Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Multi-omics approach for on-line contaminants detection in industrial ...
Coordinator
The task includes evaluation of safety parameters in traditional and novel foods through the development of: a) chemical sensors and immunosensors for the selective detection of algal and plant toxins, and trace allergens; b) portable devices based on laser photoacoustic spectroscopy (LPAS) and other spectroscopy techniques; c) Ambient Desorption Ionisation methods with High-Resolution Mass Spectrometry (DESI-HRMS); e) use of rt-PCR and digital droplet-PCR to evaluate new and (re)-emerging foodborne pathogenic species; f) metabolomics and proteomics strategies coupled to pathway analysis to evaluate the effects of emerging and re-emerging contaminants; d) analytical techniques, i.e., spectroscopic and MS-based, to determine biogenic amines, pesticides, veterinary drug residues, mycotoxins and processing toxicants; and g) new Matrix-Reference Materials to be characterised for food safety parameters will be developed, including preparation of test-lots, their characterization and homogeneity and stability studies.
Safety assessment of traditional and novel foods through targeted and untargeted methodologies (M36)
Report on rapid methods to detect foodborne pathogenic species and their metabolites (M36)
Report on the development and testing of new analytical techniques for targeted analysis of contaminants (M36)
Report on the development and testing of new rapid and direct analytical tools, chemical sensors, and portable devices (M36)
Currently, microbial contaminations of industrial fermentations are investigated by coupling conventional microbiological (plate counting) and molecular approaches (16S rDNA sequencing). These approaches have several limitations, among which the need to possess appropriate microbiological methods allowing the growth of unwanted microorganisms and long waiting time before results are available. To increase both safety and sustainability of industrial fermentations, an “online” monitoring of contaminants needs to be developed.
The exponential development of high throughput and affordable gDNA sequencing techniques (e.g. Oxford Nanopore Technology), the protein-based bacteria identification (commercial MALDI MS/MS equipment) as well as the increase of the computational power of workstations indicate there is potential to develop innovative tools allowing the microbial contaminants detection. The aim of this project is to develop a fully automated multi-omics approach able to evaluate microbial contaminations within 24 hours after the sample collection.
The following steps will be performed:
Development and validation of a fully automated multi-omics approach able to evaluate microbial contaminations within 24 hours from sample collection. Demonstration of industrial saving and reduction of industrial wastes/economic losses.
