An Untargeted Metabolomic Approach for Microphytobenthic Biofilms in Intertidal Mudflats

Abstract

Microphytobenthic (MPB) biofilms in intertidal muddy sediments play important ecological functions in coastal ecosystems. These biofilms are mainly composed of epipelic diatoms but also prokaryotes, with a dominance of bacteria, which excrete diverse extracellular polymeric substances (EPS) according to their environment. While numerous studies have investigated the main components of these EPS matrices via traditional colorimetric assays, their fine composition, notably in specialized metabolites, is still largely unknown. A better chemical characterization of these MPB biofilms is necessary, especially regarding the numerous functions their chemical components play for microorganisms (e.g., motility, cell protection, defense mechanisms, and chemical communication), but also for coastal systems (e.g., primary production, sediment stabilization, larval settlement of some invertebrates with high economical value). An alternative approach to traditional analyses is the use of untargeted metabolomic techniques, which have not yet been applied to such MPB biofilms. The objectives of the present study were to (a) propose a protocol for metabolic fingerprinting by LC-MS and GC-MS for metabolites analysis in polar and non-polar fractions in MPB biofilms extracted from mudflat sediment and to (b) apply this protocol to a case study: the effect of light exposure on the metabolomic fingerprint of the MPB biofilm community. We compared three extraction methods using different mixes of solvents and selected a methanol/chloroform mix (1:1), which gave better results for both techniques and fractions. We then applied the selected protocol to our case study using a short-term light exposure experiment in aquaria (7 days). The present study is the first using a detailed untargeted metabolomic approach on MPB biofilms from mudflat sediment and will provide a solid baseline for further work in this area.

The metabolites of light: untargeted metabolomic approaches bring new clues to understand light-driven adaptation of intertidal mudflat biofilm.

“…4): the tridecanoic acid (M111) measured in the MeOH fraction, the myristoleic acid (C14:1n-5; C56), 12methyltetradecanoic acid (anteiso-C15:0, 12-MTA; C57;) and pentadecanoic acid (C15:0; C59) measured in the CHCl 3 fraction. The latter two were previously found by our research team in the same sampling location and by the same untargeted metabolomic analysis method [20]. They are known as heterotrophic bacteria markers, usually composed by odd carbon chains, iso-and anteiso-branched SFA and MUFA [66,67] where the anteiso-C15:0 is generally associated with the genus Bacillus [68, 69].…”

“…The untargeted metabolomic analysis was performed according to the Gaubert-Boussarie method [20]. A mass of 50 mg of freeze-dried bio lm sample was resuspended in a mix of methanol (MeOH) and chloroform (CHCl 3 ) (1:1) of 6mL nal volume in Pyrex tubes under 30 min sonication.…”

“…These polymers not only hold cells and sediment particles together, but it also harbors small metabolites that allow for a diversity of interactions (communication, metabolic cooperation, or competition) between the microorganisms living within the matrix [17][18][19]. There is a lack of small matrix compounds characterization in literature [20] , and they certainly play a key role in the synchronization of the MPB organisms' migration. They could be metabolites excreted in response to light or released in the matrix by dead lysed cells.…”

“…In this work we exposed a migrational mud at bio lm for 30 min to a light gradient of photosynthetically active radiation (PAR) from 50 to 1000 µmol photons m − 2 s − 1 . To explore the global metabolic responses to the irradiances and identify compounds playing signi cant roles in the MPB light adaptation, we applied an untargeted metabolomic analysis method previously adapted for MPB in our laboratory [20].…”

Growth Substrate and Prophage Induction Collectively Influence Metabolite and Lipid Profiles in a Marine Bacterium

“…Community-level metabolomics approaches are increasingly used to characterize natural microbial populations ( 22 ). Current techniques are necessarily applied to discrete samples representing ‘snap shots’ of dynamic communities from which the status and function of these communities, or selected members within, are then inferred (e.g., ( 23 – 25 )). To facilitate the interpretation of community-level data, the extent to which ecologically relevant bacteria demonstrate metabolome flexibility requires elucidation.…”