Targeted Screening Approach to Systematically Identify the Absorbed

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Bioactive Constituents, Metabolites, and Functions

A targeted screening approach to systematically identify the absorbed effect substances of Poria cocos in vivo using ultra-high performance liquid chromatography tandem mass spectrometry Guifang Feng, Shizhe Li, Shu Liu, Fengrui Song, Zifeng Pi, and Zhiqiang Liu J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b02753 • Publication Date (Web): 09 Jul 2018 Downloaded from http://pubs.acs.org on July 10, 2018

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Journal of Agricultural and Food Chemistry

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A targeted screening approach to systematically identify the absorbed effect

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substances of Poria cocos in vivo using ultra-high performance liquid

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chromatography tandem mass spectrometry

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Guifang Fenga, b, Shizhe Lia, b, Shu Liua, *, Fengrui Songa, Zifeng Pia, Zhiqiang Liua, *

6

a

7

Spectrometry in Changchun, Jilin Province Key Laboratory of Chinese Medicine

8

Chemistry and Mass Spectrometry, Changchun Institute of Applied Chemistry,

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Chinese Academy of Sciences, Changchun 130022, P. R. China

State Key Laboratory of Electroanalytical Chemistry, National Center of Mass

10

b

University of Science and Technology of China, Hefei 230026, P. R. China

11

c

College of Chemistry, Jilin University, Changchun 130012, China

12 13 14 15 16

*Corresponding author: Shu Liu and Zhiqiang Liu

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Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 5625

18

Renmin Street, Changchun 130022, Jilin, China.

19

Tel.: +86-431-85262613; Fax: +86-431-85262044.

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E-mail addresses: [email protected](S. Liu), [email protected] (Z. Liu)

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ACS Paragon Plus Environment


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Abstract

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Poria cocos are extensively used as nutritious food, dietary supplements and oriental

24

medicine in Asia. But its effect substances are still not very clear. In this study, a targeted

25

screening approach was developed to systematically identify absorbed constituents of Poria

26

cocos in vivo using ultra-high performance liquid chromatography tandem mass spectrometry

27

combined with UNIFI™ software. First, incubation reactions in vitro with rat intestinal

28

microflora and rat liver microsomes were conducted to sum up metabolic rules of main

29

constituents. Second, the absorbed constituents in vivo were picked out and identified based

30

on the results of metabolic study in vitro. Finally, the absorbed active constituents in the

31

treatment of Alzheimer's disease were screened by targeted network pharmacology analysis.

32

A total of 62 absorbed prototypes and 59 metabolites were identified and characterized in

33

dosed plasma. 30 potential active constituents were screened and 86 drug−targets shared by

34

absorbed constituents and Alzheimer's disease were discovered by targeted network

35

pharmacology analysis. In general, this proposed targeted strategy comprehensively provides

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new insight for active ingredients of Poria cocos.

37

Keywords

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Poria cocos; absorbed constituents; ultra-high performance liquid chromatography tandem

39

mass spectrometry; targeted network pharmacology analysis

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Introduction

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Mushrooms have been widely used as nutritious food, dietary supplements and oriental

43

medicine. Poria cocos is a medicinal fungus of the family Polyporaceae that grows on the

44

roots of old, dead pine trees.

45

principle active components of Poria cocos.

46

kinds of disease, such as cancer, diabetes, inflammatory, loss of memory, etc.

47

cocos has also been used to make food supplements, such as soups, dishes, tea, snacks, and

48

desserts. And it also was used for making biscuits, cakes and bread owing to its potential

49

promotion benefits for health. These potential application of Poria cocos attribute to the

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continued considerable levels of attention.

51

substances of Poria cocos in vivo systematically.

52

[1-3]

Previous studies have shown that triterpene acids are the [4, 5]

[8-12]

They were widely applied to treat many [6, 7]

Poria

It is worthwhile to analyze the absorbed

Clarifying absorbed substances in vivo is a key step to study food metabolism.

[13, 14]

53

Unfortunately, the complexity of ingredients greatly restricts the study of its metabolic

54

components. [15, 16] And the oral administration of them makes it more complex to study these

55

components in vivo.

56

transformed by a series of intestinal bacteria. The transformed constituents would then be

57

converted under the action of liver microsomes before entering into the blood circulation. The

58

main enzyme in the system of liver microsomes was cytochrome P−450 (CYP450).

59

They play a great role in compounds metabolism in vivo through kinds of metabolic pathways,

60

mainly oxygenation metabolism. These metabolites absorbed into plasma can play a better

[17, 18]

All foods taken orally, must be exposed in intestinal tract and be

3


[19, 20]

.


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pharmacological effect in specified sites of organism in vivo. Few studies pay considerable

62

attention to these progressive metabolic processes for the identification of absorbed

63

constituents in plasma. In fact, the metabolic types of each type structure of nature

64

compounds varied with different characteristic chemical group. For example, glycosylated

65

saponins are metabolized via deglycosylation under the action of intestinal microflora, such

66

as ginsenosides.

67

methylation or other metabolic pathways under the action of CYP450.

68

challenge for complex drug metabolism is how to categorize metabolic pathways of each

69

compound and clarify the metabolic mechanism in possible specific sites.

70

[21, 22]

However, the sapogenins were transformed via the oxygenation, [23]

The major

Development of various of analytical technologies facilitate the identification and of

unknown

and

trace

substances

in

72

Quadrupole−time−of−flight mass spectrometer, taken as an example, needs small amount

73

sample for analysis with its well−known selectivity and sensitivity.

74

machine has developed several scan functions, as it shared a quadrupole, T−wave element

75

and time−of−flight cells. And the derived developed data−independent acquisitions, such as

76

data dependent acquisition (DDA) and data−independent mass spectrometry (MSE), can

77

collect all mass data of precursor and fragment ions fully.

78

acquisition modes provide a powerful platform for compounds detections with rich chemical

79

mass information. Based on these acquisition methods, more automated software has been

80

developed for detection and analysis, such as QI and UNIFI™ software. [34] The development


[32, 33]

samples.

25]

quantification

4

complex

[24,

71

[26-31]

Besides, this

In general, several of

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of software based on mass spectrometry has also verified the importance of compound

82

metabolism from another perspective.

83

For every component detected in plasma, it must have one or more targets for therapy in

84

vivo, which known as effect substances. [35, 36] The more components were detected in plasma

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in vivo, the more targets were involved in therapy possibly. Herein, the action mechanism of

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absorbed constituents in vivo is a complex biological active network. Elucidation of these

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effect substances and related targets by some methods is conducive to better clinical

88

application. Fortunately, collecting potential drug−targets and clarifying complex molecular

89

mechanisms is available, with the development of bioinformatic database.

90

collection work is still needed to do considering the complexity of multiple components and

91

multiple drug−targets.

[37, 38]

Much

92

In this study, a targeted screening strategy was developed to systematically identify the

93

absorbed effect substances of Poria cocos in vivo. The targeted screening of metabolites from

94

in vitro to in vivo was accomplished under the assist of UNIFI™ software. And the final

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objective of this study was to describe the absorbed effect substances of Poria cocos by using

96

targeted network pharmacology analysis. We believe that this exploration of absorbed

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substances would promote better application of Poria cocos as supplement food and herbal

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medicine.

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Materials and Methods

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Materials and reagents

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Poria cocos was purchased from Hebei Kaida Traditional Chinese Medicine Co. Ltd

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(Hebei China). All herb medicines were identified by Prof. Zhiqiang Liu (Changchun

103

Institute of Applied Chemistry, Chinese Academy of Sciences). Eight reference standards of

104

dehydrotrametenolic acid (1), 16α−hydroxytrametenolic acid (2), polyporenic acid C (3),

105

poricoic

106

3−o−acetyl−16α−hydroxydehydrotrametenolic acid (7) and pachymic acid (8) were obtained

107

from purification engineering technology research Center of Sichuan Province natural

108

medicine (Sichuan China). NADPH (Nicotinamide Adenine Dinucleotide Phosphate) was

109

purchased from R&D. The analytical−grade reagents, ethyl acetate, n−butanol and absolute

110

ethanol were provided by Beijing Chemical Works (Beijing China), and deionized water was

111

purified using a Milli−Q water purification system (Milford, MA, USA). HPLC−grade

112

acetonitrile and formic acid were obtained from Fisher Scientific (Loughborough, UK).

113

Leucine enkephalin and sodium formate was purchased from Waters (Milford, USA). All

114

other reagents were of analytical grade.

115

Preparation of Poria cocos extract

B

(4),

dehydrotumulosic

acid

(5),

tumulosic

acid

(6),

116

The Poria cocos powder was immersed in eight times of 75% ethanol aqueous solution

117

for 2 h, and then refluxed twice for 2 h each. The combined ethanol extracts were filtered

118

with gauze to remove any solids, and concentrated by rotary evaporation under vacuum to a

119

certain volume. One part was kept to feed rats (equivalent to 0.4 g of crude powder per

120

milliliter), while the rest were lyophilized to get extract powder. All of them were stored at

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−20 °C before the experiment.

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Animals

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Male Sprague−Dawley rats (weights 200 ± 20 g) were obtained by Dalian Medical

124

University (Dalian, China) (SCXK (Liao) 2015−0001). They were provided with standard

125

laboratory food and water and maintained on a 12−hour light/dark cycle in an

126

air−conditioned animal quarter at constant temperature (22–24°C) and humidity (50% ±

127

10%). The animals were fasted overnight with free access to water before any experiment. All

128

rats were randomly divided into 3 groups (n = 6 for each group), one group was selected as

129

control group and administrated with normal saline, the rest were marked as 1 h and 2 h

130

groups after oral administered with Poria cocos (3 g kg–1). All the experimental procedures

131

were performed in accordance with the Guide for the Care and Use of Laboratory Animals of

132

Jilin University.

133

Incubations of Poria cocos standards with intestinal microflora in vitro

134

This part work was completed referring to the previous work, including collection and

135

preparation of intestinal bacteria mixture, incubation of Poria cocos standards with intestinal

136

bacteria in vitro, namely tumulosic acid, poricoic acid B, and pachymic acid. [16]

137

Incubations of Poria cocos with rat liver microsomes (RLMs) in vitro

138

The preparation of RLMs and determination of protein content was completed referring

139

to the reported experimental method. [39] The process of incubation is roughly as follows. All

140

incubations were performed at 37 °C in a shaker. All stock solution of standards was prepared 7



141

in methanol solution. The final concentration of methanol in the incubation was less than

142

0.2% (v/v). The prepared RLMs were carefully thawed on ice before the experiment. RLM

143

proteins (0.5 mg/mL) were added to a solution of standard (20 mM) in a medium containing

144

100 mM potassium phosphate buffer (pH 7.4) and 10 mM MgCl2. The total incubation

145

volume was 150 µL. After pre−incubation for 3 min at 37 °C, the incubation reactions were

146

initiated by the addition of NADPH (1.0 mM). Control groups containing no NADPH or

147

substrates were conducted; each incubation was performed in duplicate. After a continuous

148

incubation for 60 min, the reactions were terminated with an equal volume of ice−cold

149

acetonitrile. The resulting mixture was centrifuged at 13,000 rpm for 10 min at 4 °C to pellet

150

protein. Then the supernatants were transferred to another centrifuge tube and 5 µL samples

151

were used for UHPLC−Q−TOF−MS (ultra-high performance liquid chromatography tandem

152

quadrupole−time−of−flight mass spectrometry) analysis.

153

Sample collection and preparation

154

The blood samples were collected in a 10 mL centrifuge tube with 10 µL heparin sodium

155

(1%). The plasma was obtained from the whole blood with centrifuged at 3500 rpm at 4 °C

156

for 10 min. The plasma samples were stored at −80 °C immediately. The protocol of the

157

sample preparation was described as below: 1 mL plasma was mixed with 4 mL

158

water−saturated butanol, vortexed for 30 min and centrifuged at 13000 rpm for 10 min. The

159

supernatant was dried with nitrogen gas at 40 °C. The residue was dissolved with 100 µL

160

methanol, and centrifuged at 13000 rpm for 10 min at 4 °C. 5 µL supernatant was used for

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UHPLC−Q−TOF−MS analysis finally.

162

UHPLC−Q−TOF−MS Analysis

163

An ultra-high performance liquid chromatography system (Waters ACQUITY UHPLC

164

core system, Waters), coupled with a Q−TOF SYNAPT G2 High Definition Mass

165

Spectrometer in electrospray ionization mode (Waters, Milford, MA, USA) was used to

166

obtain the specific and accurate masses of all samples. The source temperature was set at 110

167

°C, and the desolvation gas temperature was 350 °C. The flow rates of cone and desolvation

168

gas were set at 50 L h−1 and 600 L h−1, respectively. The voltages of capillary and cone in

169

negative ion mode were set at 2.0 kV and 25 V respectively. Mass spectra were acquired over

170

the m/z 50–700 range with a scan speed of 0.2 s per scan in continuum mode. The targeted

171

precursor ions were fragmented in the first T−wave element (Trap) to generate the

172

low−energy spectra. The collision energy in the trap cell was set up at 10 V to maintain

173

metastable precursor ions. The precursor ions in metastable state can be fragmented in the

174

trap cell further. The collision energy in the trap cell ranged from 35 V to 45 V to generate the

175

high−energy spectra. Leucine enkephalin (m/z 554.2615 in negative ion mode, 0.2 ng µL−1)

176

was used as lockspray for real−time correction at a flow rate of 5 µL min−1. Sodium formate

177

was used to set up mass spectrometer calibration in negative ion mode.

178

The separation was performed by a Waters ACQUITY UHPLC BEH C18 Column (2.1

179

mm × 50 mm, 1.7 µm) at 30 °C. 0.1% aqueous formic acid (V/V) (A) and acetonitrile (B)

180

were used as the mobile phase at a flow rate of 0.3 mL/min. Gradient programs were as

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follows for intestinal and liver microsomal samples: 0−2 min, 10%−45% B; 2−9 min,

182

45%−70% B; 9−10 min, 70%−100% B; 10−11 min, 100% B. The gradient program was as

183

follows for plasma samples: 0−5 min, 10%−35% B；5−10 min, 35%−50% B; 10−20 min,

184

50%−100% B; 20−21 min, 100% B.

185

Targeted network pharmacology analysis

186

All the constituents absorbed in plasma were regarded as targets to retrieval in network

187

database,

188

(http://ibts.hkbu.edu.hk/LSP/tcmsp.php)

189

(http://bionet.ncpsb.org/batman−tcm/). STITCH is a relatively authoritative resource to

190

integrate interactions among metabolic pathways, crystal structures, and drug–target

191

relationships. In fact, the number of drug−targets reported were far more than that of recorded

192

in above database because of unresponsive update of these database. The systemically hunt

193

for drug−targets was conducted in the SciFinder Scholar, which is a largest and most

194

comprehensive database of compounds in the world. All chemical structure of constituents

195

absorbed in plasma were imported into SciFinder Scholar for retrieval.

196

The

including

AD

targets

STITCH

were

gathered

(http://stitch.embl.de/,

ver.5.0),

and

from

DisGeNET

TCMSP

BATMAN−TCM

(http://www.disgenet.org

197

/web/DisGeNET/menu/home, ver. 5.0), which is one of the largest discovery platform

198

containing available genes and variants associated to human diseases (Janet Pinero et al.,

199

2017; J. Pinero et al., 2015). A total of 2245 AD targets were gathered from the DisGeNET.

200

Then the common targets shared by drugs and disease were picked up.

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Cytoscape 3.6.0 (Liu et al., 2016) was applied to visualize the interaction among the

202

compounds, drug−targets, and diseases. Cytoscape is a software platform that offers functions

203

for visualizing data and biological pathways (T. Xu et al., 2017). In the graphic network, the

204

compounds, targets and diseases were regarded as nodes, and the interactions between these

205

nodes were linked by edges. The degree of a node is defined as the number of the edges

206

linked to it.

207

The Database for Annotation, Visualization and Integrated Discovery (DAVID,

208

https://david−d.ncifcrf.gov/, ver. 6.7) was applied for Gene Ontology (GO) enrichment

209

analysis. Homo sapiens were chosen as the current background. Enriched GO terms

210

(pathways) with p−value less than 0.001 (corrected with Benjamin step down) were collected

211

and analyzed. These terms were integrated to interpret the biological meanings of these target

212

genes datasets with comprehensive set of functional annotation tools of DAVID and KEGG.

213

Results and Discussion

214 215

Systematic workflow for characterize of metabolites of Poria cocos from in vitro to in vivo

216

The systematic workflow is schematically depicted in Fig. 1. In step 1, the intestinal

217

microflora metabolites in vitro for the major triterpene acids (poricoic acid B, pachymic acid,

218

and tumulosic acid) were identified and structurally characterized based on the accurate MSE

219

date acquired by UHPLC−Q−TOF−MS. Then the metabolic rules under the action of

220

intestinal microflora metabolism in vitro for triterpene acids were summed up. In step 2, the

11



221

CYP450 metabolites in vitro for the major triterpene acids were studied (dehydrotrametenolic

222

acid, 16α−hydroxytrametenolic acid, polyporenic acid C, poricoic acid B, dehydrotumulosic

223

acid, tumulosic acid, 3−o−acetyl−16α−hydroxydehydrotrametenolic acid, and pachymic acid).

224

The metabolites in the RLMs in vitro were identified and characterized. The main metabolic

225

pathways through the action of RLMs were summed up to construct a database of metabolic

226

pathways. In step 3, the chemical profile of dosed rat plasma was described using

227

UHPLC−Q−TOF−MS. Two screening method was developed by using the UNIFI™ software,

228

namely screening of prototypes and metabolites. The prototypes screening was based on a

229

compound library while metabolites screening was based on the prototype compounds and

230

metabolic pathways. All absorbed constituents were picked out, which were detected in

231

experimental group and not in blank group. The mass behaviors and liquid retention time

232

were applied for confirming all absorbed constituents. In step 4, a targeted network

233

pharmacological analysis was conducted based on the absorbed constituents in plasma.

234 235

Characterize metabolites of representative triterpene acids transformed by intestinal microflora in vitro

236

Three representative triterpene acids of Poria cocos were selected to identify their

237

metabolites and explore metabolic rules in intestinal microflora. They represent different

238

structural types of triterpene acids and are also the major constituents of Poria cocos.

239

Triterpene acids in Poria cocos mainly are divided into two types, namely 3, 4−secolanostane

240

(poricoic acid B) and closed−lanostane (pachymic acid and tumulosic acid). Notably, the

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existence of the acetyl group at C−3−OH position distinguished pachymic acid from others.

242

However, only pachymic acid could be bio−transformed by deacetylation under the action of

243

intestinal microflora in vitro owing to the acetyl group linked to C−3−OH. It was explained

244

that the intestinal microflora composited of large amount of anaerobic flora, which live on

245

sugars, acids, proteins and so on, as a source of energy.

246

and proteins in the 75% alcohol extract of Poria cocos. In general, few metabolites of Poria

247

cocos could be detected under the action of intestinal microflora in vitro. And it was also

248

suggested that the triterpene acids of Poria cocos are mainly absorbed in the form of

249

prototype components.

250 251

[40-42]

There was no glycosyl group

Characterization of metabolites of representative triterpene acids transformed by RLMs in vitro

252

Eight representative triterpene acids in Poria cocos were selected to identify their

253

metabolites and explore metabolic rules in RLMs (Fig. 2). The stock standards (2 mM) were

254

incubated with NADPH system at different time points (30 min, 60 min and 90 min). The

255

mass data were obtained through the UHPLC−Q−TOF−MS under the MSE acquiring mode.

256

Metabolites screening was carried out with the aid of UNIFI™ software, which combined

257

with an extensive list of parent compounds and potential biotransformation reactions (e.g.,

258

dehydrogenation, oxygenation, methylation or arbitrary combination). The main filtering

259

parameters were set as followed: the mass error, 10 ppm and the retention time error, 0.2 min.

260

As the existence of structure of parent compound, the fragment information of all metabolites

13



261

was presented in two spectra, namely high−energy spectrum and low−energy spectrum. More

262

importantly, these metabolites could be confirmed manually through the rationality of every

263

fragment ion recognized automatically by Mass Fragment™ function in the UNIFI™

264

software. All identified metabolites were probably extracted to generate a series of extracted

265

ion chromatograms in each group.

266

Liver microsomes, also known as monooxygenase, can catalyze the oxidation process of

267

hundreds of compounds through the cytochrome P−450 (CYP450) in vivo. Eight reference

268

compounds were selected to explore as rich metabolic rules as possible through the action of

269

CYP450, considering little metabolites detected in the metabolic incubation with the action of

270

intestinal microflora. There were 27 metabolic types identified from metabolism of Poria

271

cocos in RLMs in vitro as shown in Table. 1. It was obvious that almost all standards were

272

metabolized via four pathways, namely M+O−H2, M+O, M+O2−H2, and M+O2, which

273

indicate that CYP450 metabolism in Poria cocos was featured with oxidation action. As the

274

difference of every triterpene acid of Poria cocos in chemical structure, the metabolic types

275

and numbers of each compound varied.

276

Poricoic acid B was a typical 3, 4−seco−lanosta type triterpene acid. Four metabolic

277

types of poricoic acid B were detected when incubating with RLMs in vitro, namely,

278

M+O−H2, M+O, M+O2−H2, and M+O2. Among, there were two mono−oxygenated products

279

extracted, the conversion yield of which reached at 85.5% and 108.0% (Fig. 3 (A−B)). This

280

result explicated that the 3, 4−seco−lansta structure shared more activity sites and higher

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transformation yield. Poricoic acid B generated a characteristic fragment ion at m/z 409.2768

282

[M−CH3CH2COOH]− at C−10 position in the negative ion mode as the base peak in the

283

MS/MS spectra (Ling, et al., 2012; W. Wang, et al., 2015). As the Fig. 3 (C−D) shown, these

284

two metabolites M+O (m/z 499.3090) at 3.02 min and 3.29 min in liquid chromatography,

285

shared three typical fragment ions at m/z 481.2905, m/z 425.2694 and m/z 409.2600,

286

corresponding to [M−H2O]−, [M−CH3CH2COOH]− and [M−H2O−CH3CH2COOH]−. It was

287

speculated that the hydroxyl group was substituted to a methyl group, which would be

288

fragmented easily. The 3, 4−seco−lansta structure makes two methyl end independent

289

compared with the closed structure of triterpene acids. It was explained that an independent

290

end was likely to be oxidized (Y. Li, et al., 2011). As the lack of standard reference material,

291

the metabolic sites couldn’t be confirmed absolutely and completely.

292

Polyporenic acid C, with an acyl group linked to the C−3 position and distinguished

293

form other triterpene acids, was used as an example to explain the metabolic rule. The acyl

294

group was proposed to be transformed to a hydroxyl through hydrogenation. In fact,

295

polyporenic acid C was biotransformed through four metabolic pathways, namely M+ H2,

296

M+O, M+H2O, M+O2, and M+H2O2. Apparently, the hydrogenation reaction happening to

297

polyporenic acid C was common. This result demonstrated that the metabolic sites of

298

polyporenic acid C was related with the acyl group linked to the C−3 position. At the same

299

time, the metabolic yield was calculated based on the peak area of liquid chromatograph of

300

parent compound, which was normalized as 100%. It was noteworthy that the peak area

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301

percent of biotransformed metabolites M+O, M+H2O, M+H2O2, M+O2, M+H2O2, and

302

M+H2O2 was 23.6%, 28.5%, 23.9%, 38.1% and 27.4% respectively, compared with the final

303

peak area of prototype compound polyporenic acid C. This indicted that polyporenic acid C

304

possessed high conversion yield and activity in the RLMs. In general, the metabolic pathway

305

of polyporenic acid C in RLMs in vitro took the M+O2 and M+H2O2 as the main metabolic

306

pathways.

307

Pachymic acid and 3−o−acetyl−16α−hydroxydehydrotrametenolic acid shared an acetyl

308

group at C−3−OH, which could be translated partially through the action of deacetylation

309

under the action of intestinal microflora. The deacetylation metabolite would be transformed

310

further under the action of CYP450. The conversion yield of pachymic acid is very low under

311

the action of CYP450, only the yield of double oxygenated metabolites can reach 2.7%. The

312

mass data of all metabolites of pachymic acid were listed in Table S1. A few metabolites of

313

pachymic acid were detected in vitro under the action of CYP450. On the other hand, it was

314

revealed that pachymic acid in prototype state was actual active ingredient in vivo. The

315

difference between pachymic acid and 3−o−acetyl−16α−hydroxydehydrotrametenolic acid

316

was the position of the alkene bond on the C−21 side chain substituents. The pachymic acid

317

was a 24, 31−ene−lanosta type structure while 3−o−acetyl−16α−hydroxydehydrotrametenolic

318

acid

319

3−o−acetyl−16α−hydroxydehydrotrametenolic acid under the action of CYP450 was a little

320

higher than that of pachymic acid relatively. It was speculated that the double bond on the

was

a

24,

25−ene−lanosta

type

structure.

16


The

translate

yield

of

Page 17 of 36


321

C−21 side chain substituents shared more activity of oxidation. And the metabolic types of

322

3−o−acetyl−16α−hydroxydehydrotrametenolic acid under the action of CYP450 were more

323

than that of pachymic acid. In that way, the 24, 25−ene−lanosta type structure shared more

324

active sites than that of 24, 31−ene−lanosta type structure in RLMs.

325

The structure of dehydrotumulosic acid and tumulosic acid is different from the numbers

326

of double bond on pentacyclic triterpenes. Tumulosic acid shares an 8−ene−lansta structure

327

while dehydrotumulosic acid shares a 7, 9 (11) −dien−lansta structure. The number and

328

metabolic types of metabolites for these two compounds were almost the same when

329

incubated with RLMs in vitro. It was speculated that the double bond on structure of

330

pentacyclic triterpenes had nothing to do with the site of oxidation in RLMs.

331

Characterization of metabolites of Poria cocos in rats in vivo

332

The metabolites in vivo of Poria cocos were analyzed by UHPLC−Q−TOF−MS in rat

333

plasma after oral administration, which was served as experiment group. The plasma with the

334

administration of distilled water to rats were served as the blank group. The blank plasm

335

sample dissolved with the extract of Poria cocos was served as control group. The

336

confirmation of prototypes was made by comparing with the data of accurate molecular mass

337

and retention time of control group. The compounds that can be detected in the both

338

experimental and control groups but not in blank group were defined as prototypes. As almost

339

all triterpene acids in the extract of Poria cocos share a carboxyl at the C−21 position, four

340

types of neutral losses were observed in MS/MS spectra, namely HCOOH (46 Da), CO2 (44

17



341

Da), CO2+CH4 (60 Da) and HCOOH+CH4 (62 Da). These neutral losses were imported into

342

UNIFI™ software for distinguishing triterpene acids in dosed plasma. But the number of all

343

triterpene acids detected in the extract of Poria cocos exceed more than that in in-house

344

database, there must some compounds identified as isomers. A total of 62 prototype

345

constituents were detected in the dosed plasma, as listed in Table S2. Eight compounds were

346

confirmed with the reference compounds. These absorbed ingredients involved the main

347

active substances in Poria cocos. Notably, the mass errors of all identified constituents were

348

within 10 ppm of error.

349

The constituents absorbed in vivo would be further metabolized by various of metabolic

350

enzymes. The compounds not detected in the control and blank groups were defined as

351

metabolites. As the above study in vitro, only pachymic acid, sharing an acetyl group at C−3

352

position, were partly transformed into tumulosic acid through the deacetylation under the

353

action of intestinal microflora. Because both of tumulosic acid and pachymic acid can be

354

absorbed in vivo as prototypes, the action of intestinal microflora could be ignored when

355

screening metabolites in vivo. In that way, the screening of absorbed metabolites in vivo only

356

need to consider the effect of CYP450, which play a key role in compounds metabolism in

357

vivo. In fact, the oxidation action plays a large part in transforming triterpene acids under the

358

action of CYP450. The screening of metabolites was mainly based on four metabolic

359

pathways, namely M+O−H2, M+O, M+O2−H2, and M+O2. The neutral losses were applied to

360

distinguish structure type of triterpene acids. The formation neutral loss 74 Da or 72 Da

18


Page 18 of 36

Page 19 of 36


361

(CH3CH2COOH/CHCH2COOH) under MSE acquiring mode were resulted from the 3,4−sec

362

structure type in mass spectrometry.

363

For example, precursor ion at m/z 453.33 was integrated in spectra for screening,

364

including blank, control, and experimental groups, as described in Fig 4. Compound P1 in

365

Table S2, was selected out based on compound screening under the UNIFI™ software. The

366

response intensity of compound at m/z 453.33 at 16.68 min in control group was relative high.

367

This compound was identified as dehydrotrametenolic acid, which was compared with the

368

retention time and accurate mass with of reference compound. Notably, there was a liquid

369

peak in experimental group at 16.68 min detected. The mass behavior of compound P1 in

370

experimental group was compared with that of dehydrotrametenolic acid in control group.

371

The compound P1 was identified as dehydrotrametenolic acid in dosed plasma in vivo.

372

Although a liquid peak could be observed in blank group, its mass behavior in mass

373

spectrometry was not constituent with that of reference of dehydrotrametenolic acid. This can

374

be defined as a false positive interference due to the complex matrix. In the other hand, this

375

result gave a proof of the importance of mass spectrometry and reference in identifying

376

compounds in complex matrix. More interestingly, there was another liquid peak M1 detected

377

at 14.64 min in experimental group but not in blank and control groups, as described in Fig. 4

378

(B). Next the MS/MS spectrum of this compound were taken into analysis. Just three

379

fragment ions were observed under the MSE acquiring mode based on the analysis of

380

UNIFI™ software, namely fragmentations at m/z 371.2571, m/z 359.2944, and m/z 319.2264.

19



381

There was a neutral loss C6H10 (84) observed resulted from the elimination of side chain,

382

corresponding to fragment ion m/z 371.2571. But the formation of compound M1 still

383

remained unclear. Two causes can result in the formation of metabolite M1, the

384

transformation of isomers and the oxidation. As the lack of enough mass fragmentations and

385

reference information, the compound M1 couldn’t be characterized absolutely. Collectively, a

386

total of 59 constituents were detected and characterized as metabolites of Poria cocos in vivo,

387

which was based on the above analysis. Almost all metabolites were classified as the products

388

of oxidation and only a small part of them were confirmed as products of isomerization. That

389

was a key problem for screening metabolites of triterpene acids as they share same chemical

390

formula and similar fragmentation behaviors in mass spectrometry. A lot of work are still

391

needed to do about completely determining the structures of all metabolites. Collectively, the

392

metabolic profilie of Poria cocos was described through a targeted analysis strategy, which

393

considered the metabolic processes of foods taken orally. This result can also provide better

394

healthy support for Poria cocos as supplement food and herbal medicine.

395

Targeted network pharmacological analysis of the bioactive constituents.

396

There are so many compounds detected and characterized in the extract crude of Poria

397

cocos. However, not all constituents of Poria cocos were reported with potential activity. In

398

this section, we retrieved all components of Poria cocos absorbed in plasma in SciFinder

399

Scholar. First, the chemical structures were imported into the SciFinder Scholar for retrieval.

400

All literatures that have recorded the information of targeted compound were listed. The

20


Page 20 of 36

Page 21 of 36


401

potential targets were selected out and collected sequentially. The related target proteins were

402

also gathered from several open source databases. A total of 30 constituents of Poria cocos

403

were summed to act with the potential targets finally. The targets of AD were also collected,

404

as the constituents of Poria cocos possess the potential activity towards AD. Only the target

405

proteins shared by drugs and disease were retained to construct the network as shown in Fig.

406

5 (86 targets). It was obvious that the larger target shared more edges with other targets, such

407

as CYP17A1, RARG, VDR, and NR3C1. A total of 198 targets were imported into the

408

bioinformatics database for GO enrichment analysis. When the background was chosen

409

Homo sapiens, only 143 targets were remained for further analysis. As shown in Table 2, the

410

pathways enriched with genes targeted by ingredients of Poria cocos were mainly involved in

411

human disease and material metabolism. Among the human disease, these were main

412

neurodegenerative disease and cancers. As well known, the problems in nervous system, such

413

as neurofibrillary tangles, neuroinflammation, and deposition of Beta amyloid, can cause the

414

incidence of AD. The material metabolism mainly focused on energy metabolism and lipid

415

metabolism. This result also reflected the multi−target and multi−function therapeutic feature

416

for the diseases treatment through complex compounds. The deep insight for Poria cocos in

417

treatment with AD can provide a new clue for further clinical application.

418

AUTHOR INFORMATION

419

Corresponding Authors

420

* E−mail address: [email protected] (S. Liu)

21



421

* E−mail address: [email protected] (Zhiqiang Liu)

422

Tel.: +86−431−85262613

423

Fax: +86−431−85262044

424

ORCID

425

Shu Liu: 0000-0002-8848-6871

426

Funding

427

This work was supported by grants from the National Natural Science Foundation of China

428

Key Program (NO. 81530094) and General Program (NO. 81573574) and the Science and

429

Technology Development Project of Jilin Province (20170623025TC).

430

Notes

431

The authors declare that there are no conflicts of interest.

432

ABBREVIATIONS

433

AD: Alzheimer's disease; CYP450: cytochrome P−450; UHPLC−Q−TOF−MS: ultra-high

434

performance liquid chromatography tandem Quadrupole−time−of−flight mass spectrometry;

435

MSE: data−independent mass spectrometry; RLMs: Preparation of rat liver microsomes.

436

Reference

437

1.

M.-K. Lu, J.-J. Cheng, C.-Y. Lin, C.-C. Chang, Purification, structural elucidation, and

438

anti-inflammatory effect of a water-soluble 1,6-branched 1,3-alpha-D-galactan from

439

cultured mycelia of Poria cocos, Food Chemistry 118(2) (2010) 349-356.

440

2.

B. Xia, Y. Zhou, H.S. Tan, L.S. Ding, H.X. Xu, Advanced ultra-performance liquid

22


Page 22 of 36

Page 23 of 36


441

chromatography-photodiode array-quadrupole time-of-flight mass spectrometric methods

442

for simultaneous screening and quantification of triterpenoids in Poria cocos, Food

443

Chem. 152 (2014) 237-244.

444

3.

Y.T. Lu, Y.C. Kuan, H.H. Chang, F. Sheu, Molecular cloning of a Poria cocos protein

445

that activates Th1 immune response and allays Th2 cytokine and IgE production in a

446

murine atopic dermatitis model, Journal of agricultural and food chemistry 62(13) (2014)

447

2861-71.

448

4.

Y. Ling, M. Chen, K. Wang, Z. Sun, Z. Li, B. Wu, C. Huang, Systematic screening and

449

characterization of the major bioactive components of Poria cocos and their metabolites

450

in rats by LC‐ESI‐MSn, Biomedical Chromatography 26(9) (2012) 1109-1117.

451

5.

W. Wang, H. Dong, R. Yan, H. Li, P. Li, P. Chen, B. Yang, Z. Wang, Comparative study

452

of lanostane-type triterpene acids in different parts of Poria cocos (Schw.) Wolf by

453

UHPLC–Fourier transform MS and UHPLC-triple quadruple MS, Journal of

454

pharmaceutical and biomedical analysis 102 (2015) 203-214.

455

6.

A.-H. Gao, X. Chen, Y. Chen, Z.-Z. Xu, Y.-N. Liu, H. Zhang, L. Zhang, Inhibition of

456

ovarian cancer proliferation and invasion by pachymic acid, Int J Clin Exp Pathol 8(2)

457

(2015) 2235-41.

458

7.

J. Wang, P. Zhang, H. He, X. Se, W. Sun, B. Chen, L. Zhang, X. Yan, K. Zou, Eburicoic

459

acid from Laetiporus sulphureus (Bull.:Fr.) Murrill attenuates inflammatory responses

460

through inhibiting LPS-induced activation of PI3K/Akt/mTOR/NF-κB pathways in

23



461 462

RAW264.7 cells, Naunyn-Schmiedeberg's Arch. Pharmacol. 390(8) (2017) 845-856. 8.

S. Eom, Y.S. Kim, S.B. Lee, S. Noh, H.D. Yeom, H. Bae, J.H. Lee, Molecular

463

Determinants of alpha 3 beta 4 Nicotinic Acetylcholine Receptors Inhibition by

464

Triterpenoids, Biological & Pharmaceutical Bulletin 41(1) (2018) 65-72.

465 466

9.

S.G. Lee, M.M. Kim, Pachymic acid promotes induction of autophagy related to IGF-1 signaling pathway in WI-38 cells, Phytomedicine 36 (2017) 82-87.

467

10. L.X. Zhu, J. Xu, S.J. Zhang, R.J. Wang, Q. Huang, H.B. Chen, X.P. Dong, Z.Z. Zhao,

468

Qualitatively and quantitatively comparing secondary metabolites in three medicinal

469

parts derived from Poria cocos (Schw.) Wolf using UHPLC-QTOF-MS/MS-based

470

chemical profiling, Journal of Pharmaceutical and Biomedical Analysis 150 (2018)

471

278-286.

472

11. H. Miao, Y.H. Zhao, N.D. Vaziri, D.D. Tang, H. Chen, H. Chen, M. Khazaeli, M.

473

Tarbiat-Boldaji, L. Hatami, Y.Y. Zhao, Lipidomics Biomarkers of Diet-Induced

474

Hyperlipidemia and Its Treatment with Poria cocos, Journal of agricultural and food

475

chemistry 64(4) (2016) 969-79.

476

12. M. Wang, D.Q. Chen, L. Chen, D. Liu, H. Zhao, Z.H. Zhang, N.D. Vaziri, Y. Guo, Y.Y.

477

Zhao, Novel RAS Inhibitors Poricoic Acid ZG and Poricoic Acid ZH Attenuate Renal

478

Fibrosis via a Wnt/beta-Catenin Pathway and Targeted Phosphorylation of smad3

479

Signaling, Journal of agricultural and food chemistry 66(8) (2018) 1828-1842.

480

13. G. Pereira-Caro, J.L. Ordonez, I. Ludwig, S. Gaillet, P. Mena, D. Del Rio, J.-M.

24


Page 24 of 36

Page 25 of 36


481

Rouanet, K.A. Bindon, J.M. Moreno-Rojas, A. Crozier, Development and validation of

482

an UHPLC-HRMS protocol for the analysis of flavan-3-ol metabolites and catabolites in

483

urine, plasma and feces of rats fed a red wine proanthocyanidin extract, Food chemistry

484

252 (2018) 49-60.

485

14. W. Song, X. Qiao, K. Chen, Y. Wang, S. Ji, J. Feng, K. Li, Y. Lin, M. Ye,

486

Biosynthesis-Based Quantitative Analysis of 151 Secondary Metabolites of Licorice To

487

Differentiate Medicinal Glycyrrhiza Species and Their Hybrids, Analytical Chemistry

488

89(5) (2017) 3146-3153.

489

15. S. Tang, S. Liu, Z. Liu, F. Song, S. Liu, Analysis and Identification of the Chemical

490

Constituents

491

HPLC-Q-TOF-MS, Chin. J. Chem. 33(4) (2015) 451-462.

492

of

Ding-Zhi-Xiao-Wan

Prescription

by

HPLC-IT-MSn

and

16. G.F. Feng, S. Liu, Z.F. Pi, F.R. Song, Z.Q. Liu, Studies on the chemical and intestinal

493

metabolic

profiles

of

Polygalae

Radix

by

using

UHPLC-IT-MS(n)

and

494

UHPLC-Q-TOF-MS method coupled with intestinal bacteria incubation model in vitro,

495

Journal of pharmaceutical and biomedical analysis 148 (2018) 298-306.

496

17. P. Gong, N. Cui, L. Wu, Y. Liang, K. Hao, X. Xu, W. Tang, G. Wang, H. Hao,

497

Chemicalome and metabolome matching approach to elucidating biological metabolic

498

networks of complex mixtures, Analytical chemistry 84(6) (2012) 2995-3002.

499

18. R. Xing, L. Zhou, L. Xie, K. Hao, T. Rao, Q. Wang, W. Ye, H. Fu, X. Wang, G. Wang,

500

Development of a systematic approach to rapid classification and identification of

25



501

notoginsenosides and metabolites in rat feces based on liquid chromatography coupled

502

triple time-of-flight mass spectrometry, Analytica chimica acta 867 (2015) 56-66.

503

19. L.A. Li, X.Y. Chen, D. Li, D.F. Zhong, Identification of 20(S)-Protopanaxadiol

504

Metabolites in Human Liver Microsomes and Human Hepatocytes, Drug Metabolism

505

and Disposition 39(3) (2011) 472-483.

506

20. Watanabe, H. Takakusa, T. Kimura, S. Inoue, H. Kusuhara, O. Ando, Analysis of

507

Mechanism-Based Inhibition of CYP 3A4 by a Series of Fluoroquinolone Antibacterial

508

Agents, Drug Metabolism and Disposition 44(10) (2016) 1608-1616.

509

21. G. Feng, S. Liu, Z. Pi, F. Song, Z. Liu, Study on the I Phase Metabolism of Ginsenoside

510

in vitro by Ultra Performance Liquid Chromatography Coupled with Mass Spectrometry,

511

Journal of Chinese Mass Spectrometry Society 38(4) (2017) 450-459.

512

22. H. Wang, Q. Wang, S.-L. Xiao, F. Yu, M. Ye, Y.-X. Zheng, C.-K. Zhao, D.-A. Sun,

513

L.-H. Zhang, D.-M. Zhou, Elucidation of the pharmacophore of echinocystic acid, a new

514

lead for blocking HCV entry, European journal of medicinal chemistry 64 (2013)

515

160-168.

516

23. Y. Li, G. Ren, Y.X. Wang, W.J. Kong, P. Yang, Y.M. Wang, Y.H. Li, H. Yi, Z.R. Li,

517

D.Q. Song, J.D. Jiang, Bioactivities of berberine metabolites after transformation through

518

CYP450 isoenzymes, Journal of translational medicine 9 (2011) 62.

519

24. Losito, L. Facchini, A. Valentini, T.R.I. Cataldi, F. Palmisano, Fatty acidomics:

520

Evaluation of the effects of thermal treatments on commercial mussels through an

26


Page 26 of 36

Page 27 of 36


521

extended characterization of their free fatty acids by liquid chromatography - Fourier

522

transform mass spectrometry, Food chemistry 255 (2018) 309-322.

523

25. H. Uchida, Y. Itabashi, R. Watanabe, R. Matsushima, H. Oikawa, T. Suzuki, M.

524

Hosokawa, N. Tsutsumi, K. Ura, D. Romanazzi, M.R. Miller, Detection and

525

identification of furan fatty acids from fish lipids by high-performance liquid

526

chromatography coupled to electrospray ionization quadrupole time-of-flight mass

527

spectrometry, Food chemistry 252 (2018) 84-91.

528

26. Bauer, J. Luetjohann, F.S. Hanschen, M. Schreiner, J. Kuballa, E. Jantzen, S. Rohn,

529

Identification and characterization of pesticide metabolites in Brassica species by liquid

530

chromatography travelling wave ion mobility quadrupole time-of-flight mass

531

spectrometry (UPLC-TWIMS-QTOF-MS), Food Chemistry 244 (2018) 292-303.

532

27. L. Righetti, M. Fenclova, L. Dellafiora, J. Hajslova, M. Stranska-Zachariasova, C.

533

Dall'Asta, High resolution-ion mobility mass spectrometry as an additional powerful tool

534

for structural characterization of mycotoxin metabolites, Food Chemistry 245 (2018)

535

768-774.

536

28. R.S. Gibbs, S.L. Murray, L.V. Watson, B.P. Nielsen, R.A. Potter, C.J. Murphy,

537

Development and Validation of a Hybrid Screening and Quantitative Method for the

538

Analysis of Eight Classes of Therapeutants in Aquaculture Products by Liquid

539

Chromatography-Tandem Mass Spectrometry, Journal of agricultural and food chemistry

540

66(20) (2018) 4997-5008.

27



Page 28 of 36

541

29. H. Enomoto, K. Sato, K. Miyamoto, A. Ohtsuka, H. Yamane, Distribution Analysis of

542

Anthocyanins, Sugars, and Organic Acids in Strawberry Fruits Using Matrix-Assisted

543

Laser Desorption/Ionization-Imaging Mass Spectrometry, Journal of agricultural and

544

food chemistry 66(19) (2018) 4958-4965.

545

30. A.D. Wylie, W.F. Zandberg, Quantitation of Sialic Acids in Infant Formulas by Liquid

546

Chromatography-Mass Spectrometry: An Assessment of Different Protein Sources and

547

Discovery of New Analogues, Journal of agricultural and food chemistry

(2018).

548

31. S. Song, K. Zhu, L. Han, Y. Sapozhnikova, Z. Zhang, W. Yao, Residue Analysis of 60

549

Pesticides in Red Swamp Crayfish Using QuEChERS with High-Performance Liquid

550

Chromatography-Tandem Mass Spectrometry, Journal of agricultural and food chemistry

551

66(20) (2018) 5031-5038.

552

32. W. Si, W. Yang, D. Guo, J. Wu, J. Zhang, S. Qiu, C. Yao, Y. Cui, W. Wu, Selective ion

553

monitoring of quinochalcone C-glycoside markers for the simultaneous identification of

554

Carthamus tinctorius L. in eleven Chinese patent medicines by UHPLC/QTOF MS,

555


556

33. W. Yang, J. Zhang, C. Yao, S. Qiu, M. Chen, H. Pan, X. Shi, W. Wu, D. Guo, Method

557

development

and

application

of

offline

558

chromatography/quadrupole time-of-flight mass spectrometry-fast data directed analysis

559

for comprehensive characterization of the saponins from Xueshuantong Injection,

560


28


two-dimensional

liquid

Page 29 of 36

561


34. S. Qiu, W.-z. Yang, C.-l. Yao, Z.-d. Qiu, X.-j. Shi, J.-x. Zhang, J.-j. Hou, Q.-r. Wang,

562

W.-y.

Wu,

D.-a.

Guo,

Nontargeted

metabolomic

analysis

and

563

"Commercial-homophyletic" comparison-induced biomarkers verification for the

564

systematic chemical differentiation of five different parts of Panax ginseng, J.

565

Chromatogr. A 1453 (2016) 78-87.

566

35. J. Fang, L. Wang, T. Wu, C. Yang, L. Gao, H. Cai, J. Liu, S. Fang, Y. Chen, W. Tan, Q.

567

Wang, Network pharmacology-based study on the mechanism of action for herbal

568

medicines in Alzheimer treatment, J Ethnopharmacol 196 (2017) 281-292.

569

36. T. Xu, S. Li, Y. Sun, Z. Pi, S. Liu, F. Song, Z. Liu, Systematically characterize the

570

absorbed effective substances of Wutou Decoction and their metabolic pathways in rat

571

plasma using UHPLC-Q-TOF-MS combined with a target network pharmacological

572

analysis, Journal of pharmaceutical and biomedical analysis 141 (2017) 95-107.

573

37. J. Liu, J. Liu, F. Shen, Z. Qin, M. Jiang, J. Zhu, Z. Wang, J. Zhou, Y. Fu, X. Chen, C.

574

Huang, W. Xiao, C. Zheng, Y. Wang, Systems pharmacology analysis of synergy of

575

TCM: an example using saffron formula, Sci Rep 8(1) (2018) 380.

576

38. Y. Luo, Q. Wang, Y. Zhang, A systems pharmacology approach to decipher the

577

mechanism of danggui-shaoyao-san decoction for the treatment of neurodegenerative

578

diseases, J Ethnopharmacol 178 (2016) 66-81.

579 580

39.

Y.-F. Bi, H.-B. Zhu, Z.-F. Pi, Z.-Q. Liu, F.-R. Song, Effects of Flavonoides from the Leaves of Acanthopanax on the Activity of CYP450 Isozymes in Rat Liver Microsomes

29



581

by a UPLC-MS/MS and Cocktail Probe Substrates Method, Chemical Journal of Chinese

582

Universities-Chinese 34(5) (2013) 1067-1071.

583

40. K. Keppler, H.-U. Humpf, Metabolism of anthocyanins and their phenolic degradation

584

products by the intestinal microflora, Bioorganic & medicinal chemistry 13(17) (2005)

585

5195-5205.

586 587

41. S.G. Parkar, T.M. Trower, D.E. Stevenson, Fecal microbial metabolism of polyphenols and its effects on human gut microbiota, Anaerobe 23 (2013) 12-19.

588

42. K. Nakamura, T. Nishihata, J.-S. Jin, C.-M. Ma, K. Komatsu, M. Iwashima, M. Hattori,

589

The C-glucosyl bond of puerarin was cleaved hydrolytically by a human intestinal

590

bacterium strain PUE to yield its aglycone daidzein and an intact glucose, Chemical and

591

Pharmaceutical Bulletin 59(1) (2011) 23-27

30


Page 30 of 36

Page 31 of 36


592

Figure Captions

593

Fig. 1 Systematic workflow for targeted screening to systematically identify the metabolites

594

of Poria cocos in rats using ultra-high performance liquid chromatography tandem mass

595

spectrometry.

596

Fig. 2 Main structures of triterpene acids of Poria cocos which were incubated with RLMs in

597

vitro.

598

Fig. 3 Base peak chromatograms of control and experimental groups of poricoic acid B in

599

RLMs in vitro (A); extract ion chromatograms of metabolites M+O (m/z 499.306, mass

600

window, 0.02 Da) of control and experimental groups of poricoic acid B in RLMs in vitro

601

(B); proposed fragmentation pathway for metabolites M+O of poricoic acid B at 3.2 min (C)

602

and 3.29 min (D) in liquid chromatography.

603

Fig. 4 Extract ion chromatograms of compounds M1 (A) and P1 (B) in plasma in the control,

604

blank, and experimental groups through UHPLC−Q−TOF MS.

605

Fig. 5 Interaction network of the effect substances (in orange), the related target proteins (in

606

blue) and the common targets shared by drug and targets (in royal blue). A node stands for a

607

constituent, a target or disease, the interactions of two nodes were represented by a line and

608

the bigger size of a node refers to a greater degree.

31



609

Table 1. Main metabolic types and numbers of triterpene acids in Poria cocos biotransformed

610

in RLMs in vitro. Numbers Peak

611 612 613 614

G S C B Q T A P Metabolic types 1 M−C2H2O−H2O−H2+O2 − − − − − − 1 − 2 M−C2H2O2−H2+O2 − − − − − − 3 2 3 M−C2H2O2+O2 − − − − − − 2 1 4 M−COO+H2O − − − − − − 1 − 5 M−COO−H2+O2 − − − − − − 2 − 6 M−C2H2O−H2+O2 − − − − − − 3 − 7 M−C2H2O+O2 − − − − − − 4 2 8 M−C2H2O−H2+O2+CH2 − − − − − − 1 9 M−H2 − − − 4 − − − 10 M+O−H2−H2 − 1 − − − 1 − − 11 M+O−H2 1 5 1 4 3 4 1 − 12 M+O 2 5 3 6 3 3 3 − 13 M+H2O − − 2 − − − − − 14 M+O2−H2−H2 − − − − 3 1 − 1 15 M+O2−H2 1 5 2 − 8 8 1 1 16 M+O+CH2−H2 − − − − − − 1 − 17 M+O+CH2 − 1 − − − − − − 18 M+O2 − 5 7 4 5 5 3 3 19 M+H2O2 − − 5 − − − − 1 20 M+O−H2+O2−H2 − − − − 1 1 − 2 21 M−H2+O2+O − 1 1 − 4 7 − − 22 M+H2O2+O2−H2 − − 5 − − 1 − − 23 M+H2O2+O − − 1 − − − 1 − − 2 − − − − − − 24 M−H2+O2+CH2 25 M+H2O2−H2+CH2 − − − − − 1 − − 26 M+CH2O2+H2 − − − − − − − − 27 M+H2O−H2+O2+CH2 − − − − − − 1 − Sum Metabolites 4 25 27 18 27 32 28 13 Note G: dehydrotrametenolic acid; S: 16α−hydroxytrametenolic acid; C: polyporenic acid C; B: poricoic B; Q: dehydrotumulosic; T: tumulosic acid; A: 3−o−acetyl−16α−hydroxydehydrotrametenolic acid; P: pachymic acid.

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Table 2 Disease associated pathways of PC through the GO enrichment analysis (P value

Targeted Screening Approach to Systematically Identify the Absorbed

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