Dynamic changes of differential metabolites and key metabolic pathways of Gastrodia elata Blume during fermentation

ABSTRACT The fermentation of Gastrodia elata Blume (GEB) is an extremely complex process, and abundant metabolites are produced, which have a great influence on the quality and flavor. The non-targeted metabolomics method was used to analyze the comprehensive changes of differential metabolites and key metabolic pathways in the fermentation process of GEB. After fermented for 60 d, carbohydrate, organic acid, peptide, and nucleic acid metabolites were 79.77%, 12.91%, 4.39% and 2.79%, respectively. Compared with unfermented GEB, the carbohydrates decreased obviously, while organic acid, peptide and nucleic acid metabolites increased. A total of 32 metabolites were identified as the differential metabolites (VIP>1 and P < .05). Subsequently, metabolic pathways of differential metabolites were analyzed and 14 key metabolic pathways were found, among which methyl butyrate metabolic pathway, TCA cycle, alanine, aspartic acid and glutamate metabolism had greater influences on the GEB fermentation. Finally, the metabolic pathways network was constructed preliminarily. This work could be helpful to understand the differential metabolites and establish a preliminary foundation for further elucidation of the flavor formation mechanism during GEB fermentation.


Introduction
Gastrodia elata Blume (GEB), a saprophytic, perennial herb in the Orchidaceae family, is native to several Asian countries, including China, Korea and Japan. [1] In China, it is an excellent plant resource that has the concomitant function of both medicine and foodstuff. [2] However, much of the current research has focused on medicine. In Shennong's Classic of Materia Medica, the first herbal monograph in Chinese history, written during the Han Dynasty, GEB was described as a "top grade medicine" that can rejuvenate the body, enhance health, and extend life without toxicity, and can be used long term without harm. [3] For centuries, it has been used to treat a variety of diseases such as depression, epilepsy, neurasthenia, headache, ischemia, vertigo and hemiplegia. [4][5][6] It also has the effect of enhancing memory, protecting the brain and preventing aging, and can effectively improve the decline in learning and memory ability and dementia caused by Alzheimer disease (AD). [1,7] The various pharmacodynamic functions of GEB are derived from its abundant active ingredients. Up to now, over 81 ingredients have been isolated, including phenolics, polysaccharides, organic acids, sterols and various trace elements. Among them, GEB polysaccharides, p-hydroxybenzyl alcohol and vanillin are the main active ingredients. [3] CONTACT Chunzhi Xie xiecz0611@foxmail.com College of Food and Biotechnology Engineering, Xuzhou University of Technology, Xuzhou, China; Juan Yang yangxz2002@126.com The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guiyang, China *Both the authors contributed equally to this article.
Fermentation is a very complicated biochemistry reaction process. Fermentation process not only provide important sources of nutrients, but also have great potential in maintaining health and preventing diseases along with the addition of desirable flavor, and texture. [8,9] Our previous study found that, fermentation can not only improve the smelly smell of horse urine, but also increased the content of functional components including p-hydroxybenzyl alcohol, γ-aminobutyric acid and p-hydroxybenzaldehyde in GEB. Among them, p-hydroxybenzyl alcohol and p-hydroxybenzaldehyde increased by 1.8 and 50 times. Compared with unfermented GEB, the total antioxidant capacity, DPPH free radical scavenging capacity and SOD enzyme activity increased by 2.6 times, 0.4 times and 1.35 times, respectively (data unpublished). Therefore, it is necessary to ferment GEB and study the differential metabolites and key metabolic pathways during the fermentation.
Due to the complexity of the fermentation process, it is difficult to explore the factors and mechanisms affecting the nutrition and flavor of fermented food by conventional research methods. Metabolomics is commonly used to measure the biochemical products of cell processes downstream of genomic, transcriptomic, and proteomic systems. [10] It could qualitatively and quantitatively analyze all metabolites in the biological body, and find the relative relationship between metabolites and target substances changes, which is very suitable for studying the complex and multifactorial biochemical pathways of substrates, nutrients and flavor substances that may be altered in fermentation process. So far, several high-throughput analytical techniques have been used for metabolite profiling. [11] Among these techniques, gas chromatography-mass spectrometry (GC-MS) can provide a relatively high reproducibility, good sensitivity, high resolution, and high-throughput analysis, which can be used for analyzing the primary metabolism products, including amino acids, organic acids, carbohydrates and fatty acids. [12,13] Metabolomics is widely applied in fermented food, [14] such as wine, [15,16] soy sauce, [17] vinegar [18] and cheonggukjang. [19] In this study, untargeted metabolomics based on Gas Chromatography-Time of Flight-Mass Spectrometry (GC-TOF-MS) was used to reveal the dynamic changes of metabolites during the GEB fermentation process. The differential metabolites were identified by OPLS-DA and key metabolic pathways were analyzed subsequently. The results will be helpful to understand the differential metabolites and establish a preliminary foundation for further elucidation of the flavor formation mechanism during the fermentation process of GEB.

Sample preparations
Fresh GEB was cleaned, mashed and loaded into a fermentation jar in turn. Then, sample was ripened by adding boiling water at a weight ratio of 1:2. Subsequently, white sugar (10%, w/w) was added and stirred for 15 min to dissolve completely. The cellulase (0.02%, w/w) was added when the temperature dropped to 50 ~ 60°C. The mixed starter composed of Lactobacillus plantarum, Acetobacter pasteurianus and Saccharomyces cerevisiae at a ratio of 1:1:1 (w/w/w). When the temperature dropped to 30 ~ 40°C, the mixed starter of 0.03% (w/w) was added. After anaerobic fermentation of 17 d, the sample was fermented aerobically for another 20 d and then after-ripened until 60 d. The samples were collected at six time points, including 0 d (D0), 7 d (D7), 17d (D17), 27 d (D27), 47 d (47) and 60 d (D60). The samples were taken at each time point and mixed evenly. Three biological replicates were performed. About 50 mL of each mixed sample was sterile sealed and stored in a refrigerator at −80°C before lyophilization.

Metabolites extraction
The sample of 5 mL was lyophilized by freeze dryer (Scientz-10 N, Ningbo Scientz Biotechnology Co., Ltd., Ningbo, China), and then dissolved in 5 mL methanol (−20°C). The sample solution was mixed by vortex oscillator (QL-901, Qilinbeier Instrument Manufacturing Co., Ltd., Nantong, China) for 1 min and centrifuged for 10 min at 12000 rpm (4°C). Subsequently, 100 μL supernatant was mixed with 400 µL methanol, and eddy oscillated for 30s. After adding 60 μL isotopic alanine (10 mM) and 60 μL of ninetecarbonate (0.2 mg/mL) as internal standard, the mixed solution was eddy oscillated for 60s and centrifuged for 10 min at 12000 rpm (4°C). The supernatant of 500 µL was lyophilized, and then mixed with 60 μL methoxy solution. The reactions were performed at 37°C for 2 h. Finally, 60 μL BSTFA reagent (containing 1% trimethylchlorosilane) was added and left to react for 90 min at 37°C. After centrifugation at 12000 rpm for 5 min, 90 ~ 100 μL of supernatant was added into the test flask for subsequent analysis.

GC-TOF-MS analysis
The GC-TOF-MS analysis was performed by an Agilent 7890 gas chromatography system (Agilent, Atlanta, GA) coupled with a Pegasus HT time-of-flight mass spectrometer (LECO Corporation, St. Joseph, MI, USA). It consisted of a HP-5 MS capillary column coated with 5% phenyl crosslinked with 95% dimethylpolysiloxane (30 m × 250 µm inner diameter, 0.25 µm film thickness; Agilent J&W Scientific, Folsom, CA, USA). The constant current helium gas at 1 mL/min was used to separate the derivatized metabolites. The sample of 1 µL was injected through an automatic sampler with a split ratio of 20:1. The injection temperature was set to 280°C. The interface was set to 150°C. The ion source was adjusted to 230°C. The initial temperature of the heating program was 60°C for 2 min. Then the temperature rose to 300°C at the rate of 10°C/min and stayed at 300°C for 5 min. A full-scan method ranging from 35 to 750 (m/z) was used for mass spectrometry. [20]

Statistical analysis of metabolomic data
The obtained raw data was converted to NetCDF format (XCMS input file format) by G1701 MSD ChemStation software (Version E.02.00.493). XCMS package of R software (Version 3.3.2) was used to perform the peak identification, peak filtration and peak alignment. The data matrix including mass-to -charge ratio (m/z), retention time (RT), retention index (RI) and peak area (intensity) were obtained. The metabolites were identified by searching the National Institute of Standards and Technology commercial database (NIST) and Wiley Registry metabolome database. The alkane retention index was used to further metabolites qualitative according to the Golm Metabolome Database (GMD) (http://gmd.mpimp-golm.mpg.de). The data including the compound name, peak area, retention time, similarity to metabolites in the database were imported into Microsoft Excel for subsequent analysis. The metabolic pathways were searched by Kyoto Encyclopedia of Genes and Genomes (KEGG) online databases. To clearly understand the changes in metabolite during fermentation, OPLS-DA was used to analyze the metabolic patterns by MetaboAnalystR package (Version 3.0). Based on the OPLS-DA model, the variable importance in the projection (VIP) values of metabolites were calculated and the differential metabolites (VIP>1, P < .05) were identified. [16] Results and discussion

Dynamics changes of metabolites during fermentation
The changes of metabolites during fermentation have important effects on food flavor and nutrition. [21] As shown in Figure 1, carbohydrates accounted for the highest proportion, followed by organic acids and polypeptides. In unfermented GEB, the carbohydrate, organic acid, peptide, and nucleic acid metabolites were 92.41%, 7.25%, 0.22% and 0.03%, respectively. With the fermentation, the proportion of carbohydrates decreased and the proportion of organic acids increased. After fermentation of 27 d, the proportion of carbohydrates began to rise, while the proportion of organic acids decreased. The reason for this phenomenon may be that the fermentation is anaerobic in the early stage and aerobic in the later stage. When fermented for 60 d, the carbohydrate, organic acid, peptide, and nucleic acid metabolites were 79.77%, 12.91%, 4.39% and 2.79%, respectively. Compared with unfermented GEB, the carbohydrates decreased obviously, while organic acid, peptide and nucleic acid metabolites increased. For that phenomenon, the possible reasons were speculated as follows. In the initial stage of fermentation, abundant nutrients and vigorous microbial metabolism resulted in a rapid carbohydrate loss. In the late stage of fermentation, microorganisms died in large quantities and cells release DNA due to autolysis.

Analysis of the differential metabolites
Based on the results of OPLS-DA, a total of 32 differential metabolites (VIP>1, P < .05) were identified during the fermentation (Figure 3 and Table 1). Among them, 14 organic acids, 5 amino acids, 5 carbohydrates, 4 sugar alcohols and 4 other metabolites were included. Compared with D0, 30 metabolites were up-regulated, while only 2 metabolites were down-regulated at D7. Compared with D27, 16 metabolites were up-regulated and 16 metabolites were down-regulated at D47. Compared with D47, there were 22 up-regulated and 10 down-regulated metabolites at D60. Organic acids are the secondary metabolites of yeast microbial fermentation and the final products of alkane compounds through oxidation. [24] There were 14 organic acids in the differential metabolites, among which γ-hydroxybutanoic acid, ribonic acid, malic acid and pyruvic acid were dominant. The γ-hydroxybutanoic acid and ribonic acidwere the highest at 60 d, accounting for 24.76% and 14.68% of the acids, respectively. In addition, pyruvic acid accounted for 23.91% at 7 d and malic acid accounted for 68.49% at 17 d. Among them, malic acid is generally produced by aspergillus, penicillium and yeast through biochemical reactions. It is also an intermediate product of glycolysis and tricarboxylic acid cycle. [25] Pyruvic acid is an important small molecular organic acid, and can be  used as a food additive to improve human body function. [26] The pyruvic acid reached the maximum at D7 and then decreased accompanied by an increase in malic acid. It is supposed that, pyruvic acid is oxidized and decarboxylated to form acetyl CoA, and then acetyl CoA condenses with oxaloacetic acid to form malic acid through the tricarboxylic acid cycle. [27] There are 5 amino acids in differential metabolites, including aspartic acid, phenylalanine, valine, leucine and methionine. As fermentation progressed, the proportion of the 5 amino acids first increased and then decreased. The relative contents of aspartic acid, phenylalanine, leucine and methionine were the highest at D27, while valine was the highest at D47. Amino acids not only serve as the building blocks of proteins, but also can enhance the flavor characteristics of food. [28] Amino acids are an important component from a nutritional point of view, especially essential amino acids, which the human body cannot synthesize them and that must be supplied from the diet. [29] Five carbohydrates, including sucrose, glucose-6-phosphate, isomaltose, fucose and rhamnose, were classified as differential metabolites. Under anaerobic conditions, carbohydrates provide energy for microbial growth through glycolysis. [30] Sucrose decreased from 45.21% (D0) to 0.05% (D60). Sucrose was the main carbohydrates and degraded into glucose and fructose during metabolism. Then, glucose and fructose can be catalyzed by fructose kinase and hexokinase respectively, and phosphorylated into glucose 6-phosphate. [31]  A total of 4 sugar alcohols were identified, including sorbitol, erythritol, ribitol and xylitol. The sugar alcohols increased gradually during the fermentation process, and reached the highest at D47, and then decreased. Therein, sorbitol and erythritol increased from 0.01%, 0.22% (D0) to 0.71%, 0.93% (D47), respectively. Sorbitol is one of the sources of fructose 1,6-bisphosphate and can be converted from glucoses by aldose reductase. [32] Erythritol can not only shorten the fermentation period, but also effectively reduce the odor of alcohol and sensory stimulation. [33]
As shown in Figure 4, 14 key metabolic pathways mainly involved carbohydrates, organic acids and amino acids. The sucrose involved in the metabolic pathway of starch and sucrose metabolism and galactose metabolism. The content of sucrose in unfermented GEB was the highest, and decreased rapidly after fermentation for 7 d, which may be ascribed to the increase of enzymes produced by microorganism metabolism. Sucrose was degraded to glucose and fructose by invertases or hydrolases. Subsequently, glucose-1-phosphate was produced by phosphorylation of glucose and was converted by the glycolysis/gluconeogenesis pathway to glucose-6-phosphate, which then entered the pentose phosphate pathway. [16] As all other hexoses can easily be converted to glucose-6-phosphate to enter the glycolysis, the metabolic pathway for galactose is more complex. [34] Galactose involved in starch and sucrose metabolism and galactose metabolism. Galactose can be oxidized to galactose-1-phosphate, which is then transformed into uridine diphosphogalactose-galactose by galactose-1-phosphate uridyltransferase, and finally converted to glucose. [35] Glucose was finally transformed into pyruvate, which participated in the TCA cycle by acetyl-CoA and produced various organic acids, [16] such as fumaric, succinic acid, cis-aconitic acid and malic acid. Phenylalanine can be converted to glutamic acid and tyrosine catalyzed by phenylalanine-4-hydroxylase through phenylalanine metabolism. Phenylalanine, glutamic acid and 4-hydroxybutanoic acid were finally converted to succinic acid and participated in the TCA cycle. Aspartic acid can generate pyruvic acid and fumaric acid, and also participated in the TCA cycle.

Conclusion
The non-targeted metabolomics method was used to comprehensively analyze the changes of differential metabolites and key metabolic pathways in the fermentation process of GEB. A total of 32 metabolites were identified as the differential metabolites (VIP>1 and P < .05) by OPLS-DA, including 14 organic acids, 5 amino acids, 5 carbohydrates, 4 sugar alcohols and 4 other metabolites. The 14 key metabolic pathways mainly involved carbohydrates, organic acids and amino acids. However, the nontargeted metabolomics is the relative quantification of compounds. It is necessary to quantify and verify the key differential metabolites. In addition, the metabolic pathways network was constructed preliminarily. But the intermediate metabolites and substrates that involved in the differential metabolite pathways have not been studied explicitly. Therefore, further work will focus on the flavor formation mechanism during GEB fermentation by integrative analysis of the genomics, proteomics and metabolomics technology.

Disclosure statement
No potential conflict of interest was reported by the author(s).