Research Projects

Peracetic acid (PAA) is an organic peroxyacid characterized by a high oxidizing power. PAA has a remarkable biocidal efficacy (higher than glutaraldehyde) and a high sterilizing efficacy even at concentrations below 0.2%. For this reason, it is a disinfectant used in many different areas. However, at high concentrations it can  be dangerous for humans. Therefore, the monitoring of the airborne PAA in workplaces is a must and  automatic monitoring represents an effective strategy for the protection of  workers’ safety and health. To date PAA has been included in the ECHA list “ Products with Emerging Viral Pathogens and Human Coronavirus claims for use against SARS-CoV-2, updated in July 2020.

It is therefore clear that the monitoring of sanitation processes and, more importantly, the certification of the safety and accessibility of sanitized workplaces after any required treatment, are major issues, which require fast, simple and reliable solutions.

The aim of this project is to propose a solution to monitor the airborne residues of PAA once disinfection is completed, setting up two mobile devices (one terrestrial and one flying) that can be controlled remotely, and which will be able to autonomously set the sensors for measurements. This approach will enable the operator to monitor the area of interest without coming into contact with potentially polluted air due to the residual presence of the disinfectant agent.

The rationale of this project is provided by a passive device for the semi-quantitative determination of the airborne PAA, developed and produced by Giotto Biotech, the leader of this network.

In addition, in the framework of this project, we plan to investigate and develop new types of sensors and sampling techniques for the optimization of the automatized system and for the detection, in different environments, of  additional airborne harmful substances, such as ammonia and oxidising compounds derived from the use of hydrogen peroxide and / or peracetic acid. It will thus be possible to obtain mobile systems for the monitoring of the most common airborne pollutants, sampling different areas of the site of interest (both indoors and outdoors) also under different atmospheric conditions,  without endangering the health of the operator, protecting the environment and reducing the time required for a full screening.

RNAct is a Marie Skłodowska-Curie Innovative Training Network (ITN) for early stage researchers (ESR) funded by the European Commission under the H2020 Programme the EU framework programme for research and innovation.

The RNAct research focusses on proteins containing RNA Recognition Motifs (RRM) to posttranscriptionally regulate gene expression and detect specific RNAs. The ability to manipulate these RRMs has wide application potential in bio-analytics and for the creation of synthetic pathways in cells, for example by enabling their activation via small molecule triggers. The 10 Early Stage Researchers (ESRs) trained through RNAct will acquire proficiency for molecular level work on proteins, with an understanding of both experiment and computation. In combination with complementary transversal and entrepreneurial skills training, this will enable the ESRs to constructively contribute to the European bio-economy in both academic and industry settings.

PhD project

GLYTUNES is a Marie Skłodowska-Curie Innovative Training Network (ITN) for early stage researchers (ESR) funded by the European Commission under the H2020 Programme the EU framework programme for research and innovation.

GLYTUNES is a multidisciplinary European Training Network on glyco-immune checkpoints built to address the main priorities of the National and European research council regarding the use of innovative methodological, interdisciplinary approaches for the treatment of human diseases. The GLYTUNES program is based on high-level multidisciplinary and multisectoral training to:

i) understand at the molecular and dynamic level how (aberrant) interactions between the immunomodulatory receptors Siglecs and their sialylated cognate ligands contribute to the etiology of immune-related diseases (infectious, and cancer diseases),

ii) how to tune this axis to provide new therapeutic approaches for the rational design and development of glycomimetics targeting the Siglec glyco-immune checkpoints. To achieve this aim, an interdisciplinary, intersectoral, international European-based training programme within an outstanding collaborative research environment has been established.

GLYTUNES involves partners from 7 European countries, combining world-class expertise in carbohydrate chemical and structural biology, drug design and computational chemistry, synthetic and medicinal chemistry, biophysics, biochemistry, glycoimmunology and molecular and medical microbiology. GLYTUNES will train 14 Early Stage Researchers (ESRs) so to acquire scientific and transferable skills to make them highly competitive and new leaders in top EU academia and research institutions, healthcare and biotech job markets.

The vision of ITFoC is a radical new approach to a true personalisation of drug therapy in many areas of medicine and prevention, and its demonstration in subarea of oncology (breast cancer), based on a deep molecular characterisation of individual tumours and patients and the establishment and use of digital medicine approaches to model effects and side effects of all therapy options. Such a vision represents a transformation in current health care practice across Europe, necessitating engagement of a wide variety of stakeholders from different European countries, from patients, clinicians, scientists, regulators and politicians and the breaking down of silos that prevent progress and adoption of such new approaches.

To move forward, we need to provide a systematic route towards the deployment of such computational models as clinical decisions helpers (to make what are ultimately life and death decisions) based on validated probabilistic, mechanistic and systemic models to predict patient responses to drugs on an individual basis. This will entail the optimisation, validation and standardisation of the computational approaches used to predict drug responses based on as many omics and clinical data as currently obtainable.

Benchmark tests will be conducted to further develop models and compare their performance in terms of sensitivity and specificity to determine the best simulation approaches. The wider community (including SMEs and industry) will be invited to test modelling methodologies within a joint platform. Evaluation also requires analysis of ethical, regulatory, acceptance and economical issues, highlighting risks/benefits of this digital medicine approach for cancer and set in place a pathway towards the policy and regulations that will ultimately enable deployment of these models as clinical decision helpers in Europe’s health care systems.

Stakeholders (e.g. politicians, citizens, patient associations, health authorities, industry, ethicists, health economists, oncologists) will be consulted to start to address the difficult challenges of regulation, cost-effectiveness, public/oncologist acceptance, and reimbursement in a diverse environment as Europe. This approach will rely on the sharing of information and the co-operation of researchers.

The Flag-ERA proof-of-concept model provides an opportunity to integrate efforts on a pan European level, not only providing access to a wide range of relevant scientific and technical expertise and resources, but also to country-specific practices and perspectives that are relevant to the acceptance and implementation of the virtual patient modelling approach in oncology. The key innovative factors of ITFoC range from the beyond state-of-the-art computational modelling technologies developed by project partners to predict patient drug response, to the systemic approach to data standardisation and validation of model-generated predictions of responder/non-responders.

Through its tightly aligned federated activities, ITFoC will aim to propose two advanced (TRFL 5-6) demonstrators in digital medicine that will set the scene for future larger-scale initiatives.

ITFoC will establish a standardised and well-validated approach for virtual patient modelling in oncology, through comparative analysis of computational model approaches for predicting patient response to treatment based on molecular data (e.g. exome/transcriptome/metabolome) from individual patients and tumours. Existing and newly generated large scale molecular and clinical datasets on (triple negative) breast cancer patients from across Europe, as well as ongoing data standard initiatives, will be leveraged to provide standardised and validated datasets, accessible via a common database (for medical data we will integrate data from distant databases).

A secure access portal will be created to enable multiple users to access and share omics data for comparative analysis of computational modelling approaches (e.g. machine learning and mechanistic modelling methodologies) to predict the response of patients (singly or as cohorts) to targeted drugs. Computer generated predictions will be validated within pre-clinical/clinical studies and the reliability of the predictions quantified and compared to effectiveness of current European-wide standards for treatment of breast cancer. This combination of standardised datasets (existing and new) and independent comparative analysis alongside preclinical/clinical validation, provides the opportunity to quantify the effectiveness of different approaches.

The results of these proof-of-principle investigations will provide nascent benchmarks for further development in larger scale initiatives. Although ITFoC places emphasis on defining the accuracy and validity of the predictive modelling approach, efforts will also be focussed on bringing the ideas and vision of a sustainable and personalised ICT-driven approach to oncology to key stakeholders. This will done by establishing a strong ITFoC network, aligned with ongoing initiatives, that will feed results generated into the wider community soliciting feedback and helping to further optimise and refine, working towards building a standardised and well-validated approach for virtual patient modelling in oncology. Each element is regarded as essential to the future implementation of virtual patient models in oncology within the health care system and will provide a baseline for future development.

We propose the development of an integrated plasmonic platform to expand the possibility of detecting, identifying and quantifying genetically modified organisms (GMOs) in the environment. The platform will provide both a rapid screening to obtain a semi-quantitative response, and a detailed analysis for a full quantitative profiling of the species present in environmental samples. Appropriate transgenic DNA sequences and / or proteic fingerprints that correlate with transgenic events in seeds or plants of interest (such as maize, canola, soya, sugar beet, tomato, tobacco, potato, vine) will be selected as biomarkers for a relevant proof of concept. Receptors for these targets will therefore be engineered for integration in the various sensors as specific recognition elements of each biomarker. The integrated platform will be composed of: 1) a multianalyte biosensor based on surface plasmon resonance imaging (SPRi) capable of simultaneous and label-free identification of several biomarkers that are co-present in a sample; 2) a cheap, portable, fast and easy-to-use colorimetric biosensor based on a suspension of plasmonic nanoparticles providing in-situ semi-quantitative information; 3) a surface-enhanced Raman spectroscopy (SERS) system based on silver / graphene substrates for recognition and quantification of biomarkers without the use of specific receptors or labels.

Overall, the integrated platform can represent an “analytical chain” for the traceability of the release of GMOs in the environment based on complementary techniques able to cover different analytical needs of the control phases: from field screening to laboratory quantitative profiling of the population composition.

Faber is a two-year project promoted by the Fondazione Cassa di Risparmio di Firenze in collaboration with Confindustria Firenze and Fondazione per la Ricerca e l’Innovazione of the University of Florence.

The project is addressed to the Italian agro-food companies: it intends to apply nuclear magnetic resonance (NMR) based metabolomics for the determination of the quality and the geographic characterization of agro-food products.

NMR metabolomics is a very reproducible and fast technique representing a good resource to combine with the traditional food biochemical techniques. Indeed, it provides the so called “metabolic fingerprint”, from which it is possible to study quantitatively and qualitatively the ensemble of metabolites of a certain food matrix, providing a desirable advantage over the standard analytical techniques based on the evaluation of a limited number of molecules.

The project will lead to the creation of a database of characteristic NMR spectra and products. This database will be used to construct accurate statistical models for the identification and traceability of the origin of the products.

AEGIS is a Marie Skłodowska -Curie Innovative Training Network (ITN) for early stage researchers (ESR) funded by the European Commission under the H2020 Programme the EU framework programme for research and innovation.

The principal aim of the AEGIS ITN is to implement the first comprehensive, intersectoral cross-disciplinary and structured curriculum for doctoral students in the European Research Area by establishing a unique training platform for the next generation of European researchers in early drug discovery. A significant added value is provided through networking with key European pharmaceutical companies. A key research aim of AEGIS is improving the efficiency and success of early stage drug development by combining innovative methods and techniques to tackle difficult but promising targets (i.e. protein-protein interactions), as potentially valuable drug targets are often neglected due to the high risk associated with their validation.

The project is intended to develop new technologies for the improvement of the standards of occupational safety and health. In particular, DICCAP project aims at addressing the problem of the detection of airborne Peracetic Acid in the workplace, an issue which has been recently become more and more serious.

Peracetic acid is a disinfectant with a high bactericidal, virucidal and sporicidal activity and it has been increasingly used over the past years as a safer and greener alternative to commonly used disinfectants. It is widely used for the sterilization of surgical instruments (endoscopes), for the disinfection of containers in the food industry and for the reduction of the bacterial load of waste waters, also thanks to its biocompatibility. Nevertheless it is a harmful compound, able to irritate eyes and mucous membranes even at very low concentrations with potentially lethal consequences; furthermore, its monitoring is still difficult, thus exposing the workers to potentially dangerous levels of this toxic chemical.

Within the DICCAP project, Giotto Biotech will develop a simple and user friendly system for the real time detection of toxic concentrations of Peracetic Acid with a potential strong impact on the safety of any worker dealing with this substance.

Recent evidence shows that a large share of proteins gain functional advantages by remaining natively unstructured, either completely or partially, thus challenging well-established concepts in structural biology. In this frame NMR plays a strategic role to characterize at atomic resolution the highly dynamical properties of such “intrinsically disordered proteins”, and follow their (possible) reorganization by interacting with partners in environments as complex as whole cells. In order to achieve the full potential of this approach current methods should be further developed and properly interfaced with other complementary techniques. The purpose of our network is thus to establish a framework to train a new generation of young researchers in this emerging area. Understanding the functional role of intrinsically disordered protein states, which are involved in many biochemical processes at the basis of life, is expected to have a significant impact in biomedical research and in the design of new drugs.

A network combining 9 academic research groups and 4 collaborating industrial companies is proposed to train the next generation of PhD students and post-doctoral researchers, in developing and applying novel experimental and theoretical methods in the NMR spectroscopy of systems containing paramagnetic metals. The assembled team, with researchers distributed throughout the EU, will investigate a variety of important problems in chemistry and biology including catalysts, battery materials, metalloproteins and large protein-protein assemblies. The researchers will be trained to attack key problems that prevent the widespread usage of NMR spectroscopy as applied to paramagnetic materials, and to develop new methods to improve significantly the structural and electronic information that can be obtained from these systems. Three experimental and theoretical work programs are proposed, which build on, but also move significantly beyond the recent advances in pNMR, many of which have originated from members of this network: i) developing experimental approaches for obtaining NMR spectra from challenging paramagnetic molecules and materials, ii) extending the fundamental theoretical understanding of pNMR parameters, and facilitating their quantum-chemical implementations in first-principles software; iii) attacking relevant chemical and biological problems, with novel techniques to determine structure (e.g., of insoluble proteins and disordered battery electrode materials), dynamics and reactivity around metal centres, and exploring interactions between, e.g., biomolecules, catalytic centres and supports. Integral to the research-based training programme is the series of workshops, practical training courses, international conferences, and outreach actions, located at the different sites. These will i) train the young researchers of the network in the basics of pNMR and ii) disseminate the results of the network to the larger NMR community and to the general public.

PATHWAY-27 is a research project carried out by a pan-European interdisciplinary team of 16 life/social scientists and 9 high tech/food processing SMEs. It will uniquely address the role and mechanisms of action of 3 bioactives: docosahexaenoic acid, β-glucan, anthocyanins. These have been chosen for known/claimed effectiveness in reducing some risk factors of Metabolic Syndrome (MS), enriching 3 different widely-consumed food matrices (dairy-, bakery-, egg products).

PATHWAY-27 will evaluate the effectiveness of the chosen bioactives as ingredient of enriched foods, evaluating both the bioactive-food matrix interactions and of the extent of synergism between the 3 active molecules. The project will determine the impact of the bioactive enriched foods (BEF) on physiologically-relevant endpoints related to MS risk and deliver a better understanding of the role and mechanisms of action of the 3 bioactives and BEF. Parallel in vitro/in vivo studies and the use of advanced omics techniques will enable the selection of robust biomarkers to be used in the evaluation of BEF effectiveness.

The final PATHWAY-27 deliverables will include not only the formulation and production of BEF having a demonstrated effect in MS dietary treatment, but also generic protocols, best practices and guidelines for planning dietary interventions, and guidance to SMEs for producing health-promoting BEF and for submitting convincing health claim dossiers to EFSA; the latter will be greatly facilitated by one SME partner who has submitted 3 successful dossiers.

PATHWAY-27 guidelines will apply to a wide range of bioactives and BEF, and therefore will be useful not only for partner SMES but suitable for a general use by the food industry.

The expected project impact will be optimised across Europe by targeted dissemination events to industry (especially SMEs), consumers and S&T stakeholders.

Biolabel project aimed to valorization of algal biomass for the isotopic labeling of biomolecules.

In particular, the project is intended as:

Phase 1 Optimization of production of isotopically labeled algal biomass

Optimization of algal growth parameters: carbon dioxide, nitrates, temperature, light intensity, pH.

Development of the equipment necessary for the optimal production of labeled biomass

Choice of best microalgae strain for the production of labeled material

Phase 2 Optimization of the use of isotopically labeled algal biomass

Identification of labeled biomolecules to be isolated from the algal biomass and its purification

Growth tests of microorganisms and/or cells in culture media produced using the residual components of the biomass extracts once the above-mentioned labeled biomolecules have been removed

Phase 3 Use of labeled products obtained from labeled algal biomass

Optimization of the production of labeled biomolecules expressed in E. coli in growth media obtained from algal biomass

Adaptation and optimization of the conditions for the expression of isotopic labeled proteins using mammalian cells (in particular, in human cells) via transient tranfection.