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1 Short Title: The acetate pathway of flavonoid biosynthesis 1 Author for contact: Alisdair R Fernie and Takayuki Tohge 2 3 Title: 4 The acetate pathway supports flavonoid and lipid 5 biosynthesis in Arabidopsis 6 Leonardo Perez de Souza 1 , Karolina Garbowicz 1 , Yariv Brotman 2 , Takayuki Tohge 1,3 , 7 Alisdair R Fernie 1* 8 9 1 Max-Planck-Institute of Molecular Plant Physiology, Am Müehlenberg 1. Potsdam- 10 Golm, 14476, Germany 11 2 Department of Life Sciences, Ben-Gurion University of the Negev, Beersheba, Israel 12 3 Graduate School of Science and Technology, Nara Institute of Science and 13 Technology, 8916-5, Takayama-cho, Ikoma, Nara, 630-0192, Japan 14 15 One-sentence summary: The Arabidopsis acetate or polyketide pathway operates 16 at the interface of central and lipid metabolism as well as supporting the much better- 17 studied phenylpropanoid pathway of flavonoid biosynthesis. 18 19 Author Contributions 20 AF and TT conceived the original screening and research plans and supervised the 21 research. LPS performed all experiments and analyzed data. YB and KG performed 22 lipidomics analysis. LPS, AF and TT contributed to the writing of the manuscript. 23 24 Funding information 25 LPS gratefully acknowledges the scholarship granted by the Brazilian National 26 Council for Scientific and Technological Development (CNPq) and support from the 27 Max Planck Society and IMPRS-PMPG program. 28 29 *Corresponding authors: Alisdair R. Fernie and Takayuki Tohge 30 Address (ARF): Max-Planck Institute of Molecular Plant Physiology, Am Mühlenberg 31 1 32 Plant Physiology Preview. Published on November 12, 2019, as DOI:10.1104/pp.19.00683 Copyright 2019 by the American Society of Plant Biologists https://plantphysiol.org Downloaded on January 27, 2021. - Published by Copyright (c) 2020 American Society of Plant Biologists. All rights reserved.

The acetate pathway supports flavonoid and lipid ...€¦ · 11/12/2019  · 1 1 Short Title: The acetate pathway of flavonoid biosynthesis 2 Author for contact: Alisdair R Fernie

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    Short Title: The acetate pathway of flavonoid biosynthesis 1 Author for contact: Alisdair R Fernie and Takayuki Tohge 2 

    3 Title: 4 The acetate pathway supports flavonoid and lipid 5 biosynthesis in Arabidopsis 6 Leonardo Perez de Souza1, Karolina Garbowicz1, Yariv Brotman2, Takayuki Tohge1,3, 7 

    Alisdair R Fernie1* 8 

    9 1Max-Planck-Institute of Molecular Plant Physiology, Am Müehlenberg 1. Potsdam-10 

    Golm, 14476, Germany 11 2Department of Life Sciences, Ben-Gurion University of the Negev, Beersheba, Israel 12 3Graduate School of Science and Technology, Nara Institute of Science and 13 

    Technology, 8916-5, Takayama-cho, Ikoma, Nara, 630-0192, Japan 14 

    15 

    One-sentence summary: The Arabidopsis acetate or polyketide pathway operates 16 at the interface of central and lipid metabolism as well as supporting the much better-17 

    studied phenylpropanoid pathway of flavonoid biosynthesis. 18 

    19 

    Author Contributions 20 AF and TT conceived the original screening and research plans and supervised the 21 

    research. LPS performed all experiments and analyzed data. YB and KG performed 22 

    lipidomics analysis. LPS, AF and TT contributed to the writing of the manuscript. 23 

    24 

    Funding information 25 LPS gratefully acknowledges the scholarship granted by the Brazilian National 26 

    Council for Scientific and Technological Development (CNPq) and support from the 27 

    Max Planck Society and IMPRS-PMPG program. 28 

    29 

    *Corresponding authors: Alisdair R. Fernie and Takayuki Tohge 30 

    Address (ARF): Max-Planck Institute of Molecular Plant Physiology, Am Mühlenberg 31 

    1 32 

    Plant Physiology Preview. Published on November 12, 2019, as DOI:10.1104/pp.19.00683

    Copyright 2019 by the American Society of Plant Biologists

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    14476, Potsdam-Golm, Germany 33 

    Tel: +49 33 1567 8211 34 

    Fax: +49 33 1567 8408 35 

    Email: [email protected] 36 

    Address (TT): Graduate School of Biological Sciences, Nara Institute of Science and 37 

    Technology, Ikoma, Nara, 630-0192, Japan 38 

    Tel: +81 743 72 5480 39 

    Email: [email protected] 40 

    41 

    There are no conflicts of interest. 42 

    43 

    ABSTRACT 44 The phenylpropanoid pathway of flavonoid biosynthesis has been the subject of 45 

    considerable research attention. By contrast, the proposed polyketide pathway, also 46 

    known as the acetate pathway, which provides malonyl-CoA moieties for the C2 47 

    elongation reaction catalyzed by chalcone synthase, is less well studied. Here, we 48 

    identified four genes as candidates for involvement in the supply of cytosolic malonyl-49 

    CoA from the catabolism of acyl-CoA, based on co-expression analysis with other 50 

    flavonoid-related genes. Two of these genes, ACC and KAT5, have been previously 51 

    characterized with respect to their involvement in lipid metabolism, but no information 52 

    concerning their relationship to flavonoid biosynthesis is available. To assess the 53 

    occurrence and importance of the acetate pathway, we characterized the 54 

    metabolomes of two mutant or transgenic Arabidopsis lines for each of the four 55 

    enzymes of this putative pathway using a hierarchical approach covering primary and 56 

    secondary metabolites as well as lipids. Intriguingly, not only flavonoid content but 57 

    also glucosinolate content was altered in lines deficient in the acetate pathway, as 58 

    well as levels of lipids and most primary metabolites. We discuss these data in the 59 

    context of our current understanding of flavonoid and lipid metabolism as well as with 60 

    regard to improving human nutrition. 61 

    62 

    Keywords: Arabidopsis, Malonyl-CoA, Acety-CoA, phenylpropanoid, lipid, polyketide 63  64 

    65 

    INTRODUCTION 66 

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    Flavonoids are secondary metabolites involved in several physiological responses to 67 

    the environment, such as defense against herbivorous, UV radiation and pathogens 68 

    (Peters and Constabel, 2002; Foster-Hartnett et al., 2007; Agati and Tattini, 2010; 69 

    Schulz et al., 2015). They are ubiquitously distributed among plant species and act at 70 

    the intersection between primary and secondary metabolism (Alseekh et al., 2015; 71 

    Alseekh and Fernie, 2018). Flavonoid uptake in the diet is also associated with 72 

    health benefits for humans mostly due to their activity as antioxidants (Zhang et al., 73 

    2015; Zhao et al., 2016; Martin and Li, 2017; Tohge et al., 2017a), and this class of 74 

    molecules has recently been compellingly demonstrated to play an important function 75 

    in normal plant root development (Silva-Navas et al., 2016; Tohge and Fernie, 2016). 76 

    Taken together these observations render the comprehensive understanding of 77 

    flavonoid biosynthesis an important fundamental research aim. 78 

    The basic backbone structure of flavonoids is synthesized by a combination of the 79 

    phenylpropanoid and polyketide (or acetate) pathways, the former providing p-80 

    coumaroyl-CoA from phenylalanine while the latter provides malonyl-CoA for C2 81 

    chain elongation by chalcone synthase (CHS) (Winkel-Shirley, 2001, 2002; Tohge et 82 

    al., 2017b). Flavonoids are one of the major secondary products in the model plant 83 

    Arabidopsis (Arabidopsis thaliana) and research in this species has considerably 84 

    improved our understanding of this pathway (Saito et al., 2013). As a consequence of 85 

    this research, most of the structural and regulatory genes of the 86 

    shikimate/phenylpropanoid part of the pathway involved in their biosynthesis have 87 

    been well described (see Saito et al. (2013) for details). 88 

    Investigation of the transparent testa (tt) mutants of Arabidopsis demonstrated that 89 

    the regulation of flavonoid biosynthesis is strongly controlled at the transcriptional 90 

    level (Borevitz et al., 2000; Xu et al., 2015). Indeed three main classes of 91 

    transcription factors (TFs) were identified regulating anthocyanin and 92 

    proanthocyanidin biosynthesis: MYBs, bHLHs and WD40s, while so far only MYBs 93 

    were described to be involved in flavonol biosynthesis (Hichri et al., 2011). 94 

    Additionally, the different branches of flavonoid metabolism are described to be 95 

    regulated by specific TFs. In Arabidopsis, PAP1 (MYB75) and PAP2 (MYB90) are 96 

    regulators of anthocyanin structural genes (Borevitz et al., 2000; Zimmermann et al., 97 

    2004), MYB123 (tt2) is a seed-specific regulator of proanthocyanidin biosynthetic 98 

    genes (Nesi et al., 2001), and MYBs 11, 12 and 111 are regulators of flavonol 99 

    structural genes (Stracke et al., 2007). 100 

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    Despite these advances one of the biggest gaps still existent in this metabolic 101 

    network is the interplay of these pathways with primary metabolism. In particular the 102 

    mechanisms involved in the mobilization of primary resources towards flavonoid 103 

    biosynthesis remain relative poorly investigated. That said, some studies suggest that 104 

    its regulation is modulated by the very same TFs previously described above. 105 

    Interesting work on tomatoes (Solanum lycopersicum) overexpressing Arabidopsis 106 

    MYB12 under the control of a fruit specific E8 promoter (Luo et al., 2008), showed 107 

    that MYB12 is capable of binding to the promoters and inducing genes from primary 108 

    metabolism, including those encoding 3-deoxy-D-arabinoheptulosonate 7-phosphate 109 

    synthase (DAHPS), a rate limiting step in the shikimate pathway for phenylalanine 110 

    biosynthesis, and the plastidial enolase (ENO) (Zhang et al., 2015). The constantly 111 

    improving resources for co-expression analysis could assist the identification of new 112 

    candidate genes involved in supplying precursors, energy and reducing power for 113 

    secondary metabolism pathways (Yonekura-Sakakibara et al., 2008). Asides from 114 

    these avenues an interesting target for exploring the communication of central carbon 115 

    metabolism with flavonoid biosynthesis, also indicated by gene co-expression 116 

    analysis, is the ketoacyl-CoA thiolase KAT5. KATs are essential enzymes for the 117 

    conversion of lipids to acetyl-CoA in the peroxisomes through β-oxidation (Li-Beisson 118 

    et al., 2013). Interestingly, the expression of the cytosolic KAT5 was recently shown 119 

    to be highly co-related with genes involved in flavonol biosynthesis in several studies 120 

    (Germain et al., 2001; Carrie et al., 2007; Yonekura-Sakakibara et al., 2008; 121 

    Wiszniewski et al., 2012). It was, therefore, postulated that KAT5 may play a role in 122 

    the mobilization of carbon resources acting as part of a regulatory network directing 123 

    flux towards flavonoid biosynthesis. The production of malonyl-CoA in the cytosol 124 

    through carboxylation of acetyl-CoA by acetyl-CoA carboxylase (ACC) is additionally 125 

    postulated to be one of the essential substrates for flavonoid biosynthesis (Figure 1). 126 

    However, the regulation of its supply remains poorly investigated. In order to better 127 

    understand the role of the so called acetate pathway here we analyze the metabolic 128 

    phenotypes of a range of genotypes, covering the reactions linking acyl-CoA to 129 

    malonyl-CoA, that were identified within the co-expression network of KAT5 and 130 

    characterized flavonoid genes. Mutant lines were isolated either from knockout 131 

    collections or generated using the amiRNA strategy. Given the importance of this 132 

    pathway to both flavonoid and lipid metabolism we evaluated the levels of primary, 133 

    secondary and lipid metabolites in these lines as well as the expression levels of key 134 

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    structural genes of the flavonoid pathway. The collective results are discussed in the 135 

    context of our current understanding of both flavonoid metabolism and the interplay 136 

    of plant primary and specialized metabolism. 137 

    138 

    139 

    140 

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    RESULTS 141 Selection of candidate genes putatively involved in malonyl-CoA supply for 142 flavonoid biosynthesis 143 Co-expression network analyses previously performed by multiple groups have 144 

    highlighted the co-expression of a 3-ketoacyl-CoA thiolase isoform (KAT5) with 145 

    genes involved in flavonoid biosynthesis (Carrie et al., 2007; Yonekura-Sakakibara et 146 

    al., 2008). KAT is one of the core enzymes in peroxisomal β-oxidation catalyzing the 147 

    brake down of 3-ketoacyl-CoA to produce acetyl-CoA and a shorter acyl-CoA that 148 

    can re-enter the cycle (Li-Beisson et al., 2013). The Arabidopsis genome contains 149 

    three loci that encode KAT enzymes, annotated as KAT1, KAT2, and KAT5, with 150 

    KAT2 as the only one expressed at significant levels during seed germination in 151 

    Arabidopsis (Germain et al., 2001; Carrie et al., 2007; Li-Beisson et al., 2013). Both 152 

    KAT2 and KAT5 are conserved in higher plants and while the three isoforms from 153 

    Arabidopsis are localized to the peroxisomes, KAT5 is the only one exhibiting an 154 

    alternative transcript the product of which is targeted to the cytosol (Wiszniewski et 155 

    al., 2012). To evaluate the possible role of this enzyme in flavonoid metabolism, we 156 

    used the ATTED-II web platform (Kagaya et al., 2017) to select the top 50 genes of 157 

    highest correlation with KAT5. The pairwise correlation for all selected genes was 158 

    retrieved from ATTED-II and used for constructing the network depicted in Figure 2A 159 

    (Supplemental Dataset S1 and S2). Genes were classified based on their 160 

    annotations on TAIR (Berardini et al., 2015), and we could observe a clear 161 

    enrichment for genes functionally involved in flavonol and lipid metabolism. 162 

    Interestingly, a group of three genes among the co-expression network (ECH 163 

    [At1g06550], HCD [At1g65560] and ACC [At1g36160]) together with KAT5, included 164 

    all necessary enzymatic steps for the production of acetyl-CoA from activated Acyl-165 

    CoA and subsequent carboxylation to malonyl-CoA (Figure 1). Furthermore, putative 166 

    orthologs of all these genes exhibited increased expression levels in Del/Ros1 167 

    transgenic tomato lines in which ectopic fruit-specific expression of the snapdragon 168 (Antirrhinum majus) transcription factors Delila (Del, bHLH) and Rosea1 (Ros1, Myb) 169 

    led to the accumulation of flavonols and anthocyanins within the fruit (Tohge et al., 170 

    2015). In order to support our hypothesis, we also performed promoter analysis 171 

    including a 2.0 kbp region upstream to the transcription start site of each candidate 172 

    gene using the web resource PlantPAN 3.0 (Chow et al., 2018). This analysis 173 

    indicated the presence of putative flavonoid related MYB111 (PFG3) binding motif for 174 

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    all candidate genes (Figure 2B, Supplemental Table S1). Taken together, the 175 

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    structure of this network and candidate genes promoters suggest a regulatory 176 

    mechanism in which transcriptional activation of flavonoid biosynthesis is co-177 

    regulated with mobilization of the cytosolic acyl-CoA pool via its degradation into the 178 

    building block malonyl-CoA, a substrate for the production of the core flavonoid 179 

    aglycone narigenin by chalcone synthase. Additionally, the acetate pathway may be 180 

    regulated by the same transcriptional mechanism activating downstream flavonoid 181 

    specific genes, as well as the shikimate pathway involved in the production of 182 

    phenylalanine upstream to the phenylpropanoid branch of flavonoid biosynthesis 183 

    (Zhang et al., 2015). 184 

    185 

    Expression analysis of transgenic lines 186 In order to investigate the metabolic roles of these genes, we obtained T-DNA 187 

    mutants from the stock center (see Materials and Methods) and screened for 188 

    homozygous lines exhibiting reduced expression of the target genes. T-DNA lines 189 

    were obtained for ECH (ech1 and ech2), HCD (hcd1 and hcd2) and KAT5 (kat5-1). 190 

    Mutant lines disrupting ACC activity were previously shown to exhibit very strong 191 

    phenotypes including defective cotyledons, deformed leaves, short primary root and 192 

    impaired embryo morphogenesis and biosynthesis of the very-long-chain fatty acids 193 

    (VLCFA) associated with cuticular waxes and triacylglycerols (Baud et al., 2003; Lü et 194 

    al., 2011; Chen et al., 2017). These led to the conclusion that our difficulties in 195 

    acquiring homozygous T-DNA lines for this gene in particular was most probably due 196 

    to an embryo-lethal phenotype. There are, however, mutants containing reductions in 197 

    ACC activity that were only severe enough to cause a differential response under 198 

    stress conditions associated with a reduced capacity of providing malonyl-CoA, but 199 

    leading to no visible phenotype at normal growth conditions (Amid et al., 2012). 200 

    Therefore, we proceeded by generating multiple amiRNA lines in order to obtain ACC 201 

    genotypes exhibiting a less severe phenotype (acc1 and acc2). We also included the 202 

    generation of an additional amiRNA KAT5 (kat5-2) in order to proceed with the 203 

    further experiments on at least two independent lines for each candidate gene. 204 

    205 

    Gene expression analysis showed not only the decrease in expression levels of 206 

    targeted genes for each line but also of all other candidates and most flavonoid 207 

    related genes (Figure 3, Supplemental Dataset S3). Interestingly, whilst these results 208 

    are consistent with the co-expression between candidate genes and flavonoid related 209 

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    genes, it also suggests that acetyl-CoA and/or malonyl-CoA levels within the cytosol 210 

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    have a significant impact in the regulation of the whole pathway. Publically available 211 

    expression data (GEO Series accession number GSE 51215) for flavonoid mutants 212 

    tt4 and tt4xMYB12OX support this hypothesis (Nakabayashi et al., 2014). Both 213 

    genotypes exhibited reduced expression of several characterized flavonoid genes 214 

    including MYB111, MYB12, pap-1d, FLS, Fd3GT, F3RT and F7RT as well as KAT5. 215 

    216 

    Metabolite profiling of transgenic lines 217 Under normal conditions, Arabidopsis (ecotype Col-0) leaves constitutively 218 

    accumulates a number of flavonols, mainly kaempferol glycosides but also, albeit at 219 

    lower levels, quercetin glycosides (Saito et al., 2013). Several anthocyanins are also 220 

    produced, but are often detected exclusively upon certain stress conditions. The 221 

    major anthocyanin detected under normal conditions is a cyanidin glycoside 222 

    conjugated to p-coumaroyl, sinapoyl and malonyl moieties named anthocyanin A11 223 

    (Saito et al., 2013). As expected, metabolite profiling of mutant lines (Figure 4, 224 

    Supplemental Dataset S4, Supplemental Dataset S5 and Supplemental Dataset S6; 225 

    (Fernie et al., 2011)) showed a clear reduction for most flavonols as well as for the 226 

    major anthocyanin A11. Despite the fact that flavonol and anthocyanin biosynthesis 227 

    are regulated by different transcription factors, and that we observed mostly flavonol 228 

    specific genes within the co-expression network described here, such results are not 229 

    surprising when considering these two metabolic pathways still share exactly the 230 

    same precursors from central metabolism. More intriguing was the reduction 231 

    observed in the tryptophan derived indolic glucosinolates. This class of metabolites 232 

    has been shown to interact with phenylpropanoid metabolism possibly via the 233 

    interaction of indole-3-acetaldoxime, a precursor in indole glucosinolate biosynthesis, 234 

    and MED5, a member of the mediator complex and thereby a repressor of 235 

    phenylpropanoid metabolism (Kim et al., 2015). However, in the mutants studied 236 

    here, it seems more likely that downregulation of the shikimate pathway for 237 

    production of both phenylalanine and tryptophan is directly affecting the levels of the 238 

    precursors of both pathways. 239 

    In central metabolism, we observed a marked reduction of several amino acids, 240 

    sugars, and organic acids involved in the TCA cycle. Interestingly, we initially 241 

    expected to observe an increased flux through the portion of the TCA cycle providing 242 

    most of the cytosolic pool of acetyl-CoA, namely the export of citrate from the 243 

    mitochondria and subsequent conversion by cytosolic ATP-citrate lyase (ACL) 244 

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    (Fatland et al., 2005), in order to compensate for the reduction in acetyl-CoA. The 245 

    results observed here, however, are more similar to what would be expected from 246 

    oxidative stress, with an overall reduction of photosynthesis, glycolysis and the TCA 247 

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    cycle related metabolites and an increase of photorespiratory related metabolites 248 

    glycine and glycerate, pyruvate and alanine (Dumont and Rivoal, 2019). Moreover, it 249 

    has been shown that plants deficient in ACL activity unexpectedly exhibit a four-fold 250 

    increase in anthocyanin accumulation despite the considerable reduction in cytosolic 251 

    acetyl-CoA (Fatland et al., 2005), suggesting the regulation of acetyl-CoA production 252 

    for flavonoid biosynthesis may occur via a pathway other than the one the ACL 253 

    belongs to. Indeed, KAT5 appears among differentially expressed genes in 254 

    antisense ACL mutants (2.7 fold change [FC]), together with tt4 (5.0 FC) and F3H 255 

    (3.2 FC) (Fatland et al., 2005). Given these results we also measured the expression 256 

    of citrate synthase in order to compare the status of the TCA cycle in mutants versus 257 

    wild type. As we anticipated, we observed a reduced expression of genes encoding 258 

    both mitochondrial isoforms of this enzyme, CSY4 and CSY5 (Figure 3). 259 

    In summary, we observed a consistent decrease of flavonol accumulation across the 260 

    mutant lines, together with a reduction in other secondary metabolites sharing 261 

    precursors with the pathway. We could additionally observe extensive changes in 262 

    central metabolism, particularly in glycolysis and the TCA cycle intermediates, 263 

    suggesting increased oxidative damage in mutant lines. 264 

    265 

    Lipid profiling 266 Considering the obvious link between the candidate genes and acyl-CoA 267 

    metabolism, differences were expected from lipidomic analysis of these mutant lines. 268 

    Indeed, we could observe consistent changes in most classes of lipids detected 269 

    (Figure 5, Supplemental Dataset S7 and Supplemental Dataset S8; (Fernie et al., 270 

    2011)). For a more detailed description of the lipid metabolism of Arabidopsis we 271 

    refer to the literature (Chapman et al., 2013; Li-Beisson et al., 2013). In brief, fatty 272 

    acids are synthesized in the chloroplasts, where they may traffic between the plastid 273 

    stroma and the endoplasmatic reticulum (ER) where they are desaturated, converted 274 

    to acyl-CoA and released in the cytosol. This cytosolic pool of acyl-CoA, suggested 275 

    here to serve as a substrate for malonyl-CoA production, can also be incorporated 276 

    into membrane phospholipids and triacylglycerols (TGA) (Chapman et al., 2013). The 277 

    phospholipids detected in our experiments include phosphatidylcholine (PC), 278 

    phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS) 279 

    and phosphatidylglycerol (PG). PEs and PGs, exhibited few significant changes. PIs 280 

    were reduced for most mutants while both PCs and PSs were increased. Despite the 281 

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    reduction of PIs, it is tempting to speculate that the increase in PCs and PSs may be 282 

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    due to a lower consumption of the acyl-CoA leading to an increase in its available 283 

    cytosolic pool. Intriguingly, the levels of TAGs which also rely upon the cytosolic pool 284 

    of acyl-CoA, were drastically reduced. It is important to note that despite its essential 285 

    role in flavonoid biosynthesis, one of the most vital functions of cytosolic malonyl-CoA 286 

    is to provide the C2 building blocks for VLCFA elongation (Baud et al., 2003). These 287 

    acyl chains are further incorporated into TAG molecules, cuticle, waxes or 288 

    sphingolipids (Roesler et al., 1994; Baud et al., 2003). We do observe a significant 289 

    reduction in the levels of several of those TAGs which incorporate VLCFAs, in our 290 

    mutant lines. However, we also observe a reduction of those TAGs that do not 291 

    incorporate such VLCFAs. Possible explanations for this observation include that 292 

    TAG reserves may be reduced due to a reduction in carbon reserves or their 293 

    mobilization to produce citrate via peroxisomal β-oxidation (Pracharoenwattana et al., 294 

    2005). It is also relevant to note here, that we could not observe differences in one of 295 

    the main products of fatty acid synthesis, palmitic acid (Ohlrogge and Browse, 1995; 296 

    Burgos et al., 2011), suggesting that these phenotypes are not associated with an 297 

    impairment in chloroplast fatty acid production but are rather related to some 298 

    downstream factor, such as changes in lipid turnover or increased lipid peroxidation. 299 

    Finally, a behavior similar to that previously described in stress situations associated 300 

    with heat (Higashi et al., 2015) and dark (Burgos et al., 2011) could be observed for 301 

    the main galactolipids constituting the chloroplast membrane, namely an overall 302 

    decrease in DGDGs and increase in MGDGs. Again, we speculate this may be due 303 

    to a mild oxidative stress affecting the mutant lines. Additionally, DGDGs and SQDGs 304 

    accumulate on membrane remodeling following Pi deficiency. This is known to be 305 

    affected by changes in auxin signaling (Narise et al., 2010), a process in which 306 

    flavonols are also known to be involved in (Silva-Navas et al., 2016) establishing a 307 

    possible link between flavonol deficiency and a change in the membrane remodeling 308 

    capacity. 309 

    310 

    Metabolic correlation network 311 In order to aid visualization and summarize all the relevant metabolic results within 312 

    the context of flavonol accumulation, the correlation network in Figure 6 313 

    (Supplemental Dataset S9) was computed. This network is based on Spearman rank 314 

    correlation using an absolute threshold of 0.5 to establish edges between all 315 

    metabolites and detected flavonols. The resulting network, shows significant 316 

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    correlation between flavonoids and most of the metabolite classes previously 317 

    described. Interestingly, we observe not only the strong correlation with indolic 318 

    glucosinolates as previously described, but also with other secondary metabolites 319 

    that were not showing consistent significant changes across multiple mutant lines. 320 

    These include sinapic acid derivatives, sharing the phenylpropanoid branch with 321 

    flavonoid biosynthesis, and methylsulfinyl glucosinolates derived from methionine. 322 

    With regard to primary metabolism, the correlation of flavonols is particularly evident 323 

    with sugars but also with many amino acids including those associated with the 324 

    shikimate pathway as well as the TCA cycle derived glutamate. The only strong 325 

    negative correlation observed, was with alanine, which was increased in the mutant 326 

    lines. Interestingly, amongst the TCA cycle compounds, we did not observe a strong 327 

    correlation with citrate but only with oxoglutarate, malate and fumarate. Amongst the 328 

    lipids we could observe a strong correlation with several of the phospholipids derived 329 

    from cytosolic acyl-CoAs, as well as with many of the TAGs, particularly those 330 

    including VLCFAs, and a considerable number of the galactolipids MDGD and 331 

    DGDG. This analysis underscores the role of the acetate pathway at the interface of 332 

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    primary and flavonoid metabolism as well as being of, albeit more minor, importance 333 

    in lipid biosynthesis. 334 

    335 

    336 

    337 

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    DISCUSSION 338 Flavonoid biosynthesis is arguably one of the most well characterized plant 339 

    secondary metabolic pathways. Flavonoids are known to possess high nutritional 340 

    value due to their antioxidant activity and are conserved across higher plants (Tohge 341 

    et al., 2013; Martin and Li, 2017), attracting great attention from breeding and 342 

    metabolic engineering perspectives. Whilst intensive research in the last decades 343 

    generated vast knowledge regarding flavonoid biosynthesis and regulation, few 344 

    advances were made regarding its integration with primary metabolism. However 345 

    flavonoid biosynthesis, together with the rest of phenylpropanoid metabolism, 346 

    represents a significant sink of carbon resources for the plant (Saito et al., 2013), and 347 

    must be tightly connected to central metabolism. That said, recent work strongly 348 

    suggests that flavonoid related transcription factors do play a role in directing 349 

    resources from central metabolism towards flavonoid biosynthesis (Zhang et al., 350 

    2015). 351 

    Strategies for gene annotation based on co-expression network analysis following a 352 

    guilt-by-association approach (Usadel et al., 2009), tend to work particularly well for 353 

    genes and pathways that are transcriptionally regulated, hence the success of this 354 

    approach in identifying many secondary metabolism structural and regulatory genes 355 

    (Achnine et al., 2005; Tohge et al., 2005; Yonekura-Sakakibara et al., 2008; 356 

    Alejandro et al., 2012; Wisecaver et al., 2017). In this current study an investigation 357 

    of flavonoid co-expression network led to an interesting gene, KAT5 that is strongly 358 

    correlated to many flavonol specific genes. By expanding KAT5 co-expression 359 

    network, it became evident the enrichment of flavonol and fatty acid related genes, 360 

    strongly suggesting a link between fatty acid degradation and flavonol biosynthesis. 361 

    The roles associated with KAT5, ECH, HCD and ACC identified by this approach, fit 362 

    perfectly with the production of malonyl-CoA, one of the building blocks for the 363 

    backbone of flavonoids (Saito et al., 2013), from activated acyl CoAs via a process 364 

    similar to β-oxidation. From all of these genes, ACC is the only one with a clear 365 

    connection to flavonoid biosynthesis. ACC is described as the main source of 366 

    cytosolic malonyl-CoA, essential for many processes including long-chain fatty acid 367 

    biosynthesis, and flavonoid production (Baud et al., 2003; Amid et al., 2012; Chen et 368 

    al., 2017). It is interesting to note that the proposed pathway for malonyl-CoA 369 

    production seems to be specifically related to the flavonols and not to other 370 

    flavonoids such as anthocyanins, suggesting the regulation of this pathway by a 371 

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  • 18

    flavonol specific MYB TF (Tohge et al., 2005; Stracke et al., 2007). Considering the 372 

    pattern of accumulation in the different branches of the pathway, it is observed that 373 

    flavonols are constitutively accumulated in the leaves while anthocyanin 374 

    accumulation is usually induced by stress. These considerations allow us to 375 

    speculate that this alternative malonyl-CoA supply and its specificity towards 376 

    flavonols may be related to the different behaviors of each branch of the pathway and 377 

    their costs to central metabolism. 378 

    The results obtained for the mutants show a clear effect on flavonoid accumulation 379 

    with a consistent reduction of flavonol accumulation in all mutant lines. Changes in 380 

    other classes of secondary metabolites, namely anthocyanins and indolic 381 

    glucosinolates, were attributed to a reduction in the availability of substrates shared 382 

    by these pathways, including malonyl-CoA and the precursors of both phenylalanine 383 

    and tryptophan in the shikimate pathway. 384 

    Previous work overexpressing Arabidopsis MYB12 in tomatoes under the control of a 385 

    fruit specific promoter demonstrated clear changes in primary metabolism. This 386 

    included higher flux of carbon through glycolysis, the pentose phosphate pathway 387 

    and the TCA cycle, with a significant reduction in the content of major sugars and 388 

    increase in aromatic amino acids other than phenylalanine (Zhang et al., 2015). Their 389 

    data provides solid evidence of an important role of the reprograming of central 390 

    metabolism following the upregulation of flavonoid biosynthesis. The most marked 391 

    differences in primary metabolism observed in this work were the reductions in amino 392 

    acids, sugars and TCA cycle intermediates. Interestingly, the phenotype of these 393 

    mutants is far less severe than that observed following deficiency in expression of 394 

    ATP citrate lyase (Fatland et al., 2005) suggesting what was previously anticipated, 395 

    that this route of acetyl-CoA production is less crucial than that of the ATP citrate 396 

    lyase which recent studies have suggested as closely associated to the activity of the 397 

    TCA cycle via a thioredox-intermediated approach (Daloso et al., 2015). Indeed, our 398 

    results combined with previous observations on ATP citrate lyase (Fatland et al., 399 

    2005) unexpected over-accumulation of anthocyanins as well as the behavior of 400 

    central metabolism under oxidative stress, exhibiting reduction on glycolysis and TCA 401 

    cycle activity (Dumont and Rivoal, 2019), suggest this may be an alternative route to 402 

    sustain the synthesis of these anti-oxidant compounds even upon conditions of 403 

    stress in which the flux of acetyl-CoA from the TCA cycle is reduced. 404 

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  • 19

    This alternative supply of acetyl-CoA via acyl-CoA degradation, implies a significant 405 

    role of lipid metabolism, hence the alterations observed in lipid profiling were 406 

    expected. The accumulation of a cytosolic pool of acyl-CoAs is suggested to be a 407 

    limiting step in the biosynthesis of many lipids (Li-Beisson et al., 2013), and we 408 

    anticipated that a reduction on the mobilization of these substrates for acetyl-CoA 409 

    production would lead to an increase in its derived lipids. We did observe a significant 410 

    increase of PSs and PCs which are some of the main phospholipids produced from 411 

    cytosolic acyl-CoA, despite of the reduction in TAGs and PIs. It is important to notice 412 

    however, that many of the TAGs reduced are indeed product of VLCFAs that need 413 

    cytosolic malonyl-CoA for the acyl chain extension. Additionally, while TAGs are a 414 

    well described source of energy for germinating seeds via β-oxidation (Germain et 415 

    al., 2001), their role is not so well understood in leaves where some evidences 416 

    suggest their action as intermediates of membrane turnover during senescence and 417 

    in a mechanisms of excess acyl-CoA scavenging followed by peroxisome 418 

    degradation (Chapman et al., 2013). 419 

    Finally, the fact that no visible phenotype is discernible to the naked eye was 420 

    somewhat surprising for us because we had anticipated that the reason the acetate 421 

    pathway had not been identified as important for flavonoid metabolism in the mutant 422 

    screens which unraveled the phenylpropanoid pathway (Winkel-Shirley, 2001), meant 423 

    they resulted in lethality due to pleotropic effects on lipid or primary metabolism. This 424 

    is not the case however, it is important to note that there was no obvious alterations 425 

    on seed or leaf pigmentation. It remains to be seen, however, how they respond 426 

    under stress conditions where such changes may be more easily observed. 427 

    428 

    429 

    CONCLUSION 430 The results presented here support the hypothesis that the flavonoid regulatory 431 

    network is not only involved in activating flavonoid specific genes and mobilizing 432 

    primary substrates from the shikimate and phenylpropanoid pathways but it is also 433 

    able to regulate carbon flux through the much less studied acetate pathway. Our data 434 

    here experimentally confirm the operation of this pathway and validate the identity of 435 

    the genes which encode it in Arabidopsis. They additionally allowing the assessment 436 

    of its importance in flavonoid and lipid biosynthesis. In both cases it would seem to 437 

    be an important supporting pathway rather than the dominant pathway, however, 438 

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  • 20

    deficiency in this pathway does result in clear deficiencies of both flavonol and lipid 439 

    levels. In the case of lipids, the mechanism described is independent of the main 440 

    source of acetyl-CoA via the export of citrate from the TCA cycle to the cytosol and 441 

    the activity of ATP-citrate lyase. Hence, this pathway allows Arabidopsis to mobilize 442 

    alternative carbon resources from its acyl-CoA pool, and modulate flavonoid 443 

    concentration without compromising the low concentration and rapid turnover pool of 444 

    cytosolic acetyl-CoA, central for many other vital processes such as terpenoid 445 

    biosynthesis and VLCFA biosynthesis. 446 

    447 

    MATERIALS AND METHODS 448  449 Co-expression network analysis 450 Co-expression information for a network consisting of the top 50 genes of highest 451 

    correlation with KAT5 was obtained from ATTED-II (Kagaya et al., 2017). The 452 

    pairwise correlation for all selected genes was used for constructing the network 453 

    depicted in Figure 2A (Supplemental Dataset S1) where edges represent Spearman 454 

    rank correlation coefficients above a threshold of 0.55. Genes that were not 455 

    connected to any other node were omitted from the network. The results were 456 

    imported and manipulated in the software Cytoscape v 3.6.1 (Shannon et al., 2003). 457 

    458 

    Artificial microRNA (amiRNA) silencing 459 Oligonucleotides for multiple amiRNA silencing of KAT5 and ACC genes 460 

    (Supplemental Table S2) were designed using the web-tool WMD3 (Ossowski et al., 461 

    2008) available at http://wmd3.weigelworld.org/cgi-bin/webapp.cgi. The amiRNA 462 

    precursors were introduced by overlapping PCR into the plasmid pRS300 according 463 

    to the protocol available in the WMD3 webpage 464 

    (http://wmd3.weigelworld.org/downloads/Cloning_of_artificial_microRNAs.pdf) 465 

    (Schwab et al., 2006), with minor changes to include the sequences necessary for 466 

    further Gateway cloning. The final expression vectors were obtained by transferring 467 

    the multiple amiRNA precursor fragments into the destination vector pB7WG2 for 468 

    constitutive expression under the 35S promoter (Karimi et al., 2007). All constructs 469 

    were confirmed by DNA sequencing, transformed into Agrobacterium tumefaciens 470 

    competent cells GV3101 by electroporation (800 ohms; 1.8 kV, capacitance 25 μF) 471 

    and subsequently used for Arabidopsis (Arabidopsis thaliana) transformation via the 472 

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  • 21

    floral dip method (Clough and Bent, 1998). Transformed plants were selected in 473 

    media with hygromycin, and T3 plants were used for all further analysis. 474 

    475 

    Plant Material and Growth Conditions 476 Arabidopsis thaliana ecotype Columbia-0 (Col-0) plants were used as the wild-type 477 

    plant in this study. T-DNA mutants were purchased from NASC (Alonso et al., 2003). 478 

    At least two independent lines (T-DNA and/or amiRNA) were obtained for each of the 479 

    candidate genes. Plants were cultured on soil in growth chamber (Percival Scientific, 480 

    CU-36L4) for 35 days at 21oC in 8/16 h light and dark cycles with light intensity of 250 481 

    µE. After this period, 10 biological replicates of each line, constituted by the whole 482 

    rosette, were harvested, immediately frozen in liquid nitrogen and powdered in a ball 483 

    mill. 484 

    485 

    RNA Isolation and RT-qPCR 486 Total RNA was isolated from four biological replicates for each line using extraction 487 

    kit "Nucleospin® RNA Plant" (Macherey-Nagel; https://www.mn‐net.com/) and treated 488 

    with Turbo DNase (Invitrogen; www.thermofisher.com) to remove contaminating 489 

    DNA. RNA quantity was determined with a NanoDrop spectrophotometer (Thermo 490 

    Fisher; www.thermofisher.com), and cDNA was synthesized from 300 ng RNA using 491 

    Maxima First Strand cDNA Synthesis Kit (Thermo Fisher; www.thermofisher.com). 492 

    For RT-qPCR, cDNA equivalent to 5 ng total RNA was used as a template, and PCR 493 

    was performed with PowerSYBER® Green PCR Master Mix (Applied Biosystems; 494 

    www.thermofisher.com) and 250 nM of each primer (Supplemental Table S3) in a 495 

    total volume of 5 μL. Two technical replicates for each sample were analyzed in ABI 496 

    Prism 7900 HT sequence detection system (Applied Biosystems; 497 

    www.thermofisher.com) with the following cycling program: 2 min 50°C, 15 min 95°C, 498 

    45 cycles of 15 s at 95°C, and 1 min at 60°C. Primer pair efficiencies were calculated 499 

    by analyzing amplification curves from a standard cDNA dilution range. Expression 500 

    levels were calculated using 2–∆∆Ct method normalized to the mean transcript level of 501 

    ACT2, UBQ10 and GAPDH3Ꞌ. 502 

    503 

    Metabolite profiling 504 Metabolites were extracted for each one of the 10 biological replicates of leaf tissues 505 

    using a modified version of the protocol previously described by (Hummel et al., 506 

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  • 22

    2011). 50 mg of the frozen material were extracted with 1 mL of pre-cooled (−20°C) 507 

    extraction buffer (methanol/methyl-tert-butyl-ether [1:3, v/v] mixture, spiked with 0.1 508 

    μg/mL of PE 34:0 [17:0, 17:0], and PC 34:0 [17:0, 17:0] as internal standards). After 509 

    10 min incubation in 4°C and sonication for 10 min in a sonic bath, 500 μl of 510 

    water/methanol mixture spiked with 0.2 ug/mL of Ribitol and Isovitexin as internal 511 

    standards was added. Samples were centrifuged (5 min, 14 000 g) to separate the 512 

    lipophilic and polar phases. Aliquots of 150 μL from the lipophilic phase and 150 μL 513 

    and 300 μL from the aqueous phase were collected and dried under vacuum. The 514 

    dried lipophilic phase was suspended in 200 μl of Acetonitrile/isopropanol (7:3, v/v) 515 

    and used for lipid analysis according to (Hummel et al., 2011). The first aliquot of the 516 

    polar phase was derivatized and analyzed by GC-TOF-MS following the protocol 517 

    described by Lisec et al. (2006). The second aliquot was directly suspended in 80% 518 

    (v/v) Methanol:water and analyzed according to the protocol described by Tohge and 519 

    Fernie (2010). Secondary metabolism and lipids were analyzed exactly as described 520 

    in Garbowicz et al. (2018) 521 

    522 

    Statistical Analysis 523 All statistical analysis and plots were performed in R (R Development Core Team, 524 

    2010) using log-transformed data and the packages ggplot2 (Wickham, 2016), 525 

    ggpubr (https://CRAN.R-project.org/package=ggpubr) and pheatmap 526 

    (https://CRAN.R-project.org/package=pheatmap). Data normality was accessed by 527 

    Shapiro-Wilk test and by visual inspection of quantile-quantile plots. Outliers were 528 

    removed using the interquartile ranges for each metabolite and line. Two-tailed t-test 529 

    was performed to compare the differences between metabolites for each line against 530 

    the wild type. 531 

    532 Correlation network analysis 533 Metabolites correlation matrix was computed using the R package Hmisc 534 

    (https://CRAN.R-project.org/package=Hmisc). Spearman rank correlation was used 535 

    for calculating the correlations and an absolute value of 0.5 was set as a threshold to 536 

    establish an edge between two metabolites, the resulting network (Figure 6) was 537 

    represented using cytoscape v3.6.1 (Shannon et al., 2003). 538 

    539 Accession Numbers 540 

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  • 23

    The AGI locus numbers for the genes discussed in this article are as follows: ECH 541 

    (At1g06550), HCD (At1g65560), KAT5 (At5g48880), ACC (At1g36160), 542 

    PAP1/MYB75 (At1g56650), PAP2/MYB90 (At1g66390), MYB11 (At3g62610), MYB12 543 

    (At2g47460), MYB111 (At5g49330), CHS/TT4 (At5g13930), CHI/TT5 (At3g55120), 544 

    F3H/TT6 (At3g51240), F3'H/TT7 (At5g07990), FLS (At5g08640), UGT78D2/Fd3GT 545 

    (At5g17050), UGT78D1/F3RT (At1g30530), UGT89C1/F7RT (At1g06000), DFR/TT3 546 

    (At5g42800), ANS/TT18 (At4g22880). 547 

    548 

    Supplemental Data 549 Supplemental Table S1 – Promoter analysis 550 

    Supplemental Table S2– amiRNA oligo sequences 551 

    Supplemental Table S3 – RT-qPCR primer sequences 552 

    Supplemental Dataset S1 – Co-expression network edges 553 

    Supplemental Dataset S2 – Co-expression network annotations 554 

    Supplemental Dataset S3 – RT-qPCR raw data 555 

    Supplemental Dataset S4 – LC-MS metabolite reporting list 556 

    Supplemental Dataset S5 – GC-MS metabolite reporting list 557 

    Supplemental Dataset S6 – Metabolite data 558 

    Supplemental Dataset S7 – LC-MS lipid reporting list 559 

    Supplemental Dataset S8 – Lipid data 560 

    Supplemental Dataset S9 – Metabolite correlation network 561 

    562 

    563 Acknowledgements 564 LPS gratefully acknowledges the scholarship granted by the Brazilian National 565 

    Council for Scientific and Technological Development (CNPq) and support from the 566 

    Max Planck Society and IMPRS-PMPG program. 567  568 Figure Legends 569  570 Figure 1. Overview of flavonoid, lipid and acetyl-CoA metabolism in 571 Arabidopsis. Cell compartments represented include mitochondria (orange), 572 chloroplast (green), endoplasmic reticulum (yellow), peroxisome (blue), nucleus 573 

    (grey) and the cytosol (white). Enzymes in the pathway proposed in this work are 574 

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  • 24

    highlighted in red. Triacylglycerol (TAG), phosphatidylinositol (PI), 575 

    phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), 576 

    oxaloacetate (OAA), very long chain fatty acid (VLCFA), enoyl-CoA hydratase (ECH), 577 

    hydroxyacyl-CoA dehydrogenase (HCD), 3-ketoacyl-CoA thiolase (KAT5), acetyl-578 

    CoA carboxylase (ACC), ATP-citrate lyase (ACL), phenylalanine ammonia lyase 579 

    (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate:coenzyme A ligase (4CL) and 580 

    chalcone synthase (CHS). 581 

    582 Figure 2. Selection and analysis of candidate genes putatively involved in 583 malonyl-CoA supply for flavonoid biosynthesis. (A) KAT5 co-expression network. 584 Top 50 genes co-expressing with KAT5 were selected based on the highest 585 

    Spearman rank correlation coefficients obtained from the web platform ATTED-II 586 

    (Kagaya et al., 2017). A pairwise correlation threshold of 0.55 was applied as a cutoff 587 

    to establish the edges between pairs of nodes (genes). Genes that were not connect 588 

    to any neighbor within the network were excluded from further analysis. Highlighted 589 

    in green are characterized flavonoid related genes, in purple are lipid related genes 590 

    and in red are the candidate genes putatively involved in fatty acid degradation and 591 

    production of malonyl-CoA selected for functional characterization. (B) Promoter 592 

    analysis of candidate genes. A 2.0 kbp region upstream to the transcription start site 593 

    (TSS) of each candidate gene was analyzed using the web resource PlantPAN 3.0 594 

    (Chow et al., 2018). Grey diamonds indicate predicted flavonoid related MYB111 595 

    (PFG3) binding motifs. 596  597 Figure 3. Transcript levels of candidate genes and characterized flavonoid 598 genes in wild type and mutant lines. Transcript levels were determined by RT-599 qPCR and normalized to ACT2, UBQ10 and GAPDH3Ꞌ. Boxplots represent at least 600 

    three biological replicates, each with two technical replicates. Statistical significance 601 

    for two-tailed student´s t-test of each line relative to wild type is coded as p-values

  • 25

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    https://www.ncbi.nlm.nih.gov/pubmed?term=Achnine%2C L%2E%2C Huhman%2C D%2EV%2E%2C Farag%2C M%2EA%2E%2C Sumner%2C L%2EW%2E%2C Blount%2C J%2EW%2E%2C and Dixon%2C R%2EA%2E %282005%29%2E Genomics%2Dbased selection and functional characterization of triterpene glycosyltransferases from the model legume Medicago truncatula%2E The Plant Journal&dopt=abstracthttps://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Achnine,&hl=en&c2coff=1https://scholar.google.com/scholar?as_q=Genomics-based selection and functional characterization of triterpene glycosyltransferases from the model legume Medicago truncatula&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1https://scholar.google.com/scholar?as_q=Genomics-based selection and functional characterization of triterpene glycosyltransferases from the model legume Medicago truncatula&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Achnine,&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1https://www.ncbi.nlm.nih.gov/pubmed?term=Agati%2C G%2E%2C and Tattini%2C M%2E %282010%29%2E Multiple functional roles of flavonoids in photoprotection%2E New Phytologist&dopt=abstracthttps://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Agati,&hl=en&c2coff=1https://scholar.google.com/scholar?as_q=Multiple functional roles of flavonoids in photoprotection&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1https://scholar.google.com/scholar?as_q=Multiple functional roles of flavonoids in photoprotection&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Agati,&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1https://www.ncbi.nlm.nih.gov/pubmed?term=Alejandro%2C S%2E%2C Lee%2C Y%2E%2C Tohge%2C T%2E%2C Sudre%2C D%2E%2C Osorio%2C S%2E%2C Park%2C J%2E%2C Bovet%2C L%2E%2C Lee%2C Y%2E%2C Geldner%2C N%2E%2C 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