@article {nikitashina_metabolic_2022,
	title = {Metabolic adaptation of diatoms to hypersalinity},
	journal = {Phytochemistry},
	year = {2022},
	pages = {113267},
	abstract = {Microalgae are important primary producers and form the basis for the marine food web. As global climate changes, so do salinity levels that algae are exposed to. A metabolic response of algal cells partly alleviates the resulting osmotic stress. Some metabolites involved in the response are well studied, but the full metabolic implications of adaptation remain unclear. Improved analytical methodology provides an opportunity for additional insight. We can now follow responses to stress in major parts of the metabolome and derive comprehensive charts of the resulting metabolic re-wiring. In this study, we subjected three species of diatoms to high salinity conditions and compared their metabolome to controls in an untargeted manner. The three well-investigated species with sequenced genomes Phaeodactylum tricornutum, Thalassiosira pseudonana, and Skeletonema marinoi were selected for our survey. The microalgae react to salinity stress with common adaptations in the metabolome by amino acid up-regulation, production of saccharides, and inositols. But also species-specific dysregulation of metabolites is common. Several metabolites previously not connected with osmotic stress reactions are identified, including 4-hydroxyproline, pipecolinic acid, myo-inositol, threonic acid, and acylcarnitines. This expands our knowledge about osmoadaptation and calls for further functional characterization of metabolites and pathways in algal stress physiology.},
	keywords = {Diatomic algae, Hypersalinity stress response, Osmolytes, Phaeodactylaceae, Phaeodactylum tricornutum, RCC75, Skeletonema marinoi, Skeletonemataceae, Thalassiosira pseudonana, Thalassiosiraceae, Untargeted metabolite profiling},
	issn = {0031-9422},
	doi = {10.1016/j.phytochem.2022.113267},
	url = {https://www.sciencedirect.com/science/article/pii/S0031942222001832},
	author = {Nikitashina, Vera and Stettin, Daniel and Pohnert, Georg}
}
@article {Stettin2020,
	title = {Metabolomics benefits from orbitrap GC{\textendash}MS{\textemdash}Comparison of low- and high-resolution GC{\textendash}MS},
	journal = {Metabolites},
	volume = {10},
	number = {4},
	year = {2020},
	note = {tex.mendeley-tags: RCC75},
	month = {apr},
	pages = {143},
	abstract = {The development of improved mass spectrometers and supporting computational tools is expected to enable the rapid annotation of whole metabolomes. Essential for the progress is the identification of strengths and weaknesses of novel instrumentation in direct comparison to previous instruments. Orbitrap liquid chromatography (LC){\textendash}mass spectrometry (MS) technology is now widely in use, while Orbitrap gas chromatography (GC){\textendash}MS introduced in 2015 has remained fairly unexplored in its potential for metabolomics research. This study aims to evaluate the additional knowledge gained in a metabolomics experiment when using the high-resolution Orbitrap GC{\textendash}MS in comparison to a commonly used unit-mass resolution single-quadrupole GC{\textendash}MS. Samples from an osmotic stress treatment of a non-model organism, the microalga Skeletonema costatum, were investigated using comparative metabolomics with low- and high-resolution methods. Resulting datasets were compared on a statistical level and on the level of individual compound annotation. Both MS approaches resulted in successful classification of stressed vs. non-stressed microalgae but did so using different sets of significantly dysregulated metabolites. High-resolution data only slightly improved conventional library matching but enabled the correct annotation of an unknown. While computational support that utilizes high-resolution GC{\textendash}MS data is still underdeveloped, clear benefits in terms of sensitivity, metabolic coverage, and support in structure elucidation of the Orbitrap GC{\textendash}MS technology for metabolomics studies are shown here.},
	keywords = {Comparative metabolomics, Diatom, High-resolution mass spectrometry (HRMS), Instrument comparison, Mass Spectrometry (Orbitrap GC-MS), Metabolite identification, Orbitrap Gas Chromatography, Osmotic stress, RCC75},
	issn = {2218-1989},
	doi = {10.3390/metabo10040143},
	url = {https://www.mdpi.com/2218-1989/10/4/143},
	author = {Stettin, Daniel and Poulin, Remington X. and Pohnert, Georg}
}
