Mots-Clés

multi-omics metabolic modeling diatoms

Description

One position is available to work on a project devoted to genome-scale metabolic model implementation for a marine diatom

Site

OGS, Trieste, Italy, in collaboration with Université de Nantes, France, and Stazione Zoologica Anton Dohrn, Italy.

Description

Genome-scale metabolic models (GSMs) are computational objects that elucidate the operating principles of cellular metabolism. Although applications of such approaches to marine unicellular organisms are still limited, their implementation will undoubtedly vastly increase our understanding of marine species and communities and will be a resource for further research. 

For implementing genome-scale modeling in the diatom framework, we propose building metabolic models for the pennate diatom Pseudo-nitzschia multistriata (1). Diatoms are key components of marine ecosystems; they fix solar energy and carry out the same ecological function plants have on the land. P. multistriata has been extensively studied in the past years and has become a model for the study of diatom life cycles. Ecological knowledge, population genetics data, gene expression and metabolomics datasets, and genomic resources, including a fully sequenced genome, are already available for this species, as well as GSMs for other diatoms (Thalassiosira pseudonana and Phaeodactylum tricornutum). 

We will first deploy a recent top-down metabolic model reconstruction technique on available data, then we will propagate these GSMs as new trait based on molecular knowledge to assess the consequences of sex on biogeochemical cycles. Finally, we will embed the new  GSM in a synthetic biology framework. 

The first step will be to deploy a recent top-down metabolic model reconstruction technique on available data (2). In particular, we aim to identify the difference in diatom sex on metabolic networks and their implications on the metabolic niche (2). As a second step, we plan to propagate these GSMs as new traits based on molecular knowledge to assess the consequences of sex on biogeochemical cycles (4). We will embed the new GSM in a synthetic framework in the final step. In particular, we will investigate potential knock-outs to increase the production of metabolites that are of interest in the broad context of the carbon cycle in the global ocean (5). Potentially, we aim to apply metabolic engineering such as the stoichiometric capacitance (6). 

The recruited scientist will work closely with modelers, oceanographers, ecologists, and molecular biologists to apply different strategies to develop the above strategy for P. multistriata. 

We plan to work towards defining the contribution of biological traits (e.g., sexual reproduction) to biogeochemical models, exploring potential applications in synthetic biology, and reconstructing the seasonally varying in situ metabolic states from meta-omics data.    

Required Degree:  

The candidate must have an academic degree in bioinformatics or computational biology. Interest in interdisciplinary studies is mandatory. The practice of constraint solvers such as CPLEX or GUROBI or an interest in marine sciences is not mandatory but a plus. 

Other requirements

The ideal candidate should have a background in computational biology or bioinformatics.

Expected starting date

Autumn 2024
 

1. Ferrante, M. I., Broccoli, A., & Montresor, M. (2023). The pennate diatom Pseudo-nitzschia multistriata as a model for diatom life cycles, from the laboratory to the sea. Journal of Phycology, 59, 637–643. https://doi.org/10.1111/jpy.13342
2. PhotoEukStein: Towards an omics-based definition of unicellular eukaryote phototrophs functional traits via metabolic modelling. Marie Burel, Antoine Régimbeau, Samuel Chaffron, Damien Eveillard, Eric Pelletier. bioRxiv 2023.05.22.541783; doi: https://doi.org/10.1101/2023.05.22.541783
3. Régimbeau, A., Budinich, M., Larhlimi, A., Pierella Karlusich, J.J., Aumont, O., Memery, L., et al. (2022) Contribution of genome-scale metabolic modelling to niche theory. Ecology Letters, 25, 1352–1364. Available from: https://doi.org/10.1111/ele.13954
4. Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015.
5. Moran, M.A., Kujawinski, E.B., Schroer, W.F. et al. Microbial metabolites in the marine carbon cycle. Nat Microbiol 7, 508–523 (2022). https://doi.org/10.1038/s41564-022-01090-3
6. Abdelhalim Larhlimi, Georg Basler, Sergio Grimbs, Joachim Selbig, Zoran Nikoloski, Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks, Bioinformatics, Volume 28, Issue 18, September 2012, Pages i502–i508, https://doi.org/10.1093/bioinformatics/bts381