Metabolic Effects of the pksCT Gene on Monascus aurantiacus Li As3

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Metabolic Effects of the pksCT Gene on Monascus aurantiacus Li As3.4384 Using Gas ChromatographyTime-of-Flight Mass Spectrometry-Based Metabolomics Zhibing Huang, Shuyun Zhang, Yang Xu, Laisheng Li, and Yanping Li J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.5b06082 • Publication Date (Web): 29 Jan 2016 Downloaded from http://pubs.acs.org on January 31, 2016

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Journal of Agricultural and Food Chemistry

Metabolic Effects of the pksCT Gene on Monascus aurantiacus Li As3.4384

1 2

Using Gas Chromatography-Time-of-Flight Mass Spectrometry-Based

3

Metabolomics

4

Zhibing Huang,*,† Shuyun Zhang,† Yang Xu,† Laisheng Li,§ and Yanping Li†

5 6 7

†

State Key Laboratory of Food Science and Technology, Sino–German Joint

8

Research Institute, Nanchang University, No. 235 Nanjing East Road, Nanchang

9

330047, China

10 11

§

Center of Analysis and Testing, Nanchang University, No. 235 Nanjing East Road,

Nanchang 330047, China

12 13

Running head: Metabolic Effects of the pksCT Gene in M. aurantiacus Li As3.4384

14

*

To whom correspondence should be addressed. (Telephone: +86-0791-88305177-8109; Fax: +86-0791-88333708;

E-mail: [email protected]).

ACS Paragon Plus Environment


15

ABSTRACT

16

Monascus spp. have been used for the production of natural pigments and

17

bioactive compounds in China for several centuries. Monascus also can produce

18

the mycotoxin citrinin, restricting its use. Disruption of the pksCT gene in Monascus

19

aurantiacus Li AS3.4384 reduces citrinin production capacity of this strain

20

(Monascus PHDS26) by over 98%. However, it is unclear how other metabolites of

21

M. aurantiacus Li AS3.4384 (the wild-type strain) are affected by the pksCT gene.

22

Here, we used metabolomics analyses to compare red yeast rice (RYR) metabolite

23

profiles of the wild-type strain and Monascus PHDS26 at different stages of

24

solid-state fermentation. Eighteen metabolites forming components within the

25

glycolysis, acetyl-CoA, amino acid, and TCA cycle metabolic processes were found

26

to be altered between the wild-type strain and Monascus PHDS26 at different

27

stages of solid-state fermentation. Thus, these findings provide important insights

28

into the metabolic pathways affected by the pksCT gene in M. aurantiacus.

29 30

KEYWORDS: Monascus aurantiacus Li AS3.4384, pksCT gene disrupted strain,

31

metabolomics, GC-TOF-MS

32


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INTRODUCTION

34

Monascus and its metabolites have been used in food and medicines for thousands

35

of years in China.1 Monascus can produce many bioactive compounds, including

36

Monascus pigments, monacolin K, γ-aminobutyric acid (GABA), and ergosterol.2,3

37

Monacolin K is usually used to reduce serum triglyceride and cholesterol levels.4

38

Some

39

immunomodulatory, and anti-inflammatory effects. Moreover, some components

40

increase levels of high-density lipoprotein cholesterol and have anti-atherosclerosis

41

and anticancer effects.5-8 However, Monascus also can produce the mycotoxin

42

citrinin, which is found after fermentation of Monascus.9 Citrinin has been shown to

43

have nephrotoxic, carcinogenic, and hepatotoxic effects.10 Notably, the citrinin

44

production capacity of Monascus is decreased following disruption of the pksCT

45

gene in M. purpureus; in this strain, which was constructed by homologous

46

recombination, citrinin is not produced.11 Additionally, in our previous study,

47

disruption of the pksCT gene in strain Monascus PHDS26 decreased citrinin

48

production capacity by over 98%.12,13 However, it is unclear how other metabolites

49

of Monascus are affected by the pksCT gene.

Monascus

pigments

have

been

shown

to

have

anti-obesity,

50

Metabolomics can be used to compare different metabolites and changes in

51

different biological samples with changes in their environment, including analysis of

52

global small molecules in biofluids.14 Metabolite analysis is usually carried out using

53

multiple experimental platforms, such as gas chromatography-mass spectrometry

54

(GC-MS),

liquid

chromatography-mass

spectrometry


(LC-MS),

capillary


55

electrophoresis-mass spectrometry (CE-MS), and nuclear magnetic resonance

56

(NMR).15-17 Unlike in genomics and proteomics studies, metabolomics cannot be

57

used to completely characterize all metabolites present in biological samples using

58

only a single analytical platform.18 Nevertheless, GC-MS-based metabolomics

59

approaches aim to target the metabolism of some intermediates, such as fatty acids,

60

nucleotides, carbohydrates, hydroxyl acids, amino acids, and related compounds.

61

GC-MS-based metabolomics is considered the most mature analytical platform;

62

more than 250,000 compounds and small molecules are included in standard

63

repositories of mass spectra, and compounds can be searched using the NIST and

64

Wiley libraries. In metabolomics approaches, large amounts of analytical data have

65

been obtained using these analytical platforms, and the data can be analyzed and

66

processed with multivariate analytical methods. Multivariate analyses usually

67

include principal component analysis (PCA), partial least-squares discriminate

68

analysis (PLS-DA), and orthogonal partial least-squares discriminate analysis

69

(OPLS-DA). These data analysis methods can cluster of metabolite profiles or be

70

used to discover important changes between different groups of samples. The

71

methods have been used to analyze metabolite profiles of traditional meju during

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fermentation,19 fast-fermented bean paste,20 and transgenic Beauveria bassiana.21

73

To the best of our knowledge, no metabolomic studies have been conducted in

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Monascus.

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Therefore, the goal of this work was to determine differences in the metabolic

76

profiles of red yeast rice (RYR) from the wild-type strain and Monascus PHDS26


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after cultivation for different fermentation times (6, 10, 14, 18, and 22 days),

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followed by GC-TOF-MS analysis and subsequent multivariate statistical analysis.

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Our results provide important insights into the metabolic profiles of Monascus spp.,

80

particularly with regard to the role of the pksCT gene.

81 82

MATERIALS AND METHODS

83

Chemicals and materials

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Rice was purchased from local supermarkets. M. aurantiacus Li As3.4384 was

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obtained from the Institute of Microbiology, Chinese Academy of Science (Beijing,

86

China). The Monascus PHDS26 strain was constructed by disrupting the pksCT gene

87

in the wild-type strain.12,13 Ribitol, methoxyamine hydrochloride, and pyridine were

88

purchased from Sigma-Aldrich (St. Louis, MO, USA). N,O-bis(trimethylsilyl)

89

trifluoroacetamide (BSTFA) and trimethylchlorosilane (TMCS) were obtained from

90

Regis Technologies, Inc. (Morton Grove, IL, USA). High-performance liquid

91

chromatography (HPLC)-grade methanol was purchased from Merck (Darmstadt,

92

Germany). All other chemicals (analytical grade) were obtained from Sinopharm

93

Chemical Reagent Co. Ltd. (Beijing, China). Distilled water was purified by the Milli-Q

94

Plus System (18.2 MΩ cm; Millipore Inc., Billerica, MA, USA).

95

Preparation and extraction of RYR

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RYR was obtained according to our previously reported methods.22 Rice was

97

soaked in water for 12 h. After draining, the rice (100 g) was placed in an Erlenmeyer

98

flask (250 mL) and then sterilized using standard procedures at 121°C for 15 min.



99

Each Erlenmeyer flask was inoculated with the seed cultures (2 mL) in an incubator at

100

30°C and fermented for 6, 10, 14, 18, or 22 days. After different periods of incubation,

101

the RYR was collected, immediately frozen in liquid nitrogen, and then stored at

102

-80°C for further freeze-drying. Each RYR (100 mg) sample was pulverized in a 2 mL

103

centrifuge tube containing a steel metal ball in a mixer-mill grinder at 70 Hz for 5 min,

104

and 60 µL of 0.2 mg/mL of ribitol (as an internal standard) was then added. The

105

samples were mixed by vortexing for 1 min, and 0.4 mL cold (-20°C)

106

methanol-chloroform (1:1, v/v) was then added, followed by mixing again with

107

vortexing for 1 min. Each sample was extracted by sonication for 30 min and then

108

shaken for 3 h at 4°C. After extraction, the sample was centrifuged at 10000 × g for

109

10 min at 4°C (Sigma-Laborzentrifugen, 2K15; Osterode, Germany), and 0.35 mL of

110

the supernatant was then collected and dried in a vacuum concentrator at 45°C for

111

1.5 h. Finally, the dry extracts were derivatized by methoxyamination using 80 µL of

112

methoxyamine-HCl (20 mg/mL in pyridine) at 37°C for 3 h. The samples were then

113

trimethylsilylated for 1 h using 100 µL of BSTFA with 1% TMCS (v/v) at 70°C with

114

shaking. After silylation, 50 µL of n-heptane was added.

115

GC-TOF-MS analysis

116

GC-TOF-MS analysis was carried out using an Agilent 7890A gas chromatograph

117

system (Agilent, Atlanta, GA, USA) coupled with a Pegasus 4D TOF mass

118

spectrometer (LECO Corp., St. Joseph, MI, USA). Each derivatized sample (1 µL)

119

was separated on a 30 m × 250 µm i.d. DB-5MS capillary column (0.25 µm film

120

thickness) coated with 5% diphenyl crosslinked with 95% dimethylpolysiloxane


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(Agilent J&W Scientific, Folsom, CA, USA). The helium (purity 99.9999%) gas flow

122

rates of the front inlet purge and through the column were 3 and 1 mL/min,

123

respectively. The temperatures set were as follows: initial temperature of 90°C for

124

0.25 min, increased to 180°C at a rate of 10°C/min, then increased to 240°C at a rate

125

of 5°C/min, and finally increased to 285°C at a rate of 20°C/min, after which the

126

samples were held at 285°C for 11.5 min. The injection, ion source, and transfer line

127

temperatures were 280, 220, and 245°C, respectively. Ions were generated by 70 eV

128

electro-impact (EI) ionization at a current of 3.0 mA, and EI spectra were acquired in

129

the m/z range of 20–600 at a rate of 100 spectra/s after a solvent delay of 7 min. Each

130

sample was analyzed with six replications.

131

Data analysis

132

The GC-TOF-MS raw data were exported to the netCDF file format using LECO

133

ChromaTOF version 4.44 software (LECO Corp., St. Joseph, MI, USA) for mass

134

spectral deconvolution and peak finding, followed by retention index matching,

135

normalization, peak merging, and statistical significance tests. The signal-to-noise

136

(S/N) ratios of peaks lower than 30 were removed. All compounds were identified

137

by comparing their mass spectra and standards with the LECO/Fiehn Metabolomics

138

Library, yielding similarity values for compound identification accuracy. If the

139

similarity was more than 700, the peak was assigned as a metabolite, and the

140

metabolite identification was considered reliable. If the similarity was less than 200,

141

the library would only use “analyte” for the compound name. If the similarity was

142

between 200 and 700, the compound name was given a putative annotation.



143

Obvious differences in the metabolites were assigned with a variable importance in

144

the projection (VIP) value of greater than 1.0. Some derivatives was assigned by

145

increasing numbers according to the retention index, e.g., serine 1, serine 2, and

146

serine 3.23

147

For multivariate analysis, the relative data matrix containing peak area

148

information as variables and sample names as observations was processed using

149

SIMCA-P version 12.0 software (Umetrics, Umeå, Sweden). PCA, PLS-DA, and

150

OPLS modelling were used to compare different metabolites from the wild-type

151

strain and Monascus PHDS26 during different fermentation stages. The

152

parameters of the models were defined as described previously.24

153 154

RESULTS AND DISCUSSION

155

GC-TOF-MS-based metabolite profiling of Monascus

156

The color value of the pigments and citrinin in the RYR obtained from the wild-type

157

strain and Monascus PHDS26 were measured by ultraviolet-visible (UV-Vis)

158

spectrophotometry and HPLC, respectively, according to previous methods.25,26 As

159

shown in Figure 1(A), no significant differences of the contents of pigments in the

160

RYR were found in the wild-type strain after different fermentation periods from 6 to

161

16 days; however, the contents of pigments increased obviously from 16 to 22 days.

162

Furthermore, as shown in Figure 1(B), the content of citrinin increased significantly

163

for M. aurantiacus Li As3.4384 during the fermentation periods from 6 to 14 days. In

164

addition, the contents of two orange pigments from M. aurantiacus Li As3.4384 also


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increased from 6 to 16 days.27 Therefore, the fermentation period from 6 to 22 days

166

was selected for analysis of the metabolic effects of pksCT gene in M. aurantiacus

167

Li As3.4384.

168

Next, the metabolic profiles of the wild-type strain and Monascus PHDS26

169

during solid-state fermentation (6, 10, 14, 18, and 22 days) were investigated by

170

GC-TOF-MS. Ribitol was used as an internal standard to evaluate the performance

171

of the GC-TOF-MS system. The retention time of the ribitol shift ranged from 0.01 to

172

0.03 min, and the RSD of the peak area ranged from 2.0% to 5.1%. The results

173

showed that the GC-TOF-MS system provided stable sample analysis. The extracts

174

of RYR from the solid-state fermentation of wild-type strain and Monascus PHDS26

175

were analyzed. The GC-TOF-MS total ion current chromatographs of RYR extracts

176

obtained from fermentation after 22 days are shown in Figure 2. Some metabolites

177

exhibited obvious increases in relative abundance, whereas others showed

178

decreasing relative abundances, and some remained unchanged after different

179

fermentation times (Figure 2). In total, 696 metabolites, including organic acids,

180

saccharides, amino acids, and amines, were detected in metabolomic profiling of

181

the RYR. Moreover, 85 metabolites of the RYR from the solid-state fermentation of

182

the wild-type strain and Monascus PHDS26 were integrated by NIST mass spectral

183

similarity scores of no less than 700 (Table 1). These known metabolites included

184

amino acids and amines (e.g., alanine, glycine, valine, proline, serine, aspartic acid,

185

oxoproline, glutamic acid, phenylalanine, glutamine, and tyrosine), organic acids

186

(e.g., oxamic acid methylmalonic acid, succinic acid, fumaric acid, L-malic acid, and



187

citric acid), and sugars and sugar alcohols (e.g., fructose, mannose, sorbitol,

188

sucrose, trehalose, isomaltose, and galactinol; Table 1). Based on the P-values (
1.0), a total of 91

190

metabolites with important roles in different groups were selected. Of these, 10

191

metabolites were identified based on similarity scores of no less than 700, 12

192

metabolites were putatively annotated according to the similarities between 200

193

and 700, and 69 exhibited unknown metabolic profiles in the RYR after fermentation

194

for 6 days by the wild-type strain and Monascus PHDS26 (Supplemental Table S1).

195

Moreover, 124 metabolites differed significantly after fermentation for 10 days (12

196

known metabolites, 17 putatively annotated metabolites, and 95 unknown

197

metabolites; Table S2). After 14 days of fermentation, 127 metabolites differed

198

significantly (seven known metabolites, 16 putatively annotated metabolites, and

199

104 unknown metabolites; Table S3). After fermentation for 18 days, 134

200

metabolites differed significantly, including seven known metabolites, 25 putatively

201

annotated metabolites, and 101 unknown metabolites (Table S4). Finally, after

202

fermentation for 22 days, 17 metabolites differed, including eight known metabolites,

203

three putatively annotated metabolites, and six unknown metabolites (Table S5). As

204

shown in Table 2, some metabolites were identified according to similarity scores of

205

no less than 700.

206

In order to study the metabolic variations between different fermentation

207

periods (from 6 to 22 days), the metabolic profiles of the wild-type strain and

208

Monascus PHDS26 after different fermentation times, e.g., 6, 10, 14, 18, and 22


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days, were compared. Figure 3 shows a region of the TIC detection of RYR

210

extracts comparing the results obtained from different fermentation periods (6 to 22

211

days). Several metabolites were measured in this region of the TIC, including

212

glutamine, trehalose, diglycerol, aminomalonic acid, fructose, L-malic acid, sorbitol,

213

threitol, citric acid, and mannose. As shown in Figure 3, the mean levels of some

214

known metabolites, such as maleimide, hydroxylamine, threitol, L-malic acid, and

215

mannose increased or decreased and then increased from 6 to 14 days, reaching

216

maximum levels in the fermentation of Monascus PHDS26 after 14 days. The

217

maximum levels of alanine, diglycerol, citric acid, and fructose were reached after

218

the fermentation of Monascus PHDS26 for 18 days. Moreover, the maximum levels

219

of

220

2,3-dihydroxybenz acid, glutamine, trehalose, and sorbitol were reached in the

221

fermentation of Monascus PHDS26 for 22 days. Additionally, the level of

222

2-hydroxybutanoic acid increased obviously from 6 to 22 days for M. aurantiacus Li

223

As3.4384 and remained unchanged from 6 to 22 days for Monascus PHDS26. The

224

contents of some metabolites, such as 2-hydroxybutanoic acid, phenylalanine,

225

2,3-dihydroxybenz acid, myristic acid, fructose, and sorbitol in the RYR produced by

226

Monascus PHDS26 were much lower than those in the RYR produced by the

227

wild-type strain. However, the levels of maleimide and trehalose were much higher

228

in the RYR produced by Monascus PHDS26, and the contents of threitol, and

229

L-malic

230

produced by the wild-type strain during the fermentation period from 10 to 22 days.

leucine,

aminomalonic

acid,

oxoproline,

phenylalanine,

asparagine,

acid were also much higher in Monascus PHDS26 than in the RYR



231

The contents of hydroxylamine, citric acid, and mannose in the RYR produced by

232

Monascus PHDS26 were also much higher than those in the RYR produced by the

233

wild-type strain during the fermentation period from 6 to 14 days. The levels of

234

L-malic

235

higher than those in the wild-type strain under normal fermentation conditions.

236

Analysis of data by PCA, PLS-DA, and OPLS-DA

acid, hydroxylamine, citric acid, and trehalose in Monascus PHDS26 were

237

To understand the overall differences in the metabolism of the RYR from the

238

wild-type strain and Monascus PHDS26, the acquired metabolomic data different

239

fermentation stages were analyzed using PCA, which was performed to discover

240

principal components for the evaluation the majority of differences in the data on

241

the basis of significantly altered metabolites. PCA has been proven to be useful for

242

discrimination and grouping in the analysis of chemical profiles of medicines and

243

food.28, 29 The total of PCA scores plot is shown in Figure 4(A), and the values of

244

R2X and Q2 were 0.609 and 0.477, respectively. The changes in metabolic profiles

245

in the RYR produced by M. aurantiacus Li As3.4384 and Monascus PHDS26 from 6

246

to 22 days are also shown in the 3D PCA scores plot graph (Figure 4(B)). As

247

shown in Figure 4, the metabolic profiles of the wild-type strain and Monascus

248

PHDS26 were changed dramatically during fermentation from 6 to 18 days, with

249

slight changes from 18 to 22 days. The PCA scores graph (R2X and Q2 were 0.79

250

and 0.468, respectively) of changes in the metabolic profiles of the wild-type strain

251

and Monascus PHDS26 are shown in Figure 4(C).

252

Next, we used PCA to compare the various metabolic components produced by


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the wild-type strain and Monascus PHDS26 during the same fermentation period.

254

As shown in Figure 5(A) and Figure S1–4(A), the values of R2X and Q2 were 0.624

255

and 0.453, 0.675 and 0.346, 0.826 and 0.548, 0.721 and 0.443, and 0.576 and

256

0.379, respectively, for differences at 6, 10, 14, 18, and 22 days of fermentation.

257

PCA score plots showed that the different RYR samples were distributed in two

258

separate areas, indicating significantly different metabolomes between the

259

wild-type and mutant Monascus strains at different fermentation stages.

260

The PLS-DA mold is widely performed for clustering and comparing nontargeted

261

metabolic profiling data of various sample groups.20,30 Thus, to identify correlations

262

of data (X) and other variables (Y, packet information), the normalized data were

263

analyzed by the partial least squares (PLS-DA) method using SIMCA-P software.

264

As shown in Figure 5(B and C) and Figure S1–4(B and C), the PLS-DA score plot

265

for the whole data set was used to categorize RYR samples from the wild-type

266

strain and Monascus PHDS26 into different fermentation stages (6, 10, 14, 18, and

267

22 days). The R2X, R2Y, and Q2 values of the PLS-DA score plot of the wild-type

268

strain and Monascus PHDS26 at the same fermentation stage were 0.623, 0.998,

269

and 0.987 for 6 days; 0.547, 0.998, and 0.981 for 10 days; 0.57, 0.999, and 0.986

270

for 14 days; 0.563, 0.999, and 0.987 for 18 days, and 0.62, 0.983, and 0.956 for 22

271

days, respectively. These results indicated that the PLS-DA models exhibited

272

differences between the different RYR samples from the wild-type strain and

273

Monascus PHDS26 in different fermentation periods.

274

To further compare the differences in metabolites closely associated with the



275

pksCT gene between the wild-type strain and Monascus PHDS26 at different

276

fermentation periods (6 to 22 days), we used the OPLS-DA model, a supervised

277

pattern recognition method that can facilitate the identification of some marker

278

metabolites responsible for maximum division by removing systematic variation

279

unrelated to grouping.21 As shown in Figure 5(D) and Figure S1–4(D), the

280

OPLS-DA model showed a clear separation between the RYR from the wild-type

281

strain and Monascus PHDS26 at the same fermentation time points (6 to 22 days)

282

according to the first component (OPLS1) in the score plots. The R2X, R2Y, and Q2

283

of the OPLS-DA score plots of the wild-type strain and Monascus PHDS26 at the

284

same fermentation time points were 0.623, 0.998, and 0.972 for 6 days; 0.547,

285

0.998, and 0.968 for 10 days; 0.57, 0.999, and 0.978 for 14 days; 0.563, 0.999, and

286

0.985 for 18 days; and 0.62, 0.983, and 0.957 for 22 days, respectively. These

287

results suggested that the OPLS-DA model was a reliable predictive method,

288

yielding R2Y and Q2 values close to 1.0, and the RYR samples of the wild-type

289

strain and Monascus PHDS26 were clearly separated into two groups.

290

Pathway analysis

291

To unravel the changes in metabolites in the metabolic network, we evaluated the

292

metabolic pathways of several identified metabolites in RYR extracts (Figure 6).

293

Some of the differential metabolites formed components in the glycolysis, acetyl-CoA,

294

amino acid, and TCA cycle metabolic pathways.

295

For glycolysis, the identified compounds included trehalose, myo-inositol,

296

phenylalanine, glucose, alanine, sorbitol, fructose, mannose, and leucine. A large


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amount of polyhydroxyl compounds, including cyclitols, sugars, and acyclic polyols,

298

are used by fungi to overcome stress conditions, such as cold, desiccation, heat, and

299

others.31 Trehalose is a nonreducing disaccharide and plays roles in protein and cell

300

membrane fluidity and stability and in maintenance of the lipid bilayer under stress

301

conditions.21,32 Trehalose has been shown to protect yeast pyrophosphatase under

302

exposure at 50°C much better than other sugars, including glucose, fructose, and

303

sucrose.31,33 In this study, the RYR was obtained by Monascus solid-fermentation in

304

the dry environment; the spores of these fungi are adapted to withstand desiccation.

305

As shown in Figure 3, the levels of trehalose produced by the wild-type strain and

306

pksCT-disrupted strain increased from 6 to 22 days. This could be explained by the

307

observation that trehalose was synthesized during the drying and ripening of the

308

spore and played a role in protection of membranes.

309

The metabolic flux moved to acetyl-CoA after glycolysis. Acetyl-CoA, a

310

biomass-derivable building block, can be indirectly transformed into malic acid and

311

asparagine and may be involved in fatty acid biosynthesis, followed by conversion

312

to myristic acid. Malic acid, another building block involved in metabolite synthesis,

313

can be produced by some fungal species, including M. araneosus, Schizophyllum

314

commune, Aspergillus flavus, and Zygosaccharomyces rouxii.34 The malic acid

315

biosynthesis pathway includes the following three routes: oxidation of citrate by the

316

TCA cycle; direct reduction of oxaloacetate; and production from acetyl-CoA via

317

glyoxylate metabolism.35 However, malic acid is primarily produced from

318

carboxylation of pyruvate during glucose metabolism, followed by reduction of



Page 16 of 38

319

oxaloacetate to malate.34 As shown in Figure 6, malic acid was produced from

320

acetyl-CoA via glyoxylate metabolism in the wild-type strain and Monascus

321

PHDS26. Acetyl-CoA is also essential for polyketide-dependent secondary

322

metabolite biosynthesis of Monascus pigments and citrinin and is formed through

323

tetraketide as a precursor intermediate, yielding polyketides.1 During cultivation of

324

the pksCT-disrupted M. aurantiacus strain Li AS3.4384 under rice, the production of

325

polyketide pigment was increased; however, citrinin production was inhibited. This

326

could be explained by the shifting of the metabolic flux of acetyl-CoA to the TCA

327

cycle, followed by switching to the biosynthetic polyketide pathway for the formation

328

of

329

2-hydroxybutanoic acid is formed from the TCA cycle via propanoyl-CoA. Several

330

compounds, including hydroxylamine, oxoproline, glutamate, and glutamine, are

331

produced from the TCA cycle via isocitrate and 2-oxoglutarate. Additionally,

332

pyroglutamic acid (oxoproline) is a γ-aminobutyric acid intermediate produced

333

during the γ-glutamyl cycle.

pigments. Citric

acid is

an intermediate in the TCA

cycle,35 and

334

In summary, the metabolic effects of the pksCT gene in M. aurantiacus Li

335

As3.4384 were monitored by GC-TOF-MS analysis. From this analysis, 85

336

compounds were identified, and 18 metabolites were found to be altered between

337

the wild-type strain and Monascus PHDS26 at different stages of solid-state

338

fermentation.

339

2,3-dihydroxybenz acid, myristic acid, fructose, allo-inositol, myo-insitol, and

340

sorbitol in the wild-type strain were higher than those in Monascus PHDS26 under

The

levels

of

2-hydroxybutanoic


acid,

phenylalanine,

Page 17 of 38


341

normal fermentation conditions (Figure 3).These metabolites forming components

342

within the glycolysis, acetyl-CoA, amino acid, and TCA cycle metabolic processes

343

were found to be altered between the wild-type strain and Monascus PHDS26 at

344

different stages of solid-state fermentation.

345

ACKNOWLEDGMENT

346

This project was financially supported by the National Natural Science Foundation of

347

China (No. 31160308 and No. 21165012). This work was also supported by the

348

Project of the Free-exploration Research Project of State Key Laboratory of Food

349

Science and Technology (SKLF-ZZB-201518).

350

Notes

351

The authors declare no competing financial interest.

352

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353

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Page 22 of 38

Page 23 of 38


465

Figure captions

466

Figure 1. (A) The color value of pigments and (B) citrinin content in the RYR

467

obtained from the wild-type strain and Monascus PHDS26 after different

468

fermentation times. 4384: wild-type strain of Monascus aurantiacus Li AS3.4384. P:

469

Monascus PHDS26 All the points of values are means of all data obtained in

470

triplicate analyses, and the relative standard deviation (RSD) range was from

471

1.57% to 7.41%. Some of points of the standard deviations are very small (within

472

the size of the points on the plots)

473

Figure 2. GC-TOF-MS total ion current chromatographs (n = 6) of RYR extracts

474

obtained from (A) the wild-type strain and (B) Monascus PHDS26 after fermentation

475

for 22 days.

476

Figure 3. Trajectory plots from GC-TOF-MS experiments representing the average

477

normalized relative peak areas of metabolites of RYR from different fermentation

478

stages for the wild-type strain and Monascus PHDS26. (All the points of values are

479

means of all data obtained by at least triplicate analyses, and the relative standard

480

deviation (RSD) range was from 1.0% to 5.5%)

481

Figure 4. (A) Total PCA score plot, (B) 3D PCA score plot graph, and (C) PCA

482

score graph of changes in metabolic profiles of the RYR from different fermentation

483

stages for the wild-type strain and Monascus PHDS26. 4384: wild-type strain of

484

Monascus aurantiacus Li AS3.4384. P: Monascus PHDS26.

485

Figure 5. (A) The PCA, (B) PLS-DA, and (C) OPLS-DA score plots of metabolic

486

differences in the RYR from the wild-type strain and Monascus PHDS26 after 22



487

days of fermentation. 4384: wild-type strain of Monascus aurantiacus Li AS3.4384.

488

P: Monascus PHDS26.

489

Figure 6. General biosynthetic pathways of some metabolites for the wild-type strain

490

and Monascus PHDS26 according to the KEGG database. The solid lines between

491

the compounds indicate a direct relationship between the compounds, and the dotted

492

lines represent indirect relationships.


Page 24 of 38

Page 25 of 38


Figure 1 8000

Color value units (U/g)

4384 P

(A)

6000

4000

2000

0 4

6

8

10 12 14 16 18 20 22 24 26 Fermentation time (d)

300 4384 P

Content of citrinin (µg/g)

250

(B)

200 150 100 50 0 4

6

8

10 12 14 16 18 20 22 24 26 Fermentation time (d)



Figure 2


Page 26 of 38

Page 27 of 38


Figure 3 Alanine

0.6

Leucine

As3.4384 PHDS26

As3.4384 PHDS26

0.06

0.5 0.4

0.04

0.3

0.02 0.2

0.00

0.1 4

6

8

10

12

14

16

18

20

22

24

4

6

8

10

Time (d)

2-hydroxybutanoic acid

14

16

18

20

22

24

Time (d)

3.0 2.5

12

8

As3.4384 PHDS26

As3.4384 PHDS26

L-malic acid

6

2.0 1.5

4

1.0

2 0.5

0

0.0 4

6

8

10

12

14

16

18

20

22

24

4

6

8

10

Time (d)

12

14

16

18

20

22

24

Time (d) 1.8

0.020

hydroxylamine

Oxoproline

As3.4384 PHDS26

0.016

1.5

0.012

1.2

0.008

As3.4384 PHDS26

0.9

0.004

0.6 0.000 4

6

8

10

12

14

16

18

20

22

24

0.3

Time (d)

4

6

8

10

12

14

16

18

20

22

24

22

24

Time (d)

0.015 Phenylalanine

As3.4384 PHDS26

0.012

As3.4384 PHDS26

Asparagine

0.009

0.006 0.009

0.003

0.006 0.003

0.000 4

6

8

10

12

14

16

Time (d)

18

20

22

24

4

6

8

10

12

14

16

18

Time (d)


20


0.25

As3.4384 PHDS26

0.03 2,3-dihydroxybenzoic acid

Page 28 of 38

Glutamine

As3.4384 PHDS26

0.20

0.02

0.15 0.10

0.01

0.05 0.00

0.00 4

6

8

10

12

14

16

18

20

22

24

4

6

8

10

12

Time (d)

Citric acid

16

18

20

22

24

Myristic Acid

0.0040

As3.4384 PHDS26

1.2

14

Time (d)

As3.4384 PHDS26

0.0032

0.8 0.0024

0.4

0.0016

0.0008

0.0 4

6

8

10

12

14

16

18

20

22

4

24

6

8

10

12

14

16

18

20

22

24

Time (d)

Time (d)

10 Fructose

Mannose

0.09

As3.4384 PHD26

8

0.06

6

As3.4384 PHDS26

4 0.03

2 0.00

0 4

6

8

10

12

14

16

18

20

22

24

4

6

8

10

Time (d)

12

14

16

18

20

22

24

Time (d)

0.012 Allo-inositol

0.05 Myo-inositol

As3.4384 PHDS26

0.009

As3.4384 PHDS26

0.04 0.03

0.006

0.02

0.003

0.01 0.00

0.000 4

6

8

10

12

14

16

18

20

22

4

24

6

8

10

12

14

16

18

20

22

24

Time (d)

Time (d)

2.5 Trehalose

Sorbitol

0.0020

As3.4384 PHDS26

As3.4384 PHDS26

2.0

0.0015

1.5

0.0010

1.0

0.0005

0.5

0.0000

0.0

4

6

8

10

12

14

16

Time (d)

18

20

22

24

4

6

8

10

12

14

16

Time (d)


18

20

22

24

Page 29 of 38


Figure 4




Page 30 of 38

Page 31 of 38


Figure 5




Page 32 of 38

Page 33 of 38


Figure 6 D-glucose-6-phosphate Phenylalanine

Shikimate

Trehalose Glucose

Sorbitol

Myo-inositol

Pyruvate

Alanine Leucine

Fructose

Mannose

Asparagine Hydroxylamine Malic acid

Acetyl-CoA

Fatty acid biosynthesis

Ammonia

Myristic acid

Oxoproline Glutamine

Citrate Propanoyl-CoA

Glutamate 2-oxoglutarate

Isocitrate

2-hydroxybutanoic acid



Page 34 of 38

Table 1 List of metabolites from RYR identified by GC-TOF-MS according to similarity score no less than 700. No.

Metabolite

Similarity

1

Oxamic acid

705

2

Methylmalonic acid

774

RT

Mass

No.

Metabolite

Similarity

RT

7.11

190

44

Glutamic acid

923

14.18

246

7.37

147

45

Phenylalanine

907

14.42

192

(min)

Mass

(min)

3

Alanine

935

7.54

116

46

Lyxose

709

14.92

217

4

Maleimide

868

7.58

154

47

Asparagine

915

14.96

231

5

Glycine

792

7.76

102

48

D-arabitol

811

15.39

217

6

Hydroxylamine

814

7.79

146

49

2,3-Dihydroxybenzoic acid

891

16.07

355

7

2-Butyne-1,4-diol

745

7.82

147

50

5-Methoxytryptamine

744

16.23

174

8

3-Hydroxypyridine

903

8.12

152

51

D-(glycerol 1-phosphate)

900

16.27

299

9

Methyl phosphate

791

8.43

241

52

Glucose-1-phosphate

806

16.38

217

712

16.48

297

4-Hydroxy-3-methoxybenz 10

2-Hydroxybutanoic acid

776

8.85

131

53

oic acid

11

Valine

902

8.92

144

54

Glutamine

931

16.57

156

12

Urea

882

9.35

189

55

Alizarin

733

16.84

369

13

Benzoic acid

923

9.48

179

56

β-Mannosylglycerate

770

16.94

204

14

Leucine

751

9.64

158

57

Citric acid

938

17.21

273

15

Phosphate

924

9.71

211

58

Ornithine

953

17.24

142

16

Isoleucine

884

9.92

158

59

Myristic acid

816

17.80

285

17

Proline

937

10.05

142

60

Fructose

901

17.96

103

18

Glycine

960

10.12

174

61

Mannose 1

889

18.43

79

19

Succinic acid

877

10.16

247

62

Mannose 2

943

18.82

319

20

2,3-Dihydroxypyridine

881

10.23

240

63

Tyrosine

802

19.31

179

21

D-glyceric acid

934

10.28

189

64

Allo-inositol

737

19.38

318

22

Oxalic acid

709

10.49

147

65

Myo-inositol 1

776

20.47

318

23

Fumaric acid

927

10.59

245

66

Palmitic acid

952

20.97

117

24

Serine

954

10.66

204

67

Myo-inositol 2

910

21.52

305

25

Mevalonic acid lactone

909

11.05

145

68

Galactose 1

839

22.09

319

26

2,3-Dihydroxypyridine

745

11.06

240

69

Galactose 2

824

22.18

103

27

β-alanine

843

11.6

248

70

Heptadecanoic acid

808

22.44

132

28

D-erythronolactone

844

11.67

247

71

Sorbitol

870

23.16

319

29

5-Methoxytryptamine

724

11.69

174

72

Oleic acid

960

23.38

339

30

5-Methylresorcinol

900

11.86

253

73

β-mannosylglycerate 1

911

23.59

132

31

Aminomalonic acid

806

12.11

218

74

β-mannosylglycerate 2

812

24.01

337

32

Citramalic acid

724

12.15

247

75

Linoleic acid

743

24.11

80

33

Glutamine

843

12.23

155

76

Gluconic lactone

752

24.48

204

34

L-malic acid

950

12.31

73

77

β-mannosylglycerate

720

24.97

204

35

Threitol 1

917

12.40

217

78

Sorbitol

833

25.33

319

36

Threitol 2

949

12.55

217

79

2-Monopalmitin

802

25.62

218


Page 35 of 38


4-Hydroxy-6-methyl-2-pyr 37

one

38

Aspartic acid

957

12.79

232

81

Sucrose

894

26.08

361

39

Oxoproline

914

12.96

156

82

Adenosine

882

26.16

236

40

4-Aminobutyric acid

923

13.01

174

83

Trehalose

930

26.90

361

3,6-Anhydro-D-galactose

704

13.30

247

84

Isomaltose

833

27.88

361

85

Galactinol

749

28.41

204

41

723

12.60

170

80

1-Monopalmitin

896

25.84

371

2-Hydroxy-3-isopropylbut 42

anedioic acid

941

13.60

275

43

Diglycerol

748

13.82

103



Page 36 of 38

Table 2 List of various metabolites from Monascus aurantiacus Li AS3.4384 and Monascus PHDS26 during the different fermentation stages from 6 to 22 days. Time

Metabolite

Similarity

RT (min)

Mass

VIP

p-Value

q-Value

Fold change

Hydroxylamine

814

7.79

146

1.381

0.021

0.033

0.207

2-Butyne-1,4-diol

745

7.82

147

2.106

0.011

0.022

7.792E+06

(days)

6

10

D-Erythronolactone

844

11.67

247

1.146

0.004

0.012

5.228

Diglycerol

748

13.82

103

2.888

0.000

0.004

0.000

2,3-Dihydroxybenzoic acid

891

16.07

355

2.347

0.036

0.046

3.806E+06

Glutamine

931

16.57

156

1.987

0.037

0.047

5.629

Myristic acid

816

17.80

285

1.280

0.001

0.004

4.034

Myo-inositol

776

20.47

318

2.070

0.006

0.015

8.747


720

24.97

204

1.413

0.007

0.017

14.858

Trehalose

930

26.90

361

2.519

0.006

0.014

0.003

Maleimide

868

7.58

154

2.461

0.001

0.004

0.000

Leucine

751

9.64

158

2.093

0.007

0.012

8.241E+07

D-Erythronolactone

844

11.67

247

1.067

0.000

0.003

7.139

Aminomalonic acid

806

12.11

218

1.281

0.021

0.022

3.177

Diglycerol

748

13.82

103

2.633

0.001

0.005

0.000

Phenylalanine

907

14.42

192

1.159

0.002

0.006

3.839

Asparagine

915

14.96

231

1.742

0.000

0.003

13.524

Glutamine

931

16.57

156

1.743

0.000

0.003

6.780

Fructose

901

17.96

103

2.022

0.042

0.035

150.846

Allo-inositol

737

19.38

318

1.316

0.026

0.025

1.409E+06


812

24.01

337

2.672

0.007

0.011

0.000

Trehalose

930

26.90

361

2.809

0.029

0.027

0.000

Maleimide

868

7.58

154

2.330

0.004

0.007

0.000

D-Erythronolactone

844

11.67

247

1.066

0.000

0.000

8.000

950

12.31

73

2.996

0.003

0.006

0.000

L-Malic

14

acid

Asparagine

915

14.96

231

1.022

0.008

0.012

2.944


812

24.01

337

2.542

0.000

0.000

0.000

Sorbitol

833

25.33

319

1.713

0.000

0.000

5.157E+05

Trehalose

930

26.90

361

2.783

0.010

0.014

0.000

Maleimide

868

7.58

154

1.989

0.000

0.001

0.111


776

8.85

131

1.152

0.000

0.000

364.884


Page 37 of 38


L-Malic

18

Threitol

950

12.31

73

2.807

0.000

0.002

0.000

917

12.40

217

2.439

0.001

0.002

0.000

Threitol

949

12.55

217

2.924

0.001

0.002

0.000


812

24.01

337

1.456

0.044

0.030

0.000

Trehalose

930

26.90

361

1.522

0.015

0.014

0.197

Alanine 1

935

7.54

116

1.480

0.036

0.024

0.412


776

8.85

131

16.208

0.000

0.000

815.109

950

12.31

73

4.816

0.001

0.002

0.000

Threitol

949

12.55

217

5.547

0.000

0.002

0.000

Oxoproline

914

12.96

156

5.308

0.002

0.004

0.458

Glutamine

931

16.57

156

1.010

0.003

0.004

0.237

Citric acid

938

17.21

273

4.357

0.000

0.002

2.385

Mannose

943

18.82

319

3.765

0.007

0.007

2.259

L-Malic

22

acid

acid



Graphic for manuscript

Metabolomics


Page 38 of 38

Metabolic Effects of the pksCT Gene on Monascus aurantiacus Li As3

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