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Food Research International 54 (2013) 487–494
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Food Research International
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Primary and secondary metabolites variation of soybean contaminatedwith Aspergillus sojae
K.M. Maria John a, Eun Sung Jung a, Sarah Lee a, Jong-Sang Kim b, Choong Hwan Lee a,⁎a Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Republic of Koreab School of Food Science and Biotechnology, Kyungpook National University, Daegu 702-701, Republic of Korea
⁎ Corresponding author. Tel.: +82 2 2049 6177; fax: +E-mail address: [email protected] (C.H. Lee).
0963-9969/$ – see front matter © 2013 Elsevier Ltd. All rihttp://dx.doi.org/10.1016/j.foodres.2013.07.045
a b s t r a c ta r t i c l e i n f o
Article history:Received 23 April 2013Accepted 15 July 2013Available online 22 July 2013
Keywords:Aspergillus sojaeGas chromatography–time of flight–massspectrometry (GC-TOF-MS)IsoflavonesPhytoalexinsUltra performance liquid chromatographyquadrupole time of flight mass spectrometry(UPLC-Q-TOF-MS)
Time-dependent primary and secondary metabolite changes of soybean contaminatedwith Aspergillus sojae andtheir associations were discussed. Partial least squares discriminant analysis showed that the patterns of fungusinfected soybeanwere clearly distinguished from untreated samples based on its time intervals. A. sojae dependson soybean for its carbon source resulting gradual decrease in the glucose, fructose and myo-inositol levels.The stimulation in L-phenylalanine by A. sojae increases the accumulation of naringenin from days 1 to 6, leadingto the changes in genistein pool. Even though the level of glucosides like daidzin, genistin and glycitin decreasedduring treatment, other isoflavones and coumestan levels enhanced. Due to the increase in glycinol, the resultingphytoalexins such as glyceollin I and glyceollin II augmented by fungal treatment. The changes in secondarymetabolites reflects in total phenolic content and because of the increase in glyceollin I, II and glyceofuran re-flect their radical scavenging capacity; A. sojae-mediated soybean registered a periodic increase in the radicalscavenging activity.
© 2013 Elsevier Ltd. All rights reserved.
From ancient times, food has been metabolically changed by pro-cessing via microbial fermentation. Soybean is well known for its highcontent of isoflavones, which show numerous health benefits, such asantioxidant potential (Kim, Song, Kwon, Kim, & Heo, 2008; Ng et al.,2011) and anti-diabetic activity (Kwon, Daily, Kim, & Park, 2010; Park,Kim, Kim, Kim, & Kim, 2012). Fermented soy food products are promi-nent in Asian countries, like China, Japan and Korea. Numerous researchfindings illustrate thatmetabolic changes in soy-based food is enhancedbymicrobial fermentation. Cheonggukjang (Baek et al., 2010; Kim et al.,2011; Park et al., 2010), Douche (Fan, Zhang, Chang, Saito, & Li, 2009)and Meju (Kang et al., 2011; Lee, Kim, et al., 2012) are some of thewell-known traditional Korean fermented soy food studied with regardto metabolic changes and antioxidant activities (Kim et al., 2008).Recently, fungus-mediated changes in secondary metabolite contentand the correlation of these changes with antioxidant activities weredocumented in soybean. Aspergillus oryzae (Jeon, Seo, Shin, & Lee,2012), Aspergillus sojae (Kim, Suh, Kim, Kang, et al., 2010; Kim, Suh,Kim, Park, et al., 2010; Ojokoh, Shi, Hujia, & Liang, 2012) and Rhizopusmicrospores (Simons, Vincken, Bohinm, et al., 2011; Simons, Vincken,Roidos, et al., 2011) were used to infect soybean seeds to produce met-abolic changes. Glyceollin, a phytoalexin present in soybean, has beenextensively studied with regard to changes in its level and antioxidant
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potential (Jeon et al., 2012; Kim, Suh, Kim, Park, et al., 2010), as wellas its estrogenic activity (Burow et al., 2001; Kim, Suh, Kim, Kang,et al., 2010). Moreover, antioxidant capacity of germinating soybean in-duced by A. oryzae was reported by Jeon et al., 2012.
Simons, Vincken, Bohinm, et al. (2011) screened for the presenceof prenylated isoflavonoids with a liquid chromatography/massspectrometry (LC/MS)-based screening method, in which they usedR. microspores-mediated metabolic changes on germinated soy seed.Boue, Carter, Ehrlich, and Cleveland (2000) studied the induction andaccumulation of phytoalexins in soybean cotyledon tissue, using 4 spe-cies of Aspergillus: A. sojae, A. oryzae, A. niger and A. flavus, but reportedonly glyceollin I, glyceollin II and glyceollin III and coumestrol changesduring treatment. Coumestan and pterocarpan changes varied basedon the fungus, indicating that the levels of metabolites will changebased on fungal type. The condition of the soybean used for fungal treat-ment is another point of concern. Previous studies report the use ofintact seed (Kim, Suh, Kim, Park, et al., 2010), germinating seeds (Jeonet al., 2012; Simons, Vincken, Bohinm, et al., 2011; Simons, Vincken,Roidos, et al., 2011) and half-broken seeds (Boue et al., 2000) for fungaltreatment. In all these studies, only secondary metabolites changes,particularly those relating to glyceollin, have been reported. Simons,Vincken, Roidos, et al. (2011) reported changes in 30 secondary compo-nents and 1 primary metabolite, viz., phenylalanine, influenced byR. microspores. Even though the primarymetabolite changes during fer-mentation of soy-based food has been reported (Kim et al., 2011), thechanges induced in soybean seeds by fungal treatment have not yetbeen compared. Such a study will help to understand the mechanism
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underlying metabolite changes during fungal treatment. Therefore,this study aimed to identify the variation in primary and secondarymetabolites of soybean contaminated with A. sojae. The role of primarymetabolites and their associations with secondary metabolite changesare also discussed.
2. Materials and methods
2.1. Chemicals and reagents
HPLC-grade water, methanol and acetonitrile were purchased fromBurdick and Jackson (Muskegon, MI, USA). All standards and otherchemicals, like 2,2′-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)diammonium salt (ABTS) and 1,1-diphenyl-2-picrylhydrazyl (DPPH),were obtained from Sigma Aldrich (St. Louis, MO, USA).
2.2. Sample preparation
Soybean (Aga No. 3) showing exceedingly high levels of isoflavoneswere obtained from Kyungpook National University Soy venture Co.,Ltd. (Daegu, South Korea) and were subjected to treat with A. sojae toevaluate metabolic changes during treatment. A. sojae cultures weregrown at 25 °C in the dark on potato dextrose agar (PDA) media fora period of 5 days. Inocula were prepared by harvesting fungi after5 days of incubation.
Dried soybeans were surface sterilized for 3 min with 70% ethanolprior to presoaked in sterile deionized water for 4–5 h. Soybean seedswere crumbled using a food homogenizer (Hanil, Bucheon, S. Korea)before fungal treatment under controlled treatment chamber. A. sojaespore suspension (10 μL) was evenly spread across the soybeans,followed by placing in a chamber at 26 °C in the dark for 7 days. Aftersterilization, the sampleswere stored at−20 °C; in themeantime, sam-ples were collected daily over the period of 7 days and were powderedand freeze-dried. The whole experiment for sample preparation wasrepeated three times andwere analyzed for primary and secondaryme-tabolite content.
2.3. Sample preparation for primary metabolite analysis
Lyophilized soybean samples (100 mg) alongwith the control (0 day,uninfected) were extracted with 1 mL of methanol:water:chloroform(2.5:1:1 v:v:v) containing norvaline as internal standard. The mixturewas placed in a Retsch ball mill at 30/s for a period of 5 min, followedby centrifugation at 5,000 rpm at 20 °C for 8 min. To a 600-μL aliquotof the supernatant was added 400 μL of water, and the sample wasthen vortexed. The resulting supernatant (400 μL) was transferred toa 1.5-mL Eppendorf tube andwas dried using a speed-vacuum followedby derivatization (Lee, Kim, et al., 2012).
2.4. Primary metabolite analysis by gas chromatography–time offlight–mass spectrometry (GC-TOF-MS)
Analysis of samples was performed using an Agilent GC-TOF-MSsystem (7890A) with an autosampler (Agilent 7693) equipped with aRtx-5MS capillary column (30 m length × 0.25 mm i.d. × 0.25 μMfilm thickness-Agilent J&W GC column). The injector temperature was250 °C, and the injection volume was 1 μL. The oven temperature pro-gram commenced from 80 °C for 2 min, followed by 300 °C from 2 to15 min, with a 10 °C/min hold, and finally a hold of 3 min, with a trans-fer line temperature of 250 °C. InMS, ionizationwas at−70 V (electronenergy) with a source temperature of 200 °C. The detector voltage was1450 V, and the mass range was set at 50–600 m/z with an acquisitionrate of 10 spectra per second.
2.5. Sample preparation for secondary metabolite analysis
Soybean samples (0.2 g) were extracted with 1.5 mL of 80% (v/v)methanol, followed by vigorous shaking for a period of 3 min in amixer mill. After 2 min of sonication, the extracts were centrifuged at10,000 rpm for 5 min. Supernatants were collected and dried underspeed vacuum. The dried extracts were again dissolved with 500 μL ofmethanol, followed by filtering through a sterile syringe filter (PTFE)with a 0.45-μm pore size, prior to analysis.
2.6. Ultra-performance liquid chromatography–quadrupole time offlight–mass spectrometry (UPLC-Q-TOF-MS) analysis
Secondary metabolite extracts of soybean samples were analyzedusing a Waters Micromass Q-TOF Premier UPLC-Q-TOF-MS systemwith UPLC Acquity System (Waters, Milford, MA, USA). Analysiswas performed employing an Acquity UPLC BEH C18 column(100 × 2.1 mm, Waters) with a particle size of 1.7 μm. The mobilephase consisted of water (A) and acetonitrile (B) with 0.1% formicacid (v/v). Five microliters of the sample was injected, and the flowrate was maintained at 0.3 mL/min. ESI was performed in the negative(−) and positive (+) ion mode within a range of 100–1,000 m/z.The operating parameters were as follows: ion source temperature,200 °C; cone gas flow, 50 L/h; desolvation gas flow, 600 L/h; capillaryvoltage, 2.8 kV; and cone voltage, up to 35 V.
2.7. Data processing
GC-TOF-MS raw data files were converted to computable documentformat (*.cdf) by the inbuilt data processing software of the AgilentGC system programs. Raw UPLC-Q-TOF data sets were converted to aNetCDFfile (*.cdf) format usingMassLynx software (version 4.1,WatersCorp). After obtaining the CDF format, the files were subjected to pre-processing, peak extraction, retention time correction and alignmentusing metAlign software package (http://www.metalign.nl). Afteranalysis, the resulting peak list was obtained as a .txt file, which waslater exported to Microsoft Excel (Microsoft, Redmond, WA, USA). TheExcel file contained the corrected peak retention time, peak area andcorresponding mass (m/z) data matrix for further analysis.
2.8. Multivariate analysis
Primary and secondary metabolites underwent multivariate sta-tistical analysis to identify those metabolites reflecting a differencebetween control and A. sojae-contaminated soybean samples, usingSIMCA-P software 12.0 (Umetrics, Umeå, Sweden). Partial least-squares discriminate analysis (PLS-DA) was carried out using auto-scaled and log-transformed data to identify the metabolites showedvariation between control and soybeans treated with fungus. Here thecontrol and A. sojae-contaminated samples served as X variables andthe components as Y variables for the analysis. Based on the variable im-portance in projection (VIP) values (N0.7) and a threshold of b0.05 forStudent's t-test of individual samples, the variable selection was madeand compared by box-and-whisker plots using STATISTICA (version7.0; StatSoft Inc., Tulsa, OK, USA). Annotation of peaks were based onstandard retention times,m/z, and existing references.
2.9. Determination of total polyphenol content (TPC) and antioxidantactivity
Differences in TPC between control and fungus-contaminated soy-bean samples were analyzed using a 96-well microplate reader. Twentymicroliters of sample from the secondary metabolite extraction wasadded to each well of the plate, followed by 100 μL of 0.2 N Folin–Ciocalteu's phenol reagent. After 3 min, 80 μL of saturated sodiumcarbonate solution was added and incubated at room temperature for
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1 h. The absorbance of each well was measured at 750 nm, and the re-sults were expressed in mg gallic acid equivalent per gram of soybean.
1,1-Diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activityof soybean contaminated with A. sojae was studied by adaptingthe procedure of Lee, Do, et al., 2012. The difference between theOD values of the blank and treated samples was used to calculatethe percentage scavenging activity. Total antioxidant capacity of soy-bean contaminated with A. sojae were studied in terms of time inter-vals using stable 2,2′-azinobis (3-thylbenzothiazoline-6-sulfonic acid)diammonium salt (ABTS) following the procedure of Lee, Do, et al.(2012). Results were analyzed statistically and the percentage of anti-oxidant potential was calculated based on the difference between theblank and treated samples, using the following calculation: scavenging(%) = [(Acontrol − Asample)/Acontrol] × 100, where A is absorbance; thecontrol contained only methanol and samples contained the soybeanextract.
3. Results and discussion
3.1. Primary metabolites analyzed by GC-TOF-MS
PLS-DA analysis of primary metabolites showed t 20.7% and t24.6% variance between control and treated samples for component 1and 2 (Fig. 1A). Analysis revealed 6 distinct clusters, in which controland soybean contaminatedwithA. sojaewere distinctly varied accordingto time intervals. The metabolites reflecting variation between controland A. sojae-treated samples were allocated to different clusters in
Fig. 1. PLS-DA analysis of primary (A) and secondary (B) metabolite of soybean con
PLS-DA analysis, as identified based on the VIP and p-values. The identi-fied metabolites were annotated based on their retention time incomparison with standards and their mass fragmentation (Table 1).A total of 12 primary metabolites, including 3 organic acids, 3 sugarsand sugar derivatives and 6 amino acids, showed significant variationamong the samples. Primary metabolite changes during A. sojae-treatedsoybean have not previously been studied, although primarymetabolitechanges in soy-based food products fermented bymicroorganisms havebeen described before (Kim et al., 2012; Lee, Kim, et al., 2012).
Malonic acid and malic acid levels were decreased when comparedto control, while levels of succinic acid increased with fungus treatedsamples (Fig. 2). In Meju, a fermented soy product, organic acid levelswere decreased and glucose content increased after fermentation (Lee,Kim, et al., 2012). In our study, the levels of organic acids decreasedunder fungus-infected samples, except for the levels of succinic acid.Succinic acid tends to be inhibited during stress conditions, but in ourstudy, the level increased; this is likely because proline, which is anosmoprotectant of succinic acid (Fang et al., 2011), was stimulatedduring fungal treatment. Sugars and sugar derivatives such as glucose,fructose and myo-inositol were decreased under A. sojae-contaminatedsoybean samples from the day one and periodically decreased through-out the experiment. Fungus depends on plant tissue for supply of carbonin the form of photosynthates. The mechanism of transport of thesesubstances during fungus–plant interaction has not yet been clearlyrevealed (Doidy et al., 2012). Based on previous findings, it was clearthat the uptake of sucrose and monosaccharides by fungus from plantsleads to the changes in the levels of their content (Doidy et al., 2012).
taminated with Aspergillus sojae analyzed by GC-TOF-MS and UPLC-Q-TOF-MS.
Table 1Details of primary metabolites changed during soybean contaminated with Aspergillus sojae analyzed by GC-TOF-MS.
S No. Name RTa MS/MSb VIPc p-valued Derivatizede MFf Ref g
Organic acid1 Malonic acid 06.44 147,73,66,59,99,133,117 0.9394 0.0000 TMS (BIS) C3H4O4 stdh
2 DL-Malic acid 09.72 73,147,133,101,117,87 0.9576 0.0000 TMS (X3) C4H6O5 std3 Succinic acid 07.74 147,73,247,129,172,116,86 1.0793 0.0000 TMS (X2) C4H6O4 std
Sugars and sugar derivatives4 Glucose 13.66 73,147,205,160,129,103,319,89 1.0475 0.0000 TMS (X5) C6H12O6 std5 Fructose 13.44 73,103,147,217,89,117,59 0.8915 0.0000 TMS (X4) C6H12O6 std6 Myo-inositol 15.20 73,147,217,191,305,129,103,59 0.9211 0.0000 TMS (X1) C6H12O6 std
Amino acid7 L-Phenylalanine 11.11 73,218,192,100,147,91,59,130 0.8188 0.0000 TMS (BIS) C9H11NO2 std8 L-Leucine 07.29 73,158,102,147,59,86,116 0.8463 0.0000 TMS (X2) C6H13NO2 std9 L-Tyrosine 13.88 73,218,100,147,179,59 0.9115 0.0000 TMS (X3) C9H11NO3 std10 L-Glutamic acid 11.02 73,246,128,147,84,56,100,230 0.9230 0.0000 TMS (X3) C5H9NO4 std11 L-Alanine 15.41 73,116,258,59,89,147,104 0.8355 0.0000 TMS (X2) C6H14N4O2 std12 L-Proline 07.59 73,142,117,59,133,103 0.9249 0.0001 TMS (BIS) C5H9NO2 std
aRetention time; bMS fragmentation; cvariable importance in projection (VIP N 0.80); dp b 0.05; enumber of hydrogen atoms derivatized; fmolecular formulae; greference; hstandards.
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The present study clearly indicated that there is no additional carbonsource supply in the treatment conditions; hence, the fungus dependsonly on soybean for its growth and development leads to the decreasein their levels.
L-Phenylalanine, L-tyrosine, L-alanine and L-glutamic acid contentswere increased among the treated samples. L-Phenylalanine is a well-
Fig. 2.Box andwhisker plot comparison of primarymetabolites significantly varied between con$Aspergillus sojae-contaminated soybean, numbers 1–7 represent the number of days soybean
known precursor of secondary metabolites and increased under fungus-contaminated conditions of soybean. Simons, Vincken, Roidos, et al.(2011) reported that L-phenylalanine content increased during fungaltreatment of germinating seeds. Our results agreed with this finding, asfungus-infected conditions resulted increased in L-phenylalanine levels.Except L-tyrosine, the level of L-phenylalanine, L-alanine and L-glutamic
trol and soybean contaminatedwith Aspergillus sojae respective of time intervals. *Control,samples elicited with A. sojae.
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acid contents decreased during the 7th day of treatment. L-Leucine andL-proline contents were increased from days 1 to 5 and the increasedid not much vary between control. In the same time, their levelswere significantly reduced during the 6th and 7th day of treatmentwhen compared to the control (Fig. 2). In Meju, L-tyrosine, L-glutamicacid, L-leucine and L-alanine levels have been shown to increase duringfermentation (Lee, Kim, et al., 2012). We observed the same trend forthese amino acids; similarly, levels of L-proline were comparativelyhigher during the initial period followed by decrease in their levelswith the 6th- and 7th-day samples. Proline is one of the stress markersthat is stimulated during abiotic stress conditions (Nayyar & Walia,2003). Even though the soybeans were treated with water to avoiddrying of samples, the level of moisture was low; hence, the aminoacid expression was high.
3.2. Secondary metabolite analysis by UPLC-Q-TOF-MS
In secondary metabolite analysis, the PLS-DA model showed 5.1%and 7.4% of variance between PLS-DA 1 and PLS-DA 2 (Fig. 1B). Thirdand forth components explained 4.1% (PLS-DA 3) and 38.3% (PLS-DA4), respectively. Six distinct clusters were obtained based on metabolicdifferences between control and A. sojae-infected samples accordingto time intervals. Close variation between fungal treated samples interms of time intervals was noticed and distinctly varied with controlbased on its metabolite content. The list of metabolites and relevant de-tails, like retention time, mass, VIP value and p-values, that contributedto variation between control and fungus treatment are presented inTable 2. A total of 20metabolites were identified as reflecting significantvariation between control and treated samples. Among them, 18metab-oliteswere annotated based on references and standards: 11 isoflavones,2 coumestans, 1 flavanone and 4 pterocarpans (Table 2).
Levels of naringenin, a flavanone found to be a precursor of thegenistein pool (Yu & McGonigle, 2005), increased during fungal treat-ment and influenced changes in the genistein pool. Malonyl glucoside(malonyl-daidzin andmalonyl-genistin) and glucoside (daidzin, genistinand glycitin) levels showed decreased with fungus elucidated soybeansamples. In the mean time, corresponding aglycon species (daidzein,genistein and glycitein)were increased based on time-dependentman-ner (Fig. 3). In soybean, glucosides are hydrolyzed into aglycones byglucosidases during fermentation, and it depends upon themicroorgan-isms used (Chun et al., 2007). On other hand, isoflavone changes duringsoybean germination were reported by Paucar-Menacho et al. (2010),
Table 2Particulars of secondary metabolites changed during soybean contaminated with Aspergillus so
No. RTa [M − H]−b [M + H]+c Calc. massd Err ppme MWf
1 4.89 253.0527 255.0655 254.0579 −2.05E−05 2542 5.49 269.0482 271.0624 270.0528 −1.71E−05 2703 5.06 283.0595 285.0757 284.0684 −3.14E−05 2844 9.31 299.2585 301.1510 3005 6.79 321.1134 323.1182 322.1205 −2.21E−05 3226 2.90 351.1234 253.2260 352.1310 −2.16E−05 3527 3.68 415.1098 417.1232 416.1107 −2.17E−06 4168 4.10 431.0976 433.1126 432.1056 −1.86E−05 4329 3.72 445.1117 446.1212 −2.13E−05 44610 4.11 501.0994 503.1129 502.1111 −2.34E−05 50211 3.59 517.2287 519.1102 518.1060 2.30E−04 51812 6.08 267.0672 268.0372 1.10E−04 26813 10.41 297.2368 299.0786 298.0477 6.40E−04 29814 10.22 271.0232 273.2080 272.0684 −1.70E−04 27215 10.5 271.0280 273.2080 272.0684 −1.50E−04 27216 7.27 337.1088 338.1154 −1.96E−05 33817 7.35 337.1070 339.1237 338.1154 −2.49E−05 33818 6.70 353.1038 355.2493 354.1103 −1.84E−05 35419 7.48 313.2430 31420 6.15 329.2395 330
aRetention time; bnegative mode; cpositive mode; dcalculated mass; eerror (ppm) between ca(VIP N 0.90); hp b 0.05; imolecular formulae, jreference: a—in-house library, b—standard, c—Si
stating that the glucosides reduced during germination and total isofla-vone content was increased. Glucosides were metabolized furtherresulted increase in the levels of 8-hydroxy glycitein, Aprenyl-daidzeinand Bprenyl-glycitein was observed. Shao et al. (2011) reported thatacidic hydrolysis increases the conversion of glucosides to aglyconesand prolonged reaction reduces the genistein content. Storage of soy-bean under different temperatures for extended periods was also re-ported for these isoflavone changes (Kim, Kim, Hahn, & Chung, 2005).
The identified two coumestan (coumestrol and isotrifoliol) and fourpterocarpans (glycinol, glyceollin I, glyceollin II and glyceofuran) con-tents were increased with time of contamination with fungus (Fig. 3).These pterocarpans in soybean served as phytoalexins and its stimula-tion during fungal infection was well documented. Daidzein andglycinol levels underwent changes during treatment; this resultedin modification of glyceollin levels, as previously reported (Banks& Dewick, 1983; Dhaubhadel, McGarvey, Williams, & Gijzen, 2003).According to Jeon et al. (2012) the total isoflavone content of soybeandecreased during germination, and fungal treatment resulted in an in-crease of coumestan and glyceollin I. But in our study, the level of gluco-sides decreased during fungal treatment, resulting in an increase inthe levels of aglycones and prenylated isoflavones. Due to this change,increases in the levels of coumestan and pterocarpans occurred.According to Simons, Vincken, Roidos, et al. (2011), pterocarpan levelsincreased in germinating soy seed induced by R. microspores. Further-more, in that study, coumestan levels were also significantly increasedduring germinating and in germinating seeds treated with fungus.According to Boue et al. (2000), the glyceollin I content was increasedafter A. sojae infection; these levels were followed by those of glyceollinII and glyceollin III. These results were matched with our findings, re-vealing that glyceollin I and II levels increased during fungal treatment.Two unidentified metabolites at the m/z of 313.2430 and 329.2395levels also increased during treatment.
3.3. TPC and antioxidant activity
The influence of fungal treatment on accumulation of total polyphe-nols was studied (Fig. 4A). The control samples registered the lowestphenolic content (0.238 mg/g) when compared with treated samples.A gradual increase in TPCwas observed with fungus-contaminated soy-bean samples, and themaximum increase was registered in the 6th day(0.497 mg/g) followed by a slight decrease (0.482 mg/g). Because of theincrease in naringenin, other secondary metabolites and 2 unidentified
jae analyzed by UPLC-Q-TOF-MS.
VIPg p-valueh Name MFi Class Ref j
2.5152 2.00E−04 Daidzein C15H10O4 Isoflavone a,b,c2.3466 3.00E−04 Genistein C15H10O5 Isoflavone a,b,c1.4610 3.20E−03 Glycitein C16H12O5 Isoflavone a,b,c2.2898 3.00E−04 8-Hydroxyglycitein Isoflavone a2.9216 2.00E−04 Aprenyl-daidzein C20H18O4 Isoflavone c0.8582 5.00E−04 Bprenyl-glycitein C21H20O5 Isoflavone c2.6605 2.00E−04 Daidzin C21H20O9 Isoflavone a,b,c2.5091 2.00E−04 Genistin C21H20O10 Isoflavone a,b,c0.9715 1.00E−04 Glycitin C22H22O10 Isoflavone a,b,c0.9423 1.60E−03 Malonyl-daidzin C24H22O12 Isoflavone a,c0.9423 3.00E−04 Malonyl-genistin C24H22O13 Isoflavone a,c2.4485 1.10E−03 Coumestrol C15H8O5 Coumestan a,c2.5299 5.00E−04 Isotrifoliol C16H10O6 Coumestan a,c2.4339 1.00E−04 Naringenin C15H12O5 Flavanone a,c1.2738 1.00E−04 Glycinol C15H12O5 Pterocarpan a,c1.1734 8.00E−04 Glyceollin I C20H18O5 Pterocarpan a,c2.9797 2.80E−03 Glyceollin II C20H18O5 Pterocarpan a,c1.1214 4.00E−04 Glyceofuran C20H18O6 Pterocarpan c2.6329 2.20E−03 Not identified1.4017 8.00E−04 Not identified
lculated mass and obtained mass; fmolecular weight; gvariable importance in projectionmons, Vincken, Roidos, et al. (2011).
Fig. 3.Box andwhisker plot comparison of secondarymetabolites contributing variation between control and soybean contaminatedwithAspergillus sojae. *Control, $A. sojae-contaminatedsoybean, numbers 1–7 represent the number of days soybean samples treated with A. sojae.
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metabolites resulted in an elevated TPC. Due to the changes in isofla-vone and total polyphenol content of fungus-contaminated soybeandirectly influences the radical scavenging potential (Fig. 4B). DPPHradical scavenging activity was markedly high in soybeans treated byfungus (34.14–62.59%) and showed an increasing trend. The level of
ABTS scavenging potential of control and fungus-treated soybean sam-ples were also compared (Fig. 4B). Here again, the scavenging potentialof fungus treated soybean showed an increasing trend (65.21–92.56%).Correlation between soy phytoalexins levels and antioxidant contenthas been previously reported by Boue et al. (2000). According to Jeon
Fig. 4. Comparison of total phenolic content (mg/g) and radical scavenging activity (%)of soybean contaminated with Aspergillus sojae (A, total polyphenol content; B, radicalscavenging activity) *Control, $A. sojae-contaminated soybean, numbers 1–7 representthe number of days soybean samples treated with A. sojae.
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et al. (2012), the phytoalexin glyceollin provides high radical scavengingactivity. Moreover, glyceollin is known tomediate anti-hormonal effectsvia the estrogen receptor (Burow et al., 2001). Our results also indicatedthat radical scavenging activity was increased during fungus treatment.Most of the identified metabolites and TPC reduced slightly during the7th day of treatment, which was reflected in the radical scavenging ac-tivity of ABTS.
Comparing the control and soybean contaminated with A. sojae aclear variation was observed based on PLS-DA analysis (Fig. 1). Par-ticularly, the amino acid content such as L-phenylalanine, L-tyrosine,L-glutamic acid, L-alanine and L-proline highly varied from the controland day 1 of infection. The same trend was observed with succinicacid and secondary metabolites like glyciollin II, glyceofuran andunidentifiedmetabolites. Where as with all other metabolites a gradualincrease (aglycones, coumestan and pterocarpans) or gradual decrease(malonyl glucoside, glucoside and sugars) when compared to controlwas observed (Figs. 2 and 3). Secondarymetabolites from the shikimatepathway, in which L-glutamic acid, L-tyrosine and L-phenylalanineitself are products, directly correlatewith secondarymetabolite produc-tion (Dewick, 2002; Maeda & Dudareva, 2012). Our results also demon-strate that the levels of these metabolites increased under fungus-contaminated conditions, leading to changes in secondary metabolitecontent. L-Proline is another amino acid that is increased during stressconditions. Here, the levels of this amino acid were also increasedunder fungus-contaminated conditions; hence, L-proline is a water-stress–related amino acid. L-Proline is the osmoprotectant of succinicacid; thus, L-proline levels underlie the increase in succinic acid contentduring treatment (Fang et al., 2011). The levels of sugar and sugar deriv-atives were decreased under fungal treatment because of the causeof fungus growth, thereby leading to a decrease in the sugar and sugarderivatives (Doidy et al., 2012). Besides these primary metabolites,
the roles of the other identified metabolites during fungal treatmentwere not clear. Isotope studies may be useful to elucidate the correla-tion between primary and secondary metabolites in terms of fungus-contaminated conditions.
Our results made it clear that the soybean contaminated withA. sojae induces primary and secondary metabolite changes over vari-ous time periods. The roles of sugar and sugar derivatives and a fewamino acids correlated with secondary metabolite biosynthesis duringthe treatment. Even though the glucoside content decreased underfungus-infected conditions, TPC increased due to the elevation on othersecondary compounds. The increase in these phytochemicals resultedin high antioxidant potential when compared to that in control samples.Moreover, themethod of fungal infection described heremay be of prac-tical use in the food industry to develop nutraceutical productswith highantioxidant capacity.
This study was supported by the National Research Foundationof Korea (grant nos. MEST 2010-0019306 and 2010-0027204), andby Bio-industry Technology Development Program (No. 110132-3)Republic of Korea.
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