Life Sciences Research for Lifelong Health

Nicolas Le Novère

Research Summary

Our group uses bioinformatic methods and mathematical modelling to study the basic processes of life. Biological research now relies on the generation and analyses of large amounts of quantitative data, coming for example from nucleic acid sequencing and mass spectrometry.

Such data need to be processed, quantified and put in context. This is done using software tools and statistics. Based on the information acquired from experiments and existing literature one can build mathematical models that can then be simulated under various conditions.

The success or failure of reproducing observed behaviours tell us if we adequately understand the mechanisms of life. This activity is an important part of what is now called "systems biology". The systems biology paradigm recognises that the behaviour of any living system emerges from the interactions between many of its components and cannot be fully understood by studying those components in isolation.

The main biological focus of the group is to understand how cellular and molecular systems interpret signals from their environment and adapt their behaviour as a consequence. This entails understanding how the various cells receive and transduce the signal, the interplay of different signalling pathways, and the final outcome for cell physiology, including gene expression and cell fate.

​Our main biological models are the synaptic signalling between neurons of the central nervous system, and the maintenance and differentiation of stem cells.

Latest Publications

Significance of stroma in biology of oral squamous cell carcinoma.
Vucicevic Boras V, Fucic A, Virag M, Gabric D, Blivajs I, Tomasovic-Loncaric C, Rakusic Z, Bisof V, Le Novere N, Velimir Vrdoljak D

The worldwide annual incidence of oral squamous cell carcinoma (OSCC) is over 300,000 cases with a mortality rate of 48%. This cancer type accounts for 90% of all oral cancers, with the highest incidence in men over 50 years of age. A significantly increased risk of developing OSCC exists among smokers and people who consume alcohol daily. OSCC is an aggressive cancer that metastasizes rapidly. Despite the development of new therapies in the treatment of OSCC, no significant increase in 5-year survival has been recorded in the past decades. The latest research suggests focus should be put on examining tumor stroma activation within OSCC, as the stroma may contain cells that can produce signal molecules and a microenvironment crucial for the development of metastases. The aim of this review is to provide an insight into the factors that activate OSCC stroma and hence faciliate neoplastic progression. It is based on the currently available data on the role and interaction between metalloproteinases, cytokines, growth factors, hypoxia factor and extracellular adhesion proteins in the stroma of OSCC and neoplastic cells. Their interplay is additionally presented using the Systems Biology Graphical Notation in order to sublimate the collected knowledge and enable the more efficient recognition of possible new biomarkers in the diagnostics and follow-up of OSCC or in finding new therapeutic targets.

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Tumori, , 2038-2529, 0, 2017

PMID: 28885677

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.
McMurry JA, Juty N, Blomberg N, Burdett T, Conlin T, Conte N, Courtot M, Deck J, Dumontier M, Fellows DK, Gonzalez-Beltran A, Gormanns P, Grethe J, Hastings J, Hériché JK, Hermjakob H, Ison JC, Jimenez RC, Jupp S, Kunze J, Laibe C, Le Novère N, Malone J, Martin MJ, McEntyre JR, Morris C, Muilu J, Müller W, Rocca-Serra P, Sansone SA, Sariyar M, Snoep JL, Soiland-Reyes S, Stanford NJ, Swainston N, Washington N, Williams AR, Wimalaratne SM, Winfree LM, Wolstencroft K, Goble C, Mungall CJ, Haendel MA, Parkinson H

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

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PLoS biology, 15, 1545-7885, e2001414, 2017

PMID: 28662064

Reciprocal regulation of ARPP-16 by PKA and MAST-3 kinases provides a cAMP-regulated switch in protein phosphatase 2A inhibition.
Musante V, Li L, Kanyo J, Lam TT, Colangelo CM, Cheng SK, Brody H, Greengard P, Le Novère N, Nairn AC

ARPP-16, ARPP-19, and ENSA are inhibitors of protein phosphatase PP2A. ARPP-19 and ENSA phosphorylated by Greatwall kinase inhibit PP2A during mitosis. ARPP-16 is expressed in striatal neurons where basal phosphorylation by MAST3 kinase inhibits PP2A and regulates key components of striatal signaling. The ARPP-16/19 proteins were discovered as substrates for PKA, but the function of PKA phosphorylation is unknown. We find that phosphorylation by PKA or MAST3 mutually suppresses the ability of the other kinase to act on ARPP-16. Phosphorylation by PKA also acts to prevent inhibition of PP2A by ARPP-16 phosphorylated by MAST3. Moreover, PKA phosphorylates MAST3 at multiple sites resulting in its inhibition. Mathematical modeling highlights the role of these three regulatory interactions to create a switch-like response to cAMP. Together the results suggest a complex antagonistic interplay between the control of ARPP-16 by MAST3 and PKA that creates a mechanism whereby cAMP mediates PP2A disinhibition.

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eLife, 6, 2050-084X, , 2017

PMID: 28613156

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Keywords

bioinformatics
computational biology
mathematical modelling
systems biology

Latest Publications

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016.

Schreiber F, Bader GD, Gleeson P

Journal of integrative bioinformatics
13 1613-4516:289 (2016)

PMID: 28187405

The health care and life sciences community profile for dataset descriptions.

Dumontier M, Gray AJ, Marshall MS

PeerJ
4 2167-8359:e2331 (2016)

PMID: 27602295

The systems biology format converter.

Rodriguez N, Pettit JB, Dalle Pezze P

BMC bioinformatics
17 1471-2105:154 (2016)

PMID: 27044654

Mathematical Models of Pluripotent Stem Cells: At the Dawn of Predictive Regenerative Medicine.

Pir P, Le Novère N

Methods in molecular biology (Clifton, N.J.)
1386 1940-6029:331-50 (2016)

PMID: 26677190

Enabling surface dependent diffusion in spatial simulations using Smoldyn.

Seeliger C, Le Novère N

BMC research notes
8 1756-0500:752 (2015)

PMID: 26647064

SBOL Visual: A Graphical Language for Genetic Designs.

Quinn JY, Cox RS, Adler A

PLoS biology
13 1545-7885:e1002310 (2015)

PMID: 26633141

Do genome-scale models need exact solvers or clearer standards?

Ebrahim A, Almaas E, Bauer E

Molecular systems biology
11 1744-4292:831 (2015)

PMID: 26467284

JSBML 1.0: providing a smorgasbord of options to encode systems biology models.

Rodriguez N, Thomas A, Watanabe L

Bioinformatics (Oxford, England)
1367-4811: (2015)

PMID: 26079347