INDIETRO

 Eusoft for OMICS4FOOD – the Cloud LIMS at the service of NGS (Next Generation Sequencing technologies)

Eusoft.Lab LIMS on CLOUD to support NGS Technologies

The OMICS4FOOD R&D Project, funded by INNONETWORK notice within POR Puglia FESR – FSE 2014 -2020, Priority Axis 1 – Research, technological development, innovation – 1.6 Action, was born in 2018 to improve production processes of flour-based fresh food through omics technologies approaches and complex information generated by an informatic system designed and developed on Cloud Computing (LIMS).  

Eusoft has led this project with multiple partners as Food Safety Lab Srl, Essenza Glutine Srl, Base Pizza Srl, Pasta Apulia Srl and the National Research Council of Italy (CNR). 

OMICS4FOOD Project included:  

  • The design of a Cloud-based LIMS (Laboratory Information Management System) for NGS (Next Generation Sequencing) platforms (Cloud NGS LIMS) aimed at managing protocols for omics studies specifically based on maximum DNA sequencing and flows of statistical and bioinformatic analysis of the data produced, and of the information coming from the critical points of the analytical process, all integrated in the Cloud NGS LIMS through advanced solutions capable of interpreting the results produced;  
  • The implementation of production schemes for conventional and gluten-free flour products, from flour preparation to product packaging in MAP (Modified Atmosphere Packaging), following the application of knowledge acquired through microbiological characterisation with metagenomic and proteomic approaches;  
  • An integrated App that allows the characteristics analysed (genomic and chemical-microbiological analyses) to be associated with the products of food companies and represented through augmented reality techniques.   

The need for this project stems from the fact that the LIMS currently on the market do not meet the needs of the NGS sector: for example, they do not allow the analysis of uncoded metadata related to samples, or to manage the different protocols of omics analysis. Moreover, they do not have developed mobile systems, nor they are SaaS (Software as a Service) Solutions taking advantage of Cloud Platforms. This could be explained by technological and scientific know-how issues, which requires deeper Research and investments regarding:  

  • The complexity of the metadata to be associated with samples and the massive amount of data produced by sequencers; 
  • Integration with sequencing tools and the need to manage a system capable of designing and executing different scientific workflows; 
  • The need to integrate bioinformatics algorithms, used by professionals to analyze data; 
  • The complexity of the representation of analysis results, which requires augmented reality solutions.  

The project proposal was therefore based on the development of a LIMS “Integrated Service” system for the industrialisation of the process of information management and analysis in Next Generation Sequencing applications in a Cloud Computing environment, taking advantage of a Research Center competences in big data, bioinformatic and software development.   

The LIMS System was then filled with data and validated through biomolecular and microbiological analyses conducted by selected food matrices related to a food industry companies cluster. These companies produce pasta and have the technological need to improve fresh products storage in a controlled atmosphere (MAP – Modified Atmosphere Packaging), as for example pasta and fermented flours.  

The NGS LIMS, aimed at microbiological analysis with metagenomic approaches, has been designed following GLP norms and tested on a selected food supply chain represented by a company’s cluster that produces both leavened and unleavened or gluten and gluten-free flours.  

During the project, Food Safety Lab laboratory and CNR-IBIOM tested Eusoft.Lab LIMS system and evaluated it through costs vs benefits KPIs. Food companies then took advantage of their food matrices through the microbiological taxonomic and functional analysis, having sufficient data to optimize their production processes related to MAP Packaging. This industrial process optimization has therefore allowed food companies to improve their shelf-life, quality and safety of their products.  

In the next weeks we will officially show and share OMICS4FOOD project results, so don’t miss the news on our website!