the acetate pathway supports flavonoid and lipid biosynthesis in … · intriguingly, not only...

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Short Title: The acetate pathway of flavonoid biosynthesis 1

Author for contact: Alisdair R Fernie and Takayuki Tohge 2

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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

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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

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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

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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

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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

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

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

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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

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There are no conflicts of interest. 42

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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

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

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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

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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

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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

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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

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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

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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

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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

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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



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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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



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



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



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



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



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 <= 602

0.0001 (****), 0.001 (***), 0.01 (**), 0.05 (*). 603

604

Figure 4. Primary and secondary metabolite profiling of candidate genes 605

mutant lines and wild type. Scales represent log2 fold change relative to the wild 606

type. Statistical significance for two-tailed t-test of each line relative to wild type is 607

25

coded as p-values <= 0.0001 (****), 0.001 (***), 0.01 (**), 0.05 (*). Heatmap was 608

produced using the function pheatmap in R. 609

610

Figure 5. Lipids profiling of candidate genes mutant lines and wild type. (A) 611

Profile containing all lipids belonging to the different classes. (B) Selected lipids 612

differentially accumulating in mutant lines. Scales represent log2 fold change relative 613

to the wild type. Statistical significance for two-tailed t-test of each line relative to wild 614

type is coded as p-values <= 0.0001 (****), 0.001 (***), 0.01 (**), 0.05 (*). Heatmap 615

was produced using the function pheatmap. Triacylglycerol (TAG), diacylglycerol 616

(DAG), phosphatidylinositol (PI), phosphatidylcholine (PC), 617

phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylglycerol (PG), 618

monogalactosyldiacylglycerol (MGDG), digalactosyldiacylglycerol (DGDG), 619

sulfoquinovosyldiacylglycerol (SQDG). The numbers in lipid name describe the fatty 620

acid chains on the lipid in the format [number of carbons in fatty acid chain]:[number 621

of double bonds in fatty acid chain] (unique numbering to distinguish isomers). 622

623

Figure 6. Metabolic correlation network. Correlation matrix was computed using 624

the R package Hmisc and represented using cytoscape v3.6.1 (Shannon et al., 625

2003). Nodes represent metabolites and edges represent pairs of metabolites with 626

spearman rank correlation above an absolute threshold of 0.5. Nodes color code 627

represent the different metabolite classes indicated within the figure. Edge colors 628

represent positive (blue) and negative (red) correlation coefficients between the pair 629

of metabolites. 630

631

632

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https://www.ncbi.nlm.nih.gov/pubmed?term=Karimi%2C M%2E%2C Depicker%2C A%2E%2C and Hilson%2C P%2E %282007%29%2E Recombinational Cloning with Plant Gateway Vectors%2E Plant Physiology&dopt=abstract

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the acetate pathway supports flavonoid and lipid biosynthesis in … · intriguingly, not only...

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