New methodologies and –omics techniques to study signalling between marine

The study of microbial communication has many challenges to face, and this is particularly true for marine chemical ecology (Goulitquer, Potin and Tonon, 2012). The high complexity of the matrix, the dilution of exuded metabolites, the high concentration of salts and the complicated dynamics that regulates marine microbial communities make the isolation and quantification of chemical cues particularly difficult. The detection of secondary metabolites, usually released in small amounts from micro- and macroorganisms, is aided by advanced extraction and enrichment techniques. In case of algal pheromones, for example, a large and dense culture of cells is necessary to isolate more than 100 µg of the active molecule and structurally identify it (Lembke, 2018). Sometimes the extraction techniques are not suitable to generate an extract that can be used to answer a specific ecological question (Chapter 7). For example, if we consider the isolation of metabolites that regulate the interactions of macroalgae with other organisms, investigations have been often done using whole cell extractions (Carvalho et al., 2017) and testing the potential antifouling and antibacterial activity of extracted metabolites in bioassay. However, to determine a realistic ecological concentration of such compounds, techniques to extract metabolites released at algal surfaces or biofilm interfaces are necessary (Nylund et al., 2007). The classical “dipping” technique, which involves immersing wet macroalgae in an

organic solvent, is a simple and powerful method for extracting surface metabolites (de Nys et al., 1998; Lachnit et al., 2009). A major drawback of this method is the damage to the algal surface provoked by the solvents. In order to overcome this problem, I developed a non-disruptive technique that use solid-phase extraction principles to extract surface metabolites (Chapter 7). The method is fast, easy to handle, does not harm the surface of the alga. From this work I have established a flexible protocol for algal research (Cirri and Pohnert, 2017) can be applied to different macroalgal specimens and potentially to other wet surfaces, as for example epilithic biofilms. By changing the extraction resin, different metabolites can be targeted, from carotenoids to lipids up to polar compounds, like osmolytes and sugars. Moreover, by extracting multiple surfaces in parallel and combine the resin in a single SPE cartridge, the concentration of interesting metabolites can be incremented. A combination of this method with novel sensitive analytical instruments (LC/GC-HR-MS) allows for the detection of known and unknown metabolites excreted at exceedingly low concentrations directly from algal surfaces.

Apart from novel sample preparation techniques and metabolites concentration protocols, a breakthrough in studying algae-bacteria interactions are represented by the introduction of - omics approaches to algal ecology. Transcriptomic analyses allow the identification of an organism’s response towards stimuli and its acclimation along time (Jamers, Blust and De Coen, 2009), thus giving useful information about evolutionary adaptation (Caron et al., 2017). Metabolomics approaches gives an important alternative to the bioassay-guided fractionation, overcoming some of the limits of this traditional methodology, like the long preparation time and the risk of losing unstable chemical cues (Kuhlisch and Pohnert, 2014). The introduction of highly sensitive high-resolution mass spectrometry techniques (Fuhrer and Zamboni, 2015) and the integration with NMR spectroscopy (Markley et al., 2017) make metabolomics a powerful tool to narrow down the selection of chemical signals or metabolites characteristic for a certain treatment within a short time, thus speeding up the procedure that brings a chemical cue from its extraction to its identification.

The potential information that could be obtained by the integration of these technologies brings new opportunities to systems biology research and many studies have demonstrated the power of omics techniques in marine ecology, for example in the context of nutrient deprivation of diatoms (Allen et al., 2008; Alipanah et al., 2015), viral infection of coccolitophores (Rosenwasser, Mausz et al., 2016) or the influence of bacteria on diatoms (Durham et al., 2015). The application of these approaches is still relatively new and it is yielding an unprecedented number of data. It is therefore crucial to carefully plan a large-

scale multiomics experiment, because the decisions taken during planning large-scale multiomics experiments have a huge impact on data quality. Quality assessment is a pivotal step in omics experiments as it assesses beforehand the possible causes of errors and it helps to minimize them (Dudzik et al., 2018). The use of quality controls, for example, is a powerful approach to control the reproducibility of the measurements, to correct for possible signal drifts within and between analytical batches and control for unwanted variances (Dudzik et al., 2018). In metabolomics, sample stabilization is also crucial in order to prevent the degradation of labile compounds, such as those involved in chemical interactions. Blank samples are fundamental to identify signals coming from impurities coming from the complex marine medium or introduced during the sample preparation procedure. Test measurements are necessary to understand the volume of spent medium (for exometabolomics) or the cell concentrations (for endometabolomics) needed to obtain samples that are not too diluted nor too concentrated. Internal standards for normalization (Sysi-Aho et al., 2007) and retention time index standards for identification (Vinaixa et al., 2016) are additional important tools, considering the high number of unknowns and the big concentration differences in aquatic samples. Also, the decision for the right statistical methods to be applied, even prior to the actual experiment, is crucial to interpret data in a meaningful way (Yi et al., 2016; Kupferschmidt, 2018).

In this thesis, I have adapted transcriptomics and metabolomics methods in order to the effects of bacteria on diatoms and other microalgae. In particular sample preparation was optimized in order to have enough volume to extract a detectable amount of metabolites. Medium blanks were used to remove, during data analysis, all possible interferences coming from artificial sea water. With a combination of transcriptomics, exometabolomics and targeted analysis, it was possible to reconstruct the broad effect of bacterial medium on the metabolism and on sexual reproduction of Seminavis robusta (Chapter 5). Moreover, by comparing the exudates of control samples (axenic S. robusta and bacterial spent medium) to samples of S. robusta treated with bacterial spent medium, it was possible to select for potential signaling molecules produced by the bacteria that may induce the rewiring of diatom’s metabolism (Chapter 5).

Furthermore, by using an endometabolomic approach, a complex metabolic rewiring of S. robusta (Chapter 3) and Nannochloropsis metabolism (Chapter 6) in a 7 days co- cultivation with bacteria was observed. In this case, metabolomics gave a snapshot of the effect of bacteria on algae metabolism and it proved to be a powerful tool to assess the quality of algae growth for industrial purposes.

New technologies, like single cell transcriptomics (Sandberg, 2014) and single cell metabolomics (Zenobi, 2013), new tools for the in-silico identification of unknown molecules (Blaženović et al., 2018), as well as the implementation of minimum reporting guidelines (Sumner et al., 2007; Considine et al., 2018), will lead aquatic chemical ecology