Nitrogen starvation induces a global stress response in microalgae that results in the accumulation of lipids as a potential source of biofuel. Using GC-MS-based metabolite and iTRAQ-labeled protein profiling, we examined and correlated the metabolic and proteomic response of Chlamydomonas reinhardtii under nitrogen stress. Key amino acids and metabolites involved in nitrogen sparing pathways, methyl group transfer reactions, and energy production were decreased in abundance, whereas certain fatty acids, citric acid, methionine, citramalic acid, triethanolamine, nicotianamine, trehalose, and sorbitol were increased in abundance. Proteins involved in nitrogen assimilation, amino acid metabolism, oxidative phosphorylation, glycolysis, TCA cycle, starch, and lipid metabolism were elevated compared with nonstressed cultures. In contrast, the enzymes of the glyoxylate cycle, one carbon metabolism, pentose phosphate pathway, the Calvin cycle, photosynthetic and light harvesting complex, and ribosomes were reduced. A noteworthy observation was that citrate accumulated during nitrogen stress coordinate with alterations in the enzymes that produce or utilize this metabolite, demonstrating the value of comparing protein and metabolite profiles to understand complex patterns of metabolic flow. Thus, the current study provides unique insight into the global metabolic adjustments leading to lipid storage during N starvation for application toward advanced biofuel production technologies.
Despite inherent complementarity, nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are routinely separately employed to characterize metabolomics samples. More troubling is the erroneous view that metabolomics is better served by exclusively utilizing MS. Instead, we demonstrate the importance of combining NMR and MS for metabolomics by using small chemical compound-treatments of Chlamydomonas reinhardtii as an illustrative example. A total of 102 metabolites were detected (82 by GC-MS, 20 by NMR and 22 by both techniques). Out of these 47 metabolites of interest were identified, where 14 metabolites were uniquely identified by NMR and 16 metabolites were uniquely identified by GC-MS. A total of 17 metabolites were identified by both NMR and GC-MS. In general, metabolites identified by both techniques exhibited similar changes upon compound treatment. In effect, NMR identified key metabolites that were missed by MS and enhanced the overall coverage of the oxidative pentose phosphate pathway, Calvin cycle, tricarboxylic acid cycle and amino acid biosynthetic pathways that informed on pathway activity in central carbon metabolism leading to fatty acid and complex lipid synthesis. Our study emphasizes a prime advantage of combining multiple analytical techniques - an improved detection and annotation of metabolites.
Microalgae are proposed as feedstock organisms useful for producing biofuels and coproducts. However, several limitations must be overcome before algae-based production is economically feasible. Among these is the ability to induce lipid accumulation and storage without affecting biomass yield. To overcome this barrier, a chemical genetics approach was employed in which 43,783 compounds were screened against Chlamydomonas reinhardtii, and 243 compounds were identified that increase triacylglyceride (TAG) accumulation without terminating growth. Identified compounds were classified by structural similarity, and 15 were selected for secondary analyses addressing impacts on growth fitness, photosynthetic pigments, and total cellular protein and starch concentrations. TAG accumulation was verified using gas chromatographymass spectrometry quantification of total fatty acids, and targeted TAG and galactolipid measurements were performed using liquid chromatography-multiple reaction monitoring/mass spectrometry. These results demonstrated that TAG accumulation does not necessarily proceed at the expense of galactolipid. Untargeted metabolite profiling provided important insights into pathway shifts due to five different compound treatments and verified the anabolic state of the cells with regard to the oxidative pentose phosphate pathway, Calvin cycle, tricarboxylic acid cycle, and amino acid biosynthetic pathways. Metabolite patterns were distinct from nitrogen starvation and other abiotic stresses commonly used to induce oil accumulation in algae. The efficacy of these compounds also was demonstrated in three other algal species. These lipid-inducing compounds offer a valuable set of tools for delving into the biochemical mechanisms of lipid accumulation in algae and a direct means to improve algal oil content independent of the severe growth limitations associated with nutrient deprivation.
We conclude with an outlook on how the field will evolve, especially in partnership with the new engineering-based, more endpoint exploitative paradigm of synthetic biology.
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