Supporting Information

Rapid and sensitive analysis of 27 underivatized free amino

acids, dipeptides and tripeptides in fruits of Siraitia grosvenorii

Swingle using HILIC-UHPLC-QTRAP/MS2 combined with

chemometrics methods

Guisheng Zhou Mengyue Wang Yang Li Ying Peng Xiaobo Li ( )

G. Zhou M. Wang Y. Li Y. Peng X. Li ( )

School of Pharmacy,

Shanghai Jiao Tong University,

Shanghai 200240, China

e-mail: xbli@sjtu.edu.cn

1

The stability of FAAs and small peptides

The temperature stability of amino acids and small peptides were very important in

this study. On the one hand, temperature was an important storage factor of amino

acids and small peptides; on the other hand, temperature was a parameter of

ultrasound-assisted extraction. The stability of analytes in 50% (v/v) acetonitrile were

evaluated by analyzing high (100 ng/mL) and low (10 ng/mL) concentrations of 27

mixture standards (n = 6) exposed to different conditions (room temperature 25°C, 12

h; 4°C, 72 h). From the results of analysis, the analytes were considered stable in 4°C

and 25°C because the response of stored samples and fresh samples, or the measured

analyte concentration and its corresponding theoretical value, differed by less than 5%

(Table S2). The thermal stability of amino acids was reported in many papers (Bada et

al. 1995; Duke et al. 1994; Yan et al. 2009). From the previous reports, we could

obtain a conclusion that the investigated amino acids in this study were stable at

relatively low temperature conditions (4°C and 25°C).

In some previous thermodynamic studies it had been shown that the addition of

cosolutes such as electrolytes, surfactants, or other biomolecules to aqueous small

peptide and amino acids solutions would have a strong effect on the hydration of these

solutes (Pałecz et al. 2010; Yan et al. 2009), and consequently invoking important

changes in their ability to bind other molecules (Singh et al. 2015; Yan et al. 2009).

Temperature might change this processes of hydration (Duke et al. 1994; Singh et al.

2015; Yan et al. 2009). Based on the previously reported, a mixture of amino acids

was relatively stable and had litter changes of thermodynamic parameters in the low

temperature (less than 328.15 k). Besides, in this study, 27 investigated compounds

were dissolved in 50% (v/v) acetonitrile without additives (electrolyte, non-

2

electrolytes, surfactants, etc.), and their thermal stability was also studied at relatively

low temperature conditions (4°C and 25°C). Hence, a mixture of the target amino

acids was stable in our research condition.

3

Optimization and verification procedures

In this study, to optimize UAE parameters, a screening design of PB was built to

identify the main factors affecting the responses (the total content of 24 FAAs and 3

active small peptides from LHG) among 6 variables (such as ultrasonic power,

frequency, extraction time, times, temperature, and the solid–liquid ratio). The

screening experiments indicated that ultrasonic power, extraction time and solid–

liquid ratio were the most effective parameters to the yield of target compounds. In

preliminary experiment, the effects of ultrasonic power, extraction time and solid–

liquid ratio on UAE were respectively studied to observe the yields of total contents

of FAAs (24 amino acids) and peptides (3 active small peptides) from LHG. On the

one hand, we paid attention on the total content of peptides using different ultrasonic

treatments; on the other hand, we also added the relevant experiments to explore the

relationship between the ultrasonic treatments and each peptide cleavage.

The PB screening experiments indicated that ultrasonic power, time and solid–

liquid ratio were the most effective ultrasonic treatments to the yield of target

compounds. In this study, the above 3 most effective ultrasonic treatments were used

to further investigate the relationship between the ultrasonic treatments and each

target peptide cleavage.

Firstly, mixture standards containing 100 ng/mL each active small peptide (GSH,

Ala-Gln and Cyst) were used to investigate the relationship between the ultrasonic

power and each target peptide cleavage. Generally speaking, ultrasonic power was a

fundamental parameter in the process of UAE. In this study, five different ultrasonic

power (100, 175, 250, 325 and 400 W) were selected to evaluate the influence of

ultrasonic power on the cleavage of each small peptide. The other ultrasonic

4

treatments such as ultrasonic time (43 min) and ultrasonic temperature (25°C) were

fixed. The results obtained by the HILIC-UHPLC–QTRAP/MS2 analysis in Fig.

S2(A) indicated that the detected concentrations of GSH, Ala-Gln and Cyst did not

significantly change with the increase of ultrasonic power from 100 to 325 W.

However, a slight decrease of the concentrations of GSH and Cyst when the

ultrasound power was increased from 325 to 400 W. Therefore, the variable of

ultrasonic power will not be a factor to degrade GSH and Cyst when ultrasonic power

was less than 325 W. In our study, the optimum ultrasonic power 280 W, which could

not degrade the 3 target peptides, was selected for the whole UAE extraction.

Secondly, the mixture standards containing 100 ng/mL each active small peptide

(GSH, Ala-Gln and Cyst) were also used to investigate the relationship between the

ultrasonic time and each target peptide cleavage. The detected concentration of each

peptide over different ultrasonic time from 30 to 50 min is shown in Fig.S2(B), when

the other factors were as follows: ultrasonic power 280 W and ultrasonic temperature

25°C. The results indicated that the detected concentrations of three target peptides

began to slowly decline when ultrasonic time was 45 min, which began to decrease

due to the degradation of peptides over longer ultrasonic time. From the Fig.S2(B),

three target peptides were relatively stable at the selected optimum ultrasonic time 43

min in this study.

Thirdly, to investigate the influence of different concentrations on the peptides

cleavage, the five different concentrations of mixture standards (50, 100, 150, 200 and

300 ng/mL) were used in this study when the ultrasonic time (43 min), power (280 W)

and ultrasonic temperature (25°C) were fixed. As shown in Fig. S2(C), there was no

significant difference between the detected concentration and the corresponding

theoretical concentration of each peptide. Therefore, the variable of concentration will

5

not be a decisive factor when investigating peptides cleavage in the stated conditions.

In conclusion, the obvious cleavage of peptides did not present using the selected

ultrasonic treatments (such as ultrasonic time 43 min and power 280 W) in this study.

Fig. 1A–C and 1a–c are the 3D surface plots and planar contour plots between

every two independent variables on the basis of Eq. (5). Fig. 1A and Fig. 1a show the

effects of ultrasonic power and extraction time on the yield of total content of FAAs

and small peptides (Y(Tc)). When the ultrasonic power fixed, Y(Tc) increased with

the increase of extraction time until reaching a maximum and then decreased.

Similarly, ultrasonic power caused an initial increase and then decrease in the Y(Tc).

This result indicated that both ultrasonic power and extraction time were important

variables for FAAs and small peptides extraction from LHG. Fig. 1B and Fig. 1b

show the effects of ultrasonic power and the solid–liquid ratio on the Y(Tc). When the

solid–liquid ratio was fixed, the Y(Tc) rapidly increased with the increase of

ultrasonic power until reaching a maximum and then slowly decreased. However, the

solid–liquid ratio had less of an effect on changing the content of the Y(Tc). From

Fig. 1C and Fig. 1c, it could be seen that the effect of the solid–liquid ratio on the

extraction rate of the Y(Tc) was not very obvious at a given value of the extraction

time as the surface was relatively flat. When the solid–liquid ratio was at a certain

value, the extraction rate of the Y(Tc) also increased and then decreased. The

extraction of the Y(Tc) depended largely on the ultrasonic power and extraction time.

The maximum yield of Y(Tc) was calculated as 5682.64 g/g in the following

optimum UAE conditions: ultrasonic power of 279.54 W, extraction time of 42.83

min and the solid–liquid ratio of 302.15 mL/g.

A desirability function test was performed using an optimizer procedure in Design–

Expert 8.5 software. This approach consisted in first converting each response

6

variable into a desirability function di, that varied from 0 to 1 (Wu and Hamada 2011).

The idea was that this desirability function acts as a penalty function that leaded the

algorithm to regions where we could find the desired response variable values. The

factor levels that taken to a maximum or a minimum of the response variable were

called “optimum points”. Eq. (1) expressed the global desirability function, D, defined

as the geometric mean of the individual desirability functions. The algorithm should

search for response variable values where D tended to 1 (Pourfarzad et al. 2014).

D = (d1 d2 ... dn)1/n……………………………………………………………(1)

where d1, d2...dn were responses and n was the total number of responses in the

measure.

The numerical optimization found a point that maximizes the desirability function

using the professional statistical software of Design–Expert 8.5. Verification of the

model was carried out by T-test using the statistical software of SPSS 16.0 to compare

the mean actual values of the responses with the predicted value.

According to the results calculated from the desirability function, the maximum D

value of 0.896 was provided when the ultrasonic power was 279.54 W, extraction

time 42.83 min and the solid–liquid ratio 302.15 mL/g. The optimum yield of total of

FAAs and small peptides was calculated as 5682.64 g/g in the above optimum

condition. However, considering the operability in actual production, the optimal

conditions could be modified as follows: ultrasound power of 280 W, extraction time

43 min and the solid–liquid ratio 302 mL/g. Under the modified conditions, the actual

maximum yields of target compounds were detected as 5590.3 ± 76.2 g/g (n = 3),

7

respectively. Thus, the predicted extraction condition was similar to the experimental

value.

8

Effect of gradient elution

In this study, 27 target compounds covered a wide range of polarities. Simultaneous

chromatographic separation of them was not commonly realized using isocratic

elution under the HILIC column. Therefore, the gradient elution was used to separate

target compounds. In the literature, buffer type and salt concentration usually affected

the HILIC separation (Cai et al. 2009). Ammonium acetate was the ideal salt because

it provided the best results in selectivity and reproducibility, presented excellent

solubility and was highly volatile, making it suitable for eventual further MS analysis

(Zhou et al. 2014). In this study, different mobile phase additives (buffer and/or pH

modifying agent) were used to improve HILIC separation. As a result, a mixed

solution including A (water, 10 mmol/L ammonium acetate and 0.5% acetic acid) and

B (acetonitrile, 1 mmol/L ammonium acetate and 0.1% acetic acid) was chosen as the

optimized mobile phase using gradient elution. Factually, it was very important that

the ionic strength was different and this could promote the overestimation or

underestimation in the late eluting compounds when the buffer was changed during

the chromatographic gradient. This problem will be comprehensively researched in

our further study. The above mentioned effect was also considered in our presented

study. To solve this problem, the general analytical method validation was researched

in this study. Validation of the method strictly complied with the ICH regulations for

confirmation analysis procedure. Several performance parameters were studied,

including matrix effects, linearity, LOD, LOQ, precision, repeatability, stability and

recovery. These results of method validation suggested the established method could

9

provide sufficient accuracy for the quantification of LHG samples. The MS response

was a stable value for each target compound with the given suitable concentration at a

specific retention time point during the chromatographic gradient, and this response

could be used for the quantification of each target compound from LHG based on the

method validation. Therefore, the presented HILIC-UHPLC-QTRAP/MS2 using

gradient elution was considered as a practical method for this study. Additionally, to

analysis amino acids, mobile phase containing ammonium acetate using gradient

elution (The detector was MS) was also reported in many published literatures (Guo

et al. 2013; Zhou et al. 2013).

10

Retention time deviations in HILIC column

The literatures reported that retention time deviations were also a problem in HILIC

analysis (Neville et al. 2012). The intra-day retention time deviation was assessed by

injecting 27 standard compounds six times during the day, while the inter-day

retention time deviation was assessed by injecting samples for three consecutive days.

Table S4 shows the data for both inter- and intra-day experiments (n = 6). There was a

small change, 0.0066 ± 0.0036 min, in the average retention times of 27 target

compounds, and there was also a small change (0.0041 ± 0.0015 min) in the time

difference between the inter- and intra-day experiments. The inter- and intra-day

experiments in this study were conducted by referring to the related literature (Neville

et al. 2012), which could provide evidence in support of the robustness of retention

times with the development HILIC method.

11

Optimization of ESI modes

According to the previous reports, while most of amino acids could be monitored

under both ESI+ and ESI− modes, the stronger response was observed under the ESI+

mode than ESI− mode and the ESI+ mode was often selected for the next study (Liu et

al. 2013). In some papers, the MS response of Asn in some matrixes was highest in

positive ion mode but signal-to-noise ratio was improved when ionisation was done in

negative ion mode (Nielsen et al. 2006; Zhang et al. 2011). However, based on the

other papers, positive ion mode, which was selected to detect Asn, had the higher MS

response and better signal-to-noise ratio than negative ion mode in their reported

matrixes or instruments (Buiarelli et al. 2013; Liu et al. 2013; Guo et al. 2013; Zhou

et al. 2013). From these reports, matrixes, instruments and/or other factors might be

important parameters to select suitable ion mode for detecting different compounds.

For these reasons, to optimize the QTRAP/MS2 conditions, Q1 full scans were

conducted under both ESI− and ESI+ modes and the comprehensive information of

each analyte was obtained operating in the above two ion modes for our present

matrixes and instruments. The results revealed that 27 target compounds had higher

sensitivity and preferable signal-to-noise ratios in the ESI+, which made it easier to

detect analytes of lower content in LHG, and easier to confirm molecular ions or

quasi-molecular ions in the identification of each peak. Thus, the ESI+ mode was

selected in the following studies.

12

Optimization of CE values

In complex functional food matrixes, it was a universal phenomenon that one matrix

might simultaneously contain different levels of compounds content. Factually, the

overload effects of high concentrate compounds were often observed if the high and

low concentrate compounds were simultaneously investigated in the same matrix. To

avoid the overload effects, the methods of dilution samples and adjustment MS

parameters (collision energy values) were employed in this study (Martínez Bueno et

al. 2011; Yu et al. 2014). Firstly, the water extract of sample was diluted by the equal

volume acetonitrile (namely the final system was 50% acetonitrile); Secondly, the

dilution sample was analyzed using the preliminary selected chromatographic and MS

conditions, and the distribution tend of different levels compounds were observed

from the chromatogram (Fig. 3); Thirdly, each compound content distribution tend of

mixture standards (Fig. S5) was prepared in accordance with the result of the above

sample. Finally, MS conditions such as collision energy (CE) of target compounds

was compromised to avoid overloading and to allow simultaneously determination of

27 analytes. In this present research, the CE values were becomingly reduced for 4

amino acids (Phe, Leu, Ile and Tyr) with both high concentrate and strong intensity.

As a result, the CE values of Phe, Leu, Ile and Tyr were 30, 5, 5 and 20 eV,

respectively. Additionally, the optimized MRM conditions were respectively used for

analyzing the rest 23 analytes (relatively low concentrate) with the maximum

sensitivities. All ESI and MS optimized parameters were listed in Table S1. From the

13

final results, the intensity of each target compound was less than 5e5 and the good

chromatographic peak were obtained for each analyte.

14

Optimization of MRM

Specific MS2 transitions (quantification–confirmatory transitions) for each target

compound were determined in order to gain sufficient sensitivity for their

qualification and quantification. In preliminary experiment, to select a proper

transition for the MS2 detection of the analyte, all the standards were examined

separately in direct infusion mode, and at least two precursor/product ion pairs for

each analyte were presented in this study. Then, according to the quantitative results,

the highest sensitive and specific ion pairs were selected for the quantification

transition (MRM determination). In this study, the qualitative identification of each

compound was replied on the MS of standard and its chromatographic retention time.

In this study, the highest sensitive and specific ion pairs were selected for the

quantification transition to analysis the target compounds in LHG samples.

Additionally, it was obvious that according to the mass spectrometry conditions the

fragmentation pathways could change. In this study, the other characteristic fragments

of each compound for qualitative identification were listed in Table S1 based on our

presented MS conditions. These fragments and their fragmentation pathways were

reported in the previous reports (Buiarelli et al. 2013; Castro-Perez et al. 2005; Chen

et al. 2014; Guo et al. 2013; Kıvrak et al. 2014; Schiesel et al. 2012). Therefore, the

detail fragmentation pathways of each compound were not displayed in our presented

study.

15

Matrix effects

In previous reports, ion suppression could occur in the ion source to cause a reduced

signal, when matrix co-elutes with the analyte peaks. Co-eluting compounds might

also play an important role in the interference of compound ionization such as

nonvolatile solute, ion-pairing agents and surfactant. The matrix effect was defined as

the ion suppression or enhancement in the process of analyte ionization (Matuszewski

et al. 2003). Due to the complexity of food samples investigated, the matrix effect was

always relevant. The latent interfering effect from co-eluting matrix constituents on

ESI response was investigated in this paper by comparing the slopes of linear

calibration curves from matrix-matched experiments with that obtained from pure

solvent standards. The slope ratios (slope matrix/slope solvent) of 1 indicate that

matrix does not significantly suppress or enhance the response of the MS, otherwise

denotes ionization suppression (< 1) or enhancement (> 1) (Chen et al. 2012). The

sample extracts, which were spiked with appropriate amounts of standards as done for

the apparent recovery measurement based on the above described recovery parameter,

were used to construct standard addition calibration curves. Then, the slopes of the

calibration curves from the standard addition experiments were compared with the

slopes obtained from the neat standards at the same concentration levels. Before

injection, the sample extracts were stored at 4°C for 24 h to allow interaction between

analytes and the matrix of the sample.

Generally, the ion source parameters, chromatographic separation condition and

16

sample preparation method were optimized to reduce or eliminate ion suppression. In

this study, the matrix effects for 27 compounds were observed by spiking samples

after extraction. Test sample S11 was spiked with the target compounds at different

concentrations (from 0.2 to 2.0 mg/kg), and the slopes of the calibration plots were

compared with results obtained when the whole process was applied to standard

solutions of 27 compounds. The slope ratio of matrix curve to neat solution curve was

calculated; the ratio value of 1.0 indicated no matrix effect. When LHG were tested,

the ratio values were between 0.92 and 1.02 (Table S5), implying that sample

preparation method and HILIC-UHPLC–QTRAP/MS2 conditions were suitable for

the determination of 27 target compounds in relatively complex functional food

matrices.

17

Analysis of tryptophan

The partition coefficient k was a phase equilibrium parameter which was influenced

by many thermodynamic properties such as temperature and pressure. The partition

coefficient k was often investigated in distribution chromatography such as high-

speed counter-current chromatography (HSCCC). However, in HILIC

chromatography, it was a complex project to accurately calculate partition coefficient

k of each compound and there were few reports to explore this problem in HILIC

column. Therefore, to accurately calculate partition coefficient k, many sides should

be considered and researched in further study. In our present study, the accurate value

of partition coefficient k of tryptophan was not investigated on the HILIC. But the

partition coefficient k of different target compounds were compared, and then the

comparative results of partition coefficient k were used to distinguish the separation

of each other. From Fig.3 and Table S4, tryptophan and phenylalanine had the same

partition coefficient k and they showed the same retention time (2.17 min) in the total

ions chromatogram (TIC). In this study, tryptophan and phenylalanine were the co-

elution compounds. Fortunately, MRM approach was employed to effectively solve

the problem of co-elution. 205.1188.0 and 166.1120.1 were the MRM transitions

of tryptophan and phenylalanine using QTrap 5500, respectively. Therefore,

tryptophan and phenylalanine could be quantitative determination. Additionally, the

partition coefficient k of tryptophan varied greatly with each other compound (except

for phenylalanine). Hence, tryptophan could be completely separated with other

compounds. Therefore, tryptophan could be analysed by the presented method.

18

The contents of total FAAs (TF) and proteins (TP) in different LHG samples

In this study, the contents of total free amino acids (TF, %) and protein (TP, %) were

respectively investigated in the present research. In different LHG samples, the values

of TF were investigated by the method of HILIC-UHPLC–QTRAP/MS2, and the

contents of TP were determined in accordance with the standard methods of AOAC

(2000). The results are all summarized in Table S6.

In three parts of LHG, TF of epicarp, mesocarp and endocarp, and seed were

0.16%, 1.24% and 0.52%, respectively, and TP of epicarp, mesocarp and endocarp,

and seed were 4.49%, 9.54% and 18.51%, respectively. The ratios (TF/TP) between

total free amino acids and total protein were 0.03, 0.130 and 0.028 in epicarp,

mesocarp and endocarp, and seed, respectively. From the results, it was indicated that

the ratio (TF/TP) and TP in the seed were the highest among three parts of LHG.

Additionally, the TF, TP and TF/TP were also studied in three different cultivated

forms (tissue culture, cultivate and cuttage) of LHG. The values of TP were 18.58%,

13.63% and 10.84% in tissue culture, cultivate and cuttage LHG samples,

respectively. And the ratios (TF/TP) of culture, cultivate and cuttage were 0.012,

0.019 and 0.020, respectively. The TP in tissue culture was much higher than the

other cultivated forms of LHG. According to the previous researches, only TP of

tissue culture and cultivate were investigated in LHG (He et al. 2012; Xu and Meng

1986). The reported results were in agreement with this study.

19

Repetitive operation of CP-ANN

In this study, operations of 100 replicates were performed for CP-ANN using

MATLAB 6.5 based on the analytical results of test samples. From the results of the

replicates, approximate 70% results were similar to our presented results. Therefore,

the established chemometric model (CP-ANN) was stable and reliable in this study.

20

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Figure Captions

Fig. S1 Chemical structures of the 27 investigated compounds

Fig. S2 Effects of different ultrasonic treatments on the influences of peptides

cleavage (n = 3). (A) ultrasonic power, (B) ultrasonic time and (C) concentrations (a:

detected concentration and b: theoretical concentration)

Fig. S3 Representative UHPLC-QTRAP/MS2 chromatograms of injecting Leu, Ile,

Glu, Gln and Lys single standard solution

Fig. S4 Representative UHPLC-QTRAP/MS2 chromatogram of 27 target

compounds in 1.0 g/mL mixture standards. Peaks: 1 Trp, 2 Phe, 3 Leu, 4 Ile, 5

GABA, 6 Met, 7 Val, 8 Pro, 9 Tyr, 10 Cys, 11 Ala, 12 Hpro, 13 Thr, 14 Gly, 15 Glu,

16 Gln, 17 Ser, 18 GSH, 19 Asn, 20 Ala-Gln, 21 Cit, 22 Asp, 23 Arg, 24 His, 25 Lys,

26 Orn and 27 Cyst

Fig. S5 The effect of chromatographic stream on the ionization and signal stability of

the target analytes

Fig. S6 The total content of 27 investigated compounds in 3 parts of LHG

23

Fig. S1

24

25

Fig. S2

Fig. S3

26

Fig. S4

27

Fig. S5

28

Fig. S6

29

Table S1 Type and MRM parameters of 27 target compounds

No. Amino acid Abb. Type

Confirmatory

transition

(m/z)

Quantification

transition

(Q1Q3, m/z)

DP

(eV)

CE

(eV)

EP

(eV)

CXP

(eV)

1 Tryptophan Trp Essential 188.0, 146.0 205.1188.0 10 20 10 15

2 Phenylalanine Phe Essential 120.1, 103.0 166.1120.1 20 30 10 15

3 Leucine Leu Essential 86.1, 69.1 132.186.1 10 5 10 15

4 Iso-leucine Ile Essential 86.1, 69.1 132.186.1 10 5 10 15

5 -Aminobutyric acid GABA Non essential 87.0, 69.0 104.187.0 80 15 10 15

6 Methionine Met Essential 104, 56, 133 150.1104.1 20 20 10 15

7 Valine Val Essential 72.1, 55.1 118.172.1 15 15 10 15

8 Proline Pro Non essential 70.0, 43.0 116.170.0 20 5 10 15

9 Tyrosine Tyr Non essential 136.0, 123.0, 91.0 182.1136.0 15 20 10 15

10 Cysteine Cys Non essential 59.0, 76.0, 105.0 122.059.0 80 30 10 15

11 Alanine Ala Non essential 44.0, 62.0 90.144.0 15 20 10 15

12 Hydroxyproline Hpro Non essential 67.9, 86.0 132.167.9 80 30 10 15

13 Threonine Thr Essential 74.0, 93.0 120.174.0 20 20 10 15

14 Glycine Gly Non essential 30.0, 48.0 76.030.0 20 20 10 15

15 Glutamic acid Glu Non essential 83.9, 56.0, 102.0 148.183.9 80 30 10 15

16 Glutamine Gln Non essential 84.0, 56.0 147.184.0 20 80 10 15

17 Serine Ser Non essential 60.0, 70.0 106.160.0 10 20 10 15

18 Glutathione GSH Non essential 179.0, 162.0, 233.1 308.1179.0 80 30 10 15

19 Asparagine Asn Non essential 74.0, 87.0 133.174.0 15 20 10 15

20 Alanyl-glutamine Ala-Gln Non essential 83.8, 129.9 218.083.8 95 21 10 15

21 Citrulline Cit Non essential 159.0, 70.0, 106.0 176.1159.0 80 15 10 15

22 Aspartic acid Asp Non essential 88.0, 74.0 134.188.0 80 15 10 15

23 Arginine Arg Non essential 70.0, 60.0, 116.0 175.170.0 80 30 10 15

24 Histidine His Non essential 110.0, 93.1 156.1110.0 80 10 10 15

25 Lysine Lys Essential 83.9,56.1, 115.0 147.183.9 80 15 10 15

26 Ornithine Orn Non essential 116.0, 69.9 133.0116.0 80 15 10 15

27 Cystine Cyst Non essential 151.9, 120.0, 74.0 240.9151.9 80 21 10 15

30

Table S2 Storage stability of each target compound at different temperature conditions (n = 6,

RSDs%)

AnalytesConc.

(ng/mL)

4°C

(72 h)

25°C

(12 h)Analytes

Conc.

(ng/mL)

4 °C

(72 h)

25 °C

(12 h)

Tryptophan 10 1.56 2.15 Glutamic acid 10 4.24 4.87

100 2.16 3.06 100 3.57 4.62

Phenylalanine 10 0.89 1.64 Glutamine 10 2.73 4.01

100 1.25 2.03 100 3.06 3.84

Leucine 10 1.07 1.75 Serine 10 3.86 4.57

100 0.83 1.22 100 2.82 4.23

Iso-leucine 10 1.25 1.06 Glutathione 10 4.25 4.94

100 1.76 1.98 100 4.63 4.76

-Aminobutyric acid 10 2.54 2.82 Asparagine 10 3.68 3.05

100 2.17 2.61 100 3.13 3.55

Methionine 10 3.04 2.76 Alanyl-glutamine 10 1.06 1.79

100 2.26 2.89 100 2.24 3.06

Valine 10 2.98 3.45 Citrulline 10 3.79 4.46

100 3.25 3.18 100 4.14 4.25

Proline 10 3.94 3.76 Aspartic acid 10 4.26 4.81

100 2.57 3.89 100 3.88 3.48

Tyrosine 10 2.18 4.12 Arginine 10 4.15 4.63

100 2.63 3.35 100 3.96 4.27

Cysteine 10 2.58 2.18 Histidine 10 4.87 4.74

100 3.06 2.53 100 4.59 4.17

Alanine 10 2.79 3.67 Lysine 10 3.34 4.08

100 3.31 3.19 100 2.85 4.79

Hydroxyproline 10 2.18 2.96 Ornithine 10 4.39 4.88

100 2.06 2.55 100 3.83 4.75

Threonine 10 4.15 4.62 Cystine 10 4.16 4.21

100 4.67 4.19 100 3.69 4.53

Glycine 10 2.58 3.66

100 4.39 3.71

31

Table S3 Box-Behnken design (uncoded) arrangement for extraction and the

responses of the content of total content of FAAs and small peptides

Std a Run x1 (W) x2 (min) x3 (mL/g) Tc (g/g) b

14 1 250.00 40.00 300.00 5618.2

3 2 250.00 30.00 400.00 4565.9

10 3 100.00 40.00 400.00 3825.3

6 4 100.00 50.00 300.00 4236.9

9 5 100.00 40.00 200.00 3654.3

5 6 100.00 30.00 300.00 3833.7

7 7 400.00 30.00 300.00 3825.8

4 8 250.00 50.00 400.00 4700.4

13 9 250.00 40.00 300.00 5538.9

15 10 250.00 40.00 300.00 5602.9

2 11 250.00 50.00 200.00 4901.3

12 12 400.00 40.00 400.00 4853.9

8 13 400.00 50.00 300.00 4906.8

11 14 400.00 40.00 200.00 4578.9

16 15 250.00 40.00 300.00 5712.9

1 16 250.00 30.00 200.00 4652.8

17 17 250.00 40.00 300.00 5611.7a Standard order.b Total content of FAAs and small peptides.

32

Table S4 Inter- and intra-day variation in retention times for 27 target compounds

(min)

FAA

The retention times of

intraday

(n = 6)

The retention times of

interday

(n = 6)

Time difference

Trp 2.170 ± 0.004 2.172 ± 0.005 0.002

Phe 2.172 ± 0.001 2.173 ± 0.002 0.001

Leu 2.189 ± 0.003 2.192 ± 0.006 0.003

Ile 2.393 ± 0.005 2.397 ± 0.003 0.004

GABA 2.461 ± 0.002 2.465 ± 0.005 0.004

Met 2.693 ± 0.003 2.694 ± 0.003 0.001

Val 2.972 ± 0.004 2.975 ± 0.005 0.003

Pro 3.142 ± 0.003 3.148 ± 0.004 0.006

Tyr 3.163 ± 0.004 3.166 ± 0.007 0.003

Cys 3.702 ± 0.004 3.707 ± 0.007 0.005

Ala 4.313 ± 0.006 4. 315 ± 0.008 0.002

Hpro 4.472 ± 0.003 4.475 ± 0.009 0.003

Thr 4.781 ± 0.005 4.786 ± 0.010 0.005

Gly 4.880 ± 0.007 4.884 ± 0.013 0.004

Glu 4.996 ± 0.004 5.001 ± 0.009 0.005

Gln 5.343 ± 0.005 5.348 ± 0.006 0.005

Ser 5.398 ± 0.006 5.404 ± 0.008 0.006

GSH 5.531 ± 0.005 5.535 ± 0.011 0.004

Asn 5.555 ± 0.009 5.560 ± 0.013 0.005

Ala-Gln 5.696 ± 0.008 5.712 ± 0.012 0.006

Cit 5.743 ± 0.005 5.747 ± 0.007 0.004

Asp 5.988 ± 0.003 5.993 ± 0.003 0.005

Arg 6.745 ± 0.007 6.949 ± 0.014 0.004

His 6.863 ± 0.004 6.869 ± 0.010 0.006

Lys 6.871 ± 0.009 6.878 ± 0.015 0.007

Orn 6.938 ± 0.006 6.943 ± 0.013 0.005

Cyst 7.373 ± 0.008 7.377 ± 0.016 0.004

33

Table S5 Linear regression data and validation of developed method for 27

investigated compounds in LHG

FAAa

Linear regression dataLOD

(ng/mL)

LOQ

(ng/mL)

Precision (RSD% ) Repeatability

(RSD%)

(n = 6)

Stability

(RSD%)

(n = 6)

Mean recovery (%)b

Matrix

EffectcLinear R2Linear range

(ng/mL)

Intraday

(n = 6)

Interday

(n = 6)

Spike level

(0.1 mg/g)

Spike level

(1.0 mg/g)

Trp y = 5064.3x – 8624.5 0.9991 3.74-468.00 0.75 2.75 1.06 1.89 3.95 2.08 96.9 (4.15) 94.4 (3.36) 0.93

Phe y = 6342.1x – 177114 0.9993 3.26-408.00 0.32 1.08 1.38 2.22 1.92 1.19 106.4 (3.83) 93.8 (4.17) 0.92

Leu y = 689.29x + 2042.6 0.9998 4.22-528.00 0.84 2.16 1.25 2.77 2.75 1.29 96.9 (2.77) 97.9 (3.89) 0.96

Ile y = 727.9x – 2165.3 0.9989 7.00-528.00 1.46 3.68 1.15 2.82 1.98 1.13 107.5 (4.52) 96.8 (5.02) 0.97

GABA y = 2240.9x + 1550.1 0.9931 1.80-320.00 0.15 0.45 1.96 2.83 3.87 2.27 98.6 (1.76) 105.5 (4.15) 0.95

Met y = 1334.8x – 4419.7 0.9982 5.18-648.00 1.04 2.68 2.04 3.15 2.51 1.64 92.3 (5.64) 93.8 (5.54) 1.06

Val y = 7304.7x – 5233.7 0.9991 7.68-192.00 2.55 6.50 1.66 4.14 4.01 2.95 96.6 (4.12) 95.8 (4.86) 0.92

Pro y = 96.24x + 190.25 0.9996 1.92-1200.00 0.21 0.72 1.83 3.06 4.25 6.16 97.9 (2.32) 94.2 (3.18) 0.94

Tyr y = 2352.2x – 17388 0.9987 2.10-780.00 0.35 1.25 0.82 2.65 3.64 2.74 102.6 (2.98) 106.6 (5.07) 0.98

Cys y = 139.46x + 540.7 0.9920 86.40-3880.0 20.50 64.80 1.66 3.95 5.15 3.61 95.4 (3.65) 97.5 (4.82) 0.93

Ala y = 1203.9x – 27630 0.9983 61.44-1536.00 15.52 46.84 1.52 3.94 3.52 2.77 96.7 (1.64) 95.1 (3.06) 0.93

Hpro y = 561.55x – 1341.7 0.9985 6.72-504.00 1.34 4.03 2.06 2.78 2.76 1.84 103.6 (2.33) 94.3 (2.52) 0.95

Thr y = 609.83x + 84579 0.9997 248.00-33480.0 29.76 148.80 3.04 5.93 4.12 3.36 94.4 (4.17) 104.3 (1.88) 0.94

Gly y = 319.7x + 15072 0.9996 84.00-4200.00 16.86 60.00 3.52 5.13 5.48 4.25 102.5 (3.65) 95.2 (4.45) 0.97

Glu y = 769.48x + 297809 0.9943 206.40-15480.0 35.50 152.50 2.15 4.06 5.17 4.06 93.3 (4.05) 92.1 (5.73) 0.92

Gln y = 1204.3x – 11127 0.9982 5.57-696.00 1.96 4.98 2.26 3.99 3.89 2.18 94.7 (2.15) 106.9 (4.12) 0.98

Ser y = 748.54x + 28141 0.9985 30.72-3840.00 10.54 26.82 1.27 3.43 5.95 4.45 92.2 (3.61) 93.3 (5.56) 0.91

GSH y = 285.3x + 11530 0.9949 42.40-3180.00 7.24 24.80 2.69 4.58 4.87 6.69 98.1 (1.97) 94.8 (4.85) 0.95

Asn y = 448.23x + 131289 0.9988 127.00-15900.0 28.18 84.36 1.58 3.63 5.02 4.15 104.6 (2.84) 92.1 (3.39) 1.06

Ala-Gln y= 647.21x + 6965.3 0.9984 12.48-1560.00 1.21 4.25 1.15 2.66 3.94 2.86 94.2 (2.63) 96.9 (5.94) 0.93

Cit y= 1742.4x – 36073 0.9954 8.54-1068.00 63.66 190.65 3.02 5.57 6.15 4.72 96.6 (3.98) 90.9 (4.45) 0.92

Asp y= 543.03x – 110.96 0.9992 93.46-4860.00 21.52 68.56 3.69 6.28 4.48 3.08 92.9 (4.25) 91.2 (6.54) 1.05

Arg y= 5418.6x + 535928 0.9982 52.00-3900.00 15.36 48.56 2.82 5.49 6.23 4.63 95.8 (3.32) 93.9 (5.89) 0.97

His y= 2732x – 15603 0.9963 45.60-3240.00 10.68 36.12 3.51 6.06 6.81 6.16 94.5 (5.27) 92.1 (5.57) 0.93

Lys y = 986.61x + 187154 0.9982 60.00-7500.00 18.15 56.75 2.89 4.84 6.25 4.14 91.6 (4.93) 90.5 (6.06) 0.91

Orn y = 448.67x + 19572 0.9943 24.60-1800.00 7.82 24.60 3.53 6.24 5.84 5.11 92.0 (5.32) 93.8 (5.73) 0.92

Cyst y= 675.92x – 6187 0.9977 4.90-612.00 0.92 2.48 2.93 5.65 5.52 4.55 93.1 (4.45) 94.2 (4.85) 1.03a analytical 27 target compounds in this study

b repeatability values, expressed as RSD are given in brackets (n = 6)

c matrix effects are calculated by slope matrix/slope solvent

34

Table S6 The contents of total free amino acids (TF, %) and proteins (TP, %), and the

values of TF/TP in different kinds of LHG samples

Samples Total FAAs (TF, %) Total protein (TP, %) TF/TP

Epicarp 0.16 4.49 0.036

Mesocarp and endocarp 1.24 9.54 0.130

Seed 0.52 18.51 0.028

Tissue culture 0.22 18.58 0.012

Cultivate 0.26 13.63 0.019

Cuttage 0.22 10.84 0.020

35