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Light-dependent metabolic shifts in the model diatom Thalassiosira pseudonana

Algal Research, ISSN: 2211-9264, Vol: 74, Page: 103172
2023
  • 2
    Citations
  • 0
    Usage
  • 12
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    2
    • Citation Indexes
      2
  • Captures
    12

Article Description

Diatoms are major producers of carbon and energy in aquatic ecosystems, however their ability to rapidly and successfully acclimate to wide ranging irradiances is poorly understood at the biochemical level. We applied complementary transcriptomic and metabolomic approaches using the model centric diatom Thalassiosira pseudonana to understand mechanisms regulating cell acclimation and growth under high and low light intensities. The integration of these omics data revealed specific mechanisms that shifted carbon and energy fluxes in T. pseudonana depending on light-driven growth rate. To support a growth rate of >1 d −1 in high light, cells upregulated metabolic pathways involved in the production of long chain fatty acids, glycolic acid, and carbohydrates. Under low light, cells maintained a growth rate of ≤0.2 d −1 by conserving photosynthetic energy through upregulation of carbon retention pathways (e.g., gluconeogenesis, glyoxylate cycle). The few significant metabolites detected in low light acclimated cells were associated with light harvesting, energy storage, and signalling. In particular, our metabolite data revealed that eicosanoic acid, a metabolite commonly involved in cellular signalling, may poise light limited cells for fast metabolic remodelling with improving light conditions. The combined physiological, gene expression and metabolite profiling data revealed key metabolic switch points that underpin diatom success and could be leveraged in cell-based models for predictions and manipulations of cell growth or bio-production.

Bibliographic Details

Nerissa L. Fisher; Kimberly H. Halsey; David J. Suggett; Michelle Pombrol; Peter J. Ralph; Adrian Lutz; E. Maggie Sogin; Jean-Baptiste Raina; Jennifer L. Matthews

Elsevier BV

Agricultural and Biological Sciences

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