Mots-Clés

Metagenome-assembled genomes (MAGs) ecogenomics Southern Ocean marine prokaryotes

Description

Scientific context:

The field of meta-omics has rapidly evolved in the past decade, allowing the discovery of novel key organisms and functions in multiple environments, including marine ecosystems (Acinas et al., 2019; Delmont et al., 2018; Salazar et al., 2019; Sunagawa et al., 2015). Among the recent global meta-omics surveys of planktonic diversity, e.g. Tara expeditions, Malaspina or Biogeotraces, only Tara Oceans investigated the Southern Ocean, and only at 2 locations (Acinas et al., 2019; Paoli et al., 2021; Salazar et al., 2019). From December 2016 to March 2017, the ACE campaign circumnavigated the Antarctic, sampling metagenomes of planktonic communities at more than 30 locations and from the surface down to 3800m depth. This campaign offers an unprecedented opportunity to decipher the taxonomic and functional diversity of planktonic communities from the Southern Ocean.

Methodology:

To study the different bacterial or archaeal populations present in this environment, one key step is genome reconstruction to obtain Metagenome-Assembled Genomes (MAGs). The different samples of the ACE dataset have been organized into groups determined by their genomic similarity at the k-mer level. For each of these groups, the quality-filtered reads have been assembled to form longer sequences called contigs. Those contigs were then binned together based on their differential coverage and k-mer profiles using CONCOCT (Clustering of contigs based on coverage and composition, Alneberg J. et al., 2014). After this binning step, a manual refinement step is required to improve the quality of the bins, removing the contigs that were falsely attributed to each bin. This internship will begin at the refinement step.

The MAGs obtained therefore will then be annotated taxonomically and functionally in order to better understand their phylogenetic relationships and metabolism. This internship will focus on one population of interest, from which the manually refined MAGs will be investigated through pangenomics to detect their potential metabolic specificities and adaptations. In order to highlight the genomic specificities of populations from the Southern Ocean, the refined MAGs will be compared to those from several databases of previous studies. These databases can contain MAGs (Delmont et al., 2018), SAGs or isolates according to the chosen population.

The choice of the population(s) of interest(s) can be discussed:

• Concerning archaeal genomes: A previous internship was completed last year on Marine Group I archaeas, focusing on their trophic type, comparing genomes from autotrophic and recently discovered heterotrophic organisms (Aylward & Santoro, 2020). It would be interesting to have a deeper look at the Southern Ocean specificities among this group. Moreover, other groups of archaea remain to be explored and could be investigated during this internship, especially in the deeper samples where archaea are more dominant.
• Concerning bacterial genomes: Polaribacter is known to be present in Antarctica but also in other oceans and was predicted in several bins during this previous internship. Six distinct Polaribacter clades were previously defined in the North Sea using phylogenetic and phylogenomic analyses with well-defined glycan niches during spring algal blooms (Avcı et al., 2020). Looking at Antarctica polynyas primary productivity, Polaribacter was found to be dominant in the peak phase with a high transcriptomic activity (Kim et al., 2019). Another population of interest outside of these propositions can also be discussed.  

Objectives:

• Manual refinement of bins annotated as containing the population of interest
• Phylogenomic placement of the bins
• Distribution of the bins in the Southern Ocean samples (and link this distribution to metadata using multivariate analysis?)
• Build a pangenome for the population of interest and identify specific genes or pathways associated with Southern Ocean specificities

Pre-requisites:

• Background in numerical ecology, bioinformatics or microbiology `
• Ability to work autonomously with R and/or Python
• Previous experience with metagenomics data would be a plus
• Interest for marine microbial ecology
• English

Bibliography :

• Acinas, S.G. et al. (2019) ‘Metabolic Architecture of the Deep Ocean Microbiome’, bioRxiv, p. 635680. doi:10.1101/635680.

• Alneberg, J. et al. (2014) ‘Binning metagenomic contigs by coverage and composition’, Nature Methods, 11(11), pp. 1144–1146. doi:10.1038/nmeth.3103.

• Avcı, B. et al. (2020) ‘Polysaccharide niche partitioning of distinct Polaribacter clades during North Sea spring algal blooms’, The ISME Journal, 14(6), pp. 1369–1383. doi:10.1038/s41396-020-0601-y.

• Aylward, F.O. and Santoro, A.E. (2020) ‘Heterotrophic Thaumarchaea with Small Genomes Are Widespread in the Dark Ocean’, mSystems, 5(3), pp. e00415-20. doi:10.1128/mSystems.00415-20.

• Delmont, T.O. et al. (2018) ‘Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes’, Nature Microbiology, 3(7), pp. 804–813. doi:10.1038/s41564-018-0176-9.

• Kim, S.-J. et al. (2019) ‘Genomic and metatranscriptomic analyses of carbon remineralization in an Antarctic polynya’, Microbiome, 7(1), p. 29. doi:10.1186/s40168-019-0643-4.

• Paoli, L. et al. (2021) ‘Uncharted biosynthetic potential of the ocean microbiome’, bioRxiv, p. 2021.03.24.436479. doi:10.1101/2021.03.24.436479.

• Salazar, G. et al. (2019) ‘Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome’, Cell, 179(5), pp. 1068-1083.e21. doi:10.1016/j.cell.2019.10.014.

• Sunagawa, S. et al. (2015) ‘Ocean plankton. Structure and function of the global ocean microbiome’, Science (New York, N.Y.), 348(6237), p. 1261359. doi:10.1126/science.1261359.