RUNNING TITLE CORRESPONDING AUTHOR 12 13 14 15 … · 27.04.2018 · 86 classes together with their precursors and metabolites, for the following reasons. 87 Phytohormones are naturally

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RUNNING TITLE 1

Multiple phytohormone screening method 2

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CORRESPONDING AUTHOR 5

Ondřej Novák 6

Laboratory of Growth Regulators, Centre of the Region Haná for Biotechnological and 7

Agricultural Research, Institute of Experimental Botany AS CR & Faculty of Science of 8

Palacký University, Šlechtitelů 27, CZ-78371 Olomouc, Czech Republic 9

E-mail: [email protected] 10

tel: +420585634853, fax: +420585634870. 11

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RESEARCH AREAS 15

Breakthrough Technologies 16

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Plant Physiology Preview. Published on April 27, 2018, as DOI:10.1104/pp.18.00293

Copyright 2018 by the American Society of Plant Biologists

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Plant hormonomics: multiple phytohormone profiling by targeted 18

metabolomics 19

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Jan Šimura, Ioanna Antoniadi, Jitka Široká, Danuše Tarkowská, Miroslav Strnad, Karin 21

Ljung, Ondřej Novák* 22

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Laboratory of Growth Regulators, Centre of the Region Haná for Biotechnological and 24

Agricultural Research, Institute of Experimental Botany, Czech Academy of Sciences, and 25

Faculty of Science, Palacký University, Šlechtitelů 27, CZ-783 71, Olomouc, Czech Republic 26

(J.Š., Ji.Š., D.T., M.S., O.N.); Department of Chemical Biology and Genetics, Centre of the 27

Region Haná for Biotechnological and Agricultural Research, Faculty of Science, Palacký 28

University, Šlechtitelů 27, CZ-783 71, Olomouc, Czech Republic (J.Š.); Umeå Plant Science 29

Centre, Department of Forest Genetics and Plant Physiology, Swedish University of 30

Agricultural Sciences, SE-90183 Umeå, Sweden (I.A., K.L.) 31

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ONE SENTENCE SUMMARY 33

A method for concurrent quantification of a large number of metabolites representing the 34

metabolic flux of seven major classes of plant hormones provides a simple and sensitive tool 35

for phytohormone studies. 36

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FOOTNOTES 38

List of author contributions 39

J.Š., I.A., K.L. and O.N. designed the study; J.Š., D.T. and O.N. participated in development 40

of the experimental protocol; J.Š. performed most of the experiments; J.Š., I.A. and Ji.Š. 41

analyzed data; J.Š. and O.N. wrote the article with contributions of all the authors; D.T., M.S., 42

K.L. and O.N. supervised the research. 43

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Funding information 45

This work was funded by the Internal Grant Agency of Palacký University (project no. 46

IGA_PrF_2018_023), the Ministry of Education, Youth and Sports of the Czech Republic 47

(National Program for Sustainability I, grant no. LO1204) and the Czech Science Foundation 48

(grant no. GA17-06613S). Support was also provided by the Swedish Governmental Agency 49

for Innovation Systems (Vinnova) and the Swedish Research Council (VR) to K.L. and I.A. 50



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* Address correspondence to [email protected] 52

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ABSTRACT 55

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Phytohormones are physiologically important small molecules, which play essential roles in 57

intricate signaling networks that regulate diverse processes in plants. We present a method for 58

the simultaneous targeted profiling of 101 phytohormone-related analytes from minute 59

amounts of fresh plant material (< 20 mg). Rapid and non-selective extraction, fast one-step 60

sample purification, and extremely sensitive ultra-high-performance liquid chromatography-61

tandem mass spectrometry (UHPLC-MS/MS) enable concurrent quantification of the main 62

phytohormone classes: cytokinins, auxins, brassinosteroids, gibberellins, jasmonates, 63

salicylates, and abscisates. We validated this ‘hormonomic’ approach in salt-stressed and 64

control Arabidopsis thaliana seedlings, quantifying a total of 43 endogenous compounds in 65

both root and shoot samples. Subsequent multivariate statistical data processing and cross-66

validation with transcriptomic data highlighted the main hormone metabolites involved in 67

plant adaptation to salt stress. 68

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INTRODUCTION 70

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During the last decade, techniques used in metabolomic analyses have advanced 72

tremendously. In plant science, the most widely used methods are based on separation by 73

liquid chromatography (LC) or gas chromatography (GC) combined with tandem mass 74

spectrometric detection (MS/MS). The main advantages of these combinations are high 75

sensitivity and versatility. To enhance signals of trace compounds, such as the plant hormones 76

(phytohormones) considered here, it is essential to reduce the influence of abundant 77

interfering compounds present in plant matrices by rigorous purification of extracts before the 78

instrumental analysis (Du et al., 2012). The sample preparation steps usually include solid-79

phase extraction (SPE) with general purpose sorbents or more selective immunosorbents that 80

specifically target the selected compounds (Pěnčík et al., 2009; Turečková et al., 2009; 81

Plačková et al., 2017; Oklestkova et al., 2017). Many analytical methods (particularly the 82

immunological methods) have been described for determination of a single compound or 83

specific class of phytohormones (Du et al., 2012; Tarkowská et al., 2014). However, there is 84

growing interest in methods capable of simultaneously analyzing phytohormones of several 85

classes together with their precursors and metabolites, for the following reasons. 86

Phytohormones are naturally occurring signaling molecules, which play key roles in 87

the regulation of plant physiology, development, and adaptation to environmental stimuli. 88

Generally, their concentrations in plant tissues are extremely low (fmol-pmol/g fresh weight, 89

FW). They are also exceptionally diverse compounds with wide ranges of physicochemical 90

properties, and are divided into several structural classes: cytokinins (CKs) and 2-methylthio 91

cytokinins (2MeSCKs), auxins (AXs), ethylene, gibberellins (GAs), abscisic acid and its 92

metabolic products (hereafter referred to as abscisates, ABAs), brassinosteroids (BRs), 93

jasmonates (JAs), salicylic acid (SA), and strigolactones (Davies, 2010; Zwanenburg et al., 94

2016). Their biological activities depend on their availability, which is controlled by their 95

biosynthetic and metabolic rates, cellular and subcellular localization, transport, and 96

responses of the signal perception and transduction pathways (Davies, 2010). Modulations at 97

any of these levels can directly affect myriads of physiological processes. Although certain 98

phytohormones are usually related to specific biological functions or responses, there is 99

increasing evidence that plant hormone signaling involves complex interactions (‘crosstalk’) 100

among all the pathways involved (Vanstraelen and Benková, 2012). Indeed, this is hardly 101

surprising as plants in natural environments may have to cope simultaneously with (for 102

example) salt, water and temperature stresses, pathogen attack, competition, and a need to 103



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complete certain physiological processes within environmentally-dictated timeframes. Thus, 104

plants’ physiological regulation involves challenging coordination of the biosynthesis, 105

transport, and metabolism of multiple hormones, their highly interacting signal transduction 106

pathways, transcription factors, and responsive genes. 107

Clearly, a convenient method to simultaneously quantify as wide a range as possible of 108

plant signaling molecules of all known classes would greatly facilitate the investigation of 109

hormone functions and networks. Thus, several plant hormone profiling techniques have been 110

published, and the number of covered compounds is increasing (Chiwoka et al., 2003; Pan et 111

al., 2008; Kojima et al., 2009; Farrow and Emery, 2012; Cao et al. 2016; Wang et al., 2017). 112

The most extensive analysis of primary and secondary metabolites published to date included 113

53 plant hormone-related compounds (Schäfer et al., 2016), and a more focused analysis of 114

plant growth substances covered 54 compounds (Cai et al., 2016). However, there is scope for 115

further extension. An ideal method should provide both a qualitative overview and precise 116

quantitative information for all covered compounds. It also requires appropriate sample 117

preparation and high instrumental performance (in terms of both robustness and sensitivity), 118

due to the low concentrations of phytohormones (relative to those of primary and secondary 119

metabolites) and wide ranges of chemical structure and stability. 120

Here we present a methodology with these features, designed to afford rapid, sensitive, 121

and simultaneous LC-MS/MS-based profiling of 101 CKs, AXs, GAs, BRs, ABAs, JAs, and 122

SA. The analytes include bioactive forms of the hormones, their precursors, and metabolites 123

to acquire quantitative snapshots of the physiological status of sampled tissues (Supplemental 124

Table S1). The protocol for isolating all 101 compounds combines rapid, one-step, non-125

selective extraction from milligram amounts of plant tissues (<20 mg FW) followed by their 126

LC separation and extremely sensitive MS-based quantification. To assess the practical utility 127

of this ‘hormonomic’ approach, the method was applied to characterize phytohormone 128

profiles in root and shoot tissues of control and salt-stressed Arabidopsis seedlings. Our 129

results highlight the value of such analysis, which (together with multivariate data analysis 130

and cross-validation with transcriptomic data), revealed the seedlings’ hormonal responses to 131

salinity stress – one of the major factors limiting crop production (Munns and Tester, 2008) 132

and differences in the responses of their roots and shoots. 133

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RESULTS 138

139

One-step extraction of distinct phytohormone classes 140

In an attempt to effectively extract targeted compounds and minimize the risk of their 141

decomposition by elevated temperatures and enzymatic degradation, the samples had to be 142

processed at the lowest temperature reliably above freezing (< 4°C) (Ljung et al., 2010). Plant 143

tissue was first homogenized and extracted with a suitable solvent in which the 144

phytohormones are soluble and chemically stable. Ice-cold acetonitrile (ACN) was chosen 145

here as the extraction solvent in accordance with several previously published studies dealing 146

with analyses of hydrophobic phytohormones, such as diterpenoid GAs (Urbanová et al., 147

2013) and triterpenoid BRs (Tarkowská et al., 2016). We tested aqueous water:ACN mixtures 148

with ACN contents ranging from 0 to 100% (vol/vol), focusing on the solubility of the most 149

hydrophobic compounds included in our study (Fig. 1). Further, to quantify impairment of the 150

final LC–MS/MS analysis by signal suppression, contents of the most abundant interfering 151

plant pigments, chlorophyll a (Chla) and b (Chlb), were determined. The solubility of all 152

investigated BRs (calculated as a percentage of maximal signal intensity) reached, on average, 153

95% in solvents with ≥ 50% ACN (vol/vol) (Fig. 1A); however, the concentration of 154

interfering plant pigments also rapidly increased with increases in ACN (Fig. 1B). Thus, ice-155

cold 50% ACN was selected as the optimal extraction solvent, providing the best balance 156

between signal intensity for selected phytohormones and chlorophyll co-extraction. 157

It was also essential to consider the chemical stability of the wide spectrum of targeted 158

analytes during sample preparation. For instance, GAs are pH-sensitive and should only be 159

exposed to solvents with pH 2.5 – 8.5 (Urbanová et al., 2013). To test the pH sensitivity of 160

our analytes, selected metabolites (Fig. 1C) were dissolved in different aqueous solutions of 1 161

M formic acid (pH < 3), 0.35 M NH4OH in 60% MeOH (vol/vol, pH > 12), or 50% ACN 162

solution (as a control); solutions that are often used in sample preparation of CKs and other 163

phytohormones during ion-exchange SPE (Dobrev and Kamínek, 2002; Kojima et al., 2009; 164

Záveská Drábková et al., 2015; Schäfer et al., 2016). A mixture with known amounts of each 165

compound (0.4 pmol of CKs and JAs, with 4 pmol of AXs and GAs) was incubated in each 166

solution for 15 min at 4°C. After evaporation under a gentle stream of nitrogen, samples were 167

dissolved in 30% ACN and analyzed by LC-MS/MS. The peak area of each compound 168

relative to corresponding peak’s area in control samples was then calculated (Fig. 1C). In the 169

case of the ammonium hydroxide solvent, levels of most of the tested compounds remained 170

close to those found in control samples, but in the acidic extraction solvent, the recoveries of 171



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GAs, JAs, and indole-3-acetic acid (IAA) amino acid conjugates were significantly lower 172

compared to control samples. To preserve the levels of all targeted compounds and limit their 173

possible structural changes and hydrolysis during sample preparation, cold extraction using 174

50% aqueous ACN with no additives was used in all subsequent phytohormone experiments 175

(see scheme in Fig. 1D). 176

177



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Reduction of a complex plant matrix by a highly efficient purification step 178

In the simultaneous analysis of phytohormones, several multistep SPE methods 179

combining the use of either silica-based reversed-phase (RP) sorbents with long 18-carbon 180

alkyl chains (C18) or polymer-based RP materials with ion-exchange properties (mixed-mode 181

sorbents) have proven efficacy for purifying samples and enrichment of the targeted analyte 182

fraction (Kojima et al, 2009; Balcke et al., 2012; Floková et al., 2014; Záveská Drábková et 183

al., 2015; Schäfer et al., 2016; Cao et al., 2016). These approaches often work with solvents 184

of various pH values, but (as mentioned above) the pH sensitivity of some of our analytes 185

limited the use of acidic conditions during sample preparation. Moreover, sample preparation 186

utilizing multiple step SPEs is very time consuming and often includes several evaporation 187

steps, which significantly reduce the effectiveness of sample preparation protocols, especially 188

for highly volatile compounds such as methyljasmonate or methylsalicylate (Floková et al., 189

2014). To avoid these problems, we used 50% ACN without any additives as both the sample 190

extraction and SPE loading solution (Fig. 1D), thus eliminating one evaporation step, 191

reducing the effects of the plant matrix, and minimizing losses caused by enzymatic 192

degradation and pH-dependent hydrolysis. To remove co-extracted plant pigments with 193

maximum efficiency while maintaining high analyte recovery, we utilized RP polymer-based 194

SPE Oasis HLB columns, which are packed with a hydrophilic-lipophilic-balanced (HLB) 195

water-wettable sorbent. Recoveries following this purification step were studied using 196

extracts from 20 mg FW of Arabidopsis plant material supplemented with authentic 197

phytohormone standards before and after SPE purification steps (Caban et al., 2012; see 198

Materials and Methods). The HLB sorbent was used to retain possible interfering compounds 199

while targeted compounds passed through the SPE column sorbent in the loading step (the 200

flow-through fraction) or were subsequently eluted with 30% ACN (vol/vol). These fractions 201

were pooled, and average total extraction yields per class ranged from 87 to 97%, except for 202

BRs, which averaged 52% (Table 1 and Supplemental Table S2). Samples were further 203

evaporated under a gentle stream of gaseous nitrogen and then dissolved in 40 µl of 30% 204

ACN prior to LC-MS/MS analysis (Fig. 2). 205

206

Profiling of 101 phytohormone-related compounds by ultrafast LC-MS/MS 207

One of the main inherent difficulties in profiling more than 100 plant hormones 208

(Supplemental Table S1) is that many of the compounds have similar core structures, 209

including isomers with the same MS fragmentation patterns (e.g. cis- and trans-zeatin, topolin 210

isomers, brassinolide and 24-epibrassinolide, castasterone and 24-epicastasterone). To 211



9

optimize baseline separation, we tested two RP ultra-high performance liquid chromatography 212

(UHPLC) columns packed with charged-surface hybrid (CSH) and ethylene-bridged hybrid 213

(BEH) polymer-based sub-2 μm sorbents. In good agreement with previously reported results 214

(Urbanová et al., 2013; Floková et al., 2014), the CSH column provided better peak shapes 215

and peak-to-peak resolution of the above-mentioned isomeric compounds than the BEH 216

column (Fig. 2A). The composition of the mobile phase and use of different mobile phase 217

additives strongly influenced the separation, peak shape, and analyte ionization. Cao et al. 218

(2016) found that increasing the concentration of formic acid in the range from 0.05 to 0.2% 219

impaired CK separation. Confirming this trend, we investigated separation of CKs using 220

0.001, 0.01, and 0.1% formic acid. However, the optimal baseline separation of CK isomers 221

was achieved on the CSH column using isocratic elution with 0.01% formic acid in both 222

mobile phase solutions (water and ACN) (Fig. 2B). 223

Retention times of the 101 targeted compounds were further determined by separate 224

injections and compared with those of 74 stable-isotope-labelled standards (Supplemental 225

Table S3). Each non-labelled and stable-isotope-labelled couple co-eluted with the same or 226

almost identical retention time, although deuterated analogues usually eluted slightly earlier 227

than corresponding authentic standards due to the chromatographic isotope effect (Pratt, 228

1986). Under our chromatographic conditions, the monitored compounds were eluted from 229



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1.28 to 14.47 min with good reproducibility of retention times below 2% (except 3.4% for the 230

most polar compound tryptamine; see Supplemental Table S4). Not all compounds were 231

separated to baseline (Fig. 2), but their determination in multiple-reaction-monitoring (MRM) 232

mode allowed precise detection due to specific precursors to product ion transitions in the 233

fragmentation of co-eluting compounds (see Supplemental Table S3). Appropriate precursor 234

ions ([M+H]+ or [M-H]–) and the most abundant product ions for each compound were 235

carefully selected, partly for this purpose. The metabolites of CKs, 2MeSCKs, AXs, BRs, and 236

some JA precursors and its amino acid conjugates were determined in positive ESI(+) mode, 237

which provided good agreement with previously published data (Tarkowski et al., 2010; 238

Novák et al., 2012; Svačinová et al., 2012; Floková et al., 2014; Tarkowská et al., 2016). All 239

other phytohormones (including ABAs, GAs, SA, and JAs) were determined in negative 240

ESI(–) mode (Turečková et al., 2009; Urbanová et al., 2013; Floková et al., 2014). Finally, the 241

collision energy and cone voltage were optimized to maximize signal intensities. The 242

optimized MS conditions are listed in Supplemental Table S3. Under these parameters, limits 243

of detection (LODs) for the 101 targeted plant hormones and their metabolites ranged from 244

0.005 fmol for 2MeSCK ribosides to 50 fmol for 12-hydroxy-jasmonic acid. The LODs and 245

limits of quantification (LOQs) were experimentally determined and defined as 3 and 10 246

times the noise level, respectively (for details see Table 1 and Supplemental Table S2). 247

The proposed method was initially designed for simultaneous analysis of positively 248

and negatively charged ions, utilizing both MRM modes (polarity switching) in single 249

analytical run. However, the ESI(–) mode is known to be generally less sensitive than the 250

positive mode, and polarity switching for simultaneous analysis of 101 phytohormones caused 251

further 4- to 12-fold reductions in signal intensity of negatively charged compounds (see 252

Supplemental Fig. S1). Instrument performance declined due to duty cycle problems, and the 253

few milliseconds required for signal recovery after every such switch. Moreover, the 254

acquisition rate in MRM modes is also determined by the dwell time, which is the amount of 255

time spent collecting a data point at a set transition or peak before switching to the next value 256

in the MRM method (O'Mahony et al., 2013). Therefore, to improve the sensitivity of MS-257

based detection, samples were analyzed in two separate runs under the same chromatographic 258

conditions, with the flow rate set to 0.5 ml min-1 and the column temperature to 50°C. Under 259

these conditions, UHPLC-ESI-MS/MS analysis of the targeted compounds in one sample 260

takes 32 min in total (Fig. 2, C and D). To further increase the duty cycle, and thus potentially 261

the signal intensity, the 17- and 15-min chromatographic separations of the targeted analytes 262

in ESI(+) and ESI(–) modes, respectively, were both divided into nine MRM scan segments. 263



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Calibration curves constructed after repeatedly injecting standard solutions revealed a 264

broad linear concentration range for most compounds, spanning at least three orders of 265

magnitude with R2 values ≥ 0.993 (Supplemental Table S3). The method sensitivity and 266

linearity were found to be comparable to those reported by authors using tandem mass 267

spectrometry for simultaneous phytohormone analysis (Kojima et al., 2009; Balcke et al., 268

2012; Floková et al., 2014; Záveská Drábková et al., 2015; Cai et al., 2016; Schäfer et al., 269

2016; Delatorre et al., 2017). 270

271

Method validation 272

Using the standard isotope dilution method, concentrations of all the analytes were 273

calculated as ratios of non-labelled compounds to labelled internal standards (IS) or closely 274

eluting stable isotope-labelled tracers (Supplemental Table S3). To validate the UHPLC-275

MS/MS method, spiked Arabidopsis seedling extracts were analyzed, and the endogenous 276

levels were subtracted from the amounts of non-labelled standards added (see Materials and 277

Methods). Finally, the calculated concentrations of each analyte were compared with the 278

known amounts added to samples and are presented as method accuracy, ranging in average 279

from 5.2% bias (JAs) to 8.68% bias (SA). Method precision was calculated as the relative 280

standard deviation (RSD) of analyte concentrations determined in three replicates. The 281

precision ranged, on average, from 1.06% RSD (ABAs) to 7.8% RSD (BRs) (Table 1; for 282

details see Supplemental Table S2). Furthermore, the reproducibility test of the LC-MS/MS 283

method was also performed by re-injection of standard mixtures prepared in low, medium, 284

and high concentrations of targeted compounds in a four-orders-of-magnitude range (see 285

Supplemental Table S4). Solutions kept in the autosampler at 4°C were analyzed in triplicate 286

on three consecutive days. For three concentration levels of the 101 targeted compounds, the 287

RSD values of analyte responses were below 15% (Supplemental Table S4). Moreover, the 288

intra- and inter-day precisions of the analytical method were quantified by evaluating the 289

closeness of a set of analytical results obtained for a series of replicate samples and was 290

expressed in terms of the RSD for those measurements. For endogenous phytohormones 291

determined in 20 mg FW of 10-day-old Arabidopsis seedlings, the intra- and inter-day 292

precisions ranged from 0.6 to 10.5% and 1.3 to 17.3%, respectively (Supplemental Table S5). 293

The overall validation parameters of the developed method demonstrate its reliability and 294

utility for simultaneous quantification of multiple classes of phytohormones in minute 295

amounts of plant material. 296

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Phytohormone quantification in plants under salinity stress 298

To assess the applicability of the newly-developed, targeted metabolomics approach, 299

we used it in a comparison of hormone-related transcript and metabolite levels in samples of 300

root and shoot tissues (<20 mg FW) of stressed Arabidopsis plants and controls. Published 301

microarray data sets were screened to identify a stimulus that affects genes involved in most 302

phytohormone metabolic pathways (Fig. 3 and Supplemental Table S6). This bioinformatics 303

analysis was performed in an unsupervised manner (without checking for up- or down-304

regulation). Salinity stress was identified as an appropriate condition, which is likely to cause 305

major alterations in metabolite levels of most hormones and corresponding changes in 306

transcript profiles (Fig. 3B). 307

We therefore conducted a salinity stress experiment, where we gently transferred 12-308

day-old Arabidopsis seedlings to new media with and without 150 mM NaCl for an additional 309

48 hours. Shoots and roots were harvested separately, and their hormonomic profiles were 310

examined (Supplemental Table S7). To show peak shapes, peak retentions compared to 311

appropriate internal standards, and signal intensities of endogenously determined 312

phytohormones, we presented representative chromatograms of treated Arabidopsis root 313

samples (Supplemental Fig. S2 and S3). Moreover, the univariate scatterplots of endogenous 314

phytohormone levels provides information about the distribution of phytohormone levels in 315

salt-stressed and control Arabidopsis seedlings under our experimental conditions 316

(Supplemental Fig. S4). In total, 45 endogenous compounds out of the 101 phytohormone-317

related analytes were detected in both root and shoot samples. Two BRs (24-epiBL and 28-318

norCS) were identified, but their levels were sub-LOQ. Thus, they were omitted in 319

subsequent statistical data analysis. According to Student’s t-test, levels of 23 of 43 320

determined compounds significantly differed between samples of roots of salt-stressed and 321

control seedlings (Fig. 4E), and levels of 15 compounds differed between their respective 322

shoots (Fig. 4F). In addition, multivariate statistical analysis revealed clear separation 323

between the hormone profiles of root and shoot samples, and between the profiles of control 324

and salt-stressed seedlings (Fig. 4B). Orthogonal projections to latent structures discriminant 325

analysis (OPLSDA)-based S-plots revealed compounds that were strongly affected by salinity 326

stress, and thus were primarily responsible for the latter separation (Fig. 4, C and D). 327

The hormonomic results were further cross-validated by comparing the transcriptomic 328

data (Fig. 3, C and D; Supplemental Tables S8 and S9) and hormonal profiles (Fig. 4, E and 329

F). ABA and JA, often referred to as plant stress hormones, have been previously shown to 330

promote salt tolerance (Ryu and Cho, 2015). Accordingly, salt stress was associated with 331



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increases in levels of ABA, its oxidation products phaseic acid (PA) and dihydrophaseic acid 332

(DPA), and JA in roots, together with up-regulation of JA biosynthesis and ABA biosynthesis 333

and oxidation genes. Similar correspondence was found between GA metabolite and 334

transcript profiles, and differential responses of the active GA4 to salt stress in shoots and 335

roots. GA biosynthesis and inactivation genes (KO and GA2ox, encoding ent-kaurene oxidase 336

and gibberellin 2-oxidase, respectively) were induced in both tissues under salt stress. 337

However, GA3ox, catalyzing the last biosynthetic step of bioactive GAs, was only induced in 338

shoots, in accordance with an observed increase in GA4 concentration in this tissue. By 339

contrast, auxin and CK metabolite outputs showed a more dynamic balance that could not be 340



14

readily linked to changes in expression profiles of genes involved in their biosynthesis and 341

metabolism under salinity stress. These findings suggest that physiological responses to 342

stimuli such as salinity are not controlled solely by a single active form of a hormone (or even 343

single active forms of several hormones), but by the combined activities and ratios of multiple 344

hormones, metabolites, and (hence) genes. Our hormonomic analysis and the cross-validation 345

with transcriptomic data highlight the value of such profiling methods, which provide potent 346

tools to assess not only transcript levels but also levels of corresponding metabolites in 347

samples, thereby obtaining global views of hormonal responses and interactions. 348

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350

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DISCUSSION 352

353

Recent technical advances in analytical methods have helped to detect more hormone 354

metabolites (precursors, catabolites, and conjugates) in one sample and thus to obtain 355

information about the overall pattern of the hormone metabolome (Novák et al, 2017). We 356

present here a ‘plant hormonomics’ technique involving a non-selective extraction and SPE 357

purification followed by high-throughput UHPLC-ESI-MS/MS separation and analysis for 358

profiling 101 phytohormones and their metabolites in a single plant sample (Supplemental 359

Table 1). Several challenges were addressed during its development and should be considered 360

in any attempts to establish such techniques. First, use of an appropriate extraction solvent is 361

crucial to minimize possible enzymatic degradation, reduce levels of interfering substances, 362

and efficiently extract the analytes from plant tissues (Hoyerová et al., 2006). This poses a 363

dilemma because increasing concentrations of organic solvents, such as methanol, ethanol, 364

acetonitrile, isopropanol, and chloroform (singly or in various combinations), generally 365

increases the extraction efficiency of both the analytes and interfering substances (e.g. 366

pigments, proteins, phenolics, or lipids). Such ballast compounds increase background noise, 367

detection limits, risks of analytes co-eluting with other substances, and fouling of the 368

instruments (Tarkowská et al., 2014). Thus, at least one purification step before final MS-369

based analysis is desirable, or even essential for high-throughput analyses (Nováková and 370

Vlčková, 2009). The risk of enzymatic or chemical breakdown of the analyte can also be 371

minimized by performing the extraction at low temperatures (Ljung et al, 2010); however, the 372

effect of this on the extraction and determination of phytohormones were not assessed herein. 373

Therefore, our protocol includes extraction of samples with an optimized solvent (ice-cold 374

50% aqueous ACN) and purification of the extracts by one-step, non-selective, reversed-375

phase SPE (Fig. 1). Acetonitrile-based extraction is frequently used in non-targeted 376

metabolomic analysis (Hyötyläinen, 2013). The relatively high polarity of acetonitrile may be 377

less suited for nonpolar substances, although the acetonitrile aqueous solution has been used 378

as an extraction solvent in methods dedicated to analyses of GAs and BRs (Urbanová et al., 379

2013; Tarkowská et al., 2016). Moreover, to prevent pH-dependent hydrolysis and/or other 380

structural changes that may occur during extraction (Novák et al., 2012), we have avoided use 381

of acidified solvents during sample extraction and purification. Based on the results of our 382

method validation, ice-cold ACN-based extraction combined with the stable isotope dilution 383

method enables efficient control of hormone losses during sample extraction and 384

homogenization. After applying 74 internal standards added before homogenization, the 385



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phytohormone levels of spiked Arabidopsis samples were recovered in the range 85.3-114.4% 386

(see Supplemental Table S2). To produce adequate and precise results, the IS-based 387

correction is therefore effective for different hormone-metabolizing activities. In addition, 388

rapid extraction and purification methods can also minimize a risk of analyte degradation or 389

readsorption onto the matrix (Albaseer et al., 2010). 390

LC was selected partly because most known phytohormones are non-volatile 391

compounds that require chemical derivatization for GC- (but not LC-) MS-based multi-392

targeted profiling (Müller et al., 2002; Birkemeyer et al., 2003). The increasing availability of 393

chromatographic columns with diverse physicochemical properties has also significantly 394

improved the versatility of LC techniques. Furthermore, the rapid development of ultra-high 395

performance liquid chromatography (UHPLC), using columns with sub-2 μm particles, has 396

greatly improved separation, resolution, sensitivity, and overall speed of LC-based analytical 397

methods (Nováková, 2013). Thus, LC is now the most robust, convenient, and widely utilized 398

technique for simultaneous phytohormone analysis (Kojima et al., 2009; Müller & Munné-399

Bosch, 2011; Balcke et al., 2012; Floková et al., 2014; Záveská Drábková et al., 2015; Cai et 400

al., 2016; Cao et al., 2016; Schäfer et al., 2016; Delatorre et al., 2017; Wang et al., 2017). 401

Furthermore, compound determination based on specific MRM with a combination of known 402

retention times of the targeted compounds and its stable isotopically labelled IS provide a 403

reliable tool for compensation of losses during extraction or matrix effect, and are used 404

widely as such throughout the LC-MS/MS plant hormone analyses (Tarkowská et al., 2014). 405

Combining one-step, non-selective SPE with optimized UHPLC-MS/MS, including use of a 406

1.7-µm particle size mix-mode hybrid C18 column, enabled sensitive and selective 407

quantification of 101 underivatized phytohormones and related compounds in two 408

independent 17-min ([M+H]+) and 15-min ([M+H]-) chromatographic runs without 409

positive/negative polarity switching (Fig. 2). 410

As mentioned above, the LC-MS/MS method was originally established for 411

simultaneous analysis operating in both modes; however, analysis of plant hormones requires 412

high sensitivity due to the very low amounts of some hormones in plant tissues. The 413

application of separate polarity modes indeed provided us with higher signal intensity, up to 414

12-fold in ESI(–) (see Supplemental Fig. S1). This may be due to the use of a longer dwell 415

time and final reduction of the overall cycle time for each MRM scan (O'Mahony et al., 416

2013). In our method, the dwell times in negative ESI(–) modes of polarity switch- and 417

nonswitch-based approaches were in the range of 8-20 ms and 20-100 ms, respectively. Dwell 418

time also represents a compromise between the signal-to-noise (S/N) ratio and the number of 419



18

data points actually needed to define a chromatographic peak (Maštovská and Lehotay, 2003). 420

Increasing the number of data points improves the S/N ratio but also increases the scan cycle 421

time resulting in the reduction of MS signal (Hird et al., 2014). Further, time-sectoring is 422

another important factor when setting up LC–MS/MS methods (O'Mahony et al., 2013). 423

Splitting of the chromatographic run into more scan windows could also help to increase the 424

sensitivity. Under our chromatographic conditions, the MRM channels were time-sectored to 425

increase the cycle time for each analyte and acquire at least 15 data points across a 426

chromatographic peak to ensure reliable integration. Finally, nine time-scan segments were 427

used for analysis of the same samples in positive and negative ion modes compared to twelve 428

scan windows in the method utilizing polarity switching in a single analytical run. 429

Given the very low amounts of some hormones in plants, the risk of false positive is 430

extremely high and one should ensure unambiguous detection of the analytes of interest 431

without any interference by other matrix compounds. The following quality criteria were used 432

to ensure correct identification and quantification of the targeted compounds: (i) the retention 433

times should match those of the standard compounds below 2% RSD, (ii) the intensity ratio of 434

the selected MRMs should be within ± 15% of that observed fort the standard compounds, 435

and (iii) the S/N ratios should be greater than 3:1. We previously showed the positive effect of 436

small amounts of plant tissue on IAA recovery using silica (C8) or polymer-based (HLB) SPE 437

columns (Novák et al., 2012). This result suggests a reduction in the matrix effect depending 438

on the increasing amount of fresh weight. Our general purification method is able to separate 439

a broad range of phytohormone metabolites from small amounts of tissue (20 mg FW). 440

However, not all targeted compounds are present in every plant tissue or plant species, even if 441

their actual levels could still be below the limit of detection of the presented method. As 442

shown in Table 1 and Supplemental Tables S2-S5, the method combining micro-extraction 443

and purification prior to UHPLC-ESI-MS/MS analysis shows good performance with respect 444

to all the validation parameters tested. The measured coefficients were mostly within 15% of 445

the nominal values, meaning that the method’s reproducibility, repeatability, accuracy, and 446

precision are consistent with the typical validation parameters and the requirements of 447

bioanalytical methods (Nováková, 2013). 448

The optimized method was applied to the phytohormone profiling of Arabidopsis 449

plants grown under salt stress and control conditions. In total, 43 phytohormones and their 450

metabolites in single plant samples were quantified simultaneously (Supplemental Table S7 451

and Supplemental Fig. S4). Uni- and multi-variate analysis of the acquired data revealed 452

significant differences in profiles of these compounds between roots and shoots, and between 453



19

controls and salt-stressed plants (Fig. 4). The analysis also revealed compounds primarily 454

responsible for the significant differences in profiles (Fig. 4, E and F), which mostly 455

corresponded well with transcriptomic data (Fig. 3, C and D). The cross-validation of the 456

hormonomic results with salt-stress-induced changes in gene expression thus highlights the 457

potential of this technique in unravelling the network of plant hormone signaling cascades. 458

In summary, our method for phytohormone profiling provides a simple, sensitive, and 459

powerful tool for phytohormonal studies. The validation experiments, in conjunction with the 460

demonstration of the hormonomic method’s accuracy and precision, confirm its reliability and 461

utility for routine quantifications of phytohormones in minute amounts of plant tissue. LC-462

MS/MS-based methods were already used to quantify phytohormone classes in carefully 463

collected material such as plant organs and specific organ parts (e.g. root apex (Plačková et 464

al., 2017), isolated cells (Petersson et al., 2009; Jin et al., 2013; Pěnčík et al., 2013; Antoniadi 465

et al., 2015), or even organelles (Ranocha et al., 2013; Jiskrová et al., 2016). In the future, 466

such material could also be used in the hormonomic analysis. Thus, the combination of 467

precise sample preparation (using, for example, fluorescence-activated cell sorting or laser 468

microdissection (Immanen et al., 2016)) with sensitive analysis will also yield more precise 469

information about the localization of determined compounds and their function. 470

471

472

MATERIALS AND METHODS 473

474

Chemicals and material 475

Authentic standards and their isotopically-labelled counterparts are listed in 476

Supplemental Table S1). Cytokinins, auxins, gibberellins, jasmonates, salicylic acid, abscisic 477

acid, phaseic acid, brassinosteroids, and their corresponding isotopically-labelled analogues 478

were purchased from Olchemim Ltd. (Olomouc, Czech Republic) and Chemiclones 479

(Waterloo, Canada), dihydrophaseic acid, neophaseic acid, 7-hydroxy-abscisic acid, and their 480

corresponding isotopically-labelled analogues were obtained from the compound library of 481

the Laboratory of Growth Regulators (Olomouc, Czech Republic; Turečková et al., 2009). 482

Formic acid (FA), acetonitrile (ACN, hypergrade for LC-MS), and methanol (MeOH, 483

hypergrade for LC-MS) were purchased from Merck (Darmstadt, Germany). Deionized 484

(Milli-Q) water was obtained using a Simplicity 185 water system (Millipore, Bedford, MA, 485

USA) and used to prepare all aqueous solutions. 486



20

487

Plant material and salinity stress experiment 488

Arabidopsis thaliana (ecotype Col-0) was used for method validation and the salt 489

stress experiments. Seedlings were grown vertically in Petri dishes in standard Murashige and 490

Skoog media in a growth chamber under long-day conditions at a light intensity of 100 µEm-2 491

s-1 (16 h light, 24°C/8 h dark cycles, 18°C) for 10 and 12 days. On the 12th day, plants 492

assigned to the salt stress treatment were transferred to new medium supplemented with 150 493

mM NaCl (8.77 g/l) prior to autoclaving, and seedlings were grown vertically for an 494

additional 48 hours. Control seedlings were grown in the same way and transferred during the 495

12th day to standard Murashige and Skoog medium. On the 14th day, seedlings of both sets 496

were harvested, shoots and roots were separated, weighed into micro tubes, immediately 497

frozen in liquid nitrogen, and stored at - 80°C until extraction and analysis. 498

499

Solubility experiment 500

The solubility of selected brassinosteroids (Supplemental Table S10) was tested by 501

adding 40 µl portions of aqueous ACN, with concentrations ranging from 10 to 70% 502

(vol/vol), to mixtures containing 50 pmol of each of the compounds in solid state. The 503

samples were thoroughly mixed by sonication for 5 min at 4°C in a Transsonic T310a 504

laboratory ultrasonicator with an ice block-filled bathtub (Elma GmbH & Co KG, Singen, 505

Germany), then filtered using modified nylon 0.2 µm Centrifugal Filters (VWR International, 506

Czech Republic). Portions (20 µl) of the filtrates were transferred to new insert-equipped vials 507

and analyzed by UHPLC-ESI-MS/MS (2 µl/injection). Finally, average peak areas of each 508

compound extracted in each solvent and relative yields (percentages of average peak areas in 509

each solvent relative to those obtained using the most effective tested solvent) were 510

calculated. 511

512

Chlorophyll extraction 513

Chlorophyll a (Chla) and b (Chlb) were extracted from 100 mg FW samples of 514

Arabidopsis seedlings using 1 ml of aqueous ACN at concentrations ranging from 10 to 100% 515

(vol/vol) (n=4, extraction solvent). After extraction and removal of solid particles by 516

centrifugation (20,000 RPM, 4°C, 10 min.), the supernatants were transferred to new 517

Eppendorf tubes and evaporated to dryness under a gentle stream of gaseous nitrogen using a 518

TurboVap® LV evaporation system (Caliper Life Sciences, Hopkinton, MA, USA). Before 519

chlorophyll determination, the pellets were dissolved in acetone p.a. (Lach-ner, Czech 520



21

Republic). The light absorbance of the resulting suspensions was measured at 663.2, 646.8, 521

and 750 nm wavelengths using an Infinite® 200 PRO spectrophotometer (Tecan, Switzerland) 522

and the sample’s chlorophyll contents were calculated according to Lichtenthaler (1987) 523

(Supplemental Table S11). 524

525

Stability experiment 526

Portions of solutions containing known amounts of selected analytes (0.4 pmol of CKs 527

and JAs, with 4 pmol of AXs and GAs per sample, n=3; Supplemental Table S12) were 528

transferred to new vials and evaporated to dryness under a gentle stream of gaseous nitrogen 529

using a TurboVap® LV evaporation system (Caliper Life Sciences, Hopkinton, MA, USA). 530

The compounds were then dissolved in 1 ml of aqueous solutions of 1 M formic acid (pH < 531

3), 0.35 M NH4OH (60% MeOH, vol/vol; pH > 12), or 50% ACN using ultrasound (5 min, 532

4°C; Transsonic T310a laboratory ultrasonicator, Elma GmbH & Co KG, Singen, Germany). 533

After incubation for 15 min at 4°C, samples were filtered using modified nylon 0.2 µm 534

Centrifugal Filters (VWR International, Czech Republic). Filtered samples were evaporated to 535

dryness as described above, dissolved in 40 µl of 30% ACN and subjected to UHPLC-536

MS/MS analysis (10 µl/injection). Relative peak areas (%) of the compounds were calculated 537

as ratios to respective peak areas obtained from analyses of reference samples in 50% ACN 538

(Fig. 1c). However, the extent of enzymatic activity in plant extracts obtained using the 539

proposed sample preparation protocol was not investigated. 540

541

Sample extraction 542

For the quantification of targeted plant hormones and related compounds, 20 mg FW 543

portions of separately harvested roots and shoots were weighed into 2 ml plastic micro tubes 544

(Eppendorf, Germany) and frozen in liquid nitrogen. To minimize the risk of false positive 545

detections, possible background levels of analytes were subtracted from measured sample 546

values. Therefore, the blank controls, 1 ml of extraction buffer containing a mixture of stable 547

isotopically-labelled internal standards were also purified. Before extraction, three 3 mm ceria 548

stabilized zirconium oxide beads (Next Advance Inc., Averill Park, NY, USA) were added to 549

each sample. A mixture of stable, isotopically-labelled internal standards (IS) was added to 550

validate the method and enable precise quantification of endogenous levels of targeted 551

compounds. The amounts of IS ranged from 0.4 – 50 pmol per sample (precise amounts are 552

listed in Supplemental Table S3). Frozen plant material was extracted in 1 ml of ice-cold 50% 553

aqueous ACN (vol/vol) using a MM 301vibration mill (Retsch GmbH & Co. KG, Haan, 554



22

Germany) operating at a frequency of 27 Hz for 5 min. Samples were then sonicated for 3 min 555

at 4°C using a Transsonic T310 ultrasonicator with an ice block-filled bathtub (Elma GmbH 556

& Co KG, Singen, Germany) and subsequently extracted using a Stuart SB3 benchtop 557

laboratory rotator (Bibby Scientific Ltd., Staffordshire, UK) for 30 min at 15 rpm and 4°C. 558

After centrifugation (10 min, 20,000 rpm, 4°C; Beckman Avanti™ 30), the supernatant was 559

transferred to clean plastic microtubes. Samples were further purified according to the scheme 560

shown in Fig. 1D. 561

562

Sample purification 563

All samples were purified using Oasis® HLB reversed-phase, polymer-based, solid-564

phase extraction (RP-SPE) cartridges (1 cc/30 mg), obtained from Waters Co. (Milford, MA, 565

USA) that had been washed with 1 ml of 100% MeOH and 1 ml of deionized water, then 566

equilibrated with 50% aqueous ACN (vol/vol). After loading a sample (supernatant obtained 567

following the procedure described above), the flow-through fraction was collected in a glass 568

tube (Fisherbrand™). The cartridge was then rinsed with 1 ml of 30% ACN (vol/vol) and this 569

fraction was collected in the same glass tube as the flow-through fraction. After this single-570

step SPE, the samples were evaporated to dryness under a gentle stream of nitrogen using a 571

TurboVap® LV evaporation system (Caliper Life Sciences, Hopkinton, MA, USA) and stored 572

at -20°C until analysis. For UHPLC–ESI–MS/MS analysis, the samples were dissolved in 40 573

µl of 30% ACN (vol/vol) and transferred to insert-equipped vials, then 20 µl portions of each 574

sample were injected (in two 10-µl injections) into the UHPLC-ESI-MS/MS system. 575

576

UHPLC-ESI-MS/MS conditions 577

Targeted compounds were analyzed using an Acquity UPLC® I-Class System 578

equipped with a Binary Solvent Manager, a Sample Manager with Flow-Through Needle, and 579

an Acquity UPLC® CSHTM C18 RP column (150 x 2.1 mm, particle size of 1.7 µm) coupled 580

to a triple quadrupole mass spectrometer Xevo® TQ-S MS, all from Waters (Manchester, 581

UK). The mobile UPLC phase consisted of binary gradients of ACN with 0.01% (vol/vol) FA 582

(A) and 0.01% (vol/vol) aqueous FA (B), flowing at 0.5 ml min-1, which depended on the ESI 583

mode, as described below. MassLynxTM software (version 4.1, Waters, Milford, MA, USA) 584

was used to control the instrument and to acquire and process the MS data. 585

Separation of compounds detected in ESI positive mode. Analytes were initially eluted 586

isocratically with 5% A (vol/vol) for 5 min, then the proportion of A was increased linearly to 587



23

80% over the following 10 min. After this, the column was washed with 100% A and then re-588

equilibrated under the initial conditions for 2 min. The column temperature was held at 50°C. 589

Separation of compounds detected in ESI negative mode. The mobile phase was the 590

same until the A:B ratio reached 65:35 (vol/vol) in the 13th minute. Then the column was 591

washed with 100% A and re-equilibrated under the initial conditions for 2 min. 592

During analytical runs in both ESI modes, the UHPLC eluate was switched to waste 593

until acquisition of the first targeted compound and back to waste after elution of the last 594

compound to minimize impairment of the MS system’s sensitivity by ballast compounds. 595

During acquisition of analytes, the eluate was introduced into the electrospray ion source of 596

the tandem MS analyzer operating under the following conditions: source/desolvation 597

temperature, 125/600°C; cone/desolvation gas flow, 150/1000 L h-1; capillary voltage, 2.1 kV 598

ESI(+), 1.5 kV ESI(–); cone voltage, 10–40 V; collision energy, 12–30 eV; collision gas flow 599

(argon), 0.21 mL min-1. The analyzed compounds and appropriate IS were quantified in 600

multiple-ion-monitoring mode (MRM) using optimized MS conditions (Supplemental Table 601

S3). The inter-scan and inter-channel delays were set to 3 ms when switching between 602

successive MRM channels and 20 ms was required for inter-channel delay when switching 603

from positive to negative ionization mode between successive channels. The dwell times 604

ranged from 8 to 100 ms to provide at least 15 data points across each chromatographic peak 605

using automatic mode. The MRM transitions were recorded over each chromatographic run in 606

9 targeted scan windows to maximize the MS signal intensity for each compound. For ESI(+) 607

runs these windows were: 1.00–5.30, 5.31–7.65, 7.30–8.40, 8.35–8.85, 8.86–10.00, 10.10–608

10.95, 11.30–11.85, 11.50–12.70, and 12.60–15.00 min. For ESI(–) runs they were: 6.30–609

7.30, 7.30–8.25, 8.20–8.70, 8.70–9.30, 9.00–9.90, 9.80–10.85, 10.90–11.30, 11.30–12.00, and 610

12.00–13.00 min. 611

612

Method validation 613

UHPLC–ESI–MS/MS calibration curves were constructed using serially-diluted 614

phytohormone standards, listed in Supplemental Table S3, and the internal labelled standards 615

(added in known concentrations). Limits of detection and quantification were defined as 616

signal-to-noise ratios of 3:1 and 10:1, respectively. 617

To evaluate losses of analytes during the purification process and validate the method, 618

three sets of samples were each prepared in triplicate and analyzed by the UHPLC–ESI–619

MS/MS system. In the first set, 20 mg FW of Arabidopsis seedlings were extracted in ice-cold 620

50% ACN spiked with known amounts of stable isotope-labelled IS (at levels listed in 621



24

Supplemental Table S2), and subsequently purified by the SPE protocol (Fig. 1D). The 622

second set consisted of identical plant tissue extracts spiked with a mixture of authentic and 623

stable isotope-labelled IS (at levels listed in Supplemental Table S2) before SPE. The third set 624

consisted of 20 mg FW portions of Arabidopsis plant tissue extracted and spiked by adding 625

non-labelled standards, in varied concentrations, directly to purified eluates after the SPE 626

step. 627

Analyte recovery (RE, %; Caban et al., 2012) following the purification process was 628

calculated as the ratio of the mean peak area of a non-labelled analyte spiked before SPE 629

(set 2) to the mean peak area of the same analyte spiked after SPE purification (set 3) 630

multiplied by 100. 631

Concentrations of plant hormones were quantified using the standard isotope dilution 632

method (Rittenberg and Foster, 1940). Concentrations of non-labelled, targeted compounds 633

added to samples from sample set 2 were calculated after subtracting their determined 634

endogenous levels (average values for each compound obtained from analyses of sample 635

set 1). Finally, determined analyte concentrations were compared with known theoretical 636

amounts of appropriate standards added to samples and presented as method accuracy 637

(expressed as percentage bias). Method precision for each analyte was calculated as the 638

relative standard deviation (%RSD) of its determined concentration in three replicates of 639

samples of set 2. 640

To test the reproducibility and repeatability of the method, two experiments were 641

carried out. First, standard mixtures containing known concentrations of the IS (medium) and 642

three concentration levels (low / medium / high) of the targeted compounds were prepared as 643

follows: CKs, 2MeSCKs: 0.001 / 0.05 / 1.0; AXs: 0.01 / 0.5 / 10; JAs (ESI+): 0.0025 / 0.05 / 644

2.5; JAs, ABAs (ESI–): 0.05 / 1 / 50; SA: 0.1 / 5 / 100; GAs: 0.005 / 0.1 / 5; and BRs: 0.05 / 645

0.05 / 10 pmol/injection. Three replicates of each of these analyte levels were injected in three 646

consecutive days and all samples were kept at 4°C throughout the experiment. The stability of 647

the retention times for all compounds was expressed as %RSD. The reproducibility of the IS-648

normalized response for each analyte was also calculated. In the second experiment, 10-day-649

old Arabidopsis seedlings (20 mg FW) were spiked with known concentration of isotope-650

labelled IS listed in Supplemental Table S2 and then endogenous phytohormones were 651

isolated using the developed method (Fig. 1D). All samples were analyzed as an independent 652

batch in five replicates on three separate days. The intraday and interday calculations were 653

based on the IS-normalized response of endogenous compounds. The results were expressed 654

as %RSD of the measurements. 655



25

656

Genevestigator analysis 657

The meta-analytical approach of Genevestigator (Hruz et al., 2008) has proven value 658

for designing new experiments and validating existing results (Saito et al., 2008). Therefore, 659

the software was initially used (in an unsupervised manner) to identify a single stress 660

condition that alters the expression of genes involved in the biosynthesis of most hormones 661

and their metabolism pathways (Supplemental Table S6). Salt stress was identified as the 662

most appropriate condition by screening using the Differential expression tool 663

(Genevestigator Experiment ID: AT-00656), and its suitability was confirmed by screening 664

shifts in expression of hormone-related genes in one more salt stress experiment 665

(Genevestigator Experiment ID: AT-00120). For representation of these results (Fig. 3B), a 666

Venn diagram was constructed using Venny 2.1 software (Oliveros, 2007-2015). The input 667

consisted of (i) hormone-related genes listed in Supplemental Table S6, and Arabidopsis 668

genes that exhibited altered expression (up- or down-regulation in greater than a 1.5-fold 669

change, p<0.01) in response to salt stress after a 24 h treatment in Arabidopsis roots (ii) and 670

shoots (iii) (Genevestigator Experiment ID: AT-00120) and after a 48 h treatment in root cell-671

specific protoplasts (iv) (Genevestigator Experiment ID: AT-00656) isolated through 672

fluorescence-activated cell sorting. To compare the data on hormonomic and transcriptomic 673

shifts under salt stress, the Perturbations tool was used. The genes listed in Supplemental 674

Table S6 that were significantly up- or down-regulated (fold change ≥ 1.5, p<0.01) in 675

response to salinity stress were identified. Log values of changes in their expression were then 676

extracted and their activities in hormone pathways were noted to check the consistency 677

between their responses and the changes we detected in the corresponding hormone 678

metabolites (Supplemental Tables S8 and S9). 679

The Genevestigator interface is a JAVA applet running in the user's browser. 680

Information about the individual tools and respective statistical analysis on the data is 681

provided on the Genevestigator website (www.genevestigator.ethz.ch). 682

683

Statistical analysis (uni- and multi-variate statistics) 684

Before multivariate statistical analysis, the missing values of the targeted compounds 685

found in some plant tissue samples under the limit of detection were imputed with two-thirds 686

of their respective LODs listed in Supplemental Table S2 (Martín-Fernández et al., 2003). 687

The compounds for which more than 50% of values were missing were removed from the 688

dataset. Multivariate analysis was performed using SIMCA software (version 14, Umetrics). 689



26

Unsupervised principal component analysis (PCA) and supervised orthogonal partial least 690

squares discriminant analysis (OPLS-DA) were applied to log-transformed and Pareto-scaled 691

data. PCA was used to obtain a general overview of the data structure, and OPLS-DA derived 692

S-plots to identify compounds responsible for separation of roots and shoots, and samples 693

from control and salinity-stressed plants. Differences in the levels of each determined 694

metabolite between these groups were also evaluated using Student’s t-test at P<0.05, P<0.01, 695

and P<0.001 levels. 696

697

ACCESSION NUMBERS 698

Sequence data from this article can be found in the GenBank data libraries under 699

accession numbers listed in Supplemental Table S6. 700

701

SUPPLEMENTAL DATA 702

The following supplemental materials are available. 703

Supplemental Figure S1. Comparison of signal intensities of indicated analytes of various 704

phytohormone classes. 705

Supplemental Figure S2. Representative MRM chromatograms of endogenous cytokinins 706

and auxins in 20 mg FW of Arabidopsis roots 48 hours after the salt-stress treatment. 707

Supplemental Figure S3. Representative MRM chromatograms of endogenous jasmonates, 708

abscisates, salicylic acid, and gibberellins in 20 mg FW of Arabidopsis roots 48 hours after 709

the salt-stress treatment. 710

Supplemental Figure S4. Scatterplots of phytohormone distributions in root and shoot 711

samples of control and salt-stressed Arabidopsis plants. 712

Supplemental Table S1. List of targeted compounds. 713

Supplemental Table S2. Method validation data. 714

Supplemental Table S3. Optimized UHPLC–MS/MS parameters. 715

Supplemental Table S4. Reproducibility of the LC-MS/MS method. 716

Supplemental Table S5. Intraday and interday precision of the method. 717

Supplemental Table S6. Phytohormone-related genes used in the experimental design 718

process. 719

Supplemental Table S7. Determined levels of plant hormones in root and shoot samples of 720

salt-stressed and control Arabidopsis plants. 721

Supplemental Table S8. Genes showing shifts in expression levels under salt stress in roots. 722



27

Supplemental Table S9. Genes showing shifts in expression levels under salt stress in 723

shoots. 724

Supplemental Table S10. Solubility of brassinosteroids. 725

Supplemental Table S11. Determination of chlorophyll (Chla,b). 726

Supplemental Table S12. Tests of pH stability. 727

728

ACKNOWLEDGMENTS 729

We thank the Swedish Metabolomics Centre for the use of instrumentation and Sees-editing 730

Ltd. for careful revision of the manuscript. We would also like to thank Eva Hrdličková 731

Hirnerová for technical support and sample preparation during the plant hormone analyses. 732

733



28

TABLES 734

735

Table 1. Overview of average recovery, minimal and maximal limits of detection (LOD), and 736

average method precision and analytical accuracy (absolute value) for each phytohormone 737

class. See Supplemental Table S2 for detailed information. 738

739

Phytohormone class

Number of compounds

Min/Max LOD (fmol)

Spiked contents (pmol)

Average recovery

(%)

Average method

precision (% RSD)

Average method

accuracy (% bias)

Cytokinins 41 0.005 / 0.5 0.5 – 5 87.0 3.30 7.49

Auxins 15 0.05 / 10 1 – 50 91.5 4.31 6.93

Jasmonates 11 0.1 / 50 10 95.3 5.70 5.20

Abscisates 5 1.0 / 10 10 95.9 1.06 5.91

Gibberellins 14 0.25 / 25 5 89.2 3.00 5.54

Salicylic Acid 1 25 100 97.3 4.05 8.68

Brassinosteroids 14 2.5 / 25 10 52.5 7.80 5.26 740



29

FIGURE LEGENDS 741

742

Figure 1. Optimization of sample preparation. A, Solubility of selected brassinosteroids (TE, 743

teasterone; TY, typhasterol; CS, castasterone; BL, brassinolide), the most hydrophobic 744

phytohormone class included in our study, in extraction solvents with varied acetonitrile 745

(ACN) content. Relative yield (ratio, in percent, of average peak area to maximal average 746

peak area per extraction solvent; error bars represent standard deviations; Supplemental Table 747

S10). B, Amounts of chlorophyll extracted (mg/l) using extraction solvents with indicated 748

ACN concentrations (error bars represent standard deviations, Supplemental Table S11). C, 749

pH-dependent stability (relative peak area, %) of selected compounds (JA-Ile, jasmonoyl-L-750

isoleucine; JA-Phe, jasmonoyl-L-phenylalanine; JA-Val, jasmonoyl-L-valine; JA-Trp, 751

jasmonoyl-L-tryptophan; IAA-Asp, indole-3-acetyl-L-aspartate; IAA-Glu, indole-3-acetyl-L-752

glutamate; GA53, Gibberellin A53; GA4, Gibberellin A4; GA24, Gibberellin A24; cZOG, cis-753

zeatin-O-glucoside; tZ9G, trans-zeatin-9-glucoside; tZROG, trans-zeatin riboside-O-754

glucoside; iP7G, N6-isopentenyladenine-7-glucoside) dissolved in 0.35 M ammonium 755

hydroxide in 60% methanol (0.35 M NH4OH in 60% MeOH) and 1 M formic acid (1 M FA), 756

based on peak areas relative to peak areas of compounds dissolved in control solvent (50% 757

ACN). The dashed line represents the average peak area and the dotted lines represent the 758

average of standard deviations for compounds dissolved in the control solvent; asterisks 759

indicate significant changes compared to control (Student’s t-test, P<0.05 (*); Supplemental 760

Table S12). D, Scheme of sample micro-extraction and purification prior to UHPLC-ESI-761

MS/MS analysis. 762

763

Figure 2. Optimization of baseline chromatographic separation. A, Peak shape of IAA-764

aspartate (IAA-Asp) and IAA-glutamate (IAA-Glu) separated on Acquity UPLC® CSH™ 765

(solid line) and Acquity UPLC® BEH shield (dashed line) columns. B, Isomer separation of 766

N/O-glucoside forms of cis/trans-zeatins (left) and brassinolide (BL/epiBL) and castasterone 767

(CS/epiCS) isobars (right) using an Acquity UPLC® CSH™ column. C and D, Overlay of 768

UHPLC-ESI-MS/MS separation of targeted compounds in ESI(+) mode (C) and ESI(–) mode 769

(D). Phytohormones are numbered according to Supplemental Table S1. 770

771

Figure 3. Alterations in expression levels of plant hormone-related genes induced by salinity 772

stress in Arabidopsis. A, Simplified scheme of plant hormone biosynthesis pathways. B, Venn 773

diagram showing numbers, percentages, and overlaps of hormone-related genes (yellow oval, 774



30

Supplemental Table S6) and transcripts with affected levels (≥1.5-fold change, p<0.01) in 775

response to salt stress experiments as described in Materials and Methods (genes in green and 776

blue ovals correspond to Arabidopsis root and shoot samples, respectively, from the 777

Genevestigator Experiment ID: AT-00120 and genes in the red oval correspond to sorted root 778

cell-specific protoplasts from Genevestigator Experiment ID: AT-00656). FACS stands for 779

Fluorescence-Activated Cell Sorting. C and D, Changes in hormone-related gene expression 780

levels in shoot (C) and root (D) tissues under salinity stress (log ratio treated/control, ≥1.5-781

fold change, p<0.01; Genevestigator Experiment ID: AT-00120; Supplemental Tables S8 and 782

S9). 783

784

Figure 4. Comparison of phytohormones in Arabidopsis roots and shoots exposed to salinity 785

stress and controls. A, Schematic illustration of the salinity-stress experiment. B, PCA score 786

plot showing separation and grouping of samples (roots and shoots of control and salt-stressed 787

plants) according to the composition and abundance of determined compounds. C and D, 788

OPLSDA S-plots showing the variables responsible for separating roots of control and salt-789

stressed plants (C) and their shoots (D), combining covariance (p1; the farther the distance 790

from zero, the higher the contribution to the difference between two groups) and correlation 791

(pcorr1; the farther the distance from zero the higher the reliability). E and F, levels of 792

targeted compounds in roots (E) and shoots (F) (pmol/g FW, logarithmic scale; asterisks 793

indicate significant differences between salt-stressed and control plants (Student’s t-test, 794

P<0.05 (*), P<0.01 (**), and P<0.001 (***); error bars represent standard deviations). 795

Compound abbreviations are listed in Supplemental Table S1. 796

797



31

798



Parsed CitationsAlbaseer SS, Rao RN, Swamy YV, Mukkanti K (2010) An overview of sample preparation and extraction of synthetic pyrethroids fromwater, sediment and soil. J Chromatogr A 1217: 5537–5554

Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Antoniadi I, Plačková L, Simonovik B, Doležal K, Turnbull C, Ljung K, Novák O (2015) Cell-type specific cytokinin distribution within theArabidopsis primary root apex. Plant Cell 27: 1955–1967


Balcke GU, Handrick V, Bergau N, Fichtner M, Henning A, Stellmach H, Tissier A, Hause B, Frolov A (2012) An UPLC-MS/MS method forhighly sensitive high-throughput analysis of phytohormones in plant tissues. Plant Methods 8: 47


Birkemeyer C, Kolasa, A, Kopka J (2003) Comprehensive chemical derivatization for gas chromatography–mass spectrometry-basedmulti-targeted profiling of the major phytohormones. J Chromatogr A 993: 89–102


Caban M, Migowska N, Stepnowski P, Kwiatkowski M, Kumirska J (2012) Matrix effects and recovery calculations in analyses ofpharmaceuticals based on the determination of β-blockers and β-agonists in environmental samples. J Chromatogr A 1258: 117–127


Cai W J, Ye TT, Wang Q, Cai BD, Feng YQ (2016) A rapid approach to investigate spatiotemporal distribution of phytohormones in rice.Plant Methods 12: 47


Cao ZY, Sun LH, Mou RX, Zhang LP, Lin XY, Zhu ZW, Chen MX (2016) Profiling of phytohormones and their major metabolites in riceusing binary solid-phase extraction and liquid chromatography-triple quadrupole mass spectrometry. J Chromatogr A 1451: 67–74


Chiwocha SD, Abrams SR, Ambrose SJ, Cutler AJ, Loewen M, Ross AR, Kermode AR (2003) A method for profiling classes of planthormones and their metabolites using liquid chromatography-electrospray ionization tandem mass spectrometry: An analysis ofhormone regulation of thermodormancy of lettuce (Lactuca sativa L.) seeds. Plant J 35: 405–417


Davies P.J. (2010) Plant Hormones: Biosynthesis, Signal Transduction, Action! 3rd Edition. Kluwer Academic Publishers, Dordrecht,Netherlands


Delatorre C, Rodríguez A, Rodríguez L, Majada JP, Ordás RJ, Feito I (2017) Hormonal profiling: Development of a simple method toextract and quantify phytohormones in complex matrices by UHPLC–MS/MS. J Chromatogr B 1040: 239–249


Dobrev PI, Kamínek M (2002) Fast and efficient separation of cytokinins from auxin and abscisic acid and their purification using mixed-mode solid-phase extraction. J Chromatogr A 950: 21–29


Du F, Ruan G, Liu H (2012) Analytical methods for tracing plant hormones. Anal Bioanal Chem 403: 55–74Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title


http://www.ncbi.nlm.nih.gov/pubmed?term=Albaseer SS%2C Rao RN%2C Swamy YV%2C Mukkanti K %282010%29 An overview of sample preparation and extraction of synthetic pyrethroids from water%2C sediment and soil%2E J Chromatogr A 1217%3A 5537�??5554&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Albaseer SS, Rao RN, Swamy YV, Mukkanti K (2010) An overview of sample preparation and extraction of synthetic pyrethroids from water, sediment and soil. J Chromatogr A 1217: 5537?5554

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Albaseer&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=An overview of sample preparation and extraction of synthetic pyrethroids from water, sediment and soil.&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=1

http://scholar.google.com/scholar?as_q=An overview of sample preparation and extraction of synthetic pyrethroids from water, sediment and soil.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Albaseer&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Antoniadi I%2C Plačková L%2C Simonovik B%2C Doležal K%2C Turnbull C%2C Ljung K%2C Novák O %282015%29 Cell%2Dtype specific cytokinin distribution within the Arabidopsis primary root apex%2E Plant Cell 27%3A 1955�??1967&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Antoniadi I, Pla?kov� L, Simonovik B, Dole?al K, Turnbull C, Ljung K, Nov�k O (2015) Cell-type specific cytokinin distribution within the Arabidopsis primary root apex. Plant Cell 27: 1955?1967

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Antoniadi&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Cell-type specific cytokinin distribution within the Arabidopsis primary root apex.&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=1

http://scholar.google.com/scholar?as_q=Cell-type specific cytokinin distribution within the Arabidopsis primary root apex.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Antoniadi&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Balcke GU%2C Handrick V%2C Bergau N%2C Fichtner M%2C Henning A%2C Stellmach H%2C Tissier A%2C Hause B%2C Frolov A %282012%29 An UPLC%2DMS%2FMS method for highly sensitive high%2Dthroughput analysis of phytohormones in plant tissues%2E Plant Methods 8%3A 47&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Balcke GU, Handrick V, Bergau N, Fichtner M, Henning A, Stellmach H, Tissier A, Hause B, Frolov A (2012) An UPLC-MS/MS method for highly sensitive high-throughput analysis of phytohormones in plant tissues. Plant Methods 8: 47

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Balcke&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=An UPLC-MS/MS method for highly sensitive high-throughput analysis of phytohormones in plant tissues.&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=1

http://scholar.google.com/scholar?as_q=An UPLC-MS/MS method for highly sensitive high-throughput analysis of phytohormones in plant tissues.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Balcke&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Birkemeyer C%2C Kolasa%2C A%2C Kopka J %282003%29 Comprehensive chemical derivatization for gas chromatography�??mass spectrometry%2Dbased multi%2Dtargeted profiling of the major phytohormones%2E J Chromatogr A 993%3A 89�??102&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Birkemeyer C, Kolasa, A, Kopka J (2003) Comprehensive chemical derivatization for gas chromatography?mass spectrometry-based multi-targeted profiling of the major phytohormones. J Chromatogr A 993: 89?102

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Birkemeyer&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Comprehensive chemical derivatization for gas chromatographyâ�?�?mass spectrometry-based multi-targeted profiling of the major phytohormones.&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=1

http://scholar.google.com/scholar?as_q=Comprehensive chemical derivatization for gas chromatographyâ�?�?mass spectrometry-based multi-targeted profiling of the major phytohormones.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Birkemeyer&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Caban M%2C Migowska N%2C Stepnowski P%2C Kwiatkowski M%2C Kumirska J %282012%29 Matrix effects and recovery calculations in analyses of pharmaceuticals based on the determination of β%2Dblockers and β%2Dagonists in environmental samples%2E J Chromatogr A 1258%3A 117�??127&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Caban M, Migowska N, Stepnowski P, Kwiatkowski M, Kumirska J (2012) Matrix effects and recovery calculations in analyses of pharmaceuticals based on the determination of ?-blockers and ?-agonists in environmental samples. J Chromatogr A 1258: 117?127

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Caban&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Matrix effects and recovery calculations in analyses of pharmaceuticals based on the determination of �?²-blockers and �?²-agonists in environmental samples.&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=1

http://scholar.google.com/scholar?as_q=Matrix effects and recovery calculations in analyses of pharmaceuticals based on the determination of �?²-blockers and �?²-agonists in environmental samples.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Caban&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Cai W J%2C Ye TT%2C Wang Q%2C Cai BD%2C Feng YQ %282016%29 A rapid approach to investigate spatiotemporal distribution of phytohormones in rice%2E Plant Methods 12%3A 47&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Cai W J, Ye TT, Wang Q, Cai BD, Feng YQ (2016) A rapid approach to investigate spatiotemporal distribution of phytohormones in rice. Plant Methods 12: 47

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Cai&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=A rapid approach to investigate spatiotemporal distribution of phytohormones in rice.&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=1

http://scholar.google.com/scholar?as_q=A rapid approach to investigate spatiotemporal distribution of phytohormones in rice.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Cai&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Cao ZY%2C Sun LH%2C Mou RX%2C Zhang LP%2C Lin XY%2C Zhu ZW%2C Chen MX %282016%29 Profiling of phytohormones and their major metabolites in rice using binary solid%2Dphase extraction and liquid chromatography%2Dtriple quadrupole mass spectrometry%2E J Chromatogr A 1451%3A 67�??74&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Cao ZY, Sun LH, Mou RX, Zhang LP, Lin XY, Zhu ZW, Chen MX (2016) Profiling of phytohormones and their major metabolites in rice using binary solid-phase extraction and liquid chromatography-triple quadrupole mass spectrometry. J Chromatogr A 1451: 67?74

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Cao&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Profiling of phytohormones and their major metabolites in rice using binary solid-phase extraction and liquid chromatography-triple quadrupole mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Profiling of phytohormones and their major metabolites in rice using binary solid-phase extraction and liquid chromatography-triple quadrupole mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Cao&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Chiwocha SD%2C Abrams SR%2C Ambrose SJ%2C Cutler AJ%2C Loewen M%2C Ross AR%2C Kermode AR %282003%29 A method for profiling classes of plant hormones and their metabolites using liquid chromatography%2Delectrospray ionization tandem mass spectrometry%3A An analysis of hormone regulation of thermodormancy of lettuce %28Lactuca sativa L%2E%29 seeds%2E Plant J 35%3A 405�??417&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Chiwocha SD, Abrams SR, Ambrose SJ, Cutler AJ, Loewen M, Ross AR, Kermode AR (2003) A method for profiling classes of plant hormones and their metabolites using liquid chromatography-electrospray ionization tandem mass spectrometry: An analysis of hormone regulation of thermodormancy of lettuce (Lactuca sativa L.) seeds. Plant J 35: 405?417

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Chiwocha&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=A method for profiling classes of plant hormones and their metabolites using liquid chromatography-electrospray ionization tandem mass spectrometry: An analysis of hormone regulation of thermodormancy of lettuce (Lactuca sativa L.) seeds.&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=1

http://scholar.google.com/scholar?as_q=A method for profiling classes of plant hormones and their metabolites using liquid chromatography-electrospray ionization tandem mass spectrometry: An analysis of hormone regulation of thermodormancy of lettuce (Lactuca sativa L.) seeds.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Chiwocha&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Davies P%2EJ%2E %282010%29 Plant Hormones%3A Biosynthesis%2C Signal Transduction%2C Action%21 3rd Edition%2E Kluwer Academic Publishers%2C Dordrecht%2C Netherlands&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Davies P.J. (2010) Plant Hormones: Biosynthesis, Signal Transduction, Action! 3rd Edition. Kluwer Academic Publishers, Dordrecht, Netherlands

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Davies&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Plant Hormones: Biosynthesis, Signal Transduction, Action! 3rd Edition.&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=1

http://scholar.google.com/scholar?as_q=Plant Hormones: Biosynthesis, Signal Transduction, Action! 3rd Edition.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Davies&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Delatorre C%2C Rodríguez A%2C Rodríguez L%2C Majada JP%2C Ordás RJ%2C Feito I %282017%29 Hormonal profiling%3A Development of a simple method to extract and quantify phytohormones in complex matrices by UHPLC�??MS%2FMS%2E J Chromatogr B 1040%3A 239�??249&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Delatorre C, Rodr�guez A, Rodr�guez L, Majada JP, Ord�s RJ, Feito I (2017) Hormonal profiling: Development of a simple method to extract and quantify phytohormones in complex matrices by UHPLC?MS/MS. J Chromatogr B 1040: 239?249

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Delatorre&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Hormonal profiling: Development of a simple method to extract and quantify phytohormones in complex matrices by UHPLCâ�?�?MS/MS.&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=1

http://scholar.google.com/scholar?as_q=Hormonal profiling: Development of a simple method to extract and quantify phytohormones in complex matrices by UHPLCâ�?�?MS/MS.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Delatorre&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Dobrev PI%2C Kamínek M %282002%29 Fast and efficient separation of cytokinins from auxin and abscisic acid and their purification using mixed%2Dmode solid%2Dphase extraction%2E J Chromatogr A 950%3A 21�??29&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Dobrev PI, Kam�nek M (2002) Fast and efficient separation of cytokinins from auxin and abscisic acid and their purification using mixed-mode solid-phase extraction. J Chromatogr A 950: 21?29

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Dobrev&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Fast and efficient separation of cytokinins from auxin and abscisic acid and their purification using mixed-mode solid-phase extraction.&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=1

http://scholar.google.com/scholar?as_q=Fast and efficient separation of cytokinins from auxin and abscisic acid and their purification using mixed-mode solid-phase extraction.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Dobrev&as_ylo=2002&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Du F%2C Ruan G%2C Liu H %282012%29 Analytical methods for tracing plant hormones%2E Anal Bioanal Chem 403%3A 55�??74&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Du F, Ruan G, Liu H (2012) Analytical methods for tracing plant hormones. Anal Bioanal Chem 403: 55?74

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Du&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Analytical methods for tracing plant hormones.&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=1

http://scholar.google.com/scholar?as_q=Analytical methods for tracing plant hormones.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Du&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1


Farrow SC, Emery RN (2012) Concurrent profiling of indole-3-acetic acid, abscisic acid, and cytokinins and structurally related purinesby high-performance-liquid-chromatography tandem electrospray mass spectrometry. Plant Methods 8: 42


Floková K, Tarkowská D, Miersch O, Strnad M, Wasternack C, Novák O (2014) UHPLC–MS/MS based target profiling of stress-inducedphytohormones. Phytochemistry 105: 147–157


Hird SJ, Lau BPY, Schuhmacher R, Krska R. (2014) Liquid chromatography-mass spectrometry for the determination of chemicalcontaminants in food. rends Analyt Chem 59: 59–72


Hoyerová K, Gaudinová A, Malbeck J, Dobrev PI, Kocábek T, Solcová B, Trávnícková A, Kamínek M. (2006) Efficiency of differentmethods of extraction and purification of cytokinins. Phytochemistry 67(11): 1151–1159


Hruz T, Laule O, Szabo G, Wessendorp F, Bleuler S, Oertle L, Widmayer P, Gruissem W, Zimmermann P (2008) GENEVESTIGATOR V3:a reference expression database for the meta-analysis of transcriptomes. Adv Bioinformatics 2008: 420747


Hyötyläinen T (2013) Sample Collection, Storage and Preparation. In T Hyotylainen, SK Wiedmer, eds, Chromatographic Methods inMetabolomics. Royal Society of Chemistry, pp 11–42


Immanen J, Nieminen K, Smolander OP, Kojima M, Alonso Serra J, Koskinen P, Zhang J, Elo A, Mähönen AP, Street N, Bhalerao RP,Paulin L, Auvinen P, Sakakibara H, Helariutta Y (2016) Cytokinin and auxin display distinct but interconnected distribution and signalingprofiles to stimulate cambial activity. Curr Biol 26: 1990–1997


Jin X, Wang RS, Zhu M, Jeon BW, Albert R, Chen S, Assmann SM (2013) Abscisic Acid-Responsive Guard Cell Metabolomes ofArabidopsis Wild-Type and gpa1 G-Protein Mutants. Plant Cell 25: 4789–4811


Jiskrová E, Novák O, Pospíšilová H, Holubová K, Karády M, Galuszka P, Robert S, Frébort I (2016) Extra- and intracellular distributionof cytokinins in the leaves of monocots and dicots. N Biotechnol 33: 735–742


Kojima M, Kamada-Nobusada T, Komatsu H, Takei K, Kuroha T, Mizutani M, Ashikari M, Ueguchi-Tanaka M, Matsuoka M, Suzuki K,Sakakibara H (2009) Highly sensitive and high-throughput analysis of plant hormones using MS-probe modification and liquidchromatography-tandem mass spectrometry: An application for hormone profiling in Oryza sativa. Plant Cell Physiol 50: 1201–1214


Lichtenthaler HK (1987) Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes. Methods Enzymol 148: 350–382Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Ljung K, Sandberg G, Moritz T. (2010) Methods of plant hormone analysis. In PJ Davies, ed., Plant hormones: Biosynthesis, SignalTransduction, Action! Springer, pp. 717–740.


Martín-Fernández JA, Barceló-Vidal C, Pawlowsky-Glahn V (2003). Dealing with zeros and missing values in compositional data setsusing nonparametric imputation. Math Geol 35: 253–278.


http://www.ncbi.nlm.nih.gov/pubmed?term=Farrow SC%2C Emery RN %282012%29 Concurrent profiling of indole%2D3%2Dacetic acid%2C abscisic acid%2C and cytokinins and structurally related purines by high%2Dperformance%2Dliquid%2Dchromatography tandem electrospray mass spectrometry%2E Plant Methods 8%3A 42&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Farrow SC, Emery RN (2012) Concurrent profiling of indole-3-acetic acid, abscisic acid, and cytokinins and structurally related purines by high-performance-liquid-chromatography tandem electrospray mass spectrometry. Plant Methods 8: 42

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Farrow&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Concurrent profiling of indole-3-acetic acid, abscisic acid, and cytokinins and structurally related purines by high-performance-liquid-chromatography tandem electrospray mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Concurrent profiling of indole-3-acetic acid, abscisic acid, and cytokinins and structurally related purines by high-performance-liquid-chromatography tandem electrospray mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Farrow&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Floková K%2C Tarkowská D%2C Miersch O%2C Strnad M%2C Wasternack C%2C Novák O %282014%29 UHPLC�??MS%2FMS based target profiling of stress%2Dinduced phytohormones%2E Phytochemistry 105%3A 147�??157&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Flokov� K, Tarkowsk� D, Miersch O, Strnad M, Wasternack C, Nov�k O (2014) UHPLC?MS/MS based target profiling of stress-induced phytohormones. Phytochemistry 105: 147?157

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Flokov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=UHPLCâ�?�?MS/MS based target profiling of stress-induced phytohormones.&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=1

http://scholar.google.com/scholar?as_q=UHPLCâ�?�?MS/MS based target profiling of stress-induced phytohormones.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Flokov�?¡&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Hird SJ%2C Lau BPY%2C Schuhmacher R%2C Krska R%2E %282014%29 Liquid chromatography%2Dmass spectrometry for the determination of chemical contaminants in food%2E rends Analyt Chem 59%3A 59�??72&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Hird SJ, Lau BPY, Schuhmacher R, Krska R. (2014) Liquid chromatography-mass spectrometry for the determination of chemical contaminants in food. rends Analyt Chem 59: 59?72

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Hird&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Liquid chromatography-mass spectrometry for the determination of chemical contaminants in food.&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=1

http://scholar.google.com/scholar?as_q=Liquid chromatography-mass spectrometry for the determination of chemical contaminants in food.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Hird&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Hoyerová K%2C Gaudinová A%2C Malbeck J%2C Dobrev PI%2C Kocábek T%2C Solcová B%2C Trávnícková A%2C Kamínek M%2E %282006%29 Efficiency of different methods of extraction and purification of cytokinins%2E Phytochemistry 67%2811%29%3A 1151�??1159&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Hoyerov� K, Gaudinov� A, Malbeck J, Dobrev PI, Koc�bek T, Solcov� B, Tr�vn�ckov� A, Kam�nek M. (2006) Efficiency of different methods of extraction and purification of cytokinins. Phytochemistry 67(11): 1151?1159

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Hoyerov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Efficiency of different methods of extraction and purification of cytokinins.&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=1

http://scholar.google.com/scholar?as_q=Efficiency of different methods of extraction and purification of cytokinins.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Hoyerov�?¡&as_ylo=2006&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Hruz T%2C Laule O%2C Szabo G%2C Wessendorp F%2C Bleuler S%2C Oertle L%2C Widmayer P%2C Gruissem W%2C Zimmermann P %282008%29 GENEVESTIGATOR V3%3A a reference expression database for the meta%2Danalysis of transcriptomes%2E Adv Bioinformatics 2008%3A 420747&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Hruz T, Laule O, Szabo G, Wessendorp F, Bleuler S, Oertle L, Widmayer P, Gruissem W, Zimmermann P (2008) GENEVESTIGATOR V3: a reference expression database for the meta-analysis of transcriptomes. Adv Bioinformatics 2008: 420747

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Hruz&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=&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=1

http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Hruz&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Hyötyläinen T %282013%29 Sample Collection%2C Storage and Preparation%2E In T Hyotylainen%2C SK Wiedmer%2C eds%2C Chromatographic Methods in Metabolomics%2E Royal Society of Chemistry%2C pp 11�??42&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Hy�tyl�inen T (2013) Sample Collection, Storage and Preparation. In T Hyotylainen, SK Wiedmer, eds, Chromatographic Methods in Metabolomics. Royal Society of Chemistry, pp 11?42

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Hy�?¶tyl�?¤inen&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Sample Collection, Storage and Preparation.&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=1

http://scholar.google.com/scholar?as_q=Sample Collection, Storage and Preparation.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Hy�?¶tyl�?¤inen&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Immanen J%2C Nieminen K%2C Smolander OP%2C Kojima M%2C Alonso Serra J%2C Koskinen P%2C Zhang J%2C Elo A%2C Mähönen AP%2C Street N%2C Bhalerao RP%2C Paulin L%2C Auvinen P%2C Sakakibara H%2C Helariutta Y %282016%29 Cytokinin and auxin display distinct but interconnected distribution and signaling profiles to stimulate cambial activity%2E Curr Biol 26%3A 1990�??1997&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Immanen J, Nieminen K, Smolander OP, Kojima M, Alonso Serra J, Koskinen P, Zhang J, Elo A, M�h�nen AP, Street N, Bhalerao RP, Paulin L, Auvinen P, Sakakibara H, Helariutta Y (2016) Cytokinin and auxin display distinct but interconnected distribution and signaling profiles to stimulate cambial activity. Curr Biol 26: 1990?1997

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Immanen&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Cytokinin and auxin display distinct but interconnected distribution and signaling profiles to stimulate cambial activity.&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=1

http://scholar.google.com/scholar?as_q=Cytokinin and auxin display distinct but interconnected distribution and signaling profiles to stimulate cambial activity.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Immanen&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Jin X%2C Wang RS%2C Zhu M%2C Jeon BW%2C Albert R%2C Chen S%2C Assmann SM %282013%29 Abscisic Acid%2DResponsive Guard Cell Metabolomes of Arabidopsis Wild%2DType and gpa1 G%2DProtein Mutants%2E Plant Cell 25%3A 4789�??4811&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Jin X, Wang RS, Zhu M, Jeon BW, Albert R, Chen S, Assmann SM (2013) Abscisic Acid-Responsive Guard Cell Metabolomes of Arabidopsis Wild-Type and gpa1 G-Protein Mutants. Plant Cell 25: 4789?4811

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Jin&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Abscisic Acid-Responsive Guard Cell Metabolomes of Arabidopsis Wild-Type and gpa1 G-Protein Mutants.&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=1

http://scholar.google.com/scholar?as_q=Abscisic Acid-Responsive Guard Cell Metabolomes of Arabidopsis Wild-Type and gpa1 G-Protein Mutants.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Jin&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Jiskrová E%2C Novák O%2C Pospíšilová H%2C Holubová K%2C Karády M%2C Galuszka P%2C Robert S%2C Frébort I %282016%29 Extra%2D and intracellular distribution of cytokinins in the leaves of monocots and dicots%2E N Biotechnol 33%3A 735�??742&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Jiskrov� E, Nov�k O, Posp�?ilov� H, Holubov� K, Kar�dy M, Galuszka P, Robert S, Fr�bort I (2016) Extra- and intracellular distribution of cytokinins in the leaves of monocots and dicots. N Biotechnol 33: 735?742

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Jiskrov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Extra- and intracellular distribution of cytokinins in the leaves of monocots and dicots.&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=1

http://scholar.google.com/scholar?as_q=Extra- and intracellular distribution of cytokinins in the leaves of monocots and dicots.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Jiskrov�?¡&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Kojima M%2C Kamada%2DNobusada T%2C Komatsu H%2C Takei K%2C Kuroha T%2C Mizutani M%2C Ashikari M%2C Ueguchi%2DTanaka M%2C Matsuoka M%2C Suzuki K%2C Sakakibara H %282009%29 Highly sensitive and high%2Dthroughput analysis of plant hormones using MS%2Dprobe modification and liquid chromatography%2Dtandem mass spectrometry%3A An application for hormone profiling in Oryza sativa%2E Plant Cell Physiol 50%3A 1201�??1214&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Kojima M, Kamada-Nobusada T, Komatsu H, Takei K, Kuroha T, Mizutani M, Ashikari M, Ueguchi-Tanaka M, Matsuoka M, Suzuki K, Sakakibara H (2009) Highly sensitive and high-throughput analysis of plant hormones using MS-probe modification and liquid chromatography-tandem mass spectrometry: An application for hormone profiling in Oryza sativa. Plant Cell Physiol 50: 1201?1214

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Kojima&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Highly sensitive and high-throughput analysis of plant hormones using MS-probe modification and liquid chromatography-tandem mass spectrometry: An application for hormone profiling in Oryza sativa.&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=1

http://scholar.google.com/scholar?as_q=Highly sensitive and high-throughput analysis of plant hormones using MS-probe modification and liquid chromatography-tandem mass spectrometry: An application for hormone profiling in Oryza sativa.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Kojima&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Lichtenthaler HK %281987%29 Chlorophylls and carotenoids%3A Pigments of photosynthetic biomembranes%2E Methods Enzymol 148%3A 350�??382&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Lichtenthaler HK (1987) Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes. Methods Enzymol 148: 350?382

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Lichtenthaler&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes.&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=1

http://scholar.google.com/scholar?as_q=Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Lichtenthaler&as_ylo=1987&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Ljung K%2C Sandberg G%2C Moritz T%2E %282010%29 Methods of plant hormone analysis%2E In PJ Davies%2C ed%2E%2C Plant hormones%3A Biosynthesis%2C Signal Transduction%2C Action%21 Springer%2C pp%2E 717�??740%2E&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ljung K, Sandberg G, Moritz T. (2010) Methods of plant hormone analysis. In PJ Davies, ed., Plant hormones: Biosynthesis, Signal Transduction, Action! Springer, pp. 717?740.

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ljung&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Methods of plant hormone analysis.&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=1

http://scholar.google.com/scholar?as_q=Methods of plant hormone analysis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ljung&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1



Maštovská K, Lehotay SJ (2003) Practical approaches to fast gas chromatography–mass spectrometry. J Chromatogr A 1000: 153–180Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Müller A, Düchting P, Weiler E (2002) A multiplex GC-MS/MS technique for the sensitive and quantitative single-run analysis of acidicphytohormones and related compounds, and its application to Arabidopsis thaliana. Planta 216: 44–56


Müller M, Munné-Bosch S (2011) Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled toelectrospray ionization tandem mass spectrometry. Plant Methods 7: 37


Munns R. Tester M (2008) Mechanisms of salinity tolerance. Annu Rev Plant Biol 59: 651–681Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Novák O, Hényková E, Sairanen I, Kowalczyk M, Pospíšil T, Ljung K (2012) Tissue-specific profiling of the Arabidopsis thaliana auxinmetabolome. Plant J 72: 523–536


Novák O, Napier R, Ljung K (2017) Zooming In on Plant Hormone Analysis: Tissue- and Cell-Specific Approaches. Annu. Rev. Plant Biol.68: 323–348


Nováková L (2013) Challenges in the development of bioanalytical liquid chromatography-mass spectrometry method with emphasis onfast analysis. J Chromatogr A 1292: 25–37


Nováková L, Vlčková H (2009) A review of current trends and advances in modern bio-analytical methods: Chromatography and samplepreparation. Anal Chim Acta 656: 8–35


Oklestkova J, Tarkowská D, Eyer L, Elbert T, Marek A, Smržová Z, Novák O, Fránek M, Zhabinskii VN, Strnad M (2017) Immunoaffinitychromatography combined with tandem mass spectrometry: a new tool for the selective capture and analysis of brassinosteroid planthormones. Talanta 170: 432–440


Oliveros, J.C. (2007-2015) Venny. An interactive tool for comparing lists with Venn's diagrams.http://bioinfogp.cnb.csic.es/tools/venny/index.html

O'Mahony J, Clarke L, Whelan M, O'Kennedy R, Lehotay SJ, Danaher M (2013) The use of ultra-high pressure liquid chromatographywith tandem mass spectrometric detection in the analysis of agrochemical residues and mycotoxins in food - challenges andapplications. J Chromatogr A 1292: 83–95


Pan X, Welti R, Wang X (2008) Simultaneous quantification of major phytohormones and related compounds in crude plant extracts byliquid chromatography–electrospray tandem mass spectrometry. Phytochemistry 69: 1773–1781


Pěnčík A, Rolčík J, Novák O, Magnus V, Barták P, Buchtík R, Salopek-Sondi B, Strnad M (2009) Isolation of novel indole-3-acetic acidconjugates by immunoaffinity extraction. Talanta 80: 651–655


http://www.ncbi.nlm.nih.gov/pubmed?term=Martín%2DFernández JA%2C Barceló%2DVidal C%2C Pawlowsky%2DGlahn V %282003%29%2E Dealing with zeros and missing values in compositional data sets using nonparametric imputation%2E Math Geol 35%3A 253�??278%2E&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Mart�n-Fern�ndez JA, Barcel�-Vidal C, Pawlowsky-Glahn V (2003). Dealing with zeros and missing values in compositional data sets using nonparametric imputation. Math Geol 35: 253?278.

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Mart�?n-Fern�?¡ndez&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Dealing with zeros and missing values in compositional data sets using nonparametric imputation&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=1

http://scholar.google.com/scholar?as_q=Dealing with zeros and missing values in compositional data sets using nonparametric imputation&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Mart�?n-Fern�?¡ndez&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Maštovská K%2C Lehotay SJ %282003%29 Practical approaches to fast gas chromatography�??mass spectrometry%2E J Chromatogr A 1000%3A 153�??180&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ma?tovsk� K, Lehotay SJ (2003) Practical approaches to fast gas chromatography?mass spectrometry. J Chromatogr A 1000: 153?180

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ma�?¡tovsk�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Practical approaches to fast gas chromatographyâ�?�?mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Practical approaches to fast gas chromatographyâ�?�?mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ma�?¡tovsk�?¡&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Müller A%2C Düchting P%2C Weiler E %282002%29 A multiplex GC%2DMS%2FMS technique for the sensitive and quantitative single%2Drun analysis of acidic phytohormones and related compounds%2C and its application to Arabidopsis thaliana%2E Planta 216%3A 44�??56&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=M�ller A, D�chting P, Weiler E (2002) A multiplex GC-MS/MS technique for the sensitive and quantitative single-run analysis of acidic phytohormones and related compounds, and its application to Arabidopsis thaliana. Planta 216: 44?56

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=M�?¼ller&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=A multiplex GC-MS/MS technique for the sensitive and quantitative single-run analysis of acidic phytohormones and related compounds, and its application to Arabidopsis thaliana.&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=1

http://scholar.google.com/scholar?as_q=A multiplex GC-MS/MS technique for the sensitive and quantitative single-run analysis of acidic phytohormones and related compounds, and its application to Arabidopsis thaliana.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=M�?¼ller&as_ylo=2002&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=M�ller M%2C Munn�%2DBosch S %282011%29 Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry%2E Plant Methods 7%3A 37&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=M�ller M, Munn�-Bosch S (2011) Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry. Plant Methods 7: 37

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Müller&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Müller&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Munns R%2E Tester M %282008%29 Mechanisms of salinity tolerance%2E Annu Rev Plant Biol 59%3A 651�??681&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Munns R. Tester M (2008) Mechanisms of salinity tolerance. Annu Rev Plant Biol 59: 651?681

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Munns&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Mechanisms of salinity tolerance.&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=1

http://scholar.google.com/scholar?as_q=Mechanisms of salinity tolerance.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Munns&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Novák O%2C Hényková E%2C Sairanen I%2C Kowalczyk M%2C Pospíšil T%2C Ljung K %282012%29 Tissue%2Dspecific profiling of the Arabidopsis thaliana auxin metabolome%2E Plant J 72%3A 523�??536&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Nov�k O, H�nykov� E, Sairanen I, Kowalczyk M, Posp�?il T, Ljung K (2012) Tissue-specific profiling of the Arabidopsis thaliana auxin metabolome. Plant J 72: 523?536

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nov�?¡k&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Tissue-specific profiling of the Arabidopsis thaliana auxin metabolome.&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=1

http://scholar.google.com/scholar?as_q=Tissue-specific profiling of the Arabidopsis thaliana auxin metabolome.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nov�?¡k&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Novák O%2C Napier R%2C Ljung K %282017%29 Zooming In on Plant Hormone Analysis%3A Tissue%2D and Cell%2DSpecific Approaches%2E Annu%2E Rev%2E Plant Biol%2E 68%3A 323�??348&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Nov�k O, Napier R, Ljung K (2017) Zooming In on Plant Hormone Analysis: Tissue- and Cell-Specific Approaches. Annu. Rev. Plant Biol. 68: 323?348

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nov�?¡k&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Zooming In on Plant Hormone Analysis: Tissue- and Cell-Specific Approaches.&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=1

http://scholar.google.com/scholar?as_q=Zooming In on Plant Hormone Analysis: Tissue- and Cell-Specific Approaches.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nov�?¡k&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Nováková L %282013%29 Challenges in the development of bioanalytical liquid chromatography%2Dmass spectrometry method with emphasis on fast analysis%2E J Chromatogr A 1292%3A 25�??37&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Nov�kov� L (2013) Challenges in the development of bioanalytical liquid chromatography-mass spectrometry method with emphasis on fast analysis. J Chromatogr A 1292: 25?37

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nov�?¡kov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Challenges in the development of bioanalytical liquid chromatography-mass spectrometry method with emphasis on fast analysis.&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=1

http://scholar.google.com/scholar?as_q=Challenges in the development of bioanalytical liquid chromatography-mass spectrometry method with emphasis on fast analysis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nov�?¡kov�?¡&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Nováková L%2C Vlčková H %282009%29 A review of current trends and advances in modern bio%2Danalytical methods%3A Chromatography and sample preparation%2E Anal Chim Acta 656%3A 8�??35&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Nov�kov� L, Vl?kov� H (2009) A review of current trends and advances in modern bio-analytical methods: Chromatography and sample preparation. Anal Chim Acta 656: 8?35

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nov�?¡kov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=A review of current trends and advances in modern bio-analytical methods: Chromatography and sample preparation.&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=1

http://scholar.google.com/scholar?as_q=A review of current trends and advances in modern bio-analytical methods: Chromatography and sample preparation.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nov�?¡kov�?¡&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Oklestkova J%2C Tarkowská D%2C Eyer L%2C Elbert T%2C Marek A%2C Smržová Z%2C Novák O%2C Fránek M%2C Zhabinskii VN%2C Strnad M %282017%29 Immunoaffinity chromatography combined with tandem mass spectrometry%3A a new tool for the selective capture and analysis of brassinosteroid plant hormones%2E Talanta 170%3A 432�??440&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Oklestkova J, Tarkowsk� D, Eyer L, Elbert T, Marek A, Smr?ov� Z, Nov�k O, Fr�nek M, Zhabinskii VN, Strnad M (2017) Immunoaffinity chromatography combined with tandem mass spectrometry: a new tool for the selective capture and analysis of brassinosteroid plant hormones. Talanta 170: 432?440

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Oklestkova&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Immunoaffinity chromatography combined with tandem mass spectrometry: a new tool for the selective capture and analysis of brassinosteroid plant hormones.&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=1

http://scholar.google.com/scholar?as_q=Immunoaffinity chromatography combined with tandem mass spectrometry: a new tool for the selective capture and analysis of brassinosteroid plant hormones.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Oklestkova&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=O%27Mahony J%2C Clarke L%2C Whelan M%2C O%27Kennedy R%2C Lehotay SJ%2C Danaher M %282013%29 The use of ultra%2Dhigh pressure liquid chromatography with tandem mass spectrometric detection in the analysis of agrochemical residues and mycotoxins in food %2D challenges and applications%2E J Chromatogr A 1292%3A 83�??95&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=O'Mahony J, Clarke L, Whelan M, O'Kennedy R, Lehotay SJ, Danaher M (2013) The use of ultra-high pressure liquid chromatography with tandem mass spectrometric detection in the analysis of agrochemical residues and mycotoxins in food - challenges and applications. J Chromatogr A 1292: 83?95

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=O'Mahony&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=The use of ultra-high pressure liquid chromatography with tandem mass spectrometric detection in the analysis of agrochemical residues and mycotoxins in food - challenges and applications.&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=1

http://scholar.google.com/scholar?as_q=The use of ultra-high pressure liquid chromatography with tandem mass spectrometric detection in the analysis of agrochemical residues and mycotoxins in food - challenges and applications.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=O'Mahony&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Pan X%2C Welti R%2C Wang X %282008%29 Simultaneous quantification of major phytohormones and related compounds in crude plant extracts by liquid chromatography�??electrospray tandem mass spectrometry%2E Phytochemistry 69%3A 1773�??1781&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Pan X, Welti R, Wang X (2008) Simultaneous quantification of major phytohormones and related compounds in crude plant extracts by liquid chromatography?electrospray tandem mass spectrometry. Phytochemistry 69: 1773?1781

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Pan&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Simultaneous quantification of major phytohormones and related compounds in crude plant extracts by liquid chromatographyâ�?�?electrospray tandem mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Simultaneous quantification of major phytohormones and related compounds in crude plant extracts by liquid chromatographyâ�?�?electrospray tandem mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Pan&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1



Pěnčík A, Simonovik B, Petersson SV, Henyková E, Simon S, Greenham K, Zhang Y, Kowalczyk M, Estelle M, Zažímalová E, Novák O,Sandberg G, Ljung K (2013) Regulation of auxin homeostasis and gradients in Arabidopsis roots through the formation of the indole-3-acetic acid catabolite 2-oxindole-3-acetic acid. Plant Cell 25: 3858–3870


Petersson SV, Johansson AI, Kowalczyk M, Makoveychuk A, Wang JY, Moritz T, Grebe M, Benfey PN, Sandberg G, Ljung K (2009) Anauxin gradient and maximum in the Arabidopsis root apex shown by high-resolution cell-specific analysis of IAA distribution andsynthesis. Plant Cell 21: 1659–1668


Plačková L, Oklestkova J, Pospíšková K, Poláková K, Buček J, Stýskala J, Zatloukal M, Šafařík I, Zbořil R, Strnad M, Doležal K, Novák O(2017) Microscale magnetic microparticle-based immunopurification of cytokinins from Arabidopsis root apex. Plant J 89: 1065–1075


Pratt JJ (1986) Isotope dilution analysis using chromatographic separation of isotopic forms of the compound to be measured. Ann ClinBiochem 23: 251–276


Ranocha P, Dima O, Nagy R, Felten J, Corratgé-Faillie C, Novák O, Morreel K, Lacombe B, Martinez Y, Pfrunder S, Jin X, Renou JP,Thibaud JB, Ljung K, Fischer U, Martinoia E, Boerjan W, Goffner D (2013) Arabidopsis WAT1 is a vacuolar auxin transport facilitatorrequired for auxin homoeostasis. Nat Commun 4: 2625


Rittenberg D, Foster GL (1940) A new procedure for quantitative analysis by isotope dilution, with application to the determination ofamino acids and fatty acids. J Biol Chem 133: 737–744


Ryu H, Cho Y (2015) Plant hormones in salt stress tolerance. J Plant Biol 58: 147–155Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Saito K, Hirai MY, Yonekura-Sakakibara K (2008) Decoding genes with coexpression networks and metabolomics: ‘majority report byprecogs’. Trends Plant Sci 13: 36–43


Schäfer M, Brütting C, Baldwin IT, Kallenbach M (2016) High-throughput quantification of more than 100 primary- and secondary-metabolites, and phytohormones by a single solid-phase extraction based sample preparation with analysis by UHPLC-HESI-MS/MS.Plant Methods 12: 30


Svačinová J, Novák O, Plačková L, Lenobel R, Holík J, Strnad M, Doležal K (2012) A new approach for cytokinin isolation fromArabidopsis tissues using miniaturized purification: Pipette tip solid-phase extraction. Plant Methods 8: 17


Tarkowská D, Novák O, Floková K, Tarkowski P, Turečková V, Grúz J, Rolčík J, Strnad M (2014). Quo vadis plant hormone analysis?Planta 240: 55–76

Tarkowská D, Novák O, Oklestkova J, Strnad M (2016). The determination of 22 natural brassinosteroids in a minute sample of planttissue by UHPLC–ESI–MS/MS. Anal Bioanal Chem 408: 6799–6812



http://www.ncbi.nlm.nih.gov/pubmed?term=P�?nčík A%2C Rolčík J%2C Novák O%2C Magnus V%2C Barták P%2C Buchtík R%2C Salopek%2DSondi B%2C Strnad M %282009%29 Isolation of novel indole%2D3%2Dacetic acid conjugates by immunoaffinity extraction%2E Talanta 80%3A 651�??655&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=P?n?�k A, Rol?�k J, Nov�k O, Magnus V, Bart�k P, Bucht�k R, Salopek-Sondi B, Strnad M (2009) Isolation of novel indole-3-acetic acid conjugates by immunoaffinity extraction. Talanta 80: 651?655

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=P�?�?n�?��?k&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Isolation of novel indole-3-acetic acid conjugates by immunoaffinity extraction.&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=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=P�?nčík A%2C Simonovik B%2C Petersson SV%2C Henyková E%2C Simon S%2C Greenham K%2C Zhang Y%2C Kowalczyk M%2C Estelle M%2C Zažímalová E%2C Novák O%2C Sandberg G%2C Ljung K %282013%29 Regulation of auxin homeostasis and gradients in Arabidopsis roots through the formation of the indole%2D3%2Dacetic acid catabolite 2%2Doxindole%2D3%2Dacetic acid%2E Plant Cell 25%3A 3858�??3870&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=P?n?�k A, Simonovik B, Petersson SV, Henykov� E, Simon S, Greenham K, Zhang Y, Kowalczyk M, Estelle M, Za?�malov� E, Nov�k O, Sandberg G, Ljung K (2013) Regulation of auxin homeostasis and gradients in Arabidopsis roots through the formation of the indole-3-acetic acid catabolite 2-oxindole-3-acetic acid. Plant Cell 25: 3858?3870

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=P�?�?n�?��?k&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Regulation of auxin homeostasis and gradients in Arabidopsis roots through the formation of the indole-3-acetic acid catabolite 2-oxindole-3-acetic acid.&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=1

http://scholar.google.com/scholar?as_q=Regulation of auxin homeostasis and gradients in Arabidopsis roots through the formation of the indole-3-acetic acid catabolite 2-oxindole-3-acetic acid.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=P�?�?n�?��?k&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

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http://search.crossref.org/?page=1&rows=2&q=Petersson SV, Johansson AI, Kowalczyk M, Makoveychuk A, Wang JY, Moritz T, Grebe M, Benfey PN, Sandberg G, Ljung K (2009) An auxin gradient and maximum in the Arabidopsis root apex shown by high-resolution cell-specific analysis of IAA distribution and synthesis. Plant Cell 21: 1659?1668

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Petersson&hl=en&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=Plačková L%2C Oklestkova J%2C Pospíšková K%2C Poláková K%2C Buček J%2C Stýskala J%2C Zatloukal M%2C Šafa�?ík I%2C Zbo�?il R%2C Strnad M%2C Doležal K%2C Novák O %282017%29 Microscale magnetic microparticle%2Dbased immunopurification of cytokinins from Arabidopsis root apex%2E Plant J 89%3A 1065�??1075&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Pla?kov� L, Oklestkova J, Posp�?kov� K, Pol�kov� K, Bu?ek J, St�skala J, Zatloukal M, ?afa?�k I, Zbo?il R, Strnad M, Dole?al K, Nov�k O (2017) Microscale magnetic microparticle-based immunopurification of cytokinins from Arabidopsis root apex. Plant J 89: 1065?1075

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Pla�?�kov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Microscale magnetic microparticle-based immunopurification of cytokinins from Arabidopsis root apex.&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=1

http://scholar.google.com/scholar?as_q=Microscale magnetic microparticle-based immunopurification of cytokinins from Arabidopsis root apex.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Pla�?�kov�?¡&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Pratt JJ %281986%29 Isotope dilution analysis using chromatographic separation of isotopic forms of the compound to be measured%2E Ann Clin Biochem 23%3A 251�??276&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Pratt JJ (1986) Isotope dilution analysis using chromatographic separation of isotopic forms of the compound to be measured. Ann Clin Biochem 23: 251?276

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Pratt&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Isotope dilution analysis using chromatographic separation of isotopic forms of the compound to be measured.&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=1

http://scholar.google.com/scholar?as_q=Isotope dilution analysis using chromatographic separation of isotopic forms of the compound to be measured.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Pratt&as_ylo=1986&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Ranocha P%2C Dima O%2C Nagy R%2C Felten J%2C Corratg�%2DFaillie C%2C Nov�k O%2C Morreel K%2C Lacombe B%2C Martinez Y%2C Pfrunder S%2C Jin X%2C Renou JP%2C Thibaud JB%2C Ljung K%2C Fischer U%2C Martinoia E%2C Boerjan W%2C Goffner D %282013%29 Arabidopsis WAT1 is a vacuolar auxin transport facilitator required for auxin homoeostasis%2E Nat Commun 4%3A 2625&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ranocha P, Dima O, Nagy R, Felten J, Corratg�-Faillie C, Nov�k O, Morreel K, Lacombe B, Martinez Y, Pfrunder S, Jin X, Renou JP, Thibaud JB, Ljung K, Fischer U, Martinoia E, Boerjan W, Goffner D (2013) Arabidopsis WAT1 is a vacuolar auxin transport facilitator required for auxin homoeostasis. Nat Commun 4: 2625

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ranocha&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Arabidopsis WAT1 is a vacuolar auxin transport facilitator required for auxin homoeostasis.&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=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=Rittenberg D%2C Foster GL %281940%29 A new procedure for quantitative analysis by isotope dilution%2C with application to the determination of amino acids and fatty acids%2E J Biol Chem 133%3A 737�??744&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Rittenberg D, Foster GL (1940) A new procedure for quantitative analysis by isotope dilution, with application to the determination of amino acids and fatty acids. J Biol Chem 133: 737?744

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http://www.ncbi.nlm.nih.gov/pubmed?term=Ryu H%2C Cho Y %282015%29 Plant hormones in salt stress tolerance%2E J Plant Biol 58%3A 147�??155&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ryu H, Cho Y (2015) Plant hormones in salt stress tolerance. J Plant Biol 58: 147?155

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ryu&hl=en&c2coff=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=Saito K%2C Hirai MY%2C Yonekura%2DSakakibara K %282008%29 Decoding genes with coexpression networks and metabolomics%3A �??majority report by precogs�??%2E Trends Plant Sci 13%3A 36�??43&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Saito K, Hirai MY, Yonekura-Sakakibara K (2008) Decoding genes with coexpression networks and metabolomics: ?majority report by precogs?. Trends Plant Sci 13: 36?43

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http://www.ncbi.nlm.nih.gov/pubmed?term=Sch�fer M%2C Br�tting C%2C Baldwin IT%2C Kallenbach M %282016%29 High%2Dthroughput quantification of more than 100 primary%2D and secondary%2Dmetabolites%2C and phytohormones by a single solid%2Dphase extraction based sample preparation with analysis by UHPLC%2DHESI%2DMS%2FMS%2E Plant Methods 12%3A 30&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Sch�fer M, Br�tting C, Baldwin IT, Kallenbach M (2016) High-throughput quantification of more than 100 primary- and secondary-metabolites, and phytohormones by a single solid-phase extraction based sample preparation with analysis by UHPLC-HESI-MS/MS. Plant Methods 12: 30

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http://scholar.google.com/scholar?as_q=High-throughput quantification of more than 100 primary- and secondary-metabolites, and phytohormones by a single solid-phase extraction based sample preparation with analysis by UHPLC-HESI-MS/MS.&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=1

http://scholar.google.com/scholar?as_q=High-throughput quantification of more than 100 primary- and secondary-metabolites, and phytohormones by a single solid-phase extraction based sample preparation with analysis by UHPLC-HESI-MS/MS.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Schäfer&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Svačinová J%2C Novák O%2C Plačková L%2C Lenobel R%2C Holík J%2C Strnad M%2C Doležal K %282012%29 A new approach for cytokinin isolation from Arabidopsis tissues using miniaturized purification%3A Pipette tip solid%2Dphase extraction%2E Plant Methods 8%3A 17&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Sva?inov� J, Nov�k O, Pla?kov� L, Lenobel R, Hol�k J, Strnad M, Dole?al K (2012) A new approach for cytokinin isolation from Arabidopsis tissues using miniaturized purification: Pipette tip solid-phase extraction. Plant Methods 8: 17

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sva�?�inov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=A new approach for cytokinin isolation from Arabidopsis tissues using miniaturized purification: Pipette tip solid-phase extraction.&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=1

http://scholar.google.com/scholar?as_q=A new approach for cytokinin isolation from Arabidopsis tissues using miniaturized purification: Pipette tip solid-phase extraction.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sva�?�inov�?¡&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Tarkowská D%2C Novák O%2C Oklestkova J%2C Strnad M %282016%29%2E The determination of 22 natural brassinosteroids in a minute sample of plant tissue by UHPLC�??ESI�??MS%2FMS%2E Anal Bioanal Chem 408%3A 6799�??6812&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Tarkowsk� D, Nov�k O, Oklestkova J, Strnad M (2016). The determination of 22 natural brassinosteroids in a minute sample of plant tissue by UHPLC?ESI?MS/MS. Anal Bioanal Chem 408: 6799?6812

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Tarkowsk�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=The determination of 22 natural brassinosteroids in a minute sample of plant tissue by UHPLCâ�?�?ESIâ�?�?MS/MS.&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=1

http://scholar.google.com/scholar?as_q=The determination of 22 natural brassinosteroids in a minute sample of plant tissue by UHPLCâ�?�?ESIâ�?�?MS/MS.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tarkowsk�?¡&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1


Tarkowski P, Václavíková K, Novák O, Pertry I, Hanuš J, Whenham R, Vereecke D, Šebela M, Strnad M (2010) Analysis of 2-methylthio-derivatives of isoprenoid cytokinins by liquid chromatography–tandem mass spectrometry. Anal Chim Acta 680, 86–91


Turečková V, Novák O, Strnad M. (2009) Profiling ABA metabolites in Nicotiana tabacum L. leaves by ultra-performance liquidchromatography–electrospray tandem mass spectrometry. Talanta 80: 390–399


Urbanová T, Tarkowská D, Novák O, Hedden P, Strnad M (2013) Analysis of gibberellins as free acids by ultra performance liquidchromatography–tandem mass spectrometry. Talanta 112: 85–94


Vanstraelen M, Benková E (2012) Hormonal interactions in the regulation of plant development. Annu Rev Cell Dev Biol 28: 463–487Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Wang Q, Cai WJ, Yu L, Ding J, Feng YQ (2017). Comprehensive profiling of phytohormones in honey by sequential liquid–liquidextraction coupled with liquid chromatography–mass spectrometry. J Agric Food Chem 65: 575–585


Záveská Drábková L, Dobrev PI, Motyka V (2015) Phytohormone profiling across the Bryophytes. PLoS One 10: e0125411Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Zwanenburg B, Pospíšil T, Ćavar Zeljković S (2016) Strigolactones: new plant hormones in action. Planta 243: 1311–1326Pubmed: Author and TitleCrossRef: Author and TitleGoogle Scholar: Author Only Title Only Author and Title


http://www.ncbi.nlm.nih.gov/pubmed?term=Tarkowski P%2C Václavíková K%2C Novák O%2C Pertry I%2C Hanuš J%2C Whenham R%2C Vereecke D%2C Šebela M%2C Strnad M %282010%29 Analysis of 2%2Dmethylthio%2Dderivatives of isoprenoid cytokinins by liquid chromatography�??tandem mass spectrometry%2E Anal Chim Acta 680%2C 86�??91&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Tarkowski P, V�clav�kov� K, Nov�k O, Pertry I, Hanu? J, Whenham R, Vereecke D, ?ebela M, Strnad M (2010) Analysis of 2-methylthio-derivatives of isoprenoid cytokinins by liquid chromatography?tandem mass spectrometry. Anal Chim Acta 680, 86?91

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http://scholar.google.com/scholar?as_q=Analysis of 2-methylthio-derivatives of isoprenoid cytokinins by liquid chromatographyâ�?�?tandem mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tarkowski&as_ylo=2010&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Turečková V%2C Novák O%2C Strnad M%2E %282009%29 Profiling ABA metabolites in Nicotiana tabacum L%2E leaves by ultra%2Dperformance liquid chromatography�??electrospray tandem mass spectrometry%2E Talanta 80%3A 390�??399&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Ture?kov� V, Nov�k O, Strnad M. (2009) Profiling ABA metabolites in Nicotiana tabacum L. leaves by ultra-performance liquid chromatography?electrospray tandem mass spectrometry. Talanta 80: 390?399

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ture�?�kov�?¡&hl=en&c2coff=1

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http://scholar.google.com/scholar?as_q=Profiling ABA metabolites in Nicotiana tabacum L.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ture�?�kov�?¡&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Urbanová T%2C Tarkowská D%2C Novák O%2C Hedden P%2C Strnad M %282013%29 Analysis of gibberellins as free acids by ultra performance liquid chromatography�??tandem mass spectrometry%2E Talanta 112%3A 85�??94&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Urbanov� T, Tarkowsk� D, Nov�k O, Hedden P, Strnad M (2013) Analysis of gibberellins as free acids by ultra performance liquid chromatography?tandem mass spectrometry. Talanta 112: 85?94

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Urbanov�?¡&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Analysis of gibberellins as free acids by ultra performance liquid chromatographyâ�?�?tandem mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Analysis of gibberellins as free acids by ultra performance liquid chromatographyâ�?�?tandem mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Urbanov�?¡&as_ylo=2013&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Vanstraelen M%2C Benková E %282012%29 Hormonal interactions in the regulation of plant development%2E Annu Rev Cell Dev Biol 28%3A 463�??487&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Vanstraelen M, Benkov� E (2012) Hormonal interactions in the regulation of plant development. Annu Rev Cell Dev Biol 28: 463?487

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Vanstraelen&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Hormonal interactions in the regulation of plant development.&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=1

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http://www.ncbi.nlm.nih.gov/pubmed?term=Wang Q%2C Cai WJ%2C Yu L%2C Ding J%2C Feng YQ %282017%29%2E Comprehensive profiling of phytohormones in honey by sequential liquid�??liquid extraction coupled with liquid chromatography�??mass spectrometry%2E J Agric Food Chem 65%3A 575�??585&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Wang Q, Cai WJ, Yu L, Ding J, Feng YQ (2017). Comprehensive profiling of phytohormones in honey by sequential liquid?liquid extraction coupled with liquid chromatography?mass spectrometry. J Agric Food Chem 65: 575?585

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Wang&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Comprehensive profiling of phytohormones in honey by sequential liquidâ�?�?liquid extraction coupled with liquid chromatographyâ�?�?mass spectrometry.&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=1

http://scholar.google.com/scholar?as_q=Comprehensive profiling of phytohormones in honey by sequential liquidâ�?�?liquid extraction coupled with liquid chromatographyâ�?�?mass spectrometry.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Wang&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Z�vesk� Dr�bkov� L%2C Dobrev PI%2C Motyka V %282015%29 Phytohormone profiling across the Bryophytes%2E PLoS One 10%3A e0125411&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Z�vesk� Dr�bkov� L, Dobrev PI, Motyka V (2015) Phytohormone profiling across the Bryophytes. PLoS One 10: e0125411

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Záveská&hl=en&c2coff=1

http://scholar.google.com/scholar?as_q=Phytohormone profiling across the Bryophytes.&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=1

http://scholar.google.com/scholar?as_q=Phytohormone profiling across the Bryophytes.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Záveská&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

http://www.ncbi.nlm.nih.gov/pubmed?term=Zwanenburg B%2C Pospíšil T%2C �?avar Zeljkovi�? S %282016%29 Strigolactones%3A new plant hormones in action%2E Planta 243%3A 1311�??1326&dopt=abstract

http://search.crossref.org/?page=1&rows=2&q=Zwanenburg B, Posp�?il T, ?avar Zeljkovi? S (2016) Strigolactones: new plant hormones in action. Planta 243: 1311?1326

http://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Zwanenburg&hl=en&c2coff=1

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RUNNING TITLE CORRESPONDING AUTHOR 12 13 14 15 … · 27.04.2018 · 86 classes together with their precursors and metabolites, for the following reasons. 87 Phytohormones are naturally