Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2021 Feb 18;16(2):e0247276. doi: 10.1371/journal.pone.0247276

Quantitative analysis of seven plant hormones in Lotus japonicus using standard addition method

Takuyu Hashiguchi 1, Masatsugu Hashiguchi 1, Hidenori Tanaka 1, Koki Fukushima 1, Takahiro Gondo 1, Ryo Akashi 1,*
Editor: Raffaella Balestrini2
PMCID: PMC7891737  PMID: 33600422

Abstract

Plant hormones have been identified to be versatile signaling molecules essential for plant growth, development, and stress response. Their content levels vary depending on the species, and they also change in response to any external stimuli. Thus, simultaneous quantification of multiple plant hormones is required to understand plant physiology. Sensitive and quantitative analysis using liquid chromatography-linked mass spectrometry (LC-MS/MS) has been used in detecting plant hormones; however, quantification without stable isotopes is yet to be established. In this study, we quantified seven representative plant hormones of Lotus japonicus, which is a model legume for standard addition method. Accurate masses for monoisotopic ions of seven phytohormones were determined for high-resolution mass spectrometry (HR-MS). Selected ion monitoring (SIM) mode based on accurate masses was used in detecting phytohormones in the roots, stems, and leaves. Evaluation of matrix effects showed ion suppression ranging from 10.2% to 87.3%. Both stable isotope dilution and standard addition methods were able to detect plant hormones in the roots, stems, and leaves, with no significant differences in using both approaches and thus a standard addition method can be used to quantify phytohormones in L. japonicus. The method will be effective, especially when stable isotopes are not available to correct for matrix effects.

Introduction

Plant hormones are identified as essential small molecules implicated in a variety of fundamental biological processes, including growth, development, and stress response [1]. These hormones are classified into nine groups: auxins, cytokinins, gibberellins, ethylene, abscisic acid, salicylic acid, jasmonic acids, strigolactones, and brassinosteroids. Each class shows bioactivities alone and in combination with other hormones, which is generally known as hormonal crosstalk [2]. Therefore, quantifying multiple plant hormones simultaneously is required to understand plant physiology. Detecting trace amounts of phytohormones in plant tissues employs two major analytical tools, that is, gas chromatography coupled with mass spectrometry (GC-MS) [3] and liquid chromatography coupled to electrospray tandem mass spectrometry (LC-ESI-MS/MS) [4], methods which have been used over the last decade. LC-ESI-MS/MS-based quantitative analysis can elucidate plant hormonomics, taking advantage of high selectivity, sensitivity, and specificity for target compounds [5–8]. Unlike GC-MS, electrospray ionization (ESI) is utilized in LC-MS/MS for ionizing analytes of a wide range of polarities without derivatization; however, this method is limited by matrix effects, such as ion enhancement or ion suppression by co-eluting compounds that interfere with target analyte quantification [9]. Several approaches have been taken to date [10–12] in an attempt to mitigate effects and ensure accurate quantitation. First is by reducing the matrix via partial purification, dilution of samples, and injection of small volumes of sample [13]. Second is by changing the ionization mode from ESI to atmospheric pressure chemical ionization (APCI) [14]. Third is by calibrating the matrix effects by applying stable isotope dilution, matrix matching, or standard addition. Plant hormones are often quantified using stable isotope dilution, which involves the addition of stable isotope-labelled counterparts to target analytes [5–7,15,16]. Stable isotope-labelled hormones have substantially the same chemical properties as target compounds. Matrix effects are considered identical with and without labelling, allowing accurate calibration of matrix effects. However, stable isotope labelling is deemed expensive and sometimes unavailable for minor phytohormone metabolites. Matrix matching is also used to calibrate matrix effects; it is often applied to detect drugs and agricultural chemicals [17–19]. This technique can be used without stable isotopes, but it requires a sample matrix without target analyte and is thus not applicable to endogenous compounds in tissues. Another method is standard addition that can be applicable, in theory, to all compounds [12,20]. Standard addition uses actual samples to create individual calibration plots. An analyte is present in both the calibration standards and sample, allowing correction of the matrix effect without stable isotopes. Standard addition is laborious in terms of preparing the calibration standards by sample, but it is still promising especially when stable isotope-labelled phytohormones are unavailable. Nevertheless, there are no reports demonstrating its ability in detecting plant hormones.

In this study, we have validated the simultaneous quantification of seven major plant hormones by standard addition using high-resolution mass spectrometry (HR-MS). We focused on Lotus japonicus, a model legume, and quantified plant hormones in its roots, stems, and leaves. The matrix effects were then examined by comparing standards in solvent with standards in matrix. This method was also compared with stable isotope addition. A detailed protocol was developed and is discussed.

Methods and materials

Materials

MG20, an experimental strain of Lotus japonicus, was obtained from LegumeBase in the National BioResource Project (https://www.legumebase.brc.miyazaki-u.ac.jp/). Isotopically labelled internal standards including [2H2]-gibberellin A4 (GA4), [2H6]-(+)-cis,trans-abscisic acid (ABA), [2H3]-brassinolide (BL), [2H4]-salicylic acid (SA), [15N4]-trans-zeatin (tZ), [15N4]-cis-zeatin (cZ), [2H6]-(±)-jasmonic acid (JA), and [2H5]-indole-3-acetic acid (IAA) were purchased from OlChemIm Ltd. (Olomouc, Czech Republic). Gibberellin A4 (GA4) was purchased from Santa Cruz Biotechnology, Inc. (CA, USA). Abscisic acid (ABA), trans-zeatin (tZ), and jasmonic acid (JA) were obtained from Tokyo Kasei Kogyo Co. (Tokyo, Japan). Salicylic acid (SA) and indole-3-acetic acid (IAA) were purchased from Wako Pure Chemical Industries Ltd. (Osaka, Japan). Brassinolide (BL) was from Cayman Chemical (MI, USA). cis-Zeatin (cZ) was from Santa Cruz Biotechnology Inc. Quartz sand was obtained from Tochu Co. (Aichi, Japan). All the other chemicals were the highest-grade commercially available products.

Growth condition

Lotus japonicus seeds were scarified, subjected to water absorption for 30 min, and sown in quartz sand. The seeds were then germinated at 25°C and grown in a plant growth chamber with daily cycle of 16 hours of light at 25°C and 8 hours of dark at 23°C (BioTRON; Nippon Medical & Chemical Instruments Co., Ltd.). The plants were fertilized with 1000-fold diluted Hyponex® solution (N:P:K = 6:10:5) once a week. One-month-old L. japonicus were used in extracting plant hormones.

Sample preparation

Extraction for plant hormones has been conducted utilizing a previously established protocol with minor modifications [6]. Briefly, leaves, roots, and stems were individually homogenized in liquid nitrogen using a TissueLyser II (Thermo Fisher Scientific). In total, 50 mg of the material was extracted with 1 ml cold 50% acetonitrile. The extract was then purified on a non-selective reversed-phase solid-phase extraction (RP-SPE) using an Oasis HLB cartridge (Waters). The column was activated with 100% methanol and ultrapure water, followed by equilibration with 50% acetonitrile. The sample was loaded onto the cartridge and flow-through collected. The residues of the target hormones were then eluted with 1 ml of 30% acetonitrile. The flow-through and eluted fractions were mixed and were evaporated to dryness in vacuum concentrator for 3 hours. Dried residuals were dissolved in 100 μl of 30% acetonitrile. The protocol was deposited in protocols.io (http://dx.doi.org/10.17504/protocols.io.bqy6mxze).

Plant hormone determination

Standard addition and stable isotope dilution methods were used in quantifying plant hormones [20–22]. Stable isotope-labelled plant hormones were fortified with samples as well as absolute standard solutions at concentrations ranging from 1.0 ng/ml to 250.0 ng/ml. Neat standard solutions were post-spiked for standard additions with actual sample in order to construct matrix calibration curves in the range of 1.0 ng/ml to 250.0 ng/ml to equalize matrix effects among samples (S1 Fig). Accordingly, actual samples were diluted (dilution factor 1.05). Calibration curves for each phytohormone were constructed for each analyte using the same matrix. Matrix effects (ME = A—B/A*100) were then calculated using the peak areas of A and B, with A identified as a peak area of an analyte in a standard solution and B as a peak area of an analyte in a matrix [9]. A peak area of an analyte derived from the sample was subtracted from B by analyzing the sample beforehand. Recovery rate was calculated by comparing the peak area of each phytohormone present in the sample spiked before SPE and the sample spiked after SPE. Limits of detection (LOD) and limit of quantification (LOQ) were defined as a signal-to-noise ratio of 3:1 and 10:1, respectively.

Ultra-high performance liquid chromatography linked with high-resolution mass spectrometry (LC-MS/MS)

Purified extracts were separated on a 2.6 μm Accucore C18 LC column (150 mm × 2.1 mm) (Thermo Fisher Scientific) using a linear methanol gradient of 1–100% for 10 min at a flow rate of 0.5 ml/min and a column oven of 40°C. MS data were acquired in targeted selected ion monitoring (t-SIM) mode using an electrospray ionization Orbitrap Q-Exactive (Thermo Fisher Scientific) linked to an UltiMate 3000 RSLC (Thermo Fisher Scientific). Mass spectrometric conditions were as follows: polarity, positive and negative ionization modes; spray voltage for positive, 3.5 kV; spray voltage for negative, 2.0 kV; sheath gas flow rate, 50; auxiliary gas, 10; sweep gas, 0; heated capillary temperature, 380°C; S-lens RF level, 50; and auxiliary gas heater temperature, 350°C. The resolution was then set at 70,000. The AGC target was 5E4. The maximum ion injection time was 200 ms. The isolation window was 10 m/z and offset two to monitor stable isotope-labelled plant hormones.

Data analysis

Raw data files were analyzed using Qual Browser software in Xcalibur (Thermo Fisher Scientific). For quantification, Quan browser software in Xcalibur 4.2.47 (Thermo Fisher Scientific) was also used. Student’s t-test was performed using the Excel software.

Results

Plant hormone detection by selected ion monitoring mode (SIM)

Major phytohormones are identified as follows: indole acetic acid (IAA), trans/cis-zeatin (tZ and cZ), abscisic acid (ABA), salicylic acid (SA), gibberellin A3 (GA3), jasmonic acid (JA), and brassinolide (BL) [1] (Fig 1).

Fig 1. The chemical structures of the seven plant hormones used in this study.

Fig 1

Open in a new tab

Stable isotope-labelled gibberellin A3 was commercially unavailable; thus, gibberellin A4 was used instead. An accurate mass of the monoisotopic ion of each plant hormone was first determined by direct infusion in positive and negative ESI mode (S1 Table). Five phytohormones were detected in negative mode, and IAA and BL were only detected in positive mode. Seven phytohormones were injected onto a C18 column, separated, and then detected in the targeted selected ion monitoring (SIM) mode using a measured accurate mass of monoisotopic ion. Except for zeatin, the other six phytohormones showed a distinct retention time and were well separated (S2 Fig). trans-Zeatin (tZ) and cis-zeatin (cZ) stereoisomers showed close retention times and could not be fully separated in the gradient used. Stable isotope-labelled phytohormones were also analyzed in order to determine accurate mass and retention time; they were then compared to non-labelled hormones (S1 Table and S3 Fig). The retention times were almost the same between the stable isotope-labelled hormones and its corresponding non-labelled counterparts. Matrix effects appear to be of the same extent regardless of labelling. Thus, we established analytical conditions for plant hormone quantification by SIM and the chromatographic patterns suggested the possibility of close correspondence between standard addition and stable isotope dilution methods.

Plant hormone extraction has been basically referred to a previous report [6] with minor modifications and workflow as described in Fig 2.

Fig 2. Experimental workflow for extraction of phytohormones.

Fig 2

Open in a new tab

Fifty mg of tissues was extracted with 50% acetonitrile; it was then partially purified by RP-SPE. Dried residue was dissolved in 30% acetonitrile and was used for LC-MS/MS analysis.

We spiked moderate levels of seven phytohormone mixtures before and after solid-phase extraction (SPE) in order to examine recovery rates and peak areas for each hormone in the leaves, roots, and stems of Lotus japonicus (S2 Table). IAA and BL were determined to show slightly lower recovery rates, but other recovery rates were around 80–100%, indicating that almost all phytohormones can be recovered from the tissues of Lotus japonicus by this extraction.

Non-negligible matrix effects of root, stem, and leaf from Lotus japonicus in plant hormone determination

Matrix effects can often cause difficulties in detecting target analytes by reducing or increasing the sensitivity of quantification [12]. Thus, we examined the matrix effects for the quantification of plant hormones in the tissue extracts from L. japonicus (Table 1).

Table 1. Matrix effects in plant hormone determination.

Tissue Compound Matrix effect (%) S.D.
Leaf IAA 72.9 4.4
cZ 37.2 9.6
ABA 53.8 3.7
GA4 51.1 3.7
SA 54.5 14.7
JA 50.9 15.8
BL 67.9 4.7
Root IAA 46.2 4.0
cZ 10.2 4.6
ABA 49.1 3.4
GA4 66.9 2.7
SA 37.4 12.0
JA 59.8 13.9
BL 87.3 1.6
Stem IAA 62.9 9.4
cZ 33.5 6.6
ABA 42.9 7.6
GA4 50.5 1.2
SA 57.3 9.0
JA 49.9 12.4
BL 77.5 0.4
Open in a new tab

Hormones were extracted from the tissues of Lotus japonicus and mixed with seven pure standards. Ten ng/mL of phytohormone mixtures was analyzed with or without the matrix, and the peak areas were compared. Matrix effects are the mean values from three biological replicates.

All tissues showed matrix effects ranging from 10.2% to 87.3%, and all matrix effects were more than 0, indicating ion suppression. cZ also showed the highest ion suppression in root extracts. However, the lowest ion suppression was found in BL in root extracts. Ion suppression might decrease the peak area of phytohormones in the presence of matrix, thereby underestimating target analyte content when an absolute standard curve is used in quantification. Thus, mitigating the matrix effect, such as using stable isotope dilution, is indispensable for the accurate quantification of plant hormones in Lotus japonicus.

Quantification of plant hormones by stable isotope dilution

Proper calibration has been identified to be essential for obtaining reliable results for targeted compounds. Generally, an internal standard calibration method using stable isotope-labelled target compounds is adopted. We then extracted the plant hormones to quantify them in the tissues of L. japonicus. Extracts were mixed with the corresponding stable isotope-labelled phytohormones and used in LC-MS/MS analysis. An absolute standard curve corrected by stable isotope addition was constructed, and plant hormones were then quantified (Table 2).

Table 2. A stable isotope-based quantification of plant hormones.

Tissue Compound Linear range (ng/ml) Curve R2 LOD LOQ Content RSD (%)
ng/ml ng/ml pmol/g FW SD
Leaf IAA 1.0–250.0 Y = 0.0479516 + 0.0808471*X 0.9999 0.03 0.1 117.5 14.1 12.0
cZ 1.0–250.0 Y = −0.119872 + 0.0903252*X 0.9988 0.1 0.2 N.D. N.D. N.D.
ABA 1.0–250.0 Y = −0.0962675 + 0.0481031*X 0.9992 0.02 0.1 219.2 102.7 46.9
GA4 1.0–250.0 Y = −0.730001 + 0.102525*X 0.9934 0.01 0.02 N.D. N.D. N.D.
SA 1.0–250.0 Y = 0.0388554 + 0.0687677*X 0.9967 0.1 0.4 2397.5 203.5 8.5
JA 1.0–250.0 Y = −0.210579 + 0.101196*X 0.9990 0.02 0.1 1042.9 113.6 10.9
BL 1.0–250.0 Y = −0.0247326 + 0.0846773*X 0.9994 0.01 0.02 4.6 0.8 18.6
Root IAA 1.0–250.0 Y = 0.0479516 + 0.0808471*X 0.9999 0.03 0.1 84.9 5.0 5.9
cZ 1.0–250.0 Y = −0.119872 + 0.0903252*X 0.9988 0.1 0.2 N.D. N.D. N.D.
ABA 1.0–250.0 Y = −0.0962675 + 0.0481031*X 0.9992 0.02 0.1 47.4 9.9 20.8
GA4 1.0–250.0 Y = −0.730001 + 0.102525*X 0.9934 0.01 0.02 N.D. N.D. N.D.
SA 1.0–250.0 Y = 0.0388554 + 0.0687677*X 0.9967 0.1 0.4 297.8 89.8 30.1
JA 1.0–250.0 Y = −0.210579 + 0.101196*X 0.9990 0.01 0.04 1187.5 349.8 29.5
BL 1.0–250.0 Y = −0.0247326 + 0.0846773*X 0.9994 0.01 0.02 N.D. N.D. N.D.
Stem IAA 1.0–250.0 Y = 0.0479516 + 0.0808471*X 0.9999 0.03 0.1 216.7 33.8 15.6
cZ 1.0–250.0 Y = −0.119872 + 0.0903252*X 0.9988 0.1 0.2 N.D. N.D. N.D.
ABA 1.0–250.0 Y = −0.0962675 + 0.0481031*X 0.9992 0.02 0.1 178.3 32.7 18.3
GA4 1.0–250.0 Y = −0.730001 + 0.102525*X 0.9934 0.01 0.02 N.D. N.D. N.D.
SA 1.0–250.0 Y = 0.0388554 + 0.0687677*X 0.9967 0.1 0.4 1758.5 227.2 12.9
JA 1.0–250.0 Y = −0.210579 + 0.101196*X 0.9990 0.01 0.04 1357.1 168.6 12.4
BL 1.0–250.0 Y = −0.0247326 + 0.0846773*X 0.9994 0.01 0.02 N.D. N.D. N.D.
Open in a new tab

Seven phytohormones were extracted and analyzed by LC-MS/MS. Calibration curves were constructed with pure standards without matrix, and the peak areas were corrected based on the peak areas of stable isotope-labelled internal standards. Plant hormone extraction was performed in biological triplicate. R2, correlation coefficient; LOD, limit of detection; LOQ, limit of quantification; RSD, relative standard deviation; FW, fresh weight.

tZ was deemed unquantifiable because a large peak appeared before the target peak. The other seven hormones were quantified. SA was determined to be the most abundant hormone found in the leaves of L. japonicus (2397.5 ± 203.5 (pmol/g FW)). JA, ABA, IAA, and BL were also detected in an order of decreasing concentration. Conversely, root extracts contained the highest JA concentration (1143.2 ± 412.4 (pmol/g FW)); SA concentration was approximately one-third of this level. SA levels in stems were comparable to JA levels. Notably, BL was only detected in leaf extracts (4.6 ± 0.8 (pmol/g FW)). Hormone profiles have been determined to be diverse in tissues of L. japonicus.

No significant difference of plant hormone content in L. japonicus between the two methods

We subsequently constructed a matrix standard curve by adding actual samples into standard solutions for quantification of phytohormones. Plant hormones were quantified in the same tissue extracts of L. japonicus as extracts used for stable isotope dilution (Table 3).

Table 3. Quantification of plant hormones using standard addition.

Tissue Compound Linear range (ng/ml) Curve R2 LOD LOQ Content RSD (%)
ng/ml ng/ml pmol/g FW SD
Leaf IAA 1.0–250.0 Y = 77271*X − 141437 0.9995 0.1 0.5 95.1 4.0 4.3
cZ 10.0–250.0 Y = 35908*X + 162509 0.9963 0.5 1.6 N.D. N.D. N.D.
ABA 1.0–250.0 Y = 66926*X − 29050 0.9998 0.1 0.3 185.7 84.4 45.4
GA4 1.0–250.0 Y = 151474*X − 147592 0.9998 0.1 0.2 N.D. N.D. N.D.
SA 1.0–250.0 Y = 96955*X + 2118049 0.9917 0.2 0.7 2480.9 198.8 8.0
JA 1.0–250.0 Y = 69832*X − 1415498 0.9990 0.1 0.2 1023.8 94.2 9.2
BL 1.0–250.0 Y = 152721*X − 327260 0.9995 0.1 0.3 10.9 0.04 0.4
Root IAA 1.0–250.0 Y = 140337*X − 13011 0.9993 0.1 0.3 71.8 10.3 14.3
cZ 10.0–250.0 Y = 33924*X − 53632 0.9975 0.3 0.9 N.D. N.D. N.D.
ABA 1.0–250.0 Y = 92423*X − 229613 0.9995 0.1 0.3 38.8 2.8 7.1
GA4 1.0–250.0 Y = 170129*X − 524708 0.9989 0.02 0.1 N.D. N.D. N.D.
SA 1.0–250.0 Y = 175984*X + 796822 0.9954 0.1 0.4 438.2 113.9 26.0
JA 1.0–250.0 Y = 74179*X + 1697965 0.9977 0.02 0.1 1129.7 347.4 30.7
BL 1.0–250.0 Y = 116960*X − 543073 0.9985 0.1 0.4 N.D. N.D. N.D.
Stem IAA 1.0–250.0 Y = 103600*X − 263583 0.9987 0.1 0.2 239.6 11.0 4.6
cZ 10.0–250.0 Y = 33302*X + 279101 0.9849 0.4 1.4 N.D. N.D. N.D.
ABA 1.0–250.0 Y = 78533*X − 134102 0.9986 0.1 0.4 161.4 20.2 12.5
GA4 1.0–250.0 Y = 199797*X − 732980 0.9986 0.02 0.1 N.D. N.D. N.D.
SA 1.0–250.0 Y = 114085*X − 1541232 0.9866 0.5 1.6 1617.9 351.3 21.7
JA 1.0–250.0 Y = 57977*X + 2093537 0.9962 0.1 0.2 1430.1 462.6 32.3
BL 1.0–250.0 Y = 132286*X − 539659 0.9973 0.1 0.2 N.D. N.D. N.D.
Open in a new tab

Seven phytohormones were extracted, and the calibration curves were constructed with sample matrix and analyzed by LC-MS/MS. Plant hormone extraction was performed in biological triplicate. R2, correlation coefficient; LOD, limit of detection; LOQ, limit of quantification; RSD, relative standard deviation; FW, fresh weight.

Leaf extract with the highest SA content (2480.9 ± 198.8 (pmol/g FW)) and the root extract with the highest JA concentration (1129.7 ± 347.4 (pmol/g FW)) were found. Phytohormone content was compared with the results from stable isotope dilution analysis (Fig 3A–3C).

Fig 3. Comparison of standard addition method with stable isotope dilution method.

Fig 3

Open in a new tab

Plant hormone contents in the leaves (A), roots (B), and stems (C) were compared between standard addition and stable isotope addition methods. Significant differences were not observed.

No significant difference was observed in the concentrations (pmol/g FW) between the two quantification methods (t-test, p > 0.05), and phytohormone profiles have exhibited similar patterns. We also evaluated repeatability (accuracy and precision) for quantification of plant hormones by standard addition method (S2 Table). Precision and accuracy, expressed as relative standard deviation (RSD) and relative error ranged from 3.5% to 16.3%, from −18.2% to +3.1%, respectively. The standard addition method is effective for quantification of hormones by correcting for matrix effects; thus it is applicable for the three major tissues of L. japonicus.

Discussion

Phytohormones are essential signaling molecules in multiple physiological processes, including growth, development, and stress response. L. japonicus is a model legume widely used in studies on nitrogen-fixing symbiosis and arbuscular mycorrhizal (AM) symbiosis; however, plant hormone profiles remain to be fully elucidated to date. Only one report was found that measured gibberellins, including active GA1, JA, SA, IAA, and ABA, which were detected in the roots. Further, GA1 and its intermediates GA8, GA19, and GA53 were significantly accumulated in response to arbuscular mycorrhizal-fungal infection [23]. We also examined the levels of the seven major plant hormones in the roots, stems, and leaves and found, for the first time, that plant hormones in stems and leaves contain high concentrations of salicylic and jasmonic acids. ABA and IAA were considerably higher in leaves and stems than in roots, and SA was higher in the root than the other parts, suggesting the existence of tissue-specific plant hormone regulation in L. japonicus. Plant hormones are fundamental signaling molecules that respond to biotic and abiotic stress [1]. Indeed, CV was comparatively large in this present study, implying that individual differences in hormones were evident and might fluctuate in response to external stimuli. Further studies would connect plant hormone profiles with plant hormone synthesis/transport network, and it will identify underlying mechanisms of hormonal crosstalk in host-bacterium mutualism. Unveiling plant hormone profiles in model legume, L. japonicus, might allow the enhancement of yields of legume crops, such as soybean since plant hormones have been implicated in plant growth and seed yield in legume [24].

Matrix effects, including ion enhancement or suppression, can often hamper accurate quantification of target analytes by LC-ESI-MS/MS. Mitigation efforts, such as purification of samples and applying proper calibration methods, are currently in use. Typically, plant hormones are purified along with spiked stable isotopes to correct for matrix effects [7]. However, stable isotope-labelled compounds for specific plant hormones are expensive and sometimes not commercially available, which limits their use. Although standard addition method is relatively more complex from a methodological point of view compared to stable isotope dilution, it is an effective method since it requires no stable isotope-labelled targets; this method is employed to detect drugs and hormones in plasma and sewage sludge [12,20,21] and pesticides in crop and feedstock [25].

We validated the standard addition method to quantify seven major plant hormones and measured their levels in the tissues of Lotus japonicus. This species is a legume, a family of principal crops like soybeans. Understanding plant hormone fluctuation in Lotus japonicus is of great interest in plant physiology [26]. The standard addition method requires a sample matrix with several concentrations of standard solution. This method is thought to be inappropriate for low concentration samples. However, recent developments in detecting the sensitivity of mass spectrometry have largely solved this problem, and a small quantity of sample (20–50 mg fresh weight per standard level) can now be enough to quantify phytohormones at attomole levels [6]. Our data using high-resolution mass spectrometry (HR-MS) detected femtomolar concentrations of plant hormones, a sensitivity lower than previous study using triple quadrupole mass spectrometry and ultra high performance liquid chromatography (UHPLC) column (particle size of 1.7 μm). Sensitivity might be improved if a UHPLC column is used. Selective reaction monitoring (SRM) has been widely used [7], but selected ion monitoring using HR-MS [27,28] has never been applied to simultaneous quantification of plant hormones. Stable isotope labelling has been considered to be ideal for matrix correction, and our data show that this method displays lower LOD, LOQ, and CV than standard addition. However, standard addition would be beneficial when corresponding stable isotopes are unavailable. Further, standard addition would also be applicable to other parts of the L. japonicus, such as nodule, flower, and pods, and likely other plant species.

Gibberellin A3 is a well-known active plant hormone, but a stable isotope-labelled form is not commercially available. Stable isotope labelling often involves culturing cells or organisms in a medium that contains stable isotope (2H-, 13C-, or 15N-)-labelled molecule building blocks [29]. Another method is to synthesize a precursor of the target compound and then use stable isotope-labelled substrate for the final reaction step [30,31]. In either case, stable isotope labelling often requires time, expense, and multiple purification steps. These issues hinder synthesis in many laboratories. Purification of plant hormones requires large amounts of organism grown in medium containing stable isotopes, since plant hormones exist in plants in trace amounts. Organic chemical synthesis for plant hormones also requires multiple reaction and purification steps in order to obtain a final product. We then validated and quantified plant hormone content in L. japonicus using a standard addition method without stable isotopes. The method was compared with stable isotope dilution, and similar plant hormone profiles in three plant organs were obtained. Next, the method would be evaluated using L. japonicus under hormone-inducing stresses such as drought or pathogen infection as well as Lotus retrotransposon 1 (LORE1) mutants which have mutations in plant hormone biosynthetic pathways. Since plant hormones in distinct organs can critically affect phenotypes, such as growth and differentiation, by plant hormone crosstalk [2], our method requiring no stable isotopes will facilitate understanding of plant hormonomics in the future.

Supporting information

S1 Fig. Preparation of samples using standard addition.

The samples after solid phase extraction (SPE) were mixed with standard solution to construct matrix calibration curve ranging from 1.0 ng/ml to 250.0 ng/ml. The target sample was diluted with 50% methanol in a dilution factor 1.05 (50 μl/47.5 μl). All samples were analyzed by LC-MS/MS analysis.

(TIF)

Click here for additional data file. (346KB, tif)
S2 Fig. Representative SIM chromatogram of seven phytohormones.

One hundred ng/ml of seven phytohormone mixture was analyzed in Quadrupole-orbitrap mass spectrometry.

(TIF)

Click here for additional data file. (615.3KB, tif)
S3 Fig. Representative SIM chromatogram of stable isotope-labeled seven phytohormones.

Ten ng/ml of stable isotope-labeled phytohormones was analyzed in Quadrupole-orbitrap mass spectrometry.

(TIF)

Click here for additional data file. (270.7KB, tif)
S1 Table. Targeted-selected ion monitoring (t-SIM) mode to detect seven plant hormones in Quadrupole-orbitrap mass spectrometer.

(TIF)

Click here for additional data file. (387.7KB, tif)
S2 Table. Recovery rate and repeatability to validate standard addition method with the tissues of Lotus japonicus.

The tissue extracts with 100 ng/ml phytohormones were subjected to solid phase extraction (SPE) and the peak areas of an analyte were determined by LC-MS/MS analysis. The samples spiked with phytohormones after SPE were also analyzed. For repeatability, the tissue extracts with 125 ng/ml phytohormones were also subjected to SPE and quantification by standard addition method. The experiments were repeated three times and the mean of recovery rate, relative standard deviation (RSD) and relative error were calculated.

(TIF)

Click here for additional data file. (287.1KB, tif)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was supported by the National BioResource Project (NBRP) of the Japan Agency for Medical Research and Development (AMED). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Asami T, Nakagawa Y. Preface to the special issue: Brief review of plant hormones and their utilization in agriculture. J Pestic Sci. 2018;43: 154–158. 10.1584/jpestics.M18-02 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Murphy A. Hormone crosstalk in plants. J Exp Bot. 2015;66: 4853–4854. 10.1093/jxb/erv339 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Müller A, Düchting P, Weiler EW. 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. 2002;216: 44–56. 10.1007/s00425-002-0866-6 [DOI] [PubMed] [Google Scholar]
  • 4.Müller M, Munné-Bosch S. Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry. Plant Methods. 2011;7; 37 10.1186/1746-4811-7-37 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Pan X, Welti R, Wang X. Simultaneous quantification of major phytohormones and related compounds in crude plant extracts by liquid chromatography-electrospray tandem mass spectrometry. Phytochemistry. 2008;69: 1773–1781. 10.1016/j.phytochem.2008.02.008 [DOI] [PubMed] [Google Scholar]
  • 6.Šimura J, Antoniadi I, Široká J, Tarkowská D, Strnad M, Ljung K, et al. Plant hormonomics: Multiple phytohormone profiling by targeted metabolomics. Plant Physiol. 2018;177: 476–489. 10.1104/pp.18.00293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Wang L, Zou Y, Kaw HY, Wang G, Sun H, Cai L, et al. Recent developments and emerging trends of mass spectrometric methods in plant hormone analysis: A review. Plant Methods. 2020;16: 54 10.1186/s13007-020-00595-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Balcke GU, Handrick V, Bergau N, Fichtner M, Henning A, Stellmach H, et al. An UPLC-MS/MS method for highly sensitive high-throughput analysis of phytohormones in plant tissues. Plant Methods. 2012;8: 47 10.1186/1746-4811-8-47 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Zhou W, Yang S, Wang PG. Matrix effects and application of matrix effect factor. Bioanalysis 2017;9: 1839–1844. 10.4155/bio-2017-0214 [DOI] [PubMed] [Google Scholar]
  • 10.Gergov M, Nenonen T, Ojanperä I, Ketola RA. Compensation of matrix effects in a standard addition method for metformin in postmortem blood using liquid chromatography-electrospray-tandem mass spectrometry. J Anal Toxicol. 2015;39: 359–364. 10.1093/jat/bkv020 [DOI] [PubMed] [Google Scholar]
  • 11.Kwon H, Lehotay SJ, Geis-Asteggiante L. variability of matrix effects in liquid and gas chromatography-mass spectrometry analysis of pesticide residues after QuEChERS sample preparation of different food crops. J Chromatogr A. 2012;1270: 235–245. 10.1016/j.chroma.2012.10.059 [DOI] [PubMed] [Google Scholar]
  • 12.Van Eeckhaut A, Lanckmans K, Sarre S, Smolders I, Michotte Y. Validation of bioanalytical LC-MS/MS assays: Evaluation of matrix effects. J Chromatogr B Analyt Technol Biomed Life Sci. 2009;877: 2198–2207. 10.1016/j.jchromb.2009.01.003 [DOI] [PubMed] [Google Scholar]
  • 13.Stahnke H, Kittlaus S, Kempe G, Alder L. Reduction of matrix effects in liquid chromatography-electrospray ionization-mass spectrometry by dilution of the sample extracts: how much dilution is needed?. Anal Chem. 2012;84: 1474–1482. 10.1021/ac202661j [DOI] [PubMed] [Google Scholar]
  • 14.Gosetti F, Mazzucco E, Zampieri D, Gennaro MC. Signal suppression/enhancement in high-performance liquid chromatography tandem mass spectrometry. J Chromatogr A. 2010;1217: 3929–3937. 10.1016/j.chroma.2009.11.060 [DOI] [PubMed] [Google Scholar]
  • 15.Kojima M, Kamada-Nobusada T, Komatsu H, Takei K, Kuroha T, Mizutani M, et al. 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. 2009;50: 1201–1214. 10.1093/pcp/pcp057 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Almeida Trapp M, De Souza GD, Rodrigues-Filho E, Boland W, Mithöfer A. Validated method for phytohormone quantification in plants. Front Plant Sci. 2014;5: 417 10.3389/fpls.2014.00417 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Lehotay SJ, de Kok A, Hiemstra M, Van Bodegraven P. Validation of a fast and easy method for the determination of residues from 229 pesticides in fruits and vegetables using gas and liquid chromatography and mass spectrometric detection. J AOAC Int. 2005;88: 595–614. [PubMed] [Google Scholar]
  • 18.Jaderson M, Park JH. Evaluation of matrix effects in quantifying microbial secondary metabolites in indoor dust using ultraperformance liquid chromatograph-tandem mass spectrometer. Saf Health Work. 2019;10: 196–204. 10.1016/j.shaw.2018.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Chawla S, Patel HK, Gor HN, Vaghela KM, Solanki PP, Shah PG. Evaluation of matrix effects in multiresidue analysis of pesticide residues in vegetables and spices by LC-MS/MS. J AOAC Int. 2017;100: 616–623. 10.5740/jaoacint.17-0048 [DOI] [PubMed] [Google Scholar]
  • 20.Cheng S-Y, Ng-A-Qui T, Eng B, Ho J. Detection of cathinone and mephedrone in plasma by LC-MS/MS using standard addition quantification technique. J Anal Sci Technol. 2017;8. [Google Scholar]
  • 21.Garcia-Rodríguez A, Sagristà E, Matamoros V, Fontàs C, Hidalgo M, Salvadó V. Determination of pharmaceutical compounds in sewage sludge using a standard addition method approach. Int J Environ Anal Chem. 2014;94: 1199–1209. [Google Scholar]
  • 22.Stark T, Wollmann N, Lösch S, Hofmann T. Quantitation of resveratrol in red wines by means of stable isotope dilution analysis-ultra-performance liquid chromatography-Quan-time-of-flight mass spectrometry and cross validation. Anal Chem. 2011;83: 3398–3405. 10.1021/ac103305s [DOI] [PubMed] [Google Scholar]
  • 23.Takeda N, Handa Y, Tsuzuki S, Kojima M, Sakakibara H, Kawaguchi M. Gibberellins interfere with symbiosis signaling and gene expression and alter colonization by arbuscular mycorrhizal fungi in Lotus japonicus. Plant Physiol. 2015;167: 545–557. 10.1104/pp.114.247700 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Wilkinson S, Kudoyarova GR, Veselov DS, Arkhipova TN, Davies WJ. Plant hormone interactions: innovative targets for crop breeding and management. J Exp Bot. 2012;63: 3499–3509. 10.1093/jxb/ers148 [DOI] [PubMed] [Google Scholar]
  • 25.Steiner D, Krska R, Malachová A, Taschl I, Sulyok M. Evaluation of matrix effects and extraction efficiencies of LC-MS/MS methods as the essential part for proper validation of multiclass contaminants in complex feed. J Agric Food Chem. 2020;68: 3868–3880. 10.1021/acs.jafc.9b07706 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Hashiguchi M, Tanaka H, Muguerza M, Akashi R, Sandal NN, Andersen SU, et al. Lotus japonicus genetic, mutant, and germplasm resources. Curr Protoc Plant Biol. 2018;3: e20070 10.1002/cppb.20070 [DOI] [PubMed] [Google Scholar]
  • 27.Kaufmann A, Butcher P, Maden K, Walker S, Widmer M. Comprehensive comparison of liquid chromatography selectivity as provided by two types of liquid chromatography detectors (high resolution mass spectrometry and tandem mass spectrometry): "where is the crossover point?". Anal Chim Acta. 2010;673: 60–72. 10.1016/j.aca.2010.05.020 [DOI] [PubMed] [Google Scholar]
  • 28.Kaufmann A. High-resolution mass spectrometry for bioanalytical applications: Is this the new gold standard?. J Mass Spectrom. 2020;55: e4533 10.1002/jms.4533 [DOI] [PubMed] [Google Scholar]
  • 29.Rinkel J, Dickschat JS. Recent highlights in biosynthesis research using stable isotopes. Beilstein J Org Chem. 2015;11: 2493–2508. 10.3762/bjoc.11.271 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Hoogstraten CG, Johnson JE. Metabolic labeling: Taking advantage of bacterial pathways to prepare spectroscopically useful isotope patterns in proteins and nucleic acids. Concepts Magn Reson. 2008;32A: 34–55. [Google Scholar]
  • 31.Kobata K, Mimura M, Sugawara M, Watanabe T. Synthesis of stable isotope-labeled precursors for the biosyntheses of capsaicinoids, capsinoids, and capsiconinoids. Biosci Biotechnol Biochem. 2011;75: 1611–1614. 10.1271/bbb.110187 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Raffaella Balestrini

30 Nov 2020

PONE-D-20-34002

Quantitative analysis of the seven plant hormones in Lotus japonicus using standard addition method

PLOS ONE

Dear Dr. Akashi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The manuscript has been revised by two reviewers that appreciated it. However, some comments should be addressed before the publication.

Please submit your revised manuscript by Jan 14 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Raffaella Balestrini

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. During your revisions, please note that a simple title correction is required: to follow correct English language usage, the title should read "Quantitative analysis of seven plant hormones in Lotus japonicus using standard addition method". Please ensure this is updated in the manuscript file and the online submission information.

3. Thank you for stating the following in the Acknowledgments Section of your manuscript:

2This work was supported by Toyota Motor Corporation and the National BioResource

Project (NBRP) of the Japan Agency for Medical Research and Development (AMED)."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

"The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

Additionally, because some of your funding information pertains to commercial funding, we ask you to provide an updated Competing Interests statement, declaring all sources of commercial funding.

In your Competing Interests statement, please confirm that your commercial funding does not alter your adherence to PLOS ONE Editorial policies and criteria by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” as detailed online in our guide for authors  http://journals.plos.org/plosone/s/competing-interests.  If this statement is not true and your adherence to PLOS policies on sharing data and materials is altered, please explain how.

Please include the updated Competing Interests Statement and Funding Statement in your cover letter. We will change the online submission form on your behalf.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: In this work, Hashiguchi and colleagues present a methodological manuscript in which they describe the quantitative analysis of seven plant hormones in Lotus japonicus roots, shoots and stems, with high-resolution mass spectrometry (HR-MS).

They showed an important technical analysis about the impact of matrix effect in the purification and quantification of hormones that can vary between 10 and 87%, therefore ion suppression can largely decrease the peak area of phytohormones. And among the main results, they demonstrated that there were no significant differences between standard addition and stable isotope addition methods, therefore allowing to quantify hormones without any treatment with stable isotopes.

Altogether the work is technically sound and the approaches are of wide interest for the community.

A further validation of the methods on a perturbed system would add some extra value to the work. For example the Authors could challenge the plants with one relevant hormone-inducing stress (just as an example drought stress to induce ABA) and further compare ABA concentration with a physiological condition. Another option would be to test a Lotus japonicus known mutant for any hormonal biosynthetic pathway.

In addition to this, I have a few specific comments:

Figure 3: Please do not use bar graphs but show all the measurements (refer to Weissgerber et al., 2015, Plos Biology, https://doi.org/10.1371/journal.pbio.1002128): this would

Finally to better validate the method, a calculation of repeatability (accuracy and precision) obtained during the validation of the method could constitute an added value. By repeating the same measurements on the same starting material how much variance are you observing? Such as done in the cited work by Trapp et al., Frontiers in Plant Science 2014. I think this is particularly important if the Authors are not adding any experiments on Lotus mutants and/or stress conditions that are inducing different hormonal changes.

As a suggestion, to improve the readability, consider to change the paragraph title by stating the key results obtained in that paragraph. For example instead of: “Quantification of plant hormones by standard addition and comparison of the two quantification methods” you could state that there is no significant difference between the two methods.

line 45-46: There are more than 8 groups of hormones: please, at least, also consider strigolactones

line 340-343: repetition of a full sentence, please correct it.

Reviewer #2: The paper “Quantitative analysis of the seven plant hormones in Lotus japonicus using standard addition method” is an interesting methodological manuscript which aims to compare standard addition and stable isotope dilution method to quantify plant hormones in different plant tissues. The authors have utilized leaves, roots and stems of Lotus japonica to test if the standard addition method could be a robust and accurate method to quantify plant hormones in plant tissues. The work was conducted utilizing a rigorous methodology and furnish a validated method to quantify plant hormones, in particular when it is difficult to find the appropriate internal standard. However, I have two main comments:

- the method is more complex, from a methodological point of view respect to the method of internal standard. I think this should be mentioned in the discussion (in addition to highlight the strong points of this method);

- the discussion should be revised in a more logical way, starting from the role of hormones and their importance in AMF- and bacterium-plant interaction (line 314-329) and then moving to the discussion of the results presented in the paper (validation of the standard addition method and comparison with the internal standard method) (line 295-313 and 330-345).

I suggest to revise also some minor points:

-line 26 “THEIR content levels vary depending on the species, and THEY also change...” I think this sentence is referred to plant hormones.

-line 55 “ionizing hydrophobic analytes”..not all plant hormones are hydrophobic substances (ex. salicylic acid, abscisic acid)..I suggest to revise this point

-line 107 “Extraction for plant hormones has BEEN CONDUCTED UTILIZING...”

-line 136: the authors have already described that extracts were purified using SPE. Here it can be said “Purified extracts were separated ....”

- line 328-329: the last sentence of the paragraph is very speculative. I suggest to revise this sentence.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Cecilia Brunetti

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Feb 18;16(2):e0247276. doi: 10.1371/journal.pone.0247276.r002

Author response to Decision Letter 0

23 Dec 2020

Response to Reviewer 1

We express our sincere gratitude to this reviewer for the questions, comments, and suggestions provided to us about our manuscript. In the revised manuscript, we have taken into account the suggestions of the reviewer and made the necessary revisions accordingly. Our answers to your questions, comments, and suggestions are listed below following each specific question/comment.

Comment 1: In this work, Hashiguchi and colleagues present a methodological manuscript in which they describe the quantitative analysis of seven plant hormones in Lotus japonicus roots, shoots and stems, with high-resolution mass spectrometry (HR-MS). They showed an important technical analysis about the impact of matrix effect in the purification and quantification of hormones that can vary between 10 and 87%, therefore ion suppression can largely decrease the peak area of phytohormones. And among the main results, they demonstrated that there were no significant differences between standard addition and stable isotope addition methods, therefore allowing to quantify hormones without any treatment with stable isotopes. Altogether the work is technically sound and the approaches are of wide interest for the community. A further validation of the methods on a perturbed system would add some extra value to the work. For example the Authors could challenge the plants with one relevant hormone-inducing stress (just as an example drought stress to induce ABA) and further compare ABA concentration with a physiological condition. Another option would be to test a Lotus japonicus known mutant for any hormonal biosynthetic pathway.

Our response: We have added the importance of the works you suggested in lines 351-354 in the discussion.

Comment 2: Figure 3: Please do not use bar graphs but show all the measurements (refer to Weissgerber et al., 2015, Plos Biology, https://doi.org/10.1371/journal.pbio.1002128): this would

Our response: We have replaced the bar graphs in Figure 3 with the scatter plots as you suggested.

Comment 3: Finally to better validate the method, a calculation of repeatability (accuracy and precision) obtained during the validation of the method could constitute an added value. By repeating the same measurements on the same starting material how much variance are you observing? Such as done in the cited work by Trapp et al., Frontiers in Plant Science 2014. I think this is particularly important if the Authors are not adding any experiments on Lotus mutants and/or stress conditions that are inducing different hormonal changes.

Our response: We have added the data on repeatability (accuracy and precision) by standard addition method in supplemental Table 2 and in lines 284-287. Accordingly, we have added the sentences in lines 464-465 and 467-470 in the table legend.

Comment 4: As a suggestion, to improve the readability, consider to change the paragraph title by stating the key results obtained in that paragraph. For example instead of: “Quantification of plant hormones by standard addition and comparison of the two quantification methods” you could state that there is no significant difference between the two methods.

Our response: We have changed the paragraph title to “No significant difference of plant hormone content in L. japonicus between the two methods” in lines 255-256 and “Non-negligible matrix effects of root, stem, and leaf from Lotus japonicus in plant hormone determination” in lines 193-194.

Comment 5: line 45-46: There are more than 8 groups of hormones: please, at least, also consider strigolactones

Our response: We have included “strigolactones” in line 46 and changed from “eight” to “nine” in line 45.

Comment 6: line 340-343: repetition of a full sentence, please correct it.

Our response: We have deleted the repetitive sentence “Thus, the standard addition method was comparable to the method using stable isotope labelling.” in this revised manuscript.

Response to reviewer 2

We express our sincere gratitude to this reviewer for the questions, comments, and suggestions provided to us about our manuscript. In the revised manuscript, we have taken into account the suggestions of the reviewer and made the necessary revisions accordingly. Our answers to your questions, comments, and suggestions are listed below following each specific question/comment.

Comment 1: The paper “Quantitative analysis of the seven plant hormones in Lotus japonicus using standard addition method” is an interesting methodological manuscript which aims to compare standard addition and stable isotope dilution method to quantify plant hormones in different plant tissues. The authors have utilized leaves, roots and stems of Lotus japonica to test if the standard addition method could be a robust and accurate method to quantify plant hormones in plant tissues. The work was conducted utilizing a rigorous methodology and furnish a validated method to quantify plant hormones, in particular when it is difficult to find the appropriate internal standard. However, I have two main comments:

- the method is more complex, from a methodological point of view respect to the method of internal standard. I think this should be mentioned in the discussion (in addition to highlight the strong points of this method);

Our response: We have added “Although standard addition method is relatively more complex from a methodological point of view compared to stable isotope dilution,” in lines 315-316 in the discussion.

Comment 2: - the discussion should be revised in a more logical way, starting from the role of hormones and their importance in AMF- and bacterium-plant interaction (line 314-329) and then moving to the discussion of the results presented in the paper (validation of the standard addition method and comparison with the internal standard method) (line 295-313 and 330-345).

Our response: As you suggested, we have started from the role of hormones in lines 291-293 and replaced the second paragraph (lines 295-313) with the first paragraph (lines 314-329) to discuss the results more logically.

Comment 3: -line 26 “THEIR content levels vary depending on the species, and THEY also change...” I think this sentence is referred to plant hormones.

Our response: We have changed the words as you pointed out in line 26 and 27.

Comment 4: -line 55 “ionizing hydrophobic analytes”..not all plant hormones are hydrophobic substances (ex. salicylic acid, abscisic acid)..I suggest to revise this point

Our response: We have revised as you suggested in line 55.

Comment 5: -line 107 “Extraction for plant hormones has BEEN CONDUCTED UTILIZING...”

Our response: We have revised as you suggested in line 109.

Comment 6: -line 136: the authors have already described that extracts were purified using SPE. Here it can be said “Purified extracts were separated ....”

Our response: We have revised as you suggested in line 139.

Comment 7: - line 328-329: the last sentence of the paragraph is very speculative. I suggest to revise this sentence.

Our response: We have changed the sentence to “Unveiling plant hormone profiles in model legume, L. japonicus, might allow the enhancement of yields of legume crops, such as soybean since plant hormones have been implicated in plant growth and seed yield in legume [24].” in lines 307-309. We also added a new reference “Wilkinson S, Kudoyarova GR, Veselov DS, Arkhipova TN, Davies WJ. Plant hormone interactions: innovative targets for crop breeding and management. J Exp Bot. 2012;63: 3499-3509.” in line 309. Accordingly, the references 25-31 have been reordered.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (22.6KB, docx)

Decision Letter 1

Raffaella Balestrini

4 Feb 2021

Quantitative analysis of seven plant hormones in Lotus japonicus using standard addition method

PONE-D-20-34002R1

Dear Dr. Akashi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Raffaella Balestrini

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Please consider to correct line 351. You wrote: "the method would be evaluated using L. japonicus" but it could be better to write that it will be important to validate the method with using...

Reviewer #2: In this revised version of the paper, the authors have addressed all the concerns and suggestions. I am satisfied by all changes carried out and endorse the publication of the manuscript.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Marco Giovannetti

Reviewer #2: Yes: Cecilia Brunetti

Acceptance letter

Raffaella Balestrini

8 Feb 2021

PONE-D-20-34002R1

Quantitative analysis of seven plant hormones in Lotus japonicus using standard addition method

Dear Dr. Akashi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Raffaella Balestrini

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Preparation of samples using standard addition.

    The samples after solid phase extraction (SPE) were mixed with standard solution to construct matrix calibration curve ranging from 1.0 ng/ml to 250.0 ng/ml. The target sample was diluted with 50% methanol in a dilution factor 1.05 (50 μl/47.5 μl). All samples were analyzed by LC-MS/MS analysis.

    (TIF)

    Click here for additional data file. (346KB, tif)
    S2 Fig. Representative SIM chromatogram of seven phytohormones.

    One hundred ng/ml of seven phytohormone mixture was analyzed in Quadrupole-orbitrap mass spectrometry.

    (TIF)

    Click here for additional data file. (615.3KB, tif)
    S3 Fig. Representative SIM chromatogram of stable isotope-labeled seven phytohormones.

    Ten ng/ml of stable isotope-labeled phytohormones was analyzed in Quadrupole-orbitrap mass spectrometry.

    (TIF)

    Click here for additional data file. (270.7KB, tif)
    S1 Table. Targeted-selected ion monitoring (t-SIM) mode to detect seven plant hormones in Quadrupole-orbitrap mass spectrometer.

    (TIF)

    Click here for additional data file. (387.7KB, tif)
    S2 Table. Recovery rate and repeatability to validate standard addition method with the tissues of Lotus japonicus.

    The tissue extracts with 100 ng/ml phytohormones were subjected to solid phase extraction (SPE) and the peak areas of an analyte were determined by LC-MS/MS analysis. The samples spiked with phytohormones after SPE were also analyzed. For repeatability, the tissue extracts with 125 ng/ml phytohormones were also subjected to SPE and quantification by standard addition method. The experiments were repeated three times and the mean of recovery rate, relative standard deviation (RSD) and relative error were calculated.

    (TIF)

    Click here for additional data file. (287.1KB, tif)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (22.6KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES