Metabolite Profiling of <i>Chlamydomonas reinhardtii</i> under Nutrient Deprivation

Bölling, Christian; Fiehn, Oliver

doi:10.1104/pp.105.071589

Cited by 205 publications

(186 citation statements)

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“…amino acids, carbohydrates, phosphorylated intermediates, nucleotides and organic acids) out of about 800 detected could be identified. The concentrations of a number of phosphorylated glycolysis intermediates increase significantly during sulfur stress (Bö lling and Fiehn, 2005), consistent with the upregulation of many genes associated with starch degradation and fermentation observed in anaerobic Chlamydomonas cells (Mus et al, 2007). Unfortunately lipid metabolism was not studied.…”

Section: Role Of Algal Genomics and Model Systems In Biofuel Productionmentioning

confidence: 50%

“…Procedures for metabolite profiling of C. reinhardtii CC-125 cells, which quickly inactivate enzymatic activity, optimize extraction capacity, and are amenable to large sample sizes, were reported recently (Bö lling and Fiehn, 2005). The study is particularly relevant to this review, because it explored profiles of Tris-acetate/phosphate-grown cells as well as cells that were deprived of sulfate.…”

Section: Role Of Algal Genomics and Model Systems In Biofuel Productionmentioning

confidence: 99%

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Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances

et al. 2008

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SummaryMicroalgae represent an exceptionally diverse but highly specialized group of micro-organisms adapted to various ecological habitats. Many microalgae have the ability to produce substantial amounts (e.g. 20-50% dry cell weight) of triacylglycerols (TAG) as a storage lipid under photo-oxidative stress or other adverse environmental conditions. Fatty acids, the building blocks for TAGs and all other cellular lipids, are synthesized in the chloroplast using a single set of enzymes, of which acetyl CoA carboxylase (ACCase) is key in regulating fatty acid synthesis rates. However, the expression of genes involved in fatty acid synthesis is poorly understood in microalgae. Synthesis and sequestration of TAG into cytosolic lipid bodies appear to be a protective mechanism by which algal cells cope with stress conditions, but little is known about regulation of TAG formation at the molecular and cellular level. While the concept of using microalgae as an alternative and renewable source of lipid-rich biomass feedstock for biofuels has been explored over the past few decades, a scalable, commercially viable system has yet to emerge. Today, the production of algal oil is primarily confined to high-value specialty oils with nutritional value, rather than commodity oils for biofuel. This review provides a brief summary of the current knowledge on oleaginous algae and their fatty acid and TAG biosynthesis, algal model systems and genomic approaches to a better understanding of TAG production, and a historical perspective and path forward for microalgae-based biofuel research and commercialization.

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Section: Role Of Algal Genomics and Model Systems In Biofuel Productionmentioning

confidence: 50%

Section: Role Of Algal Genomics and Model Systems In Biofuel Productionmentioning

confidence: 99%

Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances

et al. 2008

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“…required to react appropriately to changing environmental conditions. Dynamic metabolomic data from other divergent microbes, e.g., photosynthetic alga (32) Table 3.…”

Section: Global Trends In the Metabolome Map During Nutrient Starvationmentioning

confidence: 99%

Conservation of the metabolomic response to starvation across two divergent microbes

Brauer

Yuan

Bennett

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

243

209

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We followed 68 cellular metabolites after carbon or nitrogen starvation of Escherichia coli and Saccharomyces cerevisiae, using a filter-culture methodology that allows exponential growth, nondisruptive nutrient removal, and fast quenching of metabolism. Dynamic concentration changes were measured by liquid chromatography-tandem mass spectrometry and viewed in clustered heat-map format. The major metabolic responses anticipated from metabolite-specific experiments in the literature were observed as well as a number of novel responses. When the data were analyzed by singular value decomposition, two dominant characteristic vectors were found, one corresponding to a generic starvation response and another to a nutrient-specific starvation response that is similar in both organisms. Together these captured a remarkable 72% of the metabolite concentration changes in the full data set. The responses described by the generic starvation response vector (42%) included, for example, depletion of most biosynthetic intermediates. The nutrient-specific vector (30%) included key responses such as increased phosphoenolpyruvate signaling glucose deprivation and increased ␣-ketoglutarate signaling ammonia deprivation. Metabolic similarity across organisms extends from the covalent reaction network of metabolism to include many elements of metabolome response to nutrient deprivation as well.Escherichia coli ͉ metabolomics ͉ nitrogen/carbon metabolism ͉ Saccharomyces cerevisiae ͉ starvation response T he pathways of cellular metabolism are close to identical across widely divergent organisms (1). The prokaryote Escherichia coli and the eukaryote Saccharomyces cerevisiae share essentially the same metabolic network (2) despite radically different compartmentation. The concentrations and fluxes of metabolites depend on the interactions among this conserved network structure, the cellular environment, and species-specific factors, such as the location, activities, and regulation of metabolic enzymes. Except for a few classic examples, e.g., central carbon metabolism in E. coli and yeast (3-5) and nitrogen assimilation in bacteria (6-8) the effect of environmental nutrient perturbations on the cellular metabolome have not been directly measured.We explored exponentially growing E. coli and S. cerevisiae cultures suddenly deprived of their carbon or nitrogen sources. Metabolic composition can change in as little as a few seconds (9, 10). To get accurate snapshots of the metabolome, we devised a method of growing cells directly on filters to avoid time-consuming procedures (e.g., centrifugation or filtration) before quenching of biochemical activity (11). Transfer of a filter from a plate containing growth medium into cold organic solvent quickly quenches metabolism; transfer to a plate with a different medium composition allows a quick change of the nutrient environment (Fig. 1).For measurement of a number of metabolites simultaneously, we used a liquid chromatography-electrospray ionization-triple quadrupole mass spectrometry (LC-MS/...

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“…Using the annotated C. reinhardtii genome (Merchant et al, 2007), the C. reinhardtii transcriptome was analyzed before and after N deprivation, which revealed multiple changes in gene expression that affect diverse parts of metabolism (Miller et al, 2010;Blaby et al, 2013;Goodenough et al, 2014;Schmollinger et al, 2014). In addition, proteomics have been used to profile the changes in protein expression during N deprivation in Phaeodactylum tricornutum (Yang et al, 2014), C. reinhardtii Longworth et al, 2012;Schmollinger et al, 2014), and Nannochloropsis oceanica (Dong et al, 2013), and metabolomics have been used to assess changes in metabolite pool sizes (Bölling and Fiehn, 2005;Lee et al, 2012). These and other studies point to wide-ranging changes in the structure and operation of the metabolic and other cellular networks.…”

mentioning

confidence: 99%

The Regulation of Photosynthetic Structure and Function during Nitrogen Deprivation in Chlamydomonas reinhardtii

Deshpande²,

et al. 2014

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The accumulation of carbon storage compounds by many unicellular algae after nutrient deprivation occurs despite declines in their photosynthetic apparatus. To understand the regulation and roles of photosynthesis during this potentially bioenergetically valuable process, we analyzed photosynthetic structure and function after nitrogen deprivation in the model alga Chlamydomonas reinhardtii. Transcriptomic, proteomic, metabolite, and lipid profiling and microscopic time course data were combined with multiple measures of photosynthetic function. Levels of transcripts and proteins of photosystems I and II and most antenna genes fell with differing trajectories; thylakoid membrane lipid levels decreased, while their proportions remained similar and thylakoid membrane organization appeared to be preserved. Cellular chlorophyll (Chl) content decreased more than 2-fold within 24 h, and we conclude from transcript protein and 13 C labeling rates that Chl synthesis was down-regulated both pre-and posttranslationally and that Chl levels fell because of a rapid cessation in synthesis and dilution by cellular growth rather than because of degradation. Photosynthetically driven oxygen production and the efficiency of photosystem II as well as P700 + reduction and electrochromic shift kinetics all decreased over the time course, without evidence of substantial energy overflow. The results also indicate that linear electron flow fell approximately 15% more than cyclic flow over the first 24 h. Comparing Calvin-Benson cycle transcript and enzyme levels with changes in photosynthetic 13 CO 2 incorporation rates also pointed to a coordinated multilevel down-regulation of photosynthetic fluxes during starch synthesis before the induction of high triacylglycerol accumulation rates.

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Metabolite Profiling of Chlamydomonas reinhardtii under Nutrient Deprivation

Cited by 205 publications

References 42 publications

Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances

Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances

Conservation of the metabolomic response to starvation across two divergent microbes

The Regulation of Photosynthetic Structure and Function during Nitrogen Deprivation in Chlamydomonas reinhardtii

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