"Links between dissolved organic matter molecules and microbial communities in marine ecosystems"
Broader background of the proposed research project
Dissolved organic matter (DOM) is the main nutrient and energy source for marine bacterioplankton (Azam et al 1983, Fuhrman et al. 2015). To understand the interactions between DOM and the bacterial community, it is important to identify the key players on both sides in detail, i.e. chemically distinct moieties in DOM and the various bacterial taxa (Osterholz et al. 2015b). Technical advances in molecular microbial ecology (Edwards & Dinsdale 2007) and organic geochem-istry (Dittmar & Paeng 2009) have enabled the ultrahigh-resolution analysis of both, the microbial community and DOM. Pyrosequencing-based analysis facilitates the classification of millions of reads of environmental DNA and RNA amplicons and ultrahigh-resolution mass spectrometry (via the Fourier-transform ion cyclotron resonance technique, FT-ICR-MS) yields up to 10,000 DOM molecular formulae in a marine water sample. Linking this detailed biological and chemical information is a crucial first step towards a mechanistic understanding of the role of microorganisms in the marine carbon cycle (Romano et al. 2014, Osterholz et al. 2015b).
Outline for the proposed PhD research project
Over the past few years, we have collaboratively collected complex data sets on several hundred samples on experimental exometabolomes, natural geometabolomes, and associated microbial communities. For each sample, (semi-)quantitative information of >10,000 individual variables are available. These data have been interpreted in the context of the respective individual study, but not yet in the framework of EcoMol. Aim of this PhD thesis is to analyze the available data on correlative patterns between microbial community and molecular DOM composition. The emerging patterns will be interpreted in a biogeochemical context. We hypothesize that the bacterial community composition, especially of the active heterotrophic community, is closely related to the composition of the main energy and carbon source, DOM. We will interpret the complex microbiological and molecular information via a novel combination of multivariate statistics, as pioneered by Osterholz et al. (2015b). The same data will be analyzed by associated WP 8 (microbial communities), WP 10 (ecological modelling), and WP 11 (ecological network and time series modelling). Each of these WPs has their own focus, with different research questions and different data analysis tools. Close interactions within this sub-cluster will yield a holistic picture of molecule-organism interactions in an ecological context. In addition, we will closely interact with all WPs that require support with non-targeted molecular analysis. The PhD student of WP 4 will be involved in all interactions, but actual analytical work would be beyond the scope of the proposed PhD thesis. Practical analytical support will be provided by the technical personal in Dittmar’s research group.