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Article

Discovery, Synthesis, and Functional Characterization ofa Novel Neuroprotective Natural Product from the Fruit of

Alpinia oxyphylla for use in Parkinson’s Disease Through LC/MS–Based Multivariate Data Analysis–Guided FractionationGuohui Li, Zaijun Zhang, Quan Quan, Ren-Wang Jiang, Samuel S.W. Szeto, ShuaiYuan, Wing-Tak Wong, Herman H. C. Lam, Simon Ming Yuen Lee, and Ivan K Chu

J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00152 • Publication Date (Web): 01 Jun 2016

Downloaded from http://pubs.acs.org on June 3, 2016

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1

Discovery, Synthesis, and Functional Characterization of a Novel

Neuroprotective Natural Product from the Fruit of Alpinia oxyphylla for use

in Parkinson’s Disease Through LC/MS–Based Multivariate Data Analysis–

Guided Fractionation

by

Guohui Li1,2†

, Zaijun Zhang2,3†

, Quan Quan1,Renwang Jiang4, Samuel S.W. Szeto

1, Shuai Yuan

2, Wing-tak

Wong5, Herman H. C. Lam

1, Simon Ming-Yuen Lee

2*, Ivan K. Chu

1*

1Department of Chemistry, The University of Hong Kong, Hong Kong, China;

2State Key Laboratory

of Quality Research in Chinese Medicine and Institute of Chinese Medical Sciences, University of

Macau, Avenue Padre Tomás Pereira S.J., Taipa, Macao, China; 3Institute of New Drug Research,

Guangdong Province Key Laboratory of Pharmacodynamic, Constituents of Traditional Chinese

Medicine & New Drug Research, College of Pharmacy, Jinan University, Guangdong,

China;4Institute of Traditional Chinese Medicine and Natural Products, College of Pharmacy, Jinan

University, Guangzhou 510632, P. R. China; 5Department of Applied Biology & Chemical

Technology, The Hong Kong Polytechnic University, Hong Kong, China

*Address correspondence to:

Ivan K. Chu, Department of Chemistry, The University of Hong Kong, Pokfulam, Hong Kong,

China. Tel.: (852) 2859 2152, Fax: (852) 2857 1586, E-mail: [email protected]

Professor Simon Ming-Yuen Lee, Institute of Chinese Medical Sciences, University of Macau, Av.

Padre Tomás Pereira S.J., Taipa, Macao, China. Tel.: (853) 8397 4695, Fax: (853) 2884 1358, E-mail:

[email protected]

† Contributed equally to this study.

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Abstract

Herein we report the discovery of a novel lead compound, oxyphylla A [(R)-4-(2-hydroxy-5-

methylphenyl)-5-methylhexanoic acid] (from the fruit of Alpinia oxyphylla), which functions as a

neuroprotective agent against Parkinson’s disease. To identify a shortlist of candidates from the

extract of A. oxyphylla, we employed an integrated strategy combining liquid chromatography/mass

spectrometry, bioactivity-guided fractionation, and chemometric analysis. The neuroprotective

effects of the shortlisted candidates were validated prior to scaling up the finalized list of potential

neuroprotective constituents for more-detailed chemical and biological characterization. Oxyphylla A

has promising neuroprotective effects: (i) it ameliorates in vitro chemical-induced primary neuronal

cell damage and (ii) alleviates chemical-induced dopaminergic neuron loss and behavioral

impairment in both zebrafish and mice in vivo. Quantitative proteomics analyses of oxyphylla A–

treated primary cerebellar granule neurons that had been intoxicated with 1-methyl-4-

phenylpyridinium revealed that oxyphylla A activates nuclear factor-erythroid 2-related factor 2

(NRF2)—a master redox switch—and triggers a cascade of antioxidative responses. These

observations were verified independently through western blot analyses. Our integrated

metabolomics, chemometrics, and pharmacological strategy led to the efficient discovery of novel

bioactive ingredients from A. oxyphylla while avoiding the non-targeting, labor-intensive steps

usually required for identification of bioactive compounds. Our successful development of a

synthetic route toward oxyphylla A should lead to its availability on large scale for further functional

development and pathological studies.

Keywords: natural products · neuroprotective · Parkinson’s disease · proteomics · NRF2

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Introduction

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases, affecting up to 1%

of those over the age of 65.1 Despite the number of candidate disease-modifying agents that have

displayed promising therapeutic effects in preclinical trials, no licensed PD neuroprotective drugs are

currently available.2 In recent years, emphasis has being placed on identifying and characterizing

potentially active plant-derived pharmaceutical ingredients to fill this persistent unmet demand.3

Historically, natural products have been a main source of compounds displaying medicinal properties

and have been used as a platform for drug discovery.4-6

Despite continuing success at providing lead

compounds, within the past two decades the use of natural products had diminished, with a focus

shifting toward approaches (e.g., combinational chemistry) that might provide a range of molecules

for successful lead discovery.7, 8

In practice, however, many of the large screening collections have

been unsatisfactory at generating useful targets; instead, it is now recognized that biologically

relevant chemical space is better covered by natural products than by synthetic compounds.9, 10

Indeed, natural products remain an enormous untapped resource for continued discovery and

development of therapeutic agents for a wide range of disease conditions.11

Therefore, a reemphasis

on natural products as the foundation for drug discovery has recently emerged, but this approach is

not without significant challenges.7 Natural extracts from plants and microorganisms typically

feature a diverse and complex array of metabolites with varying and distinct chemical and physical

properties; these compounds can exist over a wide dynamic range of concentrations.12, 13

The

conventional reductionist approach of discovering bioactive compounds from natural products

involves bioassay-based screening of concentrated extract samples, followed by sequential rounds of

isolation and screening. This strategy is tedious, time-consuming, and often identifies previously

characterized compounds;11, 12, 14

it might also be ineffective for identifying compounds present at

sub-stoichiometric levels if their activities are masked by less potent, but more abundant,

compounds.15

In addition, bioassay-based screening may be confounded by additive or synergistic

effects of interacting compounds present in the extracts, thereby complicating downstream

purification and identification processes.15, 16

To tackle the complex problem of identifying bioactive compounds from natural products,

metabolomics-based approaches are becoming increasingly favored.17, 18

Metabolomics is a

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comprehensive qualitative and quantitative strategy aimed at profiling all of the metabolites in a

sample, and correlating their levels to the context of the biological situation under investigation.7

One of the main aspects of metabolomics is the application of multivariate data analysis (MVDA) to

simultaneously evaluate a vast number of identified metabolites and determine their contributions to

the observed biological activity. MVDA is a powerful technique for the analysis of datasets with a

large number of variables (e.g., metabolites), and enables visualization and downstream

interpretation of data that correlate with a target variable (e.g., bioactivity).17, 19

To date, however, the

metabolomics approach has been focused predominantly on finding system phenomena; its

application to the detection of lead compounds remains in an early stage.20

Recently, metabolomics

has demonstrated strong potential for use as a component of dereplication strategies, for evaluating

the efficacy and variability of natural product extracts, and for the efficient screening of potentially

active metabolites by linking the chemical profiles of the examined extracts to their bioactivity data.7,

12, 13, 17, 21 Considering the demonstrated utility of this tool to aid in the discovery of active

compounds from natural products, in this study we designed an integrated purification strategy,

incorporating a metabolomics component, for the efficient identification of bioactive metabolites and

their isolation from complex natural product extracts while avoiding the untargeted labor-intensive

fractionation steps of the classical approach. We chose liquid chromatography/mass spectrometry

(LC-MS) as the analytical technique because, combined with electrospray ionization, its sample

preparation is simpler than that for gas chromatography/MS; it also features high sensitivity and

selectivity, a wide dynamic range, can utilize a combination of different separation phases (i.e.,

reversed and normal LC phases), and is high-throughput with particular utility toward plant

metabolites because of their inherent chemical diversity.22-25

In addition, the MS polarities (positive

and negative modes) enable it to cover a more comprehensive range of compound species than other

analytical techniques used for chemical profiling.22, 24

This LC-MS approach also has a unique

feature in that it generates a pair-identifier (mass-to-charge ratio/retention time) of the characterized

metabolites; this highly useful information can be used to facilitate more efficient downstream

isolation of the targeted bioactive compounds.22, 23, 26

Among the various sources of natural products, interest in traditional Chinese medicines from a

modern pharmacological perspective has risen steadily, due their long historical use as foods and

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medicines with epidemiological evidence of tolerance.27

One of these well-established traditional

Chinese medicines, the fruit of Alpinia oxyphylla, has emerged as a potential source of therapeutic

compounds because an increasing amount of evidence is indicating its beneficial effects on various

neurodegenerative diseases, including Parkinson’s disease (PD).28

Also known as Yi Zhi in Chinese,

it has been used historically to treat brain-related disorders (e.g., stroke, amnesia) and many other

medical conditions since at least 1328 A.D., as documented in the ancient Chinese medicine book Shi

Yi De Xiao Fang.29

In several recent studies, modern molecular pharmacological approaches, using

multiple in vitro and in vivo PD neuronal damage models, have demonstrated the protective potential

of the ethanolic extract of the fruit of Alpinia oxyphylla (AOE).28, 30-32

Although attempts have been

made previously to determine its neuroprotective compounds, substantial profiling of AOE

metabolites33-35

has led to protocatechuic acid and chrysin being the only major neuroprotective

bioactive ingredients identified.36

In this study we employed a metabolomics-based approach to identify novel neuroprotective

compounds from AOE that might be potential leads as PD therapeutics. We used LC-MS to

characterize the metabolites present in AOE and correlated their observed bioassay activities using

chemometric analyses. Using this approach we identified a novel lead compound, oxyphylla A [(R)-

4-(2-hydroxy-5-methylphenyl)-5-methylhexanoic acid], that functions as a neuroprotective agent

against both in vitro and in vivo PD neuronal damage models. Cellular 1-methyl-4-phenylpyridinium

ion (MPP+) intoxication often involves the over-generation of reactive oxygen species (ROS) during

oxidative stress.37

The neuroprotective effects elicited by oxyphylla A was hallmarked by a number

of the differentially expressed antioxidant enzymes and oxidoreductases. Thus, the protein

expression profiles of MPP+–induced cerebellar granule neurons (CGNs) with and without oxyphylla

A treatment provide insight on the molecular mechanisms underlying these neuroprotective effects

using isobaric tags for relative and absolute quantitation (iTRAQ) tag labeling and multidimensional

liquid chromatography/tandem mass spectrometry(LC-MS/MS). We have demonstrated the utility of

a multifaceted and integrative strategy involving metabolomics, proteomics, pharmacology and

chemometrics for the discovery of A. oxyphylla fruit derived bioactive ingredients.

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Experimental Section

Chemicals and reagents

MCI gel CHP 20P (75–150 µm) was purchased from Mitsubishi Chemical (Tokyo, Japan). Sephadex

LH-20 was purchased from GE Healthcare Bio-Sciences AB (Uppsala, Sweden). TLC plates (20 ×

20 cm, AlugramSil G/UV 254) were purchased from Macherey-Nagel (Duren, Germany). Silica gel

(200–300 mesh) was purchased from Qingdao Marine Chemical Factory (Qingdao, China). AR-

grade petroleum ether was obtained from LAB-SCAN (Bangkok, Thailand); AR-grade ethyl acetate

was purchased from UNIVAR (NSW, Australia). HPLC-grade MeOH and acetonitrile (ACN) were

obtained from Scharlau (Sentmenat, Spain). Jupiter C18 packing material (3 µm particles, 300A°

pores) were purchased from Phenomenex (Torrance, CA, USA). Formic acid (≥98%) was purchased

from Fluka (St. Louis, MO). The iTRAQ kit was purchased from AB Sciex (Foster City, CA). The

Milli-Q system was purchased from Millipore (Bedford, MA). All reagents and materials for cell

culturing were purchased from Life Technologies (Carlsbad, CA). Protease inhibitor cocktail was

purchased from Roche Applied Science (Mannheim, Germany). Phenylmethylsulfonyl fluoride

(PMSF) was purchased from Sigma–Aldrich (St. Louis, MO). Rabbit anti-mouse tyrosine

hydroxylase (TH) polyclonal antibody (1:500) was obtained from Millipore (Bedford, MA).

Immunol staining primary antibody dilution buffer was obtained from Beyotime (Beijing, China).

Diaminobenzidine (DAB) Kit and horseradish peroxidase (HRP)-conjugated goat anti-rabbit

secondary antibody were obtained from Gene Company (Shanghai, China). Mouse monoclonal anti-

TH antibody MAB318 was purchased from Merck Millipore (Darmstadt, Germany). Rabbit

monoclonal antibody against erythroid 2-related factor 2 (NRF2) was purchased from Novus

Biologicals (Littleton, CO). Rabbit monoclonal antibody against heme oxygenase-1 (HO-1) was

purchased from Abcam (Cambridge, MA). Vectastain ABC kit was purchased from Vector

Laboratories (Burlingame, DA). RIPA lysis buffer and 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-

tetrazolium bromide (MTT) were purchased from Sigma–Aldrich (St. Louis, MO). MPP+, 1-methyl-

4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), DL-dithiothreitol (DTT), and iodoacetamide (IAA)

were purchased from Sigma–Aldrich (St. Louis, MO). Microcon centrifugal filters were purchased

from Merck Millipore (Darmstadt, Germany). Bio-Rad protein assay kit was purchased from Bio-

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Rad (Hercules, CA). All other chemicals were purchased from Sigma–Aldrich.

Plant material and fractionation of AOE

The fruit of A. oxyphylla were purchased from Sam Yao Hong (Macau SAR, China) and

authenticated by an experienced pharmacognosist (Dr. Zhixiu Lin, School of Chinese Medicine, The

Chinese University of Hong Kong). For the material used in this study, a voucher herbarium

specimen was deposited with the Herbarium of the Institute of Chinese Medical Sciences (No. 0011),

University of Macau, Macau SAR, China. Following coarse pulverization, 10 kg of the air-dried

fruits was obtained. The fruits of A. oxyphylla were extracted three times with 95% aqueous EtOH

(90 L) under reflux for 2 h in University o Macau. The combined extracts were concentrated through

rotary evaporation at 50 °C, resulting in the AOE (914.55 g).

The fractionation scheme used to separate out the bioactive metabolites in AOE is depicted in Figure

S-3. The AOE was re-extracted successively with petroleum ether, ethyl acetate, and EtOH; the ethyl

acetate–soluble portion (EA portion) was subjected to further fractionation to yield 11 EA

subfractions (Frs. A–K). Details please refer to the Supporting Information, Experimental

Section.

LC-MS/MS analysis

An Agilent 1100 series HPLC system (Agilent Technologies, Palo Alto, CA) coupled to a hybrid

triple-quadrupole linear ion trap (LIT) mass spectrometer with a TurboIonSpray ion source (QTRAP,

AB Sciex, Concord, Ontario, Canada), set in both positive and negative ion modes, was used for

chemical profiling of the metabolites found in fractions (Frs.) A–K: briefly, the crude ethanolic

extract of the fruits of Alpinia oxyphylla (AOE) was re-extracted petroleum ether, ethyl acetate, and

ethanol successively to yield petroleum ether–soluble portion (PE portion), an ethyl acetate–soluble

portion (EA portion), and an ethanol-soluble portion (EtOH portion). The EA portion was subjected

to further fractionation to yield 11 EA subfractions (Frs. A–K). Each of the samples (10 µL) from

Frs. A–K was injected at 1 mg/mL into an Eclipse XDB C18 column (2.1 × 150 mm, 3.5 µm; Agilent

Technologies, Santa Clara, CA) for duplicate runs. The LC and MS data acquisition parameters are

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presented in Table S-1. To determine the accurate masses of the top ten bioactive compounds, a

platform consisting of an Agilent 1200 series nano pump, equipped with a 100-well plate auto-

sampler (Agilent Technologies, Wilmington, DE), and connected to a triple-quadrupole time-of-fight

(TOF) mass spectrometer fitted with a Nanospray III source (TripleTOF 5600; AB Sciex, Concord,

Ontario, Canada), was used. The reversed phase (RP) trap column (150 µm i.d.× 50 mm length) and

analytical RP nano column (75 µm i.d.× 150 mm length) were packed in-house with Jupiter C18 bulk

materials using an ultrahigh-pressure syringe pump with maximum pressure of 6000 psi. Samples

were loaded onto an RP trap column and then eluted for LC-MS/MS analysis. The LC and MS data

acquisition parameters are presented in Table S-2. High-resolution MS data with isotopic patterns for

the ions of interest allowed accurate calculations of the elemental compositions; all of the measured

masses were within 6 ppm of the theoretical values for the proposed formulas.

Cell culture

Cerebellar granule neurons (CGNs) were isolated and cultured from Sprague–Dawley rats aged eight

days, as previously described.38

Briefly, neurons were seeded in a 96-well plate at a density of 1.5 ×

105 cells/well containing basal modified Eagle’s medium with 10% fetal bovine serum, 2 mM

glutamine, 25 Mm KCl, streptomycin (100 µg/mL), and penicillin (100 units/mL). 10 µM Cytosine

arabinoside was added to the culture medium, to inhibit the growth of non-neuronal cells, at 24 h

after plating. After implementing this protocol, approximately 95% of the cultured cells observed

appeared to be granule neurons. After six days in culture, the CGNs displayed several features of

mature neurons.39

The experiments requiring CGNs cells were performed at eight days in vitro

(DIV).

MTT assay

The MTT assay is a colorimetric assay for testing cell viability based on the principle that

intracellular NAD(P)H-dependent oxidoreductases can reduce MTT into insoluble purple formazan,

the absorbance of which can be recorded by a microplate reader to reflect the relative number of live

cells in a culture medium. CGNs at 8 DIV were pre-treated with serial concentrations of AOE, PE

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portion, EA portion, EtOH portion, 11 EA subfractions, oxyphylla A, chrysin, and teuhetenone A, for

2 h. The vehicle group was incubated with 0.1% DMSO. The cells were then exposed to 150 µM

MPP+ for 36 h. For assessment of cell viability, MTT solution (5 mg/mL, 15 µL) was added to each

well along with the medium (100 µL). The 96-well plate was then placed in the incubator at 37 °C

for 4 h. At this point, absolute DMSO (100 µL) was added to each well and then incubation was

continued for 10 min. The absorbance at 570 nm was measured using a WallacVictor3™ V

microplate reader (PerkinElmer, The Netherlands). The optical density (O.D.) of each treatment

group was normalized with respect to that of the untreated control group.

Chemical data analysis

Markerview software (v. 1.2.1; AB Sciex, Foster City, CA) was used to locate and align the LC-MS

peaks.40

Peaks were located with the minimum retention time set to 3 min, a minimum spectral width

of 0.3 Da, a subtraction offset of 15 scans, and a subtraction multiplication factor of 1.3. All peaks

were subsequently aligned with a retention time tolerance of 0.2 min and a mass tolerance of 0.2 Da

across the entire dataset. The noise threshold was set at 1000 cps for the negative mode and 2.0 × 105

cps for the positive mode, according to the background signal abundance in the total ion

chromatography profile of the enhanced MS scan. 180 and 644 monoisotopic peaks were detected in

the negative and positive modes, respectively. Following peak alignment across the 22 runs

(duplicate runs for each of the 11 EA subfractions), the area of a particular peak was normalized to

the sum of the corresponding peak areas detected across all the runs. The normalization was

performed separately for the datasets acquired in positive and negative modes.41

Detailed lists of the

monoisotopic peaks detected in negative and positive modes, and the combined list after

normalization are provided in Table S-3.A 22 × 825 (row × column) data matrix, with normalized

peak areas and bioactivity values, was inputted for MVDA using SIMICA-P software (v. 13.0;

Umetrics, Sweden). Each row represented different samples, and each sample possessed two

replicates. Each column represented an LC-MS peak having a unique pair-identifier (m/z/Rt), except

for the final column, which represented the bioactivity derived from the MTT assay. A supervised

Orthogonal-projections-to-latent-structures (OPLS) model was employed to correlate the LC-MS

profiling data with corresponding bioactivity data, according to a Pareto scaling method.13

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Peakviewer software (v. 2.0; AB Sciex, Foster City, CA) was used to process the HR-MS data.

Molecular formulas were generated using the Formula Finder tool.42

Log P values were predicted

using ChemBioDraw Ultra 12.0 (Cambridgesoftware, Cambridge, UK).43

Because of space considerations, some experimental methods related to materials, sample

preparation, liquid chromatography, mass spectrometry, husbandry and drug treatment conditions,

neurobehavioral tests, and data analysis are provided in the Supporting Information.

Purification and structural characterization of oxyphylla A, chrysin, and

teuhetenone A (compounds 1–3)

The purification scheme used to isolate compounds 1–3 is depicted in Figure S-3. Fr. F was further

fractionated through different combination of column chromatographies (e.g. silica gel, Sephadex

LH-20, MCI gel) and preparative HPLC to yield purified compound 1-3. UV, IR, NMR and MS

spectroscopic techniques were employed for the structure elucidation of compound 1-3. Optical

rotation and X-ray diffraction data were also acquired to determine the stereo structure of compound

1. Details please refer to the Supporting Information, Experimental Section.

Total synthesis and X-ray crystallographic of oxyphylla A

Oxyphylla A was synthesized from 4-Methylanisole reacting by 9 steps to get the racemic compound

i. Then the chiral isomers j and k were obtained by separation on chiral prep-HPLC. The final

structure of oxyphylla A was solved by direct methods employing SHELXS97.44

The data for

oxyphylla A have been deposited in the Cambridge Crystallographic Data Centre with reference

number CCDC 1411040. The detailed crystal data, data collection and refinement parameters please

refer to the Supporting Information, Experimental Section.

Mouse and zebrafish husbandry and drug treatment conditions

Adult male C57BL/6J mice (8–10 weeks old, 18–22 g) were maintained in a 12-/12-h light/dark

cycle with access to water and food ad libitum. They were acclimated for 1 week prior to treatment.

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The AB strain of wild-type zebrafish and the general husbandry procedures used in this study were

the same as previously described.28

All the animal handling protocols were approved by the Research

Ethics Committee, University of Macau. Embryos were collected after natural spawning, staged

according to standard criteria, and raised synchronously at 28.5 °C in embryo medium (13.7 mM

NaCl, 540 µM KCl, 25 µM Na2HPO4, 44 µM KH2PO4, 300 µM CaCl2, 100 µM MgSO4, 420 µM

NaHCO3, pH 7.4). Detailed treatment procedures with AOE and oxyphylla A are presented in the

Supporting Information, Experimental Section.

Neurobehavioral tests

For experiments involving treatment with AOE, the neurobehavioral changes of the mice were

assessed in terms of their performance in Cat Walk and open field tests. For experiments involving

the treatment with oxyphylla A, the mice were monitored for neurobehavioral changes using the

pole,45

rotarod,46

and footprint tests.47

For the experiments involving zebrafish, the fish behavior was

analyzed using a digital video tracking system (Viewpoint ZebraLab system), as previously

described.48

Details please refer to the Supporting Information, Experimental Section.

Bioactivity data, proteomic sample and proteomics data analysis

Biological data are expressed as means ± standard deviation (SD). Statistical significance was

determined by using one-way analysis of variation (ANOVA), with the Tukey–Kramer test employed

for multiple group comparisons. Significant differences were accepted with p< 0.05.

Proteomic sample& Data analysis: Pooled iTRAQ primary CGNs protein samples (20 µg) were

subjected to LC-MS/MS analysis using MD-LC-MS/MS platforms, as previously documented.49-51

MS data were collected on a Triple quadrupole time-of-fight mass spectrometry (Triple TOF 5600,

AB SCIEX, Concord, ON, Canada) equipped with a Nanospray III source (AB SCIEX, Concord,

ON, Canada). The raw WIFF data were searched against the Rattusnorvegicus Ensembl reference

proteome database (Dec. 2013; 29,704 entries: http://www.ensembl.org/Rattus_norvegicus/Info/Index)

using ProteinPilot v. 4.5 software (Applied Biosystems, Framingham, MA). The plug-in Proteomics

System Performance Evaluation Pipeline (PSPEP), featured in ProteinPilot v.4.5, was used to

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determine the false discovery rate (FDR).52

The corresponding unused score with 5% local FDR was

used to cut off the number of identified non-redundant proteins and peptides with unique sequence

and modification. The iTRAQ quantified proteins were required to have at least 4 spectra with >95%

confidence in total from the duplicate runs. The protein ratios were calculated using the weighted

average of the natural logarithm of the peptide ratios, as described in the ProteinPilot manual. A

protein was deemed as dysregulated when the protein ratio was significantly ≥1.23 or ≤0.81 in the

corresponding one-tail t-test (p-value < 0.05).53

The up- and down-regulated proteins were

highlighted in red and green, respectively, in Table S-7. Protein pathway and network analysis was

performed using the Ingenuity Pathway Analysis (IPA) program (Qigan, Redwood City, CA).

Detailed optimized MS acquisition parameters and related data analysis methods are presented in the

Experimental Section of the Supporting Information.

Western blotting, immunohistochemical sample preparation and anti-TH

immunostaining

After applying the various treatment conditions, the CGNs culture was washed three times with ice-

cold PBS and then the protein was extracted with RIPA buffer (1% Protease Inhibitor and 1% PMSF

were added) on ice for 10 min. The cell lysates were centrifuged (12,500×g, 20 min, 4 °C) and then

the supernatants were collected and stored at –80 °C until required. The protein contents were

quantified using the Bio-Rad protein assay kit. Protein samples (30 µg) were resolved using SDS-

PAGE and then transferred to PVDF membranes using a semi-dry transfer cell (Bio-Rad). After the

membrane had been washed three times with TBST solution, primary antibodies (1:1000) were

added and incubated overnight at 4 °C on a rolling mixer. After washing the membranes three times

with PBS, horseradish peroxidase-conjugated secondary antibodies (1:2000) were added and

incubated at room temperature for another 2 h on a rotating homogenizer. The membranes were then

washed three times with PBS and incubated with ECL solution, according to manufacturer’s

instructions; and immunoblots were analyzed using a chemiluminescent imaging system.

Quantitative assessment of protein blots was performed using Gel DocTM XR (Bio-Rad, Hercules,

CA, USA) equipped with QuantityOne software (Bio-Rad). Mice treated with AOE or oxyphylla A

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were sacrificed for brain tissue section. The immunohistochemistry method used has been described

previously.54

Whole-mount immunostaining of the zebrafish embryos with oxyphylla A treatment

was performed as previously described.48

Details please refer to the Supporting Information,

Experimental Section.

Results and Discussion

The aim of this study was to develop an efficient strategy involving LC-MS–based MVDA-guided

fractionation for the identification and isolation of potentially bioactive compounds. This newly

developed integrated methodology would then be implemented to identify and characterize novel

neuroprotective natural products from AOE, with the goal of isolating potential PD therapeutic lead

compounds (Figure 1). In the initial step, to establish the neuroprotective effects of AOE, a crude

extract was obtained through an ethanolic hot Soxhlet reflux extraction and examined employing a

MPTP–induced PD mouse model. The administration of AOE (i) significantly restored losses of

dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc) (Figure S-1) and (ii)

ameliorated MPTP-induced behavioral impairments (Figure S-2), indicating its neuroprotective

potential. To characterize the novel neuroprotective constituents of AOE, we subjected it to

extractions with three solvents of distinct polarities ranging from low to high, to generate the

respective PE portion, EA portion and EtOH portion (Figure S-3). We then tested these three

portions, along with AOE, for their abilities to inhibit PD models in PC12 cell and zebrafish28

as well

as MPP+-induced cell death of primary CGNs, a commonly used in vitro PD model.

39 Consistent

with previous findings using other PD experimental models, pretreatment of the CGNs with AOE

significantly prevented MPP+-induced damage in a concentration-dependent manner

28 with EA

portion displaying the highest neuroprotective potency (Figure S-4A). We then further separated EA

portion, through column chromatography, into 11 EA subfractions (Frs. A–K) (Figure S-3). Each EA

subfraction was subjected to (i) comprehensive chemical profiling analysis through LC–MS/MS in

both positive and negative ESI modes (Figure 2) and (ii) the neuroprotective activity assay (Figure 2

and Figures S-4B–D).

Next, we applied MVDA to correlate the metabolite profiles of EA subfractions (each species was

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assigned an m/z-and-retention-time data pair as an identifier) with their respective neuroprotective

activities to reveal any potential bioactive constituents in these complex metabolite profiles.

Specifically, we employed an orthogonal-projections-to-latent-structures (OPLS) model to reveal the

key potential bioactive metabolites in the fruit of A. oxyphylla. In the OPLS model, the inter-class

variance in X was modeled by the predictive component tp while the intra-class variance orthogonal

to Y was modeled by the orthogonal component to; this model provided a means to remove the

systematic variation from descriptor variables X that were not correlated to response variables Y.55, 56

As illustrated in Figure 3A, in the score plot along the direction of the first predictive component

tp1, all 11 EA subfractions were classified into two groups according to the potency of their

neuroprotective activities. Frs. A–C, J, and K were classified in the low bioactivity group, while Frs.

D–I were placed in the high neuroprotective activity group, which could be divided unambiguously

into two subgroups along the first orthogonal component to1, demonstrating intra-class variation. In

this manner, it was possible to provide a more robust and definitive interpretation for the grouping

displayed in the score plot. Accordingly, this observation confirms that the first predictive component

tp1, in the OPLS model, was associated with the bioactivity. Metabolites exhibited the greatest

influence on the discrimination in the score plot were identified in the loading plot as potential

biochemically significant metabolites (Figure 3B). The data points corresponding to 1, 2, and 3

carried the first three highest weights (PP1) along the tp1direction, indicating that they made the

greatest contribution to the discrimination in score plots according to bioactivity (Figure 3B).

Moreover, the significance of the variables in the OPLS model can also be presented in an S-plot, in

which both the covariance p and correlation p (corr) of the variables projected to the predictive

component can be visualized (Figure 3C). This plot, therefore, provides more information to assess

the reliability of the variables’ contribution; by eliminating the usual suspects and false positives, we

could identify the variables having biological significance relating to bioactivity.55, 57

By also taking

the confidence interval of each variable into account, we compiled a shortlist comprising the top 10

ranked MS peaks based on both the magnitude of their contributions and their reliability to the model

with cutoff values of p1 > 0.07 and p (corr)1 > 0.6 (Table S-4, MVDA result against single

concentration please refer to Table S-5). In addition, all 10 metabolites were statistically significant

based on their jackknifed confidence intervals (Figure 3D). Compound 1 was positioned on the wing

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of the S-plot with the highest p1value, indicating the greatest contribution to class separation and the

highest p (corr)1 value (indicative of the greatest degree of reliability; Figure 3C). Meanwhile,

compound 2 had the second-highest p1 value and also a high p (corr) 1 value (Figure 3C). MVDA

indicated that 1, 2, and 3, with features of 235.4/20.7, 253.4/21.2, and 195.2/15.7 (m/z ratio/retention

time), had the greatest influence on the neuroprotective activity; therefore, we tentatively regarded

them as the bioactive metabolites having the highest importance with respect to their

characterization. High-resolution MS data with isotopic patterns for the ions of interest allowed

accurate calculations of the elemental compositions; all of the measured masses were within 6 ppm

of the theoretical values for the proposed formulas (Table S-4). The top three ranked compounds, 1–

3, that exerted the greatest influence on neuroprotective activity in the OPLS model were scaled-up,

isolated chromatographically, and further characterized (Figure S-3 and Table S-4). Based on semi-

quantitative analysis through LC-MS, we determined that Fr. F contained the most abundant

quantities of 1, 2, and 3 among all the other fractions. Accordingly, we subjected Fr. F to further

fractionation, using three comprehensive chromatographic separation methods, to isolate the

individual compounds. The first approach, involving silica gel chromatography (separation

mechanism according to molecular polarity) coupled with Sephadex LH-20 chromatography, led to

the isolation of 1. We combined MCI gel chromatography (separation based on hydrophobicity) and

Sephadex LH-20 chromatography (acting as a molecular sieve) with preparative reversed-phase

HPLC to provide pure forms of compounds 2 and 3. Using the multiple bioassays against MPP+-

induced PC12 cell toxicity (data not shown), CGN toxicity, and dopaminergic neuron loss and

swimming behavior impairments in PD zebrafish larvae model, we confirmed the neuroprotective

activities of these three purified compounds (Figure 4A, Figure S-5 and Figure S-18).

We identified compounds 2 and 3 as chrysin and teuhetenone A, respectively; their MS/MS spectra

and LC retention times were virtually identical to those of authentic standard samples under similar

experimental conditions, with 1H and

13C NMR spectra providing unambiguous structural

confirmation (Figures S-6–S-11).58, 59

Our identification of chrysin, a known and characterized

neuroprotective compound,36

confirmed the effectiveness of this MVDA-based approach. Because

no authentic standard for 1 was available, we performed an extensive structural and stereochemical

investigation using UV, IR, 1H NMR,

13C NMR COSY, HSQC, and HMBC spectroscopies and

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optical rotation, resulting in the identification of 1 as the novel compound (R)-4-(2-hydroxy-5-

methylphenyl)-5-methylhexanoic acid (Figure 5, Figures S-12–S-16; Table S-6).60

We have named

this compound “oxyphylla A,” following the conventional nomenclature for metabolites from the

fruit of A. oxyphylla.35

Although chrysin (2) has potential therapeutic benefits, it displays low oral

bioavailability;61

this significant drawback, from a pharmacological perspective, has been

demonstrated in vivo to result from its extensive cellular metabolism and efflux of metabolites back

into the intestines for hydrolysis and elimination.61

Our present study is the first to report the

potential neuroprotective effects of teuhetenone A (3); unfortunately, it has a low probability of

traversing the blood–brain barrier (BBB), with a predicted octanol/water partition coefficient (log P,

a measure of lipophilicity) of 1.4. It has been suggested that a value of log P of at least 1.5 is

required for satisfactory penetration of the BBB, with the optimal range being between 2 and 3.62, 63

Oxyphylla A, however, has a predicted log P value of 3.2, suggesting great potential for crossing the

BBB; indeed, i.g. administration of oxyphylla A (20 mg/kg dosage) to rats led to its subsequent

presence at 10 µM in the cerebrospinal fluid (Figure S-17). Thus, from the top three compounds, we

selected oxyphylla A alone for further in vivo pharmacodynamics studies. First, we synthesized,

purified, and chirally separated it in gram quantities; the synthetic procedure is detailed in the

Supporting Information—Experimental Section and in a patent application.64

X-ray

crystallography confirmed the absolute configuration of oxyphylla A to be R, consistent with the

optical rotation reported for (–)-sesquichamaenol (Ref. #: CCDC 1411040, Supporting

Information—Experimental Section).65

To assess the neuroprotective effects of oxyphylla A in vivo, initially we used a zebrafish PD model.

Oxyphylla A moderated MPTP-induced DA neuron loss and alleviated zebrafish larvae swimming

behavioral impairments in a dose-dependent manner (Figure S-18). Next, we further examined

oxyphylla A using an MPTP-treated PD mouse model; evidence exists for the selective MPTP-

induced DA neuron loss inhibiting mitochondrial function in primates, and in mice under oxidative

stress.66

Treatment with oxyphylla A significantly moderated the TH–positive DA neuron loss of the

MPTP-treated mouse model in a concentration-dependent manner—comparable with the

performance of the positive control (rasagiline, a monoamine oxidase-B inhibitor and an FDA-

approved drug for the treatment of PD).66

At a dosage of 20 mg/kg, the efficacy of oxyphylla A was

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similar to that of rasagiline, with 85% survival of TH-positive DA neurons (Figures 4B-C and S-19).

The motor phenotypes of the PD mice were also accessed using pole, footprint, and rotarod tests to

mimic human neurological diagnosis. Oxyphylla A significantly ameliorated movement

abnormalities in a dose-dependent manner—decreasing the duration of the pole and footprint tests,

prolonging the time on the rod, and improving the stride length (Figure 4D and Figure S-19)—with

the maximum effect at a concentration of 20 mg/kg (comparable with that of rasagiline). Most

notably, the efficacy of oxyphylla A was considerably higher than that of rasagiline for mice

subjected to the rotarod test, one of the main and most sensitive tests for assessing motor function in

mice (Figure 4D).

The protein expression profiles of MPP+-induced CGNs in the presence and absence of oxyphylla A

provided insight into the molecular mechanisms underlying these neuroprotective effects: a total of

2649 non-redundant proteins were confidently identified (local FDR <5%), with 1277 quantified,

and 73 dysregulated from two technical replicates of quantitative proteomics analyses using iTRAQ

tag labeling and multidimensional LC–MS/MS (Figure S-20). Cellular MPP+

intoxication often

involves the over-generation of reactive oxygen species (ROS) during oxidative stress.37

The

neuroprotective effects elicited by oxyphylla A were hallmarked by a number of differentially

expressed antioxidant enzymes and oxidoreductases, with either restored (SOD1, NQO1, ADH5,

AKR1B1, AKR1B8, PRDX5) or up-regulated (TXN1) expression in cells pretreated with oxyphylla

A (Table S-7). Thetherapeutic effects of oxyphylla A appear to occur by restoring the loss of

antioxidant enzyme activities and partly alleviating the MPP+-induced oxidative stress. Among these

proteins, SOD1, NQO1, and TXN1 are involved in a nuclear factor-NRF2–mediated oxidative stress

response pathway (Figure S-21).37, 67-69

NRF2-dependent expression of AKR1B1, AKR1B8, and

PRDX5 has also been reported previously. NRF2 acts as the “master regulator” of the cellular

antioxidant response, controlling the basal and induced expression of an array of antioxidant

response element–dependent genes to regulate the physiological and pathophysiological outcomes of

oxidant exposure.70, 71

Examination of NRF2 expression levels through western blotting revealed that

the pretreatment of CGNs with oxyphylla A prior to MPP+

intoxication led to smaller reductions in

NRF2 protein levels—a phenomenon not observed upon MPP+ treatment alone (Figures 4E-F). The

expression of the NRF2 signaling pathway—the master redox switch—has been validated and

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characterized through Western blotting of one of the hallmark antioxidant enzymes, heme

oxygenase-1 (HO-1).38, 72, 73

HO-1 displayed an up-regulated expression change, similar to that of

NRF2, in response to treatment with oxyphylla A, in which could reverse the MPP+-induced down-

regulation of HO-1 (Figure 4G). This finding suggests that the neuroprotective effects exhibited by

oxyphylla A are mediated through induction of the NRF2 signaling pathway. In a similar scenario,

we previously reported that chrysin and another A. oxyphylla polyphenol, protocatechuic acid,

exhibited combined neuroprotective effects—again through induction of the NRF2 signaling

pathway.36

More detailed and systematic proteomics validation will be dealt with in a future report.

Conclusion

We have demonstrated the utility of LC-MS based MVDA-guided fractionation strategy involving

metabolomics, pharmacology, and chemometrics for the discovery of bioactive ingredients from the

fruit of A. oxyphylla. Through this strategy, we have identified a novel compound, oxyphylla A,

together with two known compounds, chrysin and teuhetenone A, and have validated (through

screening in a primary neuronal cell PD model) that oxyphylla A exhibits promising neuroprotective

activities in vitro. We have also confirmed the neuroprotective effects of oxyphylla A in vivo when

using zebrafish and C57BL/6 mouse PD models. By means of proteomics analyses, we determined

that the molecular mechanisms underlying the neuroprotective effects of oxyphylla A involve

activation of the NRF2 pathway. Our study suggests that oxyphylla A has strong therapeutic

potential against neurodegenerative diseases—in particular, Parkinson’s disease. Although we are

witnessing only the first report of the neuroprotective and proteomics properties of naturally

occurring oxyphylla A, it appears to display fascinating mammalian neurobiology. More importantly,

the successful development of a synthetic route toward oxyphylla A should lead to its availability on

large scale; we also isolated seven other potential neuroprotective compounds of interest from those

fractions with the highest corresponding abundances (Table S-4) for further functional

developmental and pathological studies.

ASSOCIATED CONTENT

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Supporting Information

Experimental Section – constituted of the fractionation of AOE; purification of oxyphylla A,

chrysin, and teuhetenone A (compounds 1–3); structural characterization of oxyphylla A, chrysin,

and teuhetenone A (compounds 1–3); liquid chromatography–UV analysis of rat cerebral spinal

fluid; total synthesis of oxyphylla A; X-ray crystallographic analysis of oxyphylla A; mouse

husbandry and drug treatment conditions; immunohistochemical sample preparation and anti-

tyrosine hydroxylase (TH) immunostaining; neurobehavioral tests; cerebellar granule neurons

(CGNs) protein extraction and iTRAQ labeling and proteomic sample analysis. Figure S-1 - AOE

attenuates TH-positive DA neuron loss in SNpc induced by MPTP administration in mice. Figure S-

2 - AOE ameliorates MPTP-induced behavior impairments in PD mice. Figure S-3 - Fractionation

scheme for the separation of AOE and purification of compounds 1–3. Figure S-4 - Neuroprotective

effects of AOE, PE portion, EA portion, EtOH portion, and 11 EA subfractions on MPP+-induced

primary CGN damage model. Figure S-5 - Chrysin and teuhetenone A protected against MPP+-

induced primary CGN damage. Figure S-6 - LC/ESI-MS spectrum of chrysin. Figure S-7 - 1H NMR

spectrum of chrysin (DMSO-d6, 600 MHz). Figure S-8 - 13

C NMR spectrum of chrysin (DMSO-d6,

150 MHz). Figure S-9 - LC/ESI-MS spectrum of teuhetenone A. Figure S-10 - 1H NMR spectrum

of teuhetenone A (CDCl3, 600 MHz). Figure S-11 - 13

C NMR spectrum of teuhetenone A (CDCl3,

150 MHz). Figure S-12 - UV spectrum of oxyphylla A (MeOH). Figure S-13 - IR spectrum of

oxyphylla A (KBr disc). Figure S-14 - 13

C NMR spectrum of oxyphylla A (CDCl3, 125 MHz).

Figure S-15 - HSQC spectrum of oxyphylla A (CDCl3). Figure S-16 - HMBC spectrum of

oxyphylla A (CDCl3). Figure S-17 - Representative LC-UV chromatograms of rat CSF samples.

Figure S-18 - Oxyphylla A pretreatment protected against MPTP-induced dopaminergic neuron loss

and limited swimming behavior impairments in PD zebrafish larvae model. Figure S-19 - Oxyphylla

A pretreatment protected against MPTP-induced dopaminergic neuron loss and limited behavioral

impairment in the PD mice model. Figure S-20 - Overview of primary CGN proteome characterized

by MDLC–MS/MS. Figure S-21 - NRF2 pathway is involved in the neuroprotective effects of

oxyphylla A. Table S-1 - Parameters used for mass spectrometry and independent data acquisition in

the LC–MS/MS analysis for EA subfractions. Table S-2 - Parameters used for mass spectrometry

and independent data acquisition in the LC–MS/MS analysis top 10 bioactive compounds. Table S-3

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- Monoisotopic peaks detected in negative and positive modes, and the combined list after

normalization by LC-MS. Table S-4 - Top 10 potentially bioactive MS peaks with statistical

significance and their identification. Table S-5 - List of top 10 compounds identified by MVDA at

single concentration. Table S-6 - 13

C and 1H NMR data for oxyphylla A in CDCl3. Table S-7 -

Proteins with statistically significant differential expression identified using iTRAQ proteomics. This

material is available free of charge via the Internet at http://pubs.acs.org.

Acknowledgments

This study was supported by grants from the Hong Kong Research Grants Council (project nos.

HKU 701613P and 173306015), the University of Hong Kong (Seed Funding Programme for Basic

Research 201411159067 and 201310159043), the National Natural Science Foundation of China

(NSFC 81303251 and 81328025), the Science and Technology Program of Guangzhou

(2014J4100097), the Science and Technology Development Fund (FDCT) of Macao SAR (Ref. No.

134/2014/A3 and FDCT078/2011/A3), Research Committee of University of Macau

(MYRG139(Y1-L4)-ICMS12-LMY, MYRG2015-00214-ICMS-QRCM and MYRG2015-00182-

ICMS-QRCM). We thank Professor K. W. Michael Siu and Professor Yuqiang Wang for many

helpful discussions and also thank Dr. Haiyan Tian for assisting NMR structural elucidation.

Declaration of conflicting interests

The authors declare no competing financial interest. A patent application has been filed by

University of Macau and the application number is 14/210467.

Abbreviations

AOE, the ethanolic extract of the fruit of Alpinia oxyphylla; BBB, blood–brain barrier; CGNs,

cerebellar granule neurons; DA, dopaminergic; DIV, days in vitro; DTT, DL-dithiothreitol; EA

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portion, ethyl acetate–soluble portion; EtOH portion, ethanol-soluble portion; FDR, false discovery

rate; HO-1, heme oxygenase-1; HRP, horseradish peroxidase; IAA, iodoacetamide; iTRAQ, isobaric

tags for relative and absolute quantitation; LC-MS, liquid chromatography/mass spectrometry; LC-

MS/MS, liquid chromatography/tandem mass spectrometry; LIT, linear ion trap; MPP+,1-methyl-4-

phenylpyridinium ion; MPTP, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine; MTT, 3-(4,5-dimethyl-

2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide; MVDA, multivariate data analysis; NRF2,

nuclear factor-erythroid 2-related factor 2; O.D., optical density; OPLS, orthogonal-projections-to-

latent-structures; PD, Parkinson’s disease; PE portion, petroleum ether–soluble portion; PMSF,

phenylmethylsulfonyl fluoride; ROS, reactive oxygen species; RP, reversed phase; SNpc, substantia

nigra pars compacta; TH, tyrosine hydroxylase

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Figure Legends

Figure 1. Schematic overview of the discovery of neuroprotective compounds from the fruit of

A. oxyphylla. Three major steps—extraction, fractionation, and “omics” analyses—were involved

during the discovery process. Hot reflux extraction yielded a crude extract (AOE); subsequent

Soxhlet extraction resulted in PE, EA, and EtOH portions. The most bioactive EA portion was

selected for further fractionation, yielding 11 EA subfractions; multivariate data analysis was used to

correlate the chemical profiling and biological data to narrow down the candidate compounds. The

top three compounds were isolated and characterized; their bioactivities were examined in both in

vitro and in vivo models. Proteomics and bioinformatics tools were employed to explore the

molecular mechanism underlying the bioactivities of the novel compound oxyphylla A on the protein

level. (Photograph courtesy of Guohui Li for the images in the figure. Copyright 2016.)

Figure 2. Representative LC-MS and bioassay profiling for bioactive EA subfractions. Each of

the 11 EA subfraction samples (Frs. A-K) was subjected to LC-MS analysis in negative mode. The

base peak chromatograms within the first 35 min are displayed in the left-hand panel. Meanwhile,

primary CGNs at 8 DIV were pretreated with each of the EA subfraction samples (Frs. A-K) at four

different concentrations (6, 12, 25, and 50 µg/mL) or vehicle for 2 h followed by exposure to 150

µM MPP+ for 36 h. The optical density (O.D.) value of each cell culture well, obtained from MTT

assay, was normalized by control group at which 1.0 value indicates 100 percent of cell growth in

control group. Neuroprotection activity was calculated by an equation "O.D. of drug treatment group

– O.D. of MPP+ treatment group". The neuroprotection activity index of each EA subfraction was

calculated by taking the mean value of four different treatment concentrations (3, 6, 12, and 25

µg/mL) and then shown in the right-hand panel. Data point of each fraction sample was obtained

from 3 independent experiment at which each experiment had three biological replicates.

Figure 3. OPLS identifies bioactive ingredients from AOE. A) OPLS score plot, where the EA

subfractions with greater bioactivity (Frs. D–I) can be clearly separated from those with lower

bioactivity (Frs. A–C, J, and K). B) OPLS loading plot displaying the weighting each variable carried

along the first principle component (tp1). C) OPLS S-plot demonstrating the covariance of p against

the correlation p (corr) of the variables of the observations denoted in the score plot. D) Loading plot

with jackknifed confidence intervals for the top 20 statistically significant MS peaks with the pair-

identifier (m/z)/retention time[1 (235.4/20.7), 2 (253.4/21.2), and 3 (195.2/15.7) are labeled in

purple; others among the top 10 MS peaks are labeled in red].

Figure 4. Neuroprotective effect of oxyphylla A in vitro and in vivo. A) Primary CGNs at 8 DIV

were pretreated with oxyphylla A at different concentrations (6, 12, 25 and 50 µM) as indicated or

with vehicle for 2 h, followed by exposure to 150 µM MPP+

for 36 h. The cell viability was then

assessed using the MTT assay. The OD values of treatment groups were expressed as percentages of

the control group. B) Anti-TH immunostaining of representative midbrain sections. Treatment with

oxyphylla A was tested at concentrations of 5, 10, and 20 mg/kg, followed by administration of

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MPTP. Treatment with 1 mg/kg rasagiline was used as a positive control. C) Average TH-positive

DA neurons observed in the stained sections (n = 8) for the different sample groups. D) Rotarod

(time on the rod) test conducted after treatment with oxyphylla A at 5, 10, or 20 mg/kg, followed by

MPTP lesion. E) Western blots of anti-NRF2 and anti-β-actin: CGNs were pretreated with oxyphylla

A at various concentrations for 2 h, followed by treatment with 150 µM MPP+ for 36 h. Proteins

were then extracted and western blotting was performed using anti-NRF2 and anti-β-actin

antibodies. F) NRF2 relative expression normalized to β-actin. Each bar represents mean ± SD. G)

Western blots of anti-HO-1 and anti-β-actin: CGNs were pretreated with oxyphylla A at various

concentrations for 2 h, followed by treatment with 150 µM MPP+ for 36 h. Proteins were then

extracted and western blotting was performed using anti-HO-1 and anti-β-actin antibodies. H) HO-1

relative expression normalized to β-actin. Each bar represents mean ± SD. For A, E, F, G and H, #P<

0.05 versus control group (without MPTP treatment); *P< 0.05 versus MPP

+-treated group. For B, C

and D, treatment with 1 mg/kg rasagiline was used as a positive control. #P< 0.05 versus control

group (without MPTP/MPP+ treatment);

*P< 0.05 versus vehicle (Veh) plus MPTP/MPP

+-treated

group.

Figure 5. Structural characterization of oxyphylla A through MS, NMR spectroscopy, and X-

ray crystallography. A) LC/ESI mass spectrum of oxyphylla A, including (–)-ESI-MS/MS

spectrum, isotopic distribution, and extracted-ion chromatogram (XIC) of the precursor ion [M – H]–

at m/z 235.1305 with a peak elution time of 21.2 min. B) 1H NMR spectrum of oxyphylla A (CDCl3,

600 MHz). C) 1H–

1H COSY spectrum of oxyphylla A (CDCl3). D) Solid state structure of oxyphylla

A (Ref. #: CCDC 1411040).

.

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Figure 1

Figure 2

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Figure 3

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Figure 4

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Figure 5

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For TOC only

(Photograph courtesy of Guohui Li. Copyright 2016.)

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