Bacterial genome safety assessment

Screen the bacterial genomes of your probiotics for presence of safety compromising genes

The bacterial genome can reveal a lot about its actual behaviour in your product: whether it has the potential to produce toxic products, survive treatments with antibiotics or produce antimicrobial compounds. Before subjecting your probiotic strains to expensive and lengthy experimentation on health benefit substantiating properties, an in silico genome assessment can provide you with the most important first insight: is the strain safe for application? 

NIZO offers a fast and automated genome assessment service, specifically designed to provide you with a clear overview of the genomic potential of your strains, in the areas of: 

• Antibiotic resistance 
• Virulence 
• Production of antimicrobial compounds 

By selecting this service, you will obtain: 

• Interactive strain-specific genome reports, searchable and updatable, with general genome information and lists of positively identified genes per functional module. 
• Insights in unique gene presence/absence profiles of your strain, compared to other (phylogenetically related) strains and reference strains (e.g. type strains or commercially available strains).  

Through this service, you will be able to make an informed selection on which strains are most suitable to follow up on, in more extensive and in-depth characterization studies. 

As an add-on to this automated service, NIZO can support you further with a full in silico characterization of your (foreseen) probiotic strains, for instance: 

• Expert interpretation of identified genes, in relation to safety in application. 
• Gene mobility assessment of identified genes (i.e. the chance that positively identified genes are transferred to neighbouring strains in the microbial community). 
• Genome assessment on presence of genes associated with other safety or health benefit related functionalities (e.g. adhesion, carbohydrate utilization, etc).  
• Design, validation and execution of custom-designed functional modules, based on Hidden Markov Models (HMMs). 
• In situ transcriptomic assessment (i.e. are the identified genes expressed?). 
• In vitro validation assays of predicted functionalities.  
• Support on establishing in vivo health substantiation