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Iron is an essential nutrient that functions as a catalyst for many cellular reactions, in particular those involving redox and O2 chemistry (reviewed in Briat et al., 2007; Jeong and Guerinot, 2009). For example, iron-containing proteins play key roles in the electron transport reactions of photosynthesis and respiration, and iron is also an important element in the nutritional quality of plant products. Many organisms are chronically undernourished for iron, as evidenced by the prevalence of anemia worldwide and iron limitation in crops and in ocean ecosystems. In large part, this limitation is due to the relative insolubility of the Fe(III) oxidation state, and most organisms have complicated iron uptake and metabolism pathways that involve multiple steps of chelation and redox chemistry.
Chlamydomonas reinhardtii is a useful model system for understanding iron metabolism and the impact of poor iron nutrition in plants. Urzica et al. (pages 3921–3948) present a large-scale study that examines the effect of iron limitation on the transcriptome and proteome of C. reinhardtii. The authors use RNA-Seq to analyze the effect of low iron on the transcriptome of C. reinhardtii cells grown with CO2 (photoautotrophic) or acetate (photoheterotrophic) as the carbon source. The study goes beyond transcriptomics and presents proteomics data, bioinformatics analysis, and additional experimentation, including measurement of metabolites and work with Arabidopsis thaliana, to make new discoveries relevant to the maintenance of iron homeostasis in the plant lineage.
The use of iron limitation in conjunction with carbon source (either metabolism of acetate or photosynthesis) provides new and interesting information on how iron affects metabolic pathways. When acetate is available for photosynthesis-independent growth, C. reinhardtii cells sacrifice the photosynthetic apparatus, allowing for a closer examination of the effect of iron deficiency on bioenergetic membranes in respiration. The authors also used three carefully chosen concentrations of iron to allow a close look at stress response pathways (e.g., an iron-limited medium with extremely low iron availability [0.25 μM] versus an iron-deficient medium with more moderate limitation [1 μM], compared with an iron-replete medium [20 μM]).
A comparison with microarray data for iron deficiency responses in Arabidopsis and rice (Oryza sativa) revealed a set of responses shared with C. reinhardtii. The analysis of genes regulated under iron-deficient and iron-limited conditions identified iron assimilation components, transporters, and ferric-chelate reductases that are potentially involved in cellular iron distribution. For example, phylogenetic analysis coupled with transcriptomics suggested that NRAMP4 represents a highly conserved transporter involved in iron homeostasis.
Besides transporters, a second major functional category was identified that includes components of antioxidant pathways. Primary enzymes in de novo ascorbate synthesis and ascorbate recycling, VTC2 and MDAR1, respectively, were strongly upregulated in iron-limited cells, concomitant with a 10-fold increase in ascorbate content (see figure), suggesting that ascorbate is a key stress response under iron limitation. Proteins of unknown function were also identified, such as CGLD27, which is a putative plastid protein that is highly conserved in all plastid-containing organisms. Since Arabidopsis CGLD27 is also induced by low iron, the authors tested cgld27 mutant plants and found defects when grown under iron limitation. Overall, the study presents a wealth of data that improves our understanding of iron acquisition and metabolism in plants and provides a valuable resource for further investigation.
C. reinhardtii accumulates vitamin C in response to low iron nutrition by de novo synthesis and recycling. Cells were grown in iron-replete (20 μM iron), iron-deficient (1 μM iron), or iron-limited (0.25 μM iron) medium under photoheterotrophic (acetate) and photoautotrophic (CO2) conditions. Vitamin C levels (A), VTC2 mRNA abundance (B), and MDAR1 activity and abundance (C). Error bars indicate sd; n = 3. (Adapted from Urzica et al. [2012], Figure 7.)
