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Appropriate Thiamin Pyrophosphate Levels Are Required for Acclimation to Changes in Photoperiod

Laise Rosado-Souza, Sebastian Proost, Michael Moulin, Susan Bergmann, Samuel E. Bocobza, Asaph Aharoni, Teresa B. Fitzpatrick, Marek Mutwil, Alisdair R. Fernie, Toshihiro Obata

Published May 2019. DOI: https://doi.org/10.1104/pp.18.01346

Abstract

Thiamin pyrophosphate (TPP) is the active form of vitamin B1 and works as an essential cofactor for enzymes in key metabolic pathways, such as the tricarboxylic acid (TCA) cycle and the pentose phosphate pathway. Although its action as a coenzyme has been well documented, the roles of TPP in plant metabolism are still not fully understood. Here, we investigated the functions of TPP in the regulation of the metabolic networks during photoperiod transition using previously described Arabidopsis (Arabidopsis thaliana) riboswitch mutant plants, which accumulate thiamin vitamers. The results show that photosynthetic and metabolic phenotypes of TPP riboswitch mutants are photoperiod dependent. Additionally, the mutants are more distinct from control plants when plants are transferred from a short-day to a long-day photoperiod, suggesting that TPP also plays a role in metabolic acclimation to the photoperiod. Control plants showed changes in the amplitude of diurnal oscillation in the levels of metabolites, including glycine, maltose, and fumarate, following the photoperiod transition. Interestingly, many of these changes are not present in TPP riboswitch mutant plants, demonstrating their lack of metabolic flexibility. Our results also indicate a close relationship between photorespiration and the TCA cycle, as TPP riboswitch mutants accumulate less photorespiratory intermediates. This study shows the potential role of vitamin B1 in the diurnal regulation of central carbon metabolism in plants and the importance of maintaining appropriate cellular levels of thiamin vitamers for the plant’s metabolic flexibility and ability to acclimate to an altered photoperiod.

Environmental changes, such as the diurnal light/dark cycle, regulate multiple aspects in the plant kingdom, from influencing plant development and flowering time to the detailed regulation of cellular homeostasis, such as metabolism. A growing number of reports highlight the linkage between circadian rhythm, metabolism, and metabolic homeostasis (Fukushima et al., 2009; Nakamichi et al., 2009; Bass and Takahashi, 2010; Greenham and McClung, 2015). The plant circadian system has been described as being involved in regulating the rates of carbon assimilation, starch turnover and growth, sugar metabolism, and nutrient homeostasis (Dodd et al., 2005; Graf and Smith, 2011; Farré, 2012; Haydon et al., 2015). One of the best characterized metabolic responses to photoperiod is associated with starch turnover. Starch is synthesized during the day and remobilized at night. When different photoperiods are compared, starch synthesis is faster in short photoperiods than in long photoperiods (Smith and Stitt, 2007; Sulpice et al., 2014). Starch is degraded in an essentially linear manner, leading to almost but not complete exhaustion at dawn (Graf et al., 2010; Stitt and Zeeman, 2012). When challenged by an unexpected early or late night, starch synthesis/degradation rates are adjusted almost directly, demonstrating the robustness of this mechanism against environmental changes (Lu et al., 2005; Graf et al., 2010; Pyl et al., 2012). Additionally, there is increasing evidence that metabolic outputs can contribute to circadian timing and also that rhythmic metabolism contributes to the circadian network in plants (Gibon et al., 2006; Dodd et al., 2007; Dalchau et al., 2011; Haydon et al., 2013; Sanchez-Villarreal et al., 2013; Johnston, 2014; Haydon and Webb, 2016; Boxall et al., 2017). Current research has opened up new perspectives on plausible but mostly unexpected complexity in signaling events, cross talk with metabolism, and process adjustments. However, comprehensive studies precisely showing diurnal oscillation of metabolite levels in plants are scarce, and little is known about the players mediating this oscillation.

Thiamin (or thiamine), also known as vitamin B1, is one of the water-soluble B-complex vitamins, and thiamin pyrophosphate (TPP) is the active form of this vitamin. TPP works as an essential cofactor for enzymes such as 1-deoxy-d-xylulose-5-phosphate synthase (DXPS) in nonmevalonate isoprenoid biosynthesis, α-ketose transketolase (TK) in the pentose phosphate pathway, and pyruvate dehydrogenase (PDH) and 2-oxoglutarate dehydrogenase (OGDH) in the tricarboxylic acid (TCA) cycle. TPP has been associated with resistance to both abiotic and biotic stresses in plants (Sayed and Gadallah, 2002; Ahn et al., 2005; Tunc-Ozdemir et al., 2009). Additionally, the levels of thiamin must be fine-tuned. Alterations in the content of thiamin vitamers have been shown to cause several phenotypes ranging from no visible phenotypic alteration to growth retardation, leaf chlorosis, delayed flowering, and yield penalties (Kong et al., 2008; Bocobza et al., 2013; Dong et al., 2015; Khozaei et al., 2015; Martinis et al., 2016; Wang et al., 2016; Hsieh et al., 2017). Despite its close relationship with metabolic enzymes being well documented, the functions of thiamin in plant metabolic regulation remain obscure.

In plants, thiamin is biosynthesized from pyrimidine and thiazole moieties. Thiamin monophosphate (TMP) is biosynthesized in the plastid by the action of three enzymes, thiamin C synthase (THIC; Raschke et al., 2007), thiazole synthase1 (Machado et al., 1996), and thiamin monophosphate pyrophosphorylase (Ajjawi et al., 2007b). TMP is transported to the cytosol, dephosphorylated to thiamin by thiamin monophosphate phosphatase (Mimura et al., 2016), and then pyrophosphorylated to TPP by TPP pyrophosphokinases (Ajjawi et al., 2007a). Thiamin biosynthesis is regulated by the circadian clock via the activity of the THIC promoter (Bocobza et al., 2013). Additionally, thiamin levels are largely dependent on the stability of THIC mRNA, which is regulated by a TPP-responsive riboswitch located at the 3′ untranslated region of the THIC pre-mRNA (Bocobza et al., 2013). In the presence of high TPP levels, TPP binds to the riboswitch aptamer, leading to intron splicing and nonsense-mediated degradation of THIC mRNA (Wachter et al., 2007; Bocobza and Aharoni, 2008). Thus, the TPP riboswitch mediates feedback regulation of the thiamin biosynthetic pathway.

Bocobza et al. (2013) transformed the thic knockdown line with the genomic sequence of the Arabidopsis (Arabidopsis thaliana) THIC gene harboring a mutation in the riboswitch region. The TPP riboswitch mutant (Mut) plants exhibit elevated levels of thiamin vitamers in leaves; the TPP level was moderately increased (up to 30%) and TMP accumulated to around 3-fold compared with the native riboswitch control (Nat) line (Bocobza et al., 2013). TPP-requiring enzymes, namely PDH, OGDH, and TK, extracted from the Mut plants are activated by high concentrations of TPP, suggesting the alteration of allosteric regulation of the enzymes by TPP in the Mut plants. Additionally, the respiratory activity including the TCA cycle flux was significantly up-regulated in Mut plants (Bocobza et al., 2013). The Mut line also showed chlorosis, altered starch accumulation, and delayed flowering (Bocobza et al., 2013). Interestingly, these phenotypes were photoperiod dependent, with stronger phenotypes appearing during short (10 h of light) rather than long (18 h of light) photoperiods (Bocobza et al., 2013). The chlorotic phenotype of short-day (SD)-grown plants was recovered after 2 weeks of culture under long-day (LD) conditions (Bocobza et al., 2013). Considering the photoperiod-dependent phenotype, the activation of the TCA cycle in the Mut line, together with the circadian regulation of THIC expression, we hypothesize that TPP functions in the daily regulation of metabolism during day/night transitions. The Mut plants are an ideal system in which to investigate the effect of elevated thiamin level, as the mutation causes the accumulation of TPP. In order to test the hypothesis, we conducted precise metabolic profiling of Nat and Mut plants during the photoperiod transition. The results highlight the importance of TPP homeostasis in alleviating the detrimental effects of changing light conditions.

RESULTS

TPP Riboswitch Mutant Plants Display Lower Photochemical Efficiency Specifically under LD Conditions

The photoperiod-dependent phenotype of the Mut plants has been reported in a previous study, where the chlorotic phenotype was more prominent under SD than LD conditions (Bocobza et al., 2013). However, these phenotypes were observed with plants at different developmental stages. In order to confirm the photoperiod-dependent phenotypes of the Mut lines, the plants were analyzed at similar developmental stages. Wild-type, Nat, and Mut plants were grown for 4 weeks under an 8-h light photoperiod (SD) or 3 weeks under a 16-h photoperiod (LD) to avoid flowering. Another group of plants was grown for 3 weeks in an 8-h light photoperiod and then transferred to a 16-h photoperiod for 1 week (SD-LD; Supplemental Fig. S1A). The Mut plants accumulated significantly less chlorophyll a and b than the wild-type and the Nat plants independent of the growth condition (Supplemental Figs. S1B and S2A). This led to an increase of the chlorophyll a/b ratio in this mutant (Supplemental Fig. S2A). Although difficult to explain considering that DXPS also uses TPP as a cofactor and is a key enzyme in isoprenoid biosynthesis, the chlorotic phenotype correlates with the lower availability of sugars observed in Mut plants compared with wild-type plants. Mut plants showed carotenoid and protein levels similar to both control lines in all growth conditions, although the wild type showed a significant increase of carotenoids under LD and protein levels under SD-LD at 16-h and 8-h time points, respectively (Supplemental Fig. S2, A and B).

We also analyzed the light response of chlorophyll fluorescence parameters in these plants. When grown under SD conditions, Mut plants showed a slightly lower quantum yield of photochemistry and higher quantum yield of regulated energy dissipation than the control plants under high and low light intensities (Fig. 1, A and D). Quantum yield of nonregulated energy dissipation was similar in all lines, except for the slightly lower quantum yield in Mut lines under low light intensity (Fig. 1G). The effects of the TPP riboswitch mutation were more prominent under LD and SD-LD conditions. Quantum yield of photochemistry was significantly reduced in Mut plants compared with control plants at most of the light intensities (Fig. 1, B and C). Under these photo regimes, all plants showed very similar light response curves of regulated energy dissipation (Fig. 1, E and F), while Mut lines showed significantly higher nonregulated energy dissipation at all light intensities (Fig. 1, H and I). Interestingly, nonregulated energy dissipation in the Mut line was significantly higher under LD and SD-LD conditions when compared with plants grown continuously in SD at light intensities higher than 50 µmol m−2 s−1 (Fig. 1, G–I). The maximum photochemical efficiency of PSII (Fv/Fm) of the Mut plants was significantly lower than in the two control lines under LD and SD-LD conditions, suggesting that maximum quantum yield of QA reduction is impaired in the mutants (Supplemental Fig. S3). In summary, these results suggest that the mutation in the TPP riboswitch leads to a reduction of photochemical efficiency specifically under LD conditions and that the effect is enhanced when the plants are transferred from SD to LD conditions during the vegetative growth stage.

Figure 1.
Figure 1.

Chlorophyll a fluorescence parameters from TPP riboswitch mutant plants grown in SD, LD, or SD-LD conditions. Quantum yield of photochemistry (ɸPSII), quantum yield of regulated energy dissipation (ɸNPQ), and quantum yield of nonregulated energy dissipation (ɸNO) under different photosynthetically active radiation (PAR) are shown in the wild type (Wt), Nat, and Mut plants. Values are presented as means ± se (n = 6). Asterisks indicate values that were determined by Tukey’s honest significant difference test to be significantly different (Mut different from the wild type and Nat; P ≤ 0.05).

Metabolic Effects of the Riboswitch Mutation Are More Prominent When Plants Are Moved from Short to Long Photoperiods

The metabolite profiles of rosette leaves were analyzed by gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling analysis. Forty metabolites were constantly detected in the leaf samples (Supplemental Data S1), and the relative levels of these metabolites were analyzed. A principal component analysis (PCA) was performed to analyze the similarity of the global metabolite profiles (Fig. 2). The samples tend to be separated by the sampling time along with the first principal component. The second principal component separated the samples according to the photoperiod, showing that the LD-grown plants were metabolically distinct from the SD and SD-LD conditions. Although there was no clear separation based on genotype, the Mut lines tend to appear on the top side of the PCA plot when compared with the other two control lines taken at the same time point. These observations indicate that the sampling time and the photoperiod are the main drivers of metabolic responses, but the Mut line also has distinct metabolite profiles under individual conditions (Fig. 2). The relative levels of each metabolite are shown as a heat map (Fig. 3). Some effects of the TPP riboswitch mutation were specifically observed under certain photoperiods, such as the levels of organic acids in the plants transferred from SD to LD conditions. For example, the reductions in the levels of benzoate, citrate, dehydroascorbate, fumarate, and malate were more apparent in the SD-LD condition (Fig. 3).

Figure 2.
Figure 2.

PCA of the metabolite profile of TPP riboswitch mutant plants. Symbols represent different genotypes: wild-type (Wt; squares), Nat (circles), and Mut (triangles) plants. Plants were grown in SD (black) and LD (orange) conditions or in SD-LD (red). Symbol size represents different time points: (1) beginning of day/end of night (BD/EN); (2) middle of day (MD); (3) end of day/beginning of night (ED/BN); and (4) middle of night (MN). Each data point represents the mean of five to six biological replicates. PC1 and PC2 are first and second principal components.

Figure 3.
Figure 3.

Metabolic profiling from TPP riboswitch mutant plants grown in SD, LD, or SD-LD conditions at different times in a day: (1) beginning of day/end of night (BD/EN); (2) middle of day (MD); (3) end of day/beginning of night (ED/BN); and (4) middle of night (MN). The color scale represents an increase (red) or decrease (blue) for each metabolite detected compared with the wild type in the SD condition in the beginning of the day (SD_Wt_BD/EN). Mean metabolite levels (n = 5–6) are presented as log2. Dots indicate values that were determined by Tukey’s honestly significant difference test to be significantly different in each time point (••, Mut different from the wild type and Nat; •, Mut different from the wild type; P ≤ 0.05).

Starch content shows clear diurnal oscillation and is closely related to carbohydrate metabolism (Sulpice et al., 2009; Stitt and Zeeman, 2012). Starch levels in the leaves of the Mut plant were differentially affected by the photoperiod (Fig. 4). The three lines accumulated the same level of starch throughout the day under LD conditions (Fig. 4B). In SD conditions, starch levels were lower in Mut plants during the day when compared with the wild-type plants. The rate of starch accumulation was slower in the Mut plants than in the wild type, resulting in the lower starch amount at the end of the day (Fig. 4A). When the plants were transferred from SD to LD conditions, starch levels in Mut plants kept the same level of oscillation as the SD conditions. In contrast, control plants accumulated similar amounts of starch at the end of the day in SD conditions but exhibited lower rates of synthesis and consumption under SD-LD conditions (Fig. 4C). Taken together, the photosynthetic and metabolic phenotypes of Mut plants were photoperiod dependent and more distinctive from control plants when the plants were transferred from SD to LD photoperiods. This suggests that thiamin vitamers play a role in photoperiod acclimation.

Figure 4.
Figure 4.

Diurnal changes in the levels of starch from TPP riboswitch mutant plants grown in SD, LD, or SD-LD conditions. Values are presented as means ± se (n = 6). The values of wild-type (Wt), Nat, and Mut plants are shown. For background shading, white and dark gray show the light and dark periods, respectively. Asterisks indicate values that were determined by Tukey’s honestly significant difference test to be significantly different (**, Mut different from the wild type and Nat; *, Mut different from the wild type; P ≤ 0.05). FW, Fresh weight.

During the Photoperiod Transition, TPP Levels Are Constitutively Higher in TPP Riboswitch Mutants Compared with Native Riboswitch Control Plants

In order to investigate the metabolic events that take place during the acclimation process over a prolonged photoperiod, we conducted detailed time-course experiments with several conditions of photoperiod transition. The Nat control and Mut plants were grown in 8/16-h light/dark (SD) conditions for 3 weeks and then transferred to 16/8 h (LD) or 12/12 h (12 h) briefly before the onset of the light period or kept in SD light regimes. In a separate experiment, plants were transferred to continuous light (CL), continuous dark (CD), or kept in the SD regime (Supplemental Fig. S1C). Whole rosettes were harvested every 4 h during 3 d following the photoperiod transition.

The levels of thiamin vitamers were determined by HPLC (Supplemental Fig. S4). The Mut plants accumulated 1.2 to 1.5 times more TPP compared with the Nat plants, and the levels were almost constant over the experimental period (Supplemental Fig. S4). This is in accordance with previous results (Bocobza et al., 2013). In contrast, no difference of TMP contents was found between Nat and Mut plants, which is contradictory to the previous results (Bocobza et al., 2013). The diurnal oscillation in the TMP level observed by Bocobza et al. (2013) was unclear in this study.

Photoperiod Transition Induces Transient Alterations of the Amplitude in the Diurnal Oscillation of Metabolite Levels

The relative levels of metabolites were analyzed by GC-MS-based metabolite profiling. Time-course changes in the levels of 37 constantly detected metabolites were analyzed (Figs. 5–7; Supplemental Figs. S5–S13). Many metabolites showed a tendency of diurnal oscillation. To quantitatively analyze the metabolite oscillation, we calculated the amplitude of oscillation (for details, see “Materials and Methods”; Supplemental Fig. S14; Supplemental Data S2). The levels of 16 metabolites oscillated greater than two times within a single day in at least 2 d in the Nat plants grown in the continuous SD condition (Supplemental Data S3). These metabolites include sugars (Fru, trehalose, maltose, Man/Gal, and raffinose), amino acids (Gly, Ser, Thr, Arg, Pro, β-Ala, Gln, and Asn), a polyamine (spermidine), and organic acids (fumarate, pyruvate, glycerate, succinate, and malate). Starch also showed clear diurnal oscillation (Fig. 5A). Fru (Supplemental Fig. S6A), malate and fumarate (Fig. 6A), and the metabolites involved in photorespiration (Fig. 7A) showed prominent oscillation in which the metabolite levels changed more than five times within a single day. Most of the oscillation disappeared when the plants were moved to CL or CD conditions (Supplemental Figs. S7–S13). Interestingly, Ile, β-Ala, and photorespiratory intermediates, especially glycerate, retained their tendency of diurnal oscillation in the CL condition, while the tendency became unclear at the end of the experimental period (Supplemental Figs. S9 and S10).

Figure 5.
Figure 5.

Levels of carbohydrates in TPP riboswitch mutant plants during photoperiod transition. The black and gray lines represent Nat and Mut plants, respectively. For background shading, white and dark gray show the light and dark periods, respectively. Asterisks indicate time points at which the metabolite contents were significantly different between Nat and Mut plants determined by Student’s t test (means ± se, n = 5–6; P ≤ 0.05). FW, Fresh weight.

Figure 6.
Figure 6.

Levels of TCA cycle-related organic acids in TPP riboswitch mutant plants during photoperiod transition. The black and gray lines represent Nat and Mut plants, respectively. For background shading, white and dark gray show the light and dark periods, respectively. Asterisks indicate time points at which the metabolite contents were significantly different between Nat and Mut plants determined by Student’s t test (means ± se, n = 5–6; P ≤ 0.05).

Figure 7.
Figure 7.

Levels of photorespiratory intermediates in TPP riboswitch mutant plants during photoperiod transition. The black and gray lines represent Nat and Mut plants, respectively. For background shading, white and dark gray show the light and dark periods, respectively. Asterisks indicate time points at which the metabolite contents were significantly different between Nat and Mut plants determined by Student’s t test (means ± se, n = 5–6; P ≤ 0.05).

Diurnal oscillation in the levels of some metabolites was affected by the transition of photoperiod. Total starch at the end of the day increased in Nat plants transferred to longer photoperiods (Fig. 5). Starch degradation was delayed in the Nat plants transferred to the 12-h condition at the beginning of the first night but was compensated by the faster degradation at the latter half. The Nat plants retained a constant starch degradation rate from day 2 (Fig. 5B). The oscillation of starch metabolism was further perturbed in the plants transferred to the LD condition (Fig. 5C). Arabidopsis plants transferred to longer photoperiods also displayed an incomplete turnover of starch, which can be observed by a residual starch content at the end of the night (Fig. 5, B and C). Metabolites associated with starch, such as maltose and trehalose, displayed higher accumulation during the first night after the transition to the 12-h condition (Fig. 5B) and on the second night after the transition to the LD condition (Fig. 5C; Supplemental Fig. S14) compared with the plants kept in the SD photoperiod. Fru and Glc levels in Nat plants were not altered after the transition to longer photoperiods. Among the TCA cycle-related metabolites, succinate and fumarate increased in the plants transferred to a longer photoperiod compared with the SD condition (Fig. 6; Supplemental Fig. S14). Succinate hyperaccumulated during the first and second nights when the Nat plants were transferred to 12-h and LD conditions, respectively (Fig. 6). Interestingly, amplitudes of malate levels decreased from day 1 to day 3 after the shift to the 12-h condition (Fig. 6B; Supplemental Fig. S14). Gly was the metabolite whose oscillation was most severely affected by the photoperiod transition (Fig. 7). Gly continued to accumulate until 20 h and reached twice as much as the highest levels at the SD condition at the first day following the transition to the 12-h condition, while the perturbation of the oscillation was stabilized by the end of day 3 (Fig. 7B). The transition to the LD condition abolished the diurnal oscillation of the Gly level, which reappeared at day 3 (Fig. 7C).

TPP Riboswitch Mutant Plants Show Little Changes in the Amplitude of Diurnal Oscillation in the Levels of Carbohydrates, TCA Cycle Intermediates, and Photorespiratory Metabolites following Photoperiod Transition

To investigate the effect of TPP accumulation on the metabolic acclimation to altered photoperiod, metabolite profiles of rosette leaves of Mut plants were compared with those of Nat plants in all growth conditions (Figs. 5–7; Supplemental Figs. S5–S13). Starch levels showed indistinguishable oscillation patterns in both Nat and Mut plants under SD conditions (Fig. 5A). The altered starch degradation rate observed in the Nat plants after transition to the 12-h condition was not apparent in the Mut plants (Fig. 5B). The higher accumulation of maltose, trehalose, and Fru was observed in both genotypes, while the resulting amplitudes were higher in Nat plants (Fig. 5, B and C).

The oscillation in the accumulation of the tricarboxylic acid cycle intermediates was also affected by the mutation in the TPP riboswitch (Fig. 6). Enhanced fumarate accumulation in Nat plants transferred to 12-h and LD conditions was not apparent in the Mut plants (Fig. 6, B and C; Supplemental Fig. S14). The amplitude of malate oscillation was retained to a similar level in the 12-h condition in Mut plants, while it was greater on the first day after the transition to the LD condition (Fig. 6, B and C; Supplemental Fig. S14). Interestingly, fumarate and malate are the few metabolites that showed the shift in phases of oscillation, with slightly earlier peaks of accumulation in Mut plants transferred to the LD condition than in Nat plants. While oscillation of succinate was unclear, it also showed a tendency to peak earlier in Mut plants compared with Nat plants (Fig. 6, B and C; Supplemental Fig. S14). A slight tendency of oscillation in pyruvate, succinate, fumarate, and malate was observed in the Nat plants when they were transferred to CL and CD conditions, but those were not obvious in the Mut plants (Supplemental Fig. S8).

In contrast to the severe effect of photoperiod transition on Gly accumulation in the Nat plants, Gly levels in the Mut plants oscillated similarly to that in the continuous SD condition following photoperiod transition, although their pattern was perturbed in the first 2 d following the transition to LD (Fig. 7; Supplemental Fig. S14). Nat plants showed higher amplitudes in Ser and Gly level oscillation than the Mut lines under the SD condition (Fig. 7A; Supplemental Fig. S14). However, the accumulation of Ser in the Mut plants was enhanced following the transition to the longer photoperiods, reaching the same or higher levels as the Nat plants (Fig. 7, B and C; Supplemental Fig. S14). Amplitudes of glycerate oscillation levels were not affected by photoperiod transition in both genotypes (Fig. 7C; Supplemental Fig. S14).

Genes Related to Protein and Amino Acid Degradation Are Up-Regulated in the TPP Riboswitch Mutant Plants

Various effects of the TPP riboswitch mutation on the oscillation of metabolite levels were observed when plants were transferred from the SD condition to a 12-h photoperiod, particularly at the first light/dark cycle following the transition. In order to gain mechanistic insights underlying these effects, RNA was purified from Nat and Mut plants at 8, 12, and 16 h following the transition to the 12-h photoperiod and RNA sequencing analysis was performed. These three time points correspond to the previous end of the day, new end of the day, and first time point during the dark period, respectively (Supplemental Fig. S1C). In all three time points, 2,844 genes were differentially expressed between Mut and Nat plants. The largest number of differentially expressed genes (1,367) was identified at 12 h. At time points 8 and 16 h, the numbers of differentially expressed genes were 1,127 and 350 genes, respectively. Enriched Gene Ontology (GO) terms among the 2,844 differentially expressed genes in the entire data set were identified with PLAZA 3.0 (Proost et al., 2015) and visualized using REVIGO (Supek et al., 2011). A TreeMap view of the biological processes of the genes up-regulated in the Mut plants is shown in Figure 8. A positive regulation of catalytic activity, photosynthesis genes, and genes related to pyruvate metabolic processes was observed, suggesting the interaction between TPP and carbohydrate metabolism (Fig. 8). A TreeMap view of the biological processes related to the genes down-regulated in Mut plants is shown in Supplemental Figure S15; however, no major biological process relevant to metabolic regulation was detected in this category. As expected, expression of the THIC gene and the genes responding to vitamin B1 was increased in Mut plants (Fig. 8).

Figure 8.
Figure 8.

REVIGO TreeMap view of biological processes for genes up-regulated in the TPP Mut compared with Nat plants at three time points (8, 12, and 16 h) after transfer from the SD condition to a 12-h photoperiod. Each rectangle is a single cluster representative; related clusters are joined by colors, and rectangle size reflects the log10 P value of the GO term.

The differentially expressed genes at the individual time points were also analyzed using MapMan (Thimm et al., 2004) and are represented in Supplemental Figure S16. Histograms showing the number of differentially expressed genes in each MapMan hierarchical functional category (BIN) are included in Supplemental Figure S17. A complete list of BINs, subBINs, and genes assigned to each category is available as Supplemental Data S4 to S6. At the 8- and 12-h time points, the sets of differentially expressed genes were similar (Supplemental Figs. S16 and S17). Here, the genes related to photosynthesis, amino acid metabolism, redox, RNA, DNA, and protein were up-regulated. It should be noted that the genes included in amino acid metabolism and proteins were mostly related to the catabolic processes (Supplemental Fig. S16; Supplemental Data S4–S6). At the 16-h time point in the dark, only a few genes related to metabolic processes were differentially regulated between Nat and Mut plants (Supplemental Figs. S16 and S17).

DISCUSSION

The metabolic network in photosynthetic cells changes dramatically upon the transition between day and night. This is largely dependent on photosynthetic and photorespiratory metabolism, which only operate during the day. Nitrogen fixation also takes place mainly in the daytime due to the large requirement of reducing agents. The dramatic changes in metabolic demands require a shift of flux mode of the mitochondrial tricarboxylic acid cycle at the dawn from energy metabolism to the regulation of cellular redox balance and the production of 2-oxoglutarate consumed by amino acid synthesis (Cheung et al., 2014). These metabolic shifts result in diurnal oscillation in the levels of metabolites (Gibon et al., 2006). Diurnal oscillation was observed in the levels of 17 of 37 metabolites (including starch) analyzed in this study. The diurnal oscillation of starch content and of starch breakdown products are well known in Arabidopsis leaves (Lu et al., 2005; Lu and Sharkey, 2006; Sulpice et al., 2014). It is reasonable that the metabolites involved in photorespiration (Gly, Ser, and glycerate) showed the most prominent oscillation and accumulated the most at the end of the light period. An interesting finding in this study is that the levels of photorespiratory intermediates, especially glycerate, continued to oscillate after transfer to the constant light condition in a TPP riboswitch-dependent manner. In Nat plants, oscillations in the levels of tricarboxylic acid cycle intermediates were observed after transfer to constant darkness. In contrast, no free-running oscillations were observed in Mut plants under constant dark conditions.

These results suggest that the native riboswitch and appropriate TPP levels are essential for circadian regulation of these metabolic pathways. Interestingly, some metabolites (e.g. maltose, trehalose, Fru, succinate, fumarate, malate, Gly, and Ser) showed altered oscillation in the first few days of photoperiod transition in the control plants. These changes affected the amplitude of diurnal oscillations but not period length. Additionally, many of them were transient and stabilized at day 3 following the transition of photoperiod. These transient responses of metabolite levels are most likely reflecting the adjustment of the metabolic network to the new photoperiod to buffer the effects of prolonged photosynthetic duration. However, many of these changes in the oscillation’s amplitude were not observed in the plants harboring a mutated TPP riboswitch. These plants retained the same amplitude of oscillation as those grown in the continuous SD condition for most of the metabolites, such as in the levels of succinate, fumarate, and Gly, while the Nat plants showed temporal alteration in the oscillation pattern. This indicates that the Mut plants lack flexibility of the metabolic network to adjust to altered photoperiods. This is most likely due to deregulation of respiratory flux, which resulted in constitutively high respiratory activity (Bocobza et al., 2013). It is still unclear why the Mut plant shows high respiratory flux. Bocobza et al. (2013) suggested that the constitutively high TPP levels in the Mut plant, as a result of its inability to regulate the TPP levels through the riboswitch, probably alter the allosteric regulation of TPP-dependent enzymes. This is indicated by the result that the TPP-dependent enzymes, namely PDH, OGDH, and TK, extracted from Mut plants show higher enzymatic activity at the high TPP concentration (Bocobza et al., 2013). As PDH and OGDH are the components of the mitochondrial tricarboxylic acid cycle, altered activities of these enzymes likely affect respiratory fluxes in this pathway (Bocobza et al., 2013), leading to the alteration in the amplitudes and phases of oscillation in the accumulation of the tricarboxylic acid cycle intermediates in Mut plants. This likely contributes to the inability of the riboswitch mutant to adjust its metabolic network in response to a change in photoperiod.

The lack of metabolic flexibility likely compromises the plant’s ability to acclimate to an altered photoperiod, leading to the more severe phenotypes in metabolite profiles and chlorophyll fluorescence quantum yields of Mut plants after the transition of photoperiod. These results highlight the roles of vitamins in the diurnal regulation of central carbon metabolism in plants. Fukushima et al. (2009) showed that the Arabidopsis triple mutant of clock-related pseudo-response regulator9 (PRR9), PRR7, and PRR5 (d975) overaccumulates vitamin C (ascorbate) and E (α-tocopherol) as well as the tricarboxylic acid cycle intermediates. This d975 triple mutant indeed accumulates less TMP than wild-type plants during the night (Bocobza et al., 2013). Additionally, there is cumulative evidence indicating the interrelationship between metabolism and circadian regulation in plants (Dodd et al., 2007; Dalchau et al., 2011; Haydon et al., 2013). The results in this study thus suggest a potential role of vitamin B1 in the diurnal regulation of central carbon metabolism in plants.

In the previous study, 8-week-old Mut plants showed pale-green leaves under the SD photoperiod, and these plants recovered following an additional 2 weeks of growth under the LD condition (Bocobza et al., 2013). This is most likely due to a mild but prolonged carbon starvation under the SD condition. Mut plants exhibit a higher respiratory rate, as described above (Bocobza et al., 2013). Since respiration consumes 30% to 80% of the carbon fixed by photosynthesis, respiratory activity significantly affects the plant carbon budget (Pyl et al., 2012). Overactivation of the respiration would be related to higher consumption of carbon resources, including starch (Bocobza et al., 2013; this study), leading to a mild carbon starvation. Our transcriptome analysis revealed the activation of protein and amino acid degradation pathways, which are also likely a response against carbon starvation, as degradation of protein and chlorophyll is a typical reaction under this condition (Araújo et al., 2010). This is also supported by the fact that the Mut plants recovered following 2 weeks of culture under the LD photoperiod, most likely due to sufficient carbon supply to compensate for the increased consumption by the activated tricarboxylic acid cycle during the long photoperiod (Bocobza et al., 2013).

Our results also indicate a close relationship between the operation of photorespiration and the tricarboxylic acid cycle under these conditions. None of the photorespiratory enzymes are known to require TPP as a cofactor; nevertheless, Mut plants accumulate less photorespiratory intermediates such as Gly, Ser, and glycerate. Gly and Ser are two of the metabolites whose oscillations were most dramatically affected by the photoperiod transition. Changes of these metabolites probably reflect the altered flux of photorespiratory metabolism, since the levels of these metabolites did not increase after the plants were transferred into the CD condition. Although Ser accumulated in the CD condition, the accumulation rate was much lower than that in the CL condition. This accumulation of Ser is likely due to its biosynthetic pathway in plastids (Cascales-Miñana et al., 2013). Considering the activation of the tricarboxylic acid cycle in Mut plants and the deregulation of photorespiratory intermediates upon photoperiod transition, it is reasonable to assume that the tricarboxylic acid cycle affects photorespiratory activity. There is cumulative evidence of a close relationship between the tricarboxylic acid cycle and photorespiration (Obata et al., 2016). Both of these pathways produce NADH in the mitochondria and two of the most flux-bearing pathways in the mitochondria (Fernie et al., 2013). Thus, these pathways must be coordinately controlled for the regulation of cellular redox balance (Obata et al., 2016). As the tricarboxylic acid cycle is activated in the Mut line (Bocobza et al., 2013), photorespiration (more specifically the Gly decarboxylase reaction) should be suppressed, which is indicated by the accumulation of Gly and the reduction of Ser following the transition to the LD condition.

CONCLUSION

This study showed the importance of maintaining appropriate cellular levels of vitamin B1 to maintain metabolic flexibility and the ability to acclimate to an altered photoperiod. This flexibility is most likely related to a plant’s ability to modulate tricarboxylic acid cycle flux, which is activated in the Mut plants. The tricarboxylic acid cycle is considered as a metabolic hub involved in the regulation of central carbon metabolism (Nunes-Nesi et al., 2011). The temporal alteration in the levels of tricarboxylic acid cycle intermediates, as well as closely related metabolites of photorespiration and starch degradation, would be a consequence of the reorganization of the metabolic network during acclimation to the altered photoperiod. Thus, these pathways are expected to be closely related to the diurnal metabolic oscillations. Mutant plants deficient in circadian regulation often display an altered accumulation of tricarboxylic acid cycle intermediates (Dodd et al., 2007; Fukushima et al., 2009; Nakamichi et al., 2009; Dalchau et al., 2011; Haydon et al., 2013; Sanchez-Villarreal et al., 2013), and future studies utilizing mutants of the tricarboxylic acid cycle and photorespiratory pathway will likely be instrumental in further elucidating the underlying mechanisms underpinning these observations, as would experiments utilizing other available thiamin mutants.

MATERIALS AND METHODS

Plant Materials and Growth Conditions

Arabidopsis (Arabidopsis thaliana) plant lines of TPP riboswitch mutants, specifically altered in their TPP riboswitch function, were generated as described by Bocobza et al. (2013) by transforming the thic knockdown line (SALK_011114; Kong et al., 2008) with the genomic sequence of the Arabidopsis THIC gene harboring a mutation in the riboswitch region. A control line was generated by complementing the thic knockdown line with the Nat genomic sequence (Bocobza et al., 2013). Seeds of wild-type, Nat, and Mut plants were surface sterilized with 95% (v/v) ethanol for 1 min and 42% (v/v) bleach (5% [v/v] chlorite, final volume) containing 0.1 (v/v)% Tween 20 for 10 min. Following five rinses with sterile water, seeds were sown on one-half-strength Murashige and Skoog medium (Murashige and Skoog, 1962) plus 1% (w/v) Suc plates, vernalized at 4°C for 3 d, and transferred to an environment-controlled chamber (150 µmol photons m−2 s−1, 22°C, 70% humidity, and 16-h/8-h light/dark regime) for 7 to 10 d. The seedlings were then transferred to standard greenhouse soil (Stender) in plastic pots of 0.1 L capacity. Plants were grown in SD (8/16 h of light/dark, 22°C/16°C, 60%/75% relative humidity, and 180 μmol photons m−2 s−1 light intensity), LD (16/8 h of light/dark), CL, or CD conditions as detailed in Supplemental Figure S1; all remaining conditions were the same as in the SD condition. When shifted to a new condition, plants were transferred shortly before the onset of the light period. All analyses were carried out from whole rosettes of six individual plants harvested at the specified time points. Harvested rosette samples were immediately frozen in liquid nitrogen and stored at −80°C until further analysis.

Chlorophyll a Fluorescence Measurements

Images of chlorophyll fluorescence were obtained using a MAXI version of the Imaging-PAM fluorometer (Heinz Walz). Minimum and maximum fluorescence, Fv/Fm, quantum yield of photochemistry, quantum yield of regulated energy dissipation, and quantum yield of nonregulated energy dissipation were measured on intact leaves after plants were dark adapted for 30 min (Kramer et al., 2004).

Metabolite Profiling

Metabolite extraction for GC-MS was carried out as previously described (Lisec et al., 2006) with minor modifications. Plant materials were ground to a fine powder by a ball mill (MM301; Retsch). Metabolites were extracted from 50 mg of material in 730 μL of methanol supplemented with 30 μL of ribitol (0.2 mg mL−1 in water) as an internal standard. The mixture was shaken at 1,000 rpm for 15 min at 70°C and centrifuged for 10 min at 20,800g. After centrifugation, the supernatant was transferred to a new tube and mixed with 350 μL of chloroform and 750 μL of water and centrifuged for 15 min at 20,800g to separate the polar and apolar phases. A 150-μL aliquot of the polar (upper) phase was dried in a centrifugal vacuum concentrator (SpeedVac; Thermo Scientific). The pellet of metabolites was resuspended in 40 μL of methoxyaminhydrochlorid (20 mg mL−1 in pyridine) and derivatized for 2 h at 37°C. Afterward, 70 μL of N-methyl-N-[trimethylsilyl] trifluoroacetamide was supplemented with 20 μL mL−1 each fatty acid methyl ester mixture as retention time standards. The mixture was incubated for 30 min at 37°C with shaking at 400 rpm. A volume of 1 μL of this solution was injected. The GC-MS system comprised a CTC CombiPAL autosampler, an Agilent 6890N gas chromatograph, and a LECO Pegasus III TOF-MS running in EI+ mode. Metabolites were identified in comparison with database entries of authentic standards (Kopka et al., 2005). Chromatograms and mass spectra were evaluated using Chroma TOF Software v4.51.6.0 (Leco) and TagFinder 4.0 software (Luedemann et al., 2012).

The relative level of metabolite was represented by the value with an arbitrary unit, which is calculated as the peak intensity of the specific fragment normalized by that of the internal standard (ribitol) and sample weight (milligram). To quantitatively analyze the oscillation in metabolite levels, the amplitude of oscillation was calculated as follows. For each metabolite in each genotype, the daily minimum metabolite levels were determined as the mean metabolite level at the time point showing the lowest mean value on each day (i.e. 0–24 h, 24–48 h, and 48–68 h time points). The time point showing the maximum daily metabolite level was identified by comparing the mean metabolite levels. Then the daily amplitude values were calculated by subtracting minimum metabolite levels from individual values at the time point showing the maximum daily metabolite level.

Chlorophyll a and b contents were determined in the polar phase of metabolite extracts as detailed by Lichtenthaler and Buschmann (2001). The levels of starch and total protein were determined in the pellet as previously described by Fernie et al. (2001) and Bradford (1976) adapted for microplates, respectively. Thiamin and its vitamers (TMP and TPP) contents were determined as described by Martinis et al. (2016).

RNA Extraction and Transcriptome Analysis by RNA Sequencing

RNA was extracted as described by Bugos et al. (1995). DNA was digested by DNAse I (Ambion) according to the manufacturer’s instructions. RNA quality (RNA integrity number) was determined using Bioanalyzer and Reagent Kit RNA 6000 Nano (Agilent). Sample quality control, cDNA synthesis and library preparation, detection of sequencing fragments using the Illumina platform, and demultiplexing and FASTQ file generation were performed by Beckman Coulter Genomics. All RNA sequencing files were processed using LSTrAP (Proost et al., 2017; https://github.molgen.mpg.de/proost/LSTrAP). LSTrAP automatically executes Trimmomatic (Bolger et al., 2014) to trim low-quality parts of reads, remove adapter sequences, and exclude reads that are, after trimming, shorter than 36 bp. The remaining reads were mapped against the Arabidopsis genome using BowTie2 (Langmead and Salzberg, 2012) and TopHat2 (default parameters; Kim et al., 2013), and the number of reads mapping to coding sequences was determined using HTSeq-Counts (Anders et al., 2015) using default parameters. Isoforms were removed from the Arabidopsis structural annotation (GFF file) prior to running HTSeq-Counts, keeping only the primary transcript, to ensure that no reads were lost due to matching multiple splice variants. LSTrAP combined the output from HTSeq-Count into an expression matrix and applied transcripts per million normalization (Kryuchkova-Mostacci and Robinson-Rechavi, 2017). After verifying, using a PCA and sample-distance heat map, that no samples were swapped/mislabeled, the output from HTSeq-Count was further analyzed using the R/Bioconductor (Gentleman et al., 2004) package DESeq2 (Love et al., 2014), and differentially expressed genes between the Nat and the Mut plants were determined for each time point separately. GO enrichment for each time point was calculated for differentially expressed genes (P ≤ 0.05 after correction for multiple testing Benjamini-Hochberg, separating up- and down-regulated genes, using PLAZA 3.0 Dicots and exported for further analysis (Proost et al., 2015). Overrepresented terms were visualized using REVIGO (Supek et al., 2011). The same lists of differentially expressed genes were used to determine if known biological pathways were overrepresented, and genes were assigned to hierarchical functional categories (BINs) using MapMan 3.6 RC 1 (Thimm et al., 2004).

Accession Number

Sequence data from this article can be found in the Arabidopsis Genome Initiative or GenBank/EMBL databases under accession number At2g29630 (THIC).

Supplemental Data

The following supplemental materials are available.

  • Supplemental Figure S1. Experimental design and visible phenotypes of the plants.

  • Supplemental Figure S2. Pigment content and total protein content from TPP riboswitch mutant plants grown in SD, LD, or SD-LD for 1 week.

  • Supplemental Figure S3. Fv/Fm from TPP riboswitch mutant plants grown in SD, LD, or SD-LD for 1 week.

  • Supplemental Figure S4. Analysis of thiamin and its vitamers by HPLC from TPP riboswitch mutant plants.

  • Supplemental Figure S5. Metabolic profiling of TPP riboswitch mutant plants during the acclimation following changes of photoperiod.

  • Supplemental Figure S6. Levels of carbohydrates and tricarboxylic acid cycle-related organic acids in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S7. Levels of carbohydrates in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S8. Levels of tricarboxylic acid cycle-related organic acids in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S9. Levels of photorespiratory intermediates in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S10. Levels of amino acids in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S11. Levels of organic acids in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S12. Levels of sugars in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S13. Levels of other metabolites in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S14. Amplitude in the oscillation in the levels of specific metabolites in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Figure S15. REVIGO TreeMap view of biological processes for genes down-regulated in Mut compared with Nat plants at three time points after transfer from the SD to the 12-h photoperiod.

  • Supplemental Figure S16. MapMan representation of differences in transcript levels between Mut and Nat plants after transfer from the SD to the 12-h photoperiod at 8-, 12-, and 16-h time points.

  • Supplemental Figure S17. Number of genes in each BIN differentially expressed between Mut and Nat plants after transfer from the SD to the 12-h photoperiod at 8-, 12-, and 16-h time points.

  • Supplemental Data S1. Metabolic profiling from TPP riboswitch mutant plants grown on SD, LD, and SD-LD for 1 week in different time points.

  • Supplemental Data S2. Amplitude in the oscillation in the levels of metabolites in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Data S3. Fold change of amplitude in the oscillation in the levels of metabolites in TPP riboswitch mutant plants during photoperiod transition.

  • Supplemental Data S4. List of BINs and assigned genes to each category from MapMan at the 8-h time point after transfer from the SD to the 12-h photoperiod.

  • Supplemental Data S5. List of BINs and assigned genes to each category from MapMan at the 12-h time point after transfer from the SD to the 12-h photoperiod.

  • Supplemental Data S6. List of BINs and assigned genes to each category from MapMan at the 16-h time point after transfer from the SD to the 12-h photoperiod.

Acknowledgments

We acknowledge the support provided by the Infrastructure Group Biophysics and Photosynthesis and Dr. Mark A. Schoettler (from the Max Planck Institute of Molecular Plant Physiology) for the chlorophyll a fluorescence measurements.

Footnotes

  • www.plantphysiol.org/cgi/doi/10.1104/pp.18.01346

  • The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Alisdair R. Fernie (fernie{at}mpimp-golm.mpg.de).

  • L.R.-S. performed the experiments; L.R.-S., S.P., and M.Mo. analyzed samples and data; S.B. provided technical assistance; S.E.B. and A.A. provided seed material; T.B.F. and M.Mu. contributed to writing and reviewed the manuscript; T.O. and A.R.F. designed and supervised the study; L.R.-S., T.O., and A.R.F. wrote the article, with contributions from all of the authors.

  • ↵1 This work was supported by the National Council for Scientific and Technological Development (CNPq), Brazil (scholarship 246374/2012-8 to L.R.-S.), the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Centers, Sonderforschungsbereich (grant TRR 175/1 to A.R.F.), the Swiss National Science Foundation (grants 31003A-141117/1 and 31003A_162555/1 to T.B.F.), as well as the University of Geneva.

  • ↵2 Present address: VIB-KU Leuven Center for Microbiology, Rega Instituut, Herestraat 49 bus 1030, 3000 Leuven, Belgium.

  • ↵3 Present address: CHUV Centre Hospitalier Universitaire Vaudois, Rue du Bugnon 21, CH-1011 Lausanne, Switzerland.

  • ↵4 Present address: Institute of Plant Sciences, The Volcani Center, Agricultural Research Organization Bet-Dagan 50250, Israel.

  • ↵5 Present address: School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, 8 Singapore 637551, Singapore.

  • ↵7 Senior author.

  • ↵8 Present address: Department of Biochemistry and Center for Plant Science Innovation, University of Nebraska, 1901 Vine Street, Lincoln, NE 68588.

  • ↵[OPEN] Articles can be viewed without a subscription.

  • Received October 29, 2018.
  • Accepted February 16, 2019.
  • Published March 5, 2019.

REFERENCES

  1. ↵
    1. Ahn IP,
    2. Kim S,
    3. Lee YH
    (2005) Vitamin B1 functions as an activator of plant disease resistance. Plant Physiol 138: 1505–1515
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Ajjawi I,
    2. Rodriguez Milla MA,
    3. Cushman J,
    4. Shintani DK
    (2007a) Thiamin pyrophosphokinase is required for thiamin cofactor activation in Arabidopsis. Plant Mol Biol 65: 151–162
    OpenUrlCrossRefPubMed
  3. ↵
    1. Ajjawi I,
    2. Tsegaye Y,
    3. Shintani D
    (2007b) Determination of the genetic, molecular, and biochemical basis of the Arabidopsis thaliana thiamin auxotroph th1. Arch Biochem Biophys 459: 107–114
    OpenUrlCrossRefPubMed
  4. ↵
    1. Anders S,
    2. Pyl PT,
    3. Huber W
    (2015) HTSeq: A Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166–169
    OpenUrlCrossRefPubMed
  5. ↵
    1. Araújo WL,
    2. Ishizaki K,
    3. Nunes-Nesi A,
    4. Larson TR,
    5. Tohge T,
    6. Krahnert I,
    7. Witt S,
    8. Obata T,
    9. Schauer N,
    10. Graham IA, et al.
    (2010) Identification of the 2-hydroxyglutarate and isovaleryl-CoA dehydrogenases as alternative electron donors linking lysine catabolism to the electron transport chain of Arabidopsis mitochondria. Plant Cell 22: 1549–1563
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Bass J,
    2. Takahashi JS
    (2010) Circadian integration of metabolism and energetics. Science 330: 1349–1354
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Bocobza SE,
    2. Aharoni A
    (2008) Switching the light on plant riboswitches. Trends Plant Sci 13: 526–533
    OpenUrlCrossRefPubMed
  8. ↵
    1. Bocobza SE,
    2. Malitsky S,
    3. Araújo WL,
    4. Nunes-Nesi A,
    5. Meir S,
    6. Shapira M,
    7. Fernie AR,
    8. Aharoni A
    (2013) Orchestration of thiamin biosynthesis and central metabolism by combined action of the thiamin pyrophosphate riboswitch and the circadian clock in Arabidopsis. Plant Cell 25: 288–307
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Bolger AM,
    2. Lohse M,
    3. Usadel B
    (2014) Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114–2120
    OpenUrlCrossRefPubMed
  10. ↵
    1. Boxall SF,
    2. Dever LV,
    3. Kneřová J,
    4. Gould PD,
    5. Hartwell J
    (2017) Phosphorylation of phosphoenolpyruvate carboxylase is essential for maximal and sustained dark CO2 fixation and core circadian clock operation in the obligate Crassulacean acid metabolism species Kalanchoë fedtschenkoi. Plant Cell 29: 2519–2536
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Bradford MM
    (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248–254
    OpenUrlCrossRefPubMed
  12. ↵
    1. Bugos RC,
    2. Chiang VL,
    3. Zhang XH,
    4. Campbell ER,
    5. Podila GK,
    6. Campbell WH
    (1995) RNA isolation from plant tissues recalcitrant to extraction in guanidine. Biotechniques 19: 734–737
    OpenUrlPubMed
  13. ↵
    1. Cascales-Miñana B,
    2. Muñoz-Bertomeu J,
    3. Flores-Tornero M,
    4. Anoman AD,
    5. Pertusa J,
    6. Alaiz M,
    7. Osorio S,
    8. Fernie AR,
    9. Segura J,
    10. Ros R
    (2013) The phosphorylated pathway of serine biosynthesis is essential both for male gametophyte and embryo development and for root growth in Arabidopsis. Plant Cell 25: 2084–2101
    OpenUrlAbstract/FREE Full Text
  14. ↵
    1. Cheung CY,
    2. Poolman MG,
    3. Fell DA,
    4. Ratcliffe RG,
    5. Sweetlove LJ
    (2014) A diel flux balance model captures interactions between light and dark metabolism during day-night cycles in C3 and Crassulacean acid metabolism leaves. Plant Physiol 165: 917–929
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Dalchau N,
    2. Baek SJ,
    3. Briggs HM,
    4. Robertson FC,
    5. Dodd AN,
    6. Gardner MJ,
    7. Stancombe MA,
    8. Haydon MJ,
    9. Stan GB,
    10. Gonçalves JM, et al.
    (2011) The circadian oscillator gene GIGANTEA mediates a long-term response of the Arabidopsis thaliana circadian clock to sucrose. Proc Natl Acad Sci USA 108: 5104–5109
    OpenUrlAbstract/FREE Full Text
  16. ↵
    1. Dodd AN,
    2. Salathia N,
    3. Hall A,
    4. Kévei E,
    5. Tóth R,
    6. Nagy F,
    7. Hibberd JM,
    8. Millar AJ,
    9. Webb AA
    (2005) Plant circadian clocks increase photosynthesis, growth, survival, and competitive advantage. Science 309: 630–633
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Dodd AN,
    2. Gardner MJ,
    3. Hotta CT,
    4. Hubbard KE,
    5. Dalchau N,
    6. Love J,
    7. Assie JM,
    8. Robertson FC,
    9. Jakobsen MK,
    10. Gonçalves J, et al.
    (2007) The Arabidopsis circadian clock incorporates a cADPR-based feedback loop. Science 318: 1789–1792
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Dong W,
    2. Stockwell VO,
    3. Goyer A
    (2015) Enhancement of thiamin content in Arabidopsis thaliana by metabolic engineering. Plant Cell Physiol 56: 2285–2296
    OpenUrlCrossRefPubMed
  19. ↵
    1. Farré EM
    (2012) The regulation of plant growth by the circadian clock. Plant Biol (Stuttg) 14: 401–410
    OpenUrlCrossRefPubMed
  20. ↵
    1. Fernie AR,
    2. Roessner U,
    3. Trethewey RN,
    4. Willmitzer L
    (2001) The contribution of plastidial phosphoglucomutase to the control of starch synthesis within the potato tuber. Planta 213: 418–426
    OpenUrlCrossRefPubMed
  21. ↵
    1. Fernie AR,
    2. Bauwe H,
    3. Eisenhut M,
    4. Florian A,
    5. Hanson DT,
    6. Hagemann M,
    7. Keech O,
    8. Mielewczik M,
    9. Nikoloski Z,
    10. Peterhänsel C, et al.
    (2013) Perspectives on plant photorespiratory metabolism. Plant Biol (Stuttg) 15: 748–753
    OpenUrlCrossRefPubMed
  22. ↵
    1. Fukushima A,
    2. Kusano M,
    3. Nakamichi N,
    4. Kobayashi M,
    5. Hayashi N,
    6. Sakakibara H,
    7. Mizuno T,
    8. Saito K
    (2009) Impact of clock-associated Arabidopsis pseudo-response regulators in metabolic coordination. Proc Natl Acad Sci USA 106: 7251–7256
    OpenUrlAbstract/FREE Full Text
  23. ↵
    1. Gentleman RC,
    2. Carey VJ,
    3. Bates DM,
    4. Bolstad B,
    5. Dettling M,
    6. Dudoit S,
    7. Ellis B,
    8. Gautier L,
    9. Ge Y,
    10. Gentry J, et al.
    (2004) Bioconductor: Open software development for computational biology and bioinformatics. Genome Biol 5: R80
    OpenUrlCrossRefPubMed
  24. ↵
    1. Gibon Y,
    2. Usadel B,
    3. Blaesing OE,
    4. Kamlage B,
    5. Hoehne M,
    6. Trethewey R,
    7. Stitt M
    (2006) Integration of metabolite with transcript and enzyme activity profiling during diurnal cycles in Arabidopsis rosettes. Genome Biol 7: R76
    OpenUrlCrossRefPubMed
  25. ↵
    1. Graf A,
    2. Smith AM
    (2011) Starch and the clock: The dark side of plant productivity. Trends Plant Sci 16: 169–175
    OpenUrlCrossRefPubMed
  26. ↵
    1. Graf A,
    2. Schlereth A,
    3. Stitt M,
    4. Smith AM
    (2010) Circadian control of carbohydrate availability for growth in Arabidopsis plants at night. Proc Natl Acad Sci USA 107: 9458–9463
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Greenham K,
    2. McClung CR
    (2015) Integrating circadian dynamics with physiological processes in plants. Nat Rev Genet 16: 598–610
    OpenUrlCrossRefPubMed
  28. ↵
    1. Haydon MJ,
    2. Webb AA
    (2016) Assessing the impact of photosynthetic sugars on the Arabidopsis circadian clock. Methods Mol Biol 1398: 133–140
    OpenUrl
  29. ↵
    1. Haydon MJ,
    2. Hearn TJ,
    3. Bell LJ,
    4. Hannah MA,
    5. Webb AA
    (2013) Metabolic regulation of circadian clocks. Semin Cell Dev Biol 24: 414–421
    OpenUrlCrossRefPubMed
  30. ↵
    1. Haydon MJ,
    2. Román Á,
    3. Arshad W
    (2015) Nutrient homeostasis within the plant circadian network. Front Plant Sci 6: 299
    OpenUrl
  31. ↵
    1. Hsieh WY,
    2. Liao JC,
    3. Wang HT,
    4. Hung TH,
    5. Tseng CC,
    6. Chung TY,
    7. Hsieh MH
    (2017) The Arabidopsis thiamin-deficient mutant pale green1 lacks thiamin monophosphate phosphatase of the vitamin B1 biosynthesis pathway. Plant J 91: 145–157
    OpenUrl
  32. ↵
    1. Johnston JD
    (2014) Physiological links between circadian rhythms, metabolism and nutrition. Exp Physiol 99: 1133–1137
    OpenUrlCrossRefPubMed
  33. ↵
    1. Khozaei M,
    2. Fisk S,
    3. Lawson T,
    4. Gibon Y,
    5. Sulpice R,
    6. Stitt M,
    7. Lefebvre SC,
    8. Raines CA
    (2015) Overexpression of plastid transketolase in tobacco results in a thiamine auxotrophic phenotype. Plant Cell 27: 432–447
    OpenUrlAbstract/FREE Full Text
  34. ↵
    1. Kim D,
    2. Pertea G,
    3. Trapnell C,
    4. Pimentel H,
    5. Kelley R,
    6. Salzberg SL
    (2013) TopHat2: Accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14: R36
    OpenUrlCrossRefPubMed
  35. ↵
    1. Kong D,
    2. Zhu Y,
    3. Wu H,
    4. Cheng X,
    5. Liang H,
    6. Ling HQ
    (2008) AtTHIC, a gene involved in thiamine biosynthesis in Arabidopsis thaliana. Cell Res 18: 566–576
    OpenUrlCrossRefPubMed
  36. ↵
    1. Kopka J,
    2. Schauer N,
    3. Krueger S,
    4. Birkemeyer C,
    5. Usadel B,
    6. Bergmüller E,
    7. Dörmann P,
    8. Weckwerth W,
    9. Gibon Y,
    10. Stitt M, et al.
    (2005) GMD@CSB.DB: The Golm Metabolome Database. Bioinformatics 21: 1635–1638
    OpenUrlCrossRefPubMed
  37. ↵
    1. Kramer DM,
    2. Johnson G,
    3. Kiirats O,
    4. Edwards GE
    (2004) New fluorescence parameters for the determination of QA redox state and excitation energy fluxes. Photosynth Res 79: 209–218
    OpenUrlCrossRefPubMed
  38. ↵
    1. Kryuchkova-Mostacci N,
    2. Robinson-Rechavi M
    (2017) A benchmark of gene expression tissue-specificity metrics. Brief Bioinform 18: 205–214
    OpenUrlCrossRef
  39. ↵
    1. Langmead B,
    2. Salzberg SL
    (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9: 357–359
    OpenUrlCrossRefPubMed
  40. ↵
    1. Lichtenthaler HK,
    2. Buschmann C
    (2001) Chlorophylls and carotenoids: Measurement and characterization by UV-VIS spectroscopy. Current Protocols in Food Analytical Chemistry 1: F4.3.1–F4.3.8
    OpenUrl
  41. ↵
    1. Lisec J,
    2. Schauer N,
    3. Kopka J,
    4. Willmitzer L,
    5. Fernie AR
    (2006) Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat Protoc 1: 387–396
    OpenUrlCrossRefPubMed
  42. ↵
    1. Love MI,
    2. Huber W,
    3. Anders S
    (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550
    OpenUrlCrossRefPubMed
  43. ↵
    1. Lu Y,
    2. Sharkey TD
    (2006) The importance of maltose in transitory starch breakdown. Plant Cell Environ 29: 353–366
    OpenUrlCrossRefPubMed
  44. ↵
    1. Lu Y,
    2. Gehan JP,
    3. Sharkey TD
    (2005) Daylength and circadian effects on starch degradation and maltose metabolism. Plant Physiol 138: 2280–2291
    OpenUrlAbstract/FREE Full Text
  45. ↵
    1. Luedemann A,
    2. von Malotky L,
    3. Erban A,
    4. Kopka J
    (2012) TagFinder: Preprocessing software for the fingerprinting and the profiling of gas chromatography-mass spectrometry based metabolome analyses. Methods Mol Biol 860: 255–286
    OpenUrlCrossRefPubMed
  46. ↵
    1. Machado CR,
    2. de Oliveira RL,
    3. Boiteux S,
    4. Praekelt UM,
    5. Meacock PA,
    6. Menck CF
    (1996) Thi1, a thiamine biosynthetic gene in Arabidopsis thaliana, complements bacterial defects in DNA repair. Plant Mol Biol 31: 585–593
    OpenUrlCrossRefPubMed
  47. ↵
    1. Martinis J,
    2. Gas-Pascual E,
    3. Szydlowski N,
    4. Crèvecoeur M,
    5. Gisler A,
    6. Bürkle L,
    7. Fitzpatrick TB
    (2016) Long-distance transport of thiamine (vitamin B1) is concomitant with that of polyamines. Plant Physiol 171: 542–553
    OpenUrlAbstract/FREE Full Text
  48. ↵
    1. Mimura M,
    2. Zallot R,
    3. Niehaus TD,
    4. Hasnain G,
    5. Gidda SK,
    6. Nguyen TND,
    7. Anderson EM,
    8. Mullen RT,
    9. Brown G,
    10. Yakunin AF, et al.
    (2016) Arabidopsis TH2 encodes the orphan enzyme thiamin monophosphate phosphatase. Plant Cell 28: 2683–2696
    OpenUrlAbstract/FREE Full Text
  49. ↵
    1. Murashige T,
    2. Skoog F
    (1962) A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiol Plant 15: 473–497
    OpenUrlCrossRef
  50. ↵
    1. Nakamichi N,
    2. Fukushima A,
    3. Kusano M,
    4. Sakakibara H,
    5. Mizuno T,
    6. Saito K
    (2009) Linkage between circadian clock and tricarboxylic acid cycle in Arabidopsis. Plant Signal Behav 4: 660–662
    OpenUrlCrossRefPubMed
  51. ↵
    1. Nunes-Nesi A,
    2. Araújo WL,
    3. Fernie AR
    (2011) Targeting mitochondrial metabolism and machinery as a means to enhance photosynthesis. Plant Physiol 155: 101–107
    OpenUrlFREE Full Text
  52. ↵
    1. Obata T,
    2. Florian A,
    3. Timm S,
    4. Bauwe H,
    5. Fernie AR
    (2016) On the metabolic interactions of (photo)respiration. J Exp Bot 67: 3003–3014
    OpenUrlCrossRefPubMed
  53. ↵
    1. Proost S,
    2. Van Bel M,
    3. Vaneechoutte D,
    4. Van de Peer Y,
    5. Inzé D,
    6. Mueller-Roeber B,
    7. Vandepoele K
    (2015) PLAZA 3.0: An access point for plant comparative genomics. Nucleic Acids Res 43: D974–D981
    OpenUrlCrossRefPubMed
  54. ↵
    1. Proost S,
    2. Krawczyk A,
    3. Mutwil M
    (2017) LSTrAP: Efficiently combining RNA sequencing data into co-expression networks. BMC Bioinformatics 18: 444
    OpenUrl
  55. ↵
    1. Pyl ET,
    2. Piques M,
    3. Ivakov A,
    4. Schulze W,
    5. Ishihara H,
    6. Stitt M,
    7. Sulpice R
    (2012) Metabolism and growth in Arabidopsis depend on the daytime temperature but are temperature-compensated against cool nights. Plant Cell 24: 2443–2469
    OpenUrlAbstract/FREE Full Text
  56. ↵
    1. Raschke M,
    2. Bürkle L,
    3. Müller N,
    4. Nunes-Nesi A,
    5. Fernie AR,
    6. Arigoni D,
    7. Amrhein N,
    8. Fitzpatrick TB
    (2007) Vitamin B1 biosynthesis in plants requires the essential iron sulfur cluster protein, THIC. Proc Natl Acad Sci USA 104: 19637–19642
    OpenUrlAbstract/FREE Full Text
  57. ↵
    1. Sanchez-Villarreal A,
    2. Shin J,
    3. Bujdoso N,
    4. Obata T,
    5. Neumann U,
    6. Du SX,
    7. Ding Z,
    8. Davis AM,
    9. Shindo T,
    10. Schmelzer E, et al.
    (2013) TIME FOR COFFEE is an essential component in the maintenance of metabolic homeostasis in Arabidopsis thaliana. Plant J 76: 188–200
    OpenUrlCrossRefPubMed
  58. ↵
    1. Sayed SA,
    2. Gadallah MAA
    (2002) Effects of shoot and root application of thiamin on salt-stressed sunflower plants. Plant Growth Regul 36: 71–80
    OpenUrlCrossRef
  59. ↵
    1. Smith AM,
    2. Stitt M
    (2007) Coordination of carbon supply and plant growth. Plant Cell Environ 30: 1126–1149
    OpenUrlCrossRefPubMed
  60. ↵
    1. Stitt M,
    2. Zeeman SC
    (2012) Starch turnover: Pathways, regulation and role in growth. Curr Opin Plant Biol 15: 282–292
    OpenUrlCrossRefPubMed
  61. ↵
    1. Sulpice R,
    2. Pyl ET,
    3. Ishihara H,
    4. Trenkamp S,
    5. Steinfath M,
    6. Witucka-Wall H,
    7. Gibon Y,
    8. Usadel B,
    9. Poree F,
    10. Piques MC, et al.
    (2009) Starch as a major integrator in the regulation of plant growth. Proc Natl Acad Sci USA 106: 10348–10353
    OpenUrlAbstract/FREE Full Text
  62. ↵
    1. Sulpice R,
    2. Flis A,
    3. Ivakov AA,
    4. Apelt F,
    5. Krohn N,
    6. Encke B,
    7. Abel C,
    8. Feil R,
    9. Lunn JE,
    10. Stitt M
    (2014) Arabidopsis coordinates the diurnal regulation of carbon allocation and growth across a wide range of photoperiods. Mol Plant 7: 137–155
    OpenUrlCrossRefPubMed
  63. ↵
    1. Supek F,
    2. Bošnjak M,
    3. Škunca N,
    4. Šmuc T
    (2011) REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6: e21800
    OpenUrlCrossRefPubMed
  64. ↵
    1. Thimm O,
    2. Bläsing O,
    3. Gibon Y,
    4. Nagel A,
    5. Meyer S,
    6. Krüger P,
    7. Selbig J,
    8. Müller LA,
    9. Rhee SY,
    10. Stitt M
    (2004) MAPMAN: A user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37: 914–939
    OpenUrlCrossRefPubMed
  65. ↵
    1. Tunc-Ozdemir M,
    2. Miller G,
    3. Song L,
    4. Kim J,
    5. Sodek A,
    6. Koussevitzky S,
    7. Misra AN,
    8. Mittler R,
    9. Shintani D
    (2009) Thiamin confers enhanced tolerance to oxidative stress in Arabidopsis. Plant Physiol 151: 421–432
    OpenUrlAbstract/FREE Full Text
  66. ↵
    1. Wachter A,
    2. Tunc-Ozdemir M,
    3. Grove BC,
    4. Green PJ,
    5. Shintani DK,
    6. Breaker RR
    (2007) Riboswitch control of gene expression in plants by splicing and alternative 3′ end processing of mRNAs. Plant Cell 19: 3437–3450
    OpenUrlAbstract/FREE Full Text
  67. ↵
    1. Wang L,
    2. Ye X,
    3. Liu H,
    4. Liu X,
    5. Wei C,
    6. Huang Y,
    7. Liu Y,
    8. Tu J
    (2016) Both overexpression and suppression of an Oryza sativa NB-LRR-like gene OsLSR result in autoactivation of immune response and thiamine accumulation. Sci Rep 6: 24079
    OpenUrl
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Appropriate Thiamin Pyrophosphate Levels Are Required for Acclimation to Changes in Photoperiod
Laise Rosado-Souza, Sebastian Proost, Michael Moulin, Susan Bergmann, Samuel E. Bocobza, Asaph Aharoni, Teresa B. Fitzpatrick, Marek Mutwil, Alisdair R. Fernie, Toshihiro Obata
Plant Physiology May 2019, 180 (1) 185-197; DOI: 10.1104/pp.18.01346
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