Abstract
Unicellular phototrophic algae can form massive blooms with up to millions of individual cells per milliliter in freshwater and marine ecosystems. Despite the temporal dominance of bloom formers many algal species can co-exist and compete for nutrients and space, creating a complex and diverse community. While microscopy and single cell genomics can address the taxonomic inventory, the cellular metabolome has yet to be thoroughly explored to determine the physiological status of microalgae. This might, however, provide a key to understand the observed species diversity in the homogeneous environment. Here, we introduce an effective, rapid and versatile method to analyze living single cells from aqueous substrata with laser-desorption/ionization mass spectrometry (LDI-MS) using a simple and inexpensive matrix-free support. The cells deposited on a cultivation-medium wetted support are analyzed with minimal disturbance as they remain in their natural viable state until their disruption during LDI-MS. Metabolites desorbed from single cells are analyzed on High-Resolution Mass Spectrometry (HR-MS) using the Orbitrap FT-MS technology to fingerprint cellular chemistry. This live single-cell mass spectrometry (LSC-MS) allows assessing the physiological status and strain-specifics of different microalgae, including marine diatoms and freshwater chlorophytes, at the single-cell level. We further report a reliable and robust data treatment pipeline to perform multivariate statistics on the replicated LSC-MS data. Comparing single cell MS spectra from natural phytoplankton samples and from laboratory strains allows the identification and discrimination of inter and intra-specific metabolic variability and thereby has promising applications in addressing highly complex phytoplankton communities. Notably, the herein described matrix-free live-single-cell LDI-HR-MS approach enables monitoring dynamics of the plankton and might explain why key-players survive, thrive, avoid selective feeding or pathogenic virus and bacteria, while others are overcome and die.
Highlights
Cell-to-cell heterogeneity is defined by differential metabolic expression resulting in diverse phenotypes in seemingly homogeneous populations (Malviya et al, 2016)
These were directly analyzed with ambient pressure Laser desorption/ionization (LDI)-High-Resolution Mass Spectrometry (HR-MS) in both polarities
Raw spectra were processed with an in-house script based on the MALDIquant R package, reducing the background noise signal, removing the signals from the culture medium, and including a total ion current (TIC) normalization as recommended when working with MALDI-MS (Gibb and Strimmer, 2012; Emara et al, 2017)
Summary
Cell-to-cell heterogeneity is defined by differential metabolic expression resulting in diverse phenotypes in seemingly homogeneous populations (Malviya et al, 2016). Cellular responses to intra- or inter-specific infochemicals released by the conspecifics or competing species can be diverse according to the physiological state of the respective cells (Zenobi, 2013). Numerous challenges are faced when addressing the concentration, structural identity and functional role of cellular metabolites (Kuhlisch and Pohnert, 2015). Rapid and high throughput methods are required to cover the dynamics of metabolite expression that is causing substantial fluctuations in concentrations over the course of the development of a culture or bloom (Barofsky et al, 2010; Vidoudez and Pohnert, 2012). Being able to identify and quantify metabolites in single cells, will support the prediction of dynamics in large populations of microalgae by assigning fitness status to respective cell cohorts (Acevedo-Trejos et al, 2018)
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