Frontiers in Chemistry (May 2018)

Metabolic Patterns in Spirodela polyrhiza Revealed by 15N Stable Isotope Labeling of Amino Acids in Photoautotrophic, Heterotrophic, and Mixotrophic Growth Conditions

  • Erin M. Evans,
  • Erin M. Evans,
  • Dana M. Freund,
  • Dana M. Freund,
  • Veronica M. Sondervan,
  • Jerry D. Cohen,
  • Jerry D. Cohen,
  • Adrian D. Hegeman,
  • Adrian D. Hegeman,
  • Adrian D. Hegeman

DOI
https://doi.org/10.3389/fchem.2018.00191
Journal volume & issue
Vol. 6

Abstract

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In this study we describe a [15N] stable isotopic labeling study of amino acids in Spirodela polyrhiza (common duckweed) grown under three different light and carbon input conditions which represent unique potential metabolic modes. Plants were grown with a light cycle, either with supplemental sucrose (mixotrophic) or without supplemental sucrose (photoautotrophic) and in the dark with supplemental sucrose (heterotrophic). Labeling patterns, pool sizes (both metabolically active and inactive), and kinetics/turnover rates were estimated for 17 of the proteinogenic amino acids. Estimation of these parameters followed several overall trends. First, most amino acids showed plateaus in labeling patterns of <100% [15N]-labeling, indicating the possibility of a large proportion of amino acids residing in metabolically inactive metabolite pools. Second, total pool sizes appear largest in the dark (heterotrophic) condition, whereas active pool sizes appeared to be largest in the light with sucrose (mixotrophic) growth condition. In contrast turnover measurements based on pool size were highest overall in the light with sucrose experiment, with the exception of leucine/isoleucine, lysine, and arginine, which all showed higher turnover in the dark. K-means clustering analysis also revealed more rapid turnover in the light treatments with many amino acids clustering in lower-turnover groups. Emerging insights from other research were also supported, such as the prevalence of alternate pathways for serine metabolism in non-photosynthetic cells. These data provide extensive novel information on amino acid pool size and kinetics in S. polyrhiza and can serve as groundwork for future metabolic studies.

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