FAIROmics - PhD fellowship in fellowship in integrative bioinformatics and systems biology - From sequence to strain-specific phenotypes.

"FAIRification of multiOmics data to link databases and create knowledge graphs for fermented foods" MSCA-DN-JD Doctoral Network.

The FAIROmics initiative, an interdisciplinary research programme, will gather universities, research centres and private companies to enable the FAIRification of omics data and databases interoperability and develop knowledge graphs for data-driven decision-making to rationally design microbial communities for imparting desirable characteristics to plant-based fermented foods in the context of open science and its regulations. The FAIROmics training programme aims to develop doctoral candidates’ skills at the interface between artificial intelligence, life sciences, humanities, and social sciences.     

Plant-based dairy and meat alternatives have grown in popularity in recent years for various reasons, including sustainability and health benefits, as well as lifestyle trends and dietary restrictions. However, plant-based food products can be nutritionally unbalanced, and their flavour profiles may limit their acceptance by consumers. Microorganisms have been used in making food products for millennia. However, the diversity of microbial communities driving plant-based fermentations, as well as their key genetic and phenotypic traits and potential synergies among community members, remain poorly characterised. Many data exist, but they are spread into different literature (scientific and grey) or, in the best case, in different databases. However, they are not always reusable because they are difficult to find and access and because databases are not systematically interoperable.

Please note that this PhD position will lead to the award of a double diploma after the completion of a stay in each of these organisations: The Free University of Amsterdam (VUA), Netherlands and the University of Bologna (UNIBO), Italy.

Objectives:

The project aims at developing models to improve the prediction of strain-specific phenotypes. The models will handle different levels of granularity and combine genomic information, mechanistic knowledge (enzyme signatures, promoter architecture, context methods such as operon structures or co-expression, thermodynamic data) and phenotypic data with artificial intelligence and machine learning techniques. Phenotypic data will include data from available strain collections with sequenced strains and information on their phenotypic behaviour, as well as data from strains screened within FAIROmics for activities during plant-based fermentations.

Expected results:

DC5 will deliver insight into to what extent integration of mechanistic knowledge and experimental data with AI/ML methods can lead to reliable predictions of variation in traits from variations in sequences. In the process, we will develop an inventory of relevant features and mechanisms and associated databases (or links thereto), methods and predictive models.

Location and planned secondments:

The PhD student will mainly be located at VUA in Amsterdam for 22 months. Two secondments are planned :

• One at UNIBO in Bologna for 12 months for the training and development of hybrid mechanistic/AI methods.
• One at Chr. Hansen in Hoersholm (Denmark) to apply methods to in-house data for two months.

Enrolment in Doctoral degree:

1st-degree awarding organisation: Vrije Universiteit Amsterdam, https://vu.nl/en
2nd-degree awarding organisation: University of Bologna, https://www.unibo.it/en/homepage

Supervisors team:

The Free University of Amsterdam:

• Prof. Bas Teusink, professor in systems biology, co-leader of the Systems Biology Lab and Scientific Director of the Amsterdam Institute of Molecular and Life Science. The Systems Biology Lab houses expertise in molecular systems biology, with a focus on the regulation of cellular metabolism. It combines theoretical, computational and quantitative experimental approaches. Teusink is an expert in cellular physiology, genome-scale metabolic modelling and resource allocation, with food microbiology as a key application area. He will supervise the mechanistic aspects of the project.
• Dr. Douwe Molenaar, associated professor is an expert in microbiology, bioinformatics and multivariate statistics. He will supervise the data-driven part of the project and act as a daily supervisor.

The Universita di Bologna:

• Prof. Daniel Remondini, professor in physics and specialised in the application of mathematical models in Biology, such as Network Theory for the study of Complex Systems and the development of innovative algorithms for the analysis of high dimensional biological data.

Host institutions description

The Systems Biology Lab houses both experimental and computational expertise and is part of the Amsterdam Institute of Molecular and Life Science, offering expertise in relevant disciplines such as protein structure modelling and AI applications in biochemistry. The VU University offers bachelor and master teaching in the life sciences with a strong emphasis on the inter-disciplinarity of modern biology, with a strong focus on bioinformatics, systems biology, imaging, and multi-omics technologies in the priority areas of Health and Life Sciences and Science for Sustainability.

The research group in UNIBO has been active for almost 20 years in the modelling and analysis of biological processes and high-throughput data. The group applies and develops bioinformatics and statistical analysis algorithms, as well as network-based approaches to complex systems. This expertise has also been applied in clinical and industrial contexts in relation to the development of automated diagnostic and classification tools. Network theory, Statistical Mechanics, Machine Learning and Deep Learning are among the tools used for these purposes.