transcriptome-trait matching (TTM, i.e. associating gene-expression profiles to bacterial traits) is a logical and useful variant of gene-trait matching, since some complex phenotypes (traits) correspond to differences in the level of gene expression, rather than to the presences or absence of (a set of) genes. Another strategy is to use gene-metabolite matching (GMM) which involves coupling the presence of metabolites to the presence of specific microbial genes.