Infrared-metabolomics approach in detecting changes in Andrographis paniculata ...

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IR- Metabolomics Approach in Detecting Changes of Andrographis

paniculata Metabolites due to Different Harvesting Ages and Times

Nur A’thifah Yusof,a Azizul Isha,a Intan Safinar Ismail,*a Alfi Khatib,a,b Khozirah Shaari,a Faridah

Abas,a and Yaya Rukayadia

Correspondence to: Intan Safinar Ismail, Laboratory of Natural Products, Institute of Bioscience,

Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia.E-mail: [email protected]

aLaboratory of Natural Products, Institute of Bioscience, Universiti Putra Malaysia, 43400 UPM

Serdang, Selangor, Malaysia

bKuliyyah of Pharmacy, International Islamic University Malaysia, 25710 Kuantan, Pahang,

Malaysia.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/jsfa.6987


Abstract

BACKGROUND: The metabolite changes in three germplasm accessions of Malaysia

Andrographis paniculata (Burm. F.) Nees, viz 11265 (H), 11341 (P), 11248 (T) due to their

different harvesting ages and times were successfully evaluated by Attenuated Total Reflectance

(ATR)-Fourier Transform Infrared (FTIR) spectroscopy and translated through multivariate

data analysis of Principal Component Analysis (PCA) and Orthogonal Partial Least Square-

Discriminant Analysis (OPLS-DA). This present study revealed the feasibility of ATR-FTIR in

detecting the trend changes of the major metabolites, andrographolide and

neoandrographolide, functional groups in A. paniculata leaves of different accessions. The

harvesting parameter was set at three different ages of 120, 150 and 180 days after

transplanting (DAT) and at two different time sessions of morning (7.30 am–10.30 am) and

evening (2.30 pm–5.30 pm).

RESULTS: OPLS-DA successfully discriminated the A. paniculata crude extracts into groups of

which the main constituents, andographolide and neoandrographolide, could be mainly

observed in the morning session of 120 DAT for P and T, while H gave the highest intensities of

these constituents at 150 DAT.

CONCLUSION: The information extracted from ATR-FTIR data through OPLS-DA could be

useful in tailoring this plant harvest stage in relation to its two major diterpene lactones,

andographolide and neoandrographolide, contents.

Keywords: Fourier Transform Infrared, metabolomics, Andrographis paniculata, harvesting

age, harvesting time


Abbreviations

ATR-FTIR Attenuated Total Reflectance-Fourier Transform Infrared

DAT Days After Transplanting

FTIR Fourier Transform Infrared

IR Infrared

OPLS-DA Orthogonal Partial Least Square-Discriminant Analysis

PCA Principal Component Analysis

VIP Variables Influence on Projection


INTRODUCTION

Andrographis paniculata (Burm. F.) Nees is an annual herbaceous medicinal plant belongs to

Acanthaceae family which is widely used and can be found abundantly in many Asian countries

including Malaysia.1 Owing to the extremely bitter characteristic of this herb; A. paniculata is

commonly known as the “King of Bitters” or in Malaysia locally known as “Hempedu Bumi”. The

leaves and roots are usually used for a wide variety of ailments as well as herbal supplements.

Among its wide range of medicinal and pharmacological applications, Malaysian usually used this

plant to treat diabetes and hypertension.2 The juice of fresh leaves is used in the treatment of colic

pain, loss of appetite, irregular stools and diarrhea.3 Hitherto, the main chemical constituents of A.

paniculata which are believed to be responsible components for most of the biological activities are

diterpenoids with the primary medicinal agent being the diterpene lactone, andrographolide,4 and

flavonoids.5 The other diterpene lactones are neoandrographolide, 14-deoxy-11,12-

didehydroandrographolide, and 14- deoxyandrographolide.6

A. paniculata was reported to have different accumulation of the active components in which

at the initial flowering stage, andrographolide was high in the plant leaves.1 The harvesting step was

therefore recommended to be performed from the initial flowering period until around 50% of the

blooming7 or when the age reached 110-150 days.8 During this period, the plant leaf was observed to

contain the highest percentage of the active components.9 It was suggested that plants including

herbaceous type undergo natural variations due to the factors such as varieties and geographical

origins. Plants are also constantly interacting with environment in their growing conditions, for

example climate, exposure of light, water conditions or even other organisms. The chemical

components of A. paniculata might also be influenced by one or more of these factors. Hence, the

detection of the variations in A. paniculata leaves metabolites, either in identity or intensity, due to the

different harvesting times and ages might be useful in targeting desired compound compositions for a

selected remedy. ATR-FTIR spectroscopy has been shown to be a rapid and direct analytical

technique with the advantage of no sample preparation.10 Taking this advantage into account, the


feasibility of ATR-FTIR associated with multivariate data analysis (OPLS-DA) for the evaluation of

A. paniculata major trends in the metabolite composition changes is challenged in this study.

EXPERIMENTAL

Plant materials

The A. paniculata seeds from three germplasm accessions of Malaysia (Accession 11265, 11341 and

11248 which are designated as H, P and T respectively) were collected in July 2011 from Ladang

Dua, Universiti Putra Malaysia (UPM). The seeds were germinated at Agro Gene Bank (Seed Bank)

by using sand scarification method.11 The scarified seeds were then soaked in the distilled water

before arranged properly in a Petri dish containing 90 seeds from each accession. Two filter papers

(Whatman, No.2) which have been moistened with distilled water were used as the seedbed inside the

Petri dish as to allow water to get through the embryo and accelerated the germination rate. All the

Petri dishes were sealed with parafilm and incubated in the controlled growth chamber with the

average temperature from 26 °C to 32 °C and relative humidity varied between 60% and 75%.

Plant cultivation

The cultivation took place at the Institute of Bioscience (IBS), UPM wherein within two weeks all of

the germinated seeds were transferred into Jiffy-7 seedling pots (Hydro-Grow, UK Ltd). After the

plants reached a month old, they were again transferred into polybags (14 cm x 10 cm, black)

containing fine sand, topsoil and organic material in the ratio of 2:1:1. The planting distance between

each plant was set at 30 cm x 30 cm. In order to enhance the growing process, the Welgro fertilizer

(Vitapro, Petaling Jaya, Selangor) which was enriched with the Nitrogen, Phosphorous and Potassium

(NPK; 15:30:15) was sprayed once a week in the morning to the whole plants. The Welgro fertilizer

of 2 g dissolved in 6 L of distilled water was freshly prepared for each irrigation time. All the leaves

(1-8 cm long, 0.5-3.0 cm wide) of each plant were harvested in January, February and March 2012

(120, 150 and 180 DAT) at two different time sessions of morning (7.30 am-10.30 am) and evening

(2.30 pm-5.30 pm), whereby resulted in 10 biological replications for each age of an accession (n=5

for morning; n=5 for evening session). Each replicate was quenched with liquid nitrogen, ground into


homogenized powder form and stored at -80 °C prior to drying by freeze-dry system (Labconco,

Texas, USA) before used.

Sample preparation

The freeze-dried leaves powder of A. paniculata in 150 mg was extracted by sonication in 5 mL

methanol commercial grade (30 minutes, 40 °C). The extraction step was repeated twice and the total

combined supernatant was filtered through filter paper (Whatman, 125mm) and evaporated by using

miVac Modular Concentrator series (Genevac Ltd., Suffolk, UK). The crude extracts were then kept

in -80 °C until IR analysis. The crude samples were freeze-dried again before submitting to IR

analysis to prevent the absorbance interference caused by the water content.

ATR- FTIR analysis

IR spectra were recorded by using Spectrum 100 Fourier transform infrared (FT-IR) spectrometer

(Perkin Elmer, CA, USA) with a single reflectance horizontal ATR cell equipped with a zinc selenide

crystal. The analyses were made in absorption mode on a small amount of crude sample deposited on

the ATR crystal. The spectra of five biological replicates and pure compounds in three technical

replicates were obtained in the frequency range of 4000-280 cm-1 with a resolution of 4 cm-1 and a

total accumulation of 16 scans. The pure compounds of the main diterpene lactones, andrographolide

and neoandrographolide, were obtained from the in-house isolation by which their physical and

chemical data were confirmed of those main compounds (Supplementary Material).

Multivariate Data Analysis

All of the spectra were baseline-corrected and smoothed before converted into ASCII format and

collected into a single table of Microsoft Office Excel 97-2003. The processed data were then

imported into SIMCA-P version 13.0 (Umetrics, Umeå, Sweden) for multivariate statistical analysis

in scaling parameter of unit variance, UV. PCA was adopted for the initial exploratory data analysis

whereby the scores plot reflected separation among the sample. However, OPLS-DA was preferably

employed due to the clearly observed discrimination of the samples in accordance to their harvesting


ages and times. The employed model was described by the criterion of R2 which indicated the

goodness of fit and Q2 the goodness of prediction. The variables influences on projection (VIP) values

exceeding 1.0 were selected as metabolite cut off in order to identify the important peak signals of the

absorbance in the loading scatter plots. These VIPs ≥1 were matched to those peaks in the loading

column plot which made possible the correlation to the observations in the respective quadrant of the

scores plots. Moreover, the significance of each model established was validated by p-Value (p<0.05)

of CV-ANOVA (Supplementary Material).

RESULTS AND DISCUSSION

Sharma and co-workers reported that the highest level of andrographolide content was in the leaves

while the seeds gave the lowest.12 This diterpene lactone along with its derivatives,

neoandrographolide, could be extracted out in greater amounts when using methanol compared to

other solvent extractions.13,14 Even though some previous phytochemical screenings of A. paniculata

leaves have showed that the methanol extract might contain various of other components such as

glycosides, steroids, phenols, tannins and saponins,3 the maximum extraction of the main compounds

diterpene lactones is also in methanol.15 Due to the ease of sample preparation and rapid analysis of

ATR-FTIR, this technique was applied to the A. paniculata leaves methanol extracts to capture the

metabolome changes in the phenomenon of different harvesting ages and times. The metabolites

which could be suggested presence based on the IR functional groups are as tabulated in Table 1. The

maximum absorption peak signals of the functional groups were observed to vary in the leaves of

each accession, which can be suggested to be due to the different origins of the plant seeds. The

metabolites presence in each sample were assigned by functional groups absorption peak values

compared to the measured standard compounds of the two main diterpene lactones and also other data

published elsewhere. The obtained ATR-FTIR spectra revealed that the absorption signals were in

close similarity to those of andrographolide and neoandrographolide. Based on the spectral data, the

differences of the metabolite signals were visualized via statistical analysis of PCA and OPLS-DA by

which the influences of the two harvesting parameters of ages and times were deciphered.

Harvesting ages of 120, 150 and 180 DAT for H, P and T accessions


The characterization of absorptions was achieved based on the specific assignment for each related

structural functional group in the obtained spectra (Table 1) to those of known or reported data.

Figures 1, 2 and 3 show the spectra of each accession for three different harvesting ages of 120, 150

and 180 DAT. The spectra for all accessions are generally showing a similar pattern of absorption

peaks as listed in Table 1 whereby indicating that the leaves of A. paniculata at different ages might

possess the same major constituents. However, some variations in peak shapes such as band shoulder,

and the peak intensities particularly observed in the regions of 1300-1100 and 770-650 cm-1 were

detected by the multivariate data analysis of both PCA and OPLS-DA.

PCA is an unsupervised discrimination method applied to preliminarily visualize the possible

trends and discover the outliers which might not fit in the model.24,25 The PCA models for each

accession were as visualized in Figure 4 from which a few outliers fall outside the 95% confidence

level of Hotelling’s T2 (Supplementary Material) were diagnosed. The plots of the two PCs (PC1 and

PC2) of these three PCA models demonstrated the R2 and Q2 values of over 85% and 65%,

respectively. The PCA score plots of P, T, and H accessions exhibited high goodness of fit (R2X=

0.849, 0.871 and 0.889, respectively) and predictability (Q2= 0.688, 0.742 and 0.825, respectively)

which are greater than 0.5 for each model (Figure 4). The clustering between the harvesting ages of P

and H accessions could be roughly defined in the PCA models, but not in T accession which gave

distribution of undefined grouping. In view of the good fit and predictability obtained for all PCA

models, OPLS-DA statistical approach was adopted to further find out which metabolites contribute

to the discrimination between the different plant ages and harvesting time sessions.

The OPLS-DA scores plots for different ages of H, P, and T accessions were analyzed as

shown in Figure 5 wherein all accessions gave a distinct discrimination among the three different

harvesting ages of 120, 150 and 180 DAT in PC2. The positive values are seen for the variables

associated with 120 DAT whereas 150 and 180 DAT are associated with negative values.

Examination of the loading plots of all accessions for the three harvesting ages overlapped with the

ATR-FTIR data of the two major diterpene lactones (Andrographolide; A and Neoandrographolide;

N) showed that the intensities of these lactones strongly contributing to the separation. The


responsible loading plots corresponding to the peak signals of andrographolide and

neoandrographolide functional groups were mostly spotted at 120 DAT for P and T, whereas H is at

150 DAT (Figure 5). The correlation between measured IR data of both standard compounds and the

crude extracts were graphically presented together in the loading scatter plot. The spectral regions

responsible for the specific clustering could easily be observed and distinguished wherein the major

compounds of andrographolide and neoandrographolide could be seen intensely during morning of

120 DAT for P and T; and morning of 150 DAT for H accession.

P accession discriminated 120 DAT from the other two harvesting ages by the absorption

peaks at ~2930, ~2850, ~1380, ~1271, ~1176 and ~1070 cm-1 in which the two strong peaks at ~2930

and ~2850 cm-1 are due to the presence of asymmetric and symmetric long-chain alkyl compounds,

respectively. As for T accession, the peaks which responsible for the observed separation of 120 DAT

are ~1380, ~1274, ~1202 and ~821 cm-1. Both P and T accessions also possessed prominent

absorption peaks that discriminated them from each other in the range of 1300-1100 cm-1. Most of

these significant spectral variables of 120 DAT were also observed as peak signals which

distinguished this age from 150 and 180 DAT. Unlike P and T accessions, the ATR-FTIR peaks at

~1070, ~1030, ~820, ~770 and ~710 cm-1 were mostly observed in 150 DAT of the H accession.

Differently from other accessions, H also showed an obvious hydroxyl group absorption peak at

~3330 cm-1 for 180 DAT. This observation suggested that the latter the harvesting age of the leaves

might show the possible presence of higher content of compounds embodying hydroxyl groups. The

most attributable region for the discrimination is the fingerprint below 800 cm-1 that having

remarkably high intensities of the band shoulders at ~770 and ~710 cm-1. These two peaks were also

spotted in high intensities for 180 DAT of P accession.

Concentrated markers of andrographolide and neoandrographolide could be observed for H

accession of 150 DAT as shown in Figure 5c, which suggested that these two compounds were

intense during this age. These diterpene lactones could possibly being produced at the growing stage

of 120 to 150 DAT, but started to decrease within the aging leaves in 180 DAT. These results are in

agreement with those of previous works on the total of andrographolide and neoandrographolide


which increased over different maturity dates.26 In 1991, Suwanbareerak and Chaichantipyuth8 also

recommended that A. paniculata should be harvested within the age of 110-150 days, which this study

support that the best harvesting age for P and T is at 120 DAT, and H at 150 DAT. The significant

difference between these harvesting ages for each accession was established based on the p-Value of

CV-ANOVA of less than 0.05 (Supplementary Material). Pholphana and co-workers27 reported that

the variations in A. paniculata active compounds have been mainly due to the differences in

genotypes, growing environment, harvesting time and age of leaves.

Harvesting time of morning and evening sessions

At the selected harvesting ages (P and T; 120 DAT, and H; 150 DAT) which showed high major

compounds intensities, their harvesting times of morning and evening sessions in relation to those

compounds contents were evaluated. The data set for each harvesting time at the selected age of P, T

and H were generated individually by using OPLS-DA as depicted in Figure 6. The morning session

of P showed a few pronounced peaks with higher intensities at ~1600, ~1373, ~1274, ~1206, ~1176,

~1070 and ~1030 cm-1, which were deciphered in negative quadrant of PC2. The highlighted regions

of the standard compounds within the loading scatter plots were correlated to the loading line plot

(Figure 6). The OPLS-DA model for P was established by using one predictive and one orthogonal

component (R2X=0.333, R2Y=0.608, Q2=0.169) which resulted in a higher p-value (p>0.05). Thus,

suggesting the insignificant discrimination due to the small differences and low predictability of the

model in discriminating between the morning and evening harvesting sessions (Supplementary

Material).

Almost similar to P, the T morning harvesting session also possessed the peaks at~1380,

~1274, and ~1206 cm-1 based on the model evaluated with one predictive and one orthogonal

component with R2X, R2Y and Q2 values of 0.424, 0.599 and 0.348. The result of morning harvesting

session possessed two noticeable peaks at: ~1740 and ~1440 (sh) cm-1 led to the discrimination of the

harvesting times for H (Figure 6c), which was explained by OPLS-DA model with R2X, R2Y and Q2

values of 0.905, 0.979 and 0.767. The peak at ~1740 cm-1 is suggested to be due to the stretching


vibration of carbonyl group which is possibly from andrographolide, neoandrographolide and

flavonoids. Both T and H accessions, however; exhibited significant difference between morning and

evening harvesting sessions with p-value of both accessions being lower than 0.05 (Supplementary

Material).

CONCLUSION

The results showed that ATR-FTIR spectra from each accession exhibited differences which were

discriminated and clustered into groups through Multivariate Data Analysis of OPLS-DA. Thus the A.

paniculata leaves metabolome changes, interpreted based on the two major compounds

andrographolide and neoandrographolide, due to the harvesting ages as well as the times were

observed to be high in the morning of 120 DAT for P and T, but at 150 DAT for H. These findings

could be useful as a guide to which time and age of A. paniculata should be harvested to have the

targeted major diterpene lactones intensities.

ACKNOWLEDGEMENTS

This work received financial support through Exploratory Research Grant Scheme (5527124) from

the Ministry of Education (MOE) and Research University Grant Scheme of Universiti Putra

Malaysia (9375600 and 9196800). The first author would like to thank UPM for the Graduate

Research Fellowship (GRF). The authors also thank Mrs. Rusnani Amirudin, Mr. Tajuddin Abd.

Manap and Dr. Daryush Talei for their advice and help throughout this work, and Professor Johnson

Stanslas for the provision of the pure diterpene lactones.

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Table1. FTIR-peaks assignment of Andrographis paniculata based on published reported data and measured

standard compounds

Wavenumber

(cm-1)

Base group and vibration

mode

Main attribution Reported 11, 16-

23

Measured

A N A N

3330

2930

2850

1735

1600

1440

1380

1274

1206

1176

1070

1030

900

820

770

710

υ(O-H)

υas(C-H)

υs(C-H)

υ(C=O)

υ(C=C)

υ(C=C), υ(aromatic)

δs(C-H)

υas(C-CO)

δ(C-H)

υ(C-O), δ(C-OH)

υ(C-C), δ(C-OH)

υ(=C-O-C), υ(C-C), δ(C-

OH)

γ(C-H)

γ(C-H)

γ(C-H)

υ(C-H)

Hydroxyl

Methylene

Methylene

Ester, carbonyl, ketone

Aromatic benzene ring

CH3, CH2, aromatic ring

CH3

Phenolic hydroxyl

CH of phenyl

Ester, tertiary alcohol

groups

Secondary alcohol groups

Aromatics, primary alcohol

groups

End methylene

Benzene ring

Benzene ring

CH2 rocking

1728

1595

1459

1367

1266

1220

1158

1079

1034

909

816

715

1749

1594

1443

1383

1287

1174

1072

1031

908

835

2932

2857

1721

1596

1458

1367

1278

1219

1055

849

2931

2858

1731

1452

1372

1287

1214

1016

902

831

717

Note: υ, stretching or vibration; δ, in plane deformation; γ, out-of-plane deformation; s, symmetrical; as, asymmetrical; sh,

shoulder; A= Andrographolide, N= Neoandrographolide


a

b

c

Fig.1 ATR-FTIR spectra of 4000-650 cm-1 region for P accession, harvested at; a) 120 DAT. b) 150 DAT. c)

180 DAT harvesting age (30 replicates of 10 biological replicates).

υ(C-O), δ(C-OH) υs(C-H)

δs(C-H)

γ(C-H)

υas(C-CO)υas(C-H) υ(C-C),

δ(C-OH)

�(C-H)


a

b

c

Fig.2 ATR-FTIR spectra of 4000-650 cm-1 region for T accession, harvested at; a) 120 DAT. b) 150 DAT. c)


υas(C-CO)

γ(C-H)

δs(C-H)

δ(C-H)


a

b

c

Fig.3 ATR-FTIR spectra of 4000-650 cm-1 region for H accession, harvested at; a) 120 DAT. b) 150 DAT. c)


υ(C-C), δ(C-OH)

υ(O-H)

γ(C-H)

υ(=C-O-C), υ(C-C), δ(C-OH)

γ(C-H)

υ(C-H)

a

b

c

Fig. 4 PCA scores scatter plot of the FTIR spectra, 30 representatives for each accession ( 120 DAT; 150

DAT; 180 DAT harvesting age): a) P accession. b) T accession. c) H accession.


a

b

c

Fig. 5 OPLS-DA score and loading scatter plot of the FTIR spectra, 30 representatives for each accession (

120 DAT; 150 DAT; 180 DAT harvesting age): a) P accession. b) T accession. c) H accession

(Andrographolide, A; Neoandrographolide, N). (Groups are highlighted by the circles manually drawn)


a

b

c

Fig. 6 OPLS-DA score and loading scatter plot, and loading line plot for of the FTIR spectra of 15 representatives ( morning; evening session) a) 120 DAT, P

accession. b) 120 DAT, T accession. c) 150 DAT, H accession (Andrographolide, A; Neoandrographolide, N) (Groups are highlighted by the circles manually drawn).

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Infrared-metabolomics approach in detecting changes in Andrographis paniculata ...

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