Systems Biology - SYSBIOL

Understanding, at the molecular level, the pathogenesis of diseases previously labeled “idiopathic” has greatly benefited from the recent development of powerful “-omics” analysis techniques. In particular, the characterization of the human genome and the refinement of sequencing techniques have enabled the identification of mutations causing a number of monogenic diseases and the more recent development of polygenic risk scores for common diseases. However, we know that variations at the genome level, taken in isolation, are only weakly correlated with the clinical phenotype, due to multiple levels of regulation downstream of gene expression. Taking into account this complex regulation (epigenetic, post-transcriptional and -translational) requires the use of additional layers of analyses, among others at the level of the transcriptome, proteome and metabolome. The integration of these “multi-omics” data with the clinical phenotype, or even environmental data (the “exposome”) allows a holistic, non-biased approach to understanding complex diseases (1). However, it poses the challenge of analyzing data sets which require the development of sophisticated bioinformatics tools, with the possible support of artificial intelligence algorithms (2).

To meet this challenge, several players in the Health Sciences Sector (SSS/UCLouvain and Cliniques Saint-Luc-Woluwé campus) have decided to pool their expertise to form a single sector, going from the patient to the identification of Pathophysiological “nodes” of his disease using a “Systems Biology” approach. This sector (or “pipeline”) includes the collection of clinical data and biological samples from patients, the pre-analytical processing of these samples, the analysis of them using the most recent genomic and meta-genomic techniques. , transcriptomics, proteomics and metabolomics, the integration of the results into a multi-modal database and their bioinformatics processing using, among other things, an analysis of “interaction networks” (“network biology” (1,2) ), inspired by mathematical theories of complex graph analysis.

Initially set up thanks to funding from the “Sofina Solidarity Fund” via the Saint-Luc Foundation, which made it possible to strengthen the equipment and personnel of existing “omics” platforms, this “pipeline” was (and still is) applied to the study of the pathophysiology of SARS-COV-2 infection, and in particular the mechanisms underlying the “long COVID” syndrome (HYGIEIA project (3)). Initially single-center, recruitment for this study was extended to the Grand Hôpital de Charleroi (GHDC), CHU Namur-Mont-Godinne, Clinique de l’Europe and Clinique Saint-Pierre, Ottignies. More broadly, the project is integrated into the “MedReSyst” project portfolio (“Medicine of Networks and Systems”; https://medresyst.org/) of the Strategic Innovation Initiative of the Walloon Region within the framework of FEDER funding from the European Commission.

Building on this expansion, the founders of the project decided to open access to the “pipeline” to clinicians and academic researchers who wish to apply this paradigm to their clinical or fundamental research, by creating the “Systems Biology Core Facility” within the Sector. This new platform is “trans-institutional”, since it involves people and structures from IREC, LDRI and DDUV, as well as Cliniques Saint-Luc (see above).

The access terms are intended to be simple and flexible: the interested academic manager completes an interactive form available on the SYSBIOL platform website to describe the main points of their project; a steering committee evaluates the project and, if necessary, organizes a meeting with the applicant to specify the objectives and modalities; based on this, a quote is calculated and a timetable set.

The platform operates according to a “fee-for-service” scheme and offers prices which are intended to be advantageous compared to the “benchmark” (a.o. commercial), while guaranteeing the coverage of operating and personnel costs in proportion to usage. . The user can opt for single- or multi-omics analyses, with or without downstream bioinformatics/biostatistical analysis.

Schematic representation of the “Systems Biology” pipeline applied to COVID-19 in the HYGIEIA project.

References

1 . Silverman EK, Schmidt HHHW, Anastasiadou E, Altucci L, Angelini M, Badimon L, Balligand JL, Benincasa G, Capasso G, Conte F, Di Costanzo A, Farina L, Fiscon G, Gatto L, Gentili M, Loscalzo J, Marchese C, Napoli C, Paci P, Petti M, Quackenbush J, Tieri P, Viggiano D, Vilahur G, Glass K, Baumbach J. Molecular networks in Network Medicine: Development and applications. Wiley Interdiscip Rev Syst Biol Med. 2020 Nov;12(6):e1489. doi: 10.1002/wsbm.1489. Epub 2020 Apr 19. PMID: 32307915; PMCID: PMC7955589.

2. Maron BA, Altucci L, Balligand JL, Baumbach J, Ferdinandy P, Filetti S, Parini P, Petrillo E, Silverman EK, Barabási AL, Loscalzo J; International Network Medicine Consortium. A global network for network medicine. NPJ Syst Biol Appl. 2020 Aug 31;6(1):29. doi: 10.1038/s41540-020-00143-9. PMID: 32868765; PMCID: PMC7459285.

3. Ward B, Yombi JC, Balligand JL, Cani PD, Collet JF, de Greef J, Dewulf JP, Gatto L, Haufroid V, Jodogne S, Kabamba B, Pyr Dit Ruys S, Vertommen D, Elens L, Belkhir L. HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach. Viruses. 2022 Jun 23;14(7):1373. doi: 10.3390/v14071373. PMID: 35891354; PMCID: PMC9318602.