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Bioinformatics and ecosystems modeling

Work-Package 5 description

Objectives

The main objective of this working group is to integrate knowledge from genetic, morphological and oceanographic data sets. More specifically, an ecosystem approach is used to characterize and predict the structure, function and evolution of marine plankton communities worldwide.

 

 

 

Scientists involved in this task work on the unique data sets provided by the working groups n°1 to 4. They improve existing tools, models and theories, or develop new ones to reach a comprehensive and holistic view of plankton communities at different levels (molecular, cellular and oceanographic).

 

 

 

This working group will define approach strategies to be used in the applied component of OCEANOMICS (Screening and research of active compounds).

 

 

 

 

Image icon p.himgamp-c.bowler.jpg
Pascal Hingamp and Chris Bowler together coordinate the Bioinformatics and ecosystem tasks

This group is coordinated by Pascal Hingamp from the Mediterranean Institute of Oceanography (Marseille) and Chris Bowler from the ENS Institute of Biology (Paris). It involves many other partners: the UMR7144 of the Roscoff Marine Station, the Oceanographic Laboratory of Villefranche-sur-Mer, Genoscope in Evry and the Plant Cell Physiology laboratory in Grenoble. The VIB Structural Biology Research Center and the Naples Zoological Station also collaborate in this work.

#1

Bioinformatics of ecosystem structure - Task 5.1

This task aims at characterizing the functional and taxonomic structures of plankton ecosystems and acquiring new biological knowledge from the OCEANOMICS datasets.

 

 

 

This work is divided into 3 approaches:

 

  • Community composition and ecosystem classification

 

The species composition of the samples, revealed by microscopic and genetic data analysis (working groups n°3 and 4), is statistically compared to functional and oceanographic parameters (see task 4.3 and working group n°2 respectively) to obtain an objective eco-morpho-genetic classification of plankton communities. Taxonomic data will also help thoroughly define the ecosystem classification.

 

  • Activities of the communities

 

The metatranscriptomic sequences mapped on metagenomes or reference genomes (protists, metazoans, SAGs) are studied to identify gene expression within different ecosystems. This is interpreted in terms of contribution levels for different taxa in the functional activity of the associated ecosystems.

 

  • New genes of fundamental and biotechnological interest

 

Preliminary studies show that the data sets contain an impressive number of unknown genes. Phylogenomic data are explored to identify these new genes or new subfamilies within already known genes. Their abundance and geographic distribution are characterized, as well as their potential hosts. A particular attention is paid to lipid metabolism and biosynthesis pathways of secondary metabolites due to their fundamental interest and the related potential biotechnological applications.

#2

Bioinformatics of ecosystem evolutionary dynamics - Task 5.2

This task focuses on the evolution dynamics of plankton communities by integrating data from different levels of systemic organization. Its purpose is to globally understand ecosystems in terms of ecology and evolution of genomes or organisms.

#3

Bioinformatics of ecosystems functioning - Task 5.3

This work aims at integrating eco-morpho-genetic data to understand how ecosystems function. This implies in silico reconstruction of metabolic pathways and interaction networks within a species or between different ones. Descriptors enable to predict the connections between ecosystems and the environmental conditions.

 

The overall work performed within OCEANOMICS will help define the optimal environmental conditions for bioprospecting (see working Group n°7).

#4

Modeling of ecosystem biogeography

Based on molecular and biophysical parameters, the goal here is to extend this group’s analysis and predictions to the whole ocean.