African Journal of
Plant Science

  • Abbreviation: Afr. J. Plant Sci.
  • Language: English
  • ISSN: 1996-0824
  • DOI: 10.5897/AJPS
  • Start Year: 2007
  • Published Articles: 780

Full Length Research Paper

Identification and relative quantitative comparison of compounds in bottle gourds [Lagenaria siceraria (Mol.) Standl.]

Zhaohui Zhang
  • Zhaohui Zhang
  • Shanghai Academy of Agricultural Sciences, Zhuanghang Comprehensive Experiment Station, Shanghai, 201403, China.
  • Google Scholar
Xuan Du
  • Xuan Du
  • The Protected Horticulture Institute, Shanghai Academy of Agricultural Sciences, Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai, 201403, China.
  • Google Scholar
Na Liu
  • Na Liu
  • The Protected Horticulture Institute, Shanghai Academy of Agricultural Sciences, Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai, 201403, China.
  • Google Scholar
Chunhong Chen
  • Chunhong Chen
  • Shanghai Academy of Agricultural Sciences, Zhuanghang Comprehensive Experiment Station, Shanghai, 201403, China.
  • Google Scholar


  •  Received: 25 March 2022
  •  Accepted: 30 June 2022
  •  Published: 31 July 2022

 ABSTRACT

To study the diversity and cultivar-specific of phytochemicals in bottle gourd, Gas chromatography-mass spectrometry (GC-MS)-based untargeted metabolomics method was used to analyze the metabolic profiles of two groups of bottle gourd cultivars exhibiting different tastes and flavors: fresh and slightly bitter (BBGs) / fragrant and sweet (SBG). A total of 155 metabolites (16 differential metabolites and 139 non-differential metabolites) were identified/annotated. The relative contents of 16 differential metabolites in BBGs are all higher than that in SBGs. The differential metabolites profiles of the two different groups were distinguished using principal component analysis (PCA), and the main differential metabolic pathways between the BBG and the SBG included those relating to plant nutrition and energy metabolism. This study provides new insights into the differences in metabolite profiles among bottle gourds with different tastes and flavors.

 

Key words: Gas chromatography-mass spectrometry (GC-MS), metabolomics, bottle gourd, taste, flavor.


 INTRODUCTION

Bottle gourd [Lagenaria siceraria (Mol.) Standl.] (2n = 2x = 22), also known as long calabash, is an annual cucurbit crop, and its tender fruit is cooked as a vegetable because of its unique flavor (Wu et al., 2017). The bottle gourd contains essential nutrients, such as protein, vitamin, pectin, fibers, etc (Zhang et al., 2020). It is planted in Asia and Africa, as well as it is used in crafts, decorations, and medicinal (Xu et al., 2011). It can be used as the rootstock of other Cucurbitaceae, such as watermelon (Sari, 2003).

 

The fruits of different gourd varieties have different shapes, sizes and flavors (Wu et al., 2017; Zhang et al., 2020). These phenotypic differences are caused by gene transcription regulation (Zhang et al., 2020), and differences at gene level led to differences at metabolic level. There are few studies on the differences of metabolism of different gourd fruits.

 

Sugars, amino acids (Kader et al., 1978), organic acids (Robert and Franco, 2018), vitamins (Kafkas et al., 2006) components of plant organisms, but also the ratio of their contents to their contents affects the taste and flavor of edible parts of plants, such as fruits (Hobson and Bedford, 2015). The tastes that human beings can perceive are sweet, sour, bitter, salty and delicious. Generally speaking, the taste of the fruit is caused by its organic components. And traditionally, sugar content determines the sweetness of the fruit. However, with the continuous discovery of new organic compounds and technological progress, sugar is not the only substance with a sweet taste. For example, thaumatin is a kind of protein with a sweeter taste than sucrose (Healey et al., 2017). In addition, the content of organic acids and their derivatives in fruit pulp has important dietary considerations, which affect the taste of fruit and the applicability of processing into various fruit products in some cases. It can be seen that whether the fruit is sweet or sour has a great relationship with the proportion of sweet and sour substances in the fruit. The taste of tomato was the first concern and a balanced sugar-acid ratio was preferred in cherry tomatoes (Hobson and Bedford, 2015). Cucurbita pepo contains the toxic tetracyclic triterpenoid compound cucurbitacin, which is the cause of bitterness and toxicity (Verma and Jaiswal, 2015). The factors affecting fruit umami are free amino acids, nucleotides (monophosphates of inosinate or guanylate, inosine 5′-monophosphate, and guanosine-5′monophosphate), short peptides and organic acids (Kurihara, 2009; Wu et al., 2017). Previous studies have found that, free glutamate (Glu) was found to have the most significant association with umami taste, suggesting that free Glu was the main umami-conferring ingredient of bottle gourd (Wu et al., 2017).

 

Although the above-mentioned research shows that free glucose is an important factor affecting the fresh taste of bottle gourd fruit, there are many factors involved in the taste of the fruit, and the metabolomics analysis of bottle gourd with different tastes can reveal the metabolic reasons for this difference. However, there is no report on the metabolism of bottle gourd fruit taste. Therefore, in order to find out the difference of metabolism between two kinds of bottle gourd fruits with different tastes and provide a theoretical basis for quality breeding of bottle gourd, we collected and analyzed the metabonomic information of slightly bitter bottle gourd (BBG) and sweet bottle gourd (SBG).


 MATERIALS AND METHODS

Plant materials and chemicals

 

Five bottle gourd cultivars were cultivated in a randomized field plot according to standard agricultural practices in a field at the Zhuanghang comprehensive experimental station (E 121°28, N 30°57′) of the Shanghai Academy of Agriculture Sciences in 2019. Two bitter-tasted bottle gourd cv. BG27 and BG32, and three sweet-tasted bottle gourd cv. BG33, BG56, and BG58 were cultivated. They were sowed in March and planted in April. The photon flux density was range 650~850 W.m-2. The temperature and relative humidity of the cultivation environment were about 10~25°C and 50~70%, respectively. The fruits were selected 14 days after simultaneous pollination, having a length of 20-35 cm and a diameter of 4.2-5.8 cm. Three marketable immature fruits were harvested for each cultivar and homogenized with equal weight to form a sample. All samples were stored at −80°C until analysis.

 

Chromatographic grade methanol and chloroform were purchased from Merck Chemicals (Germany). All of the chemicals, such as pyridine, methoxyamine hydrochloride, and N, O-bis (trimethylsilyl) trifluoroacetamide (BSTFA) containing 1% trimethylchlorosilane (TMCS), and the reference standards used in the study were purchased from Sigma-Aldrich (St. Louis, MO, USA). L-2-Chlorophenylalanine at 3.1 mg ml−1 in water was prepared and used as internal standards (IS).

 

Sample preparation and extraction for metabolomic analysis

 

An aliquot of 1 g bottle gourd sample and 10 ml methanol-water (7:3 v/v) were mixed for metabolite extraction at 60 Hz for 180 s on a tissuelyzer. Further, the mixtures were ultrasonically extracted for 40 min and stored at 4°C for 24 h. After centrifugation at 12,000 × g for 10 min, 400 μl of the supernatant was spiked with 4 μl of the IS, L-2-chlorophenylalanine, and dried completely in a vacuum concentrator. An aliquot of 80 μl methoxyamine hydrochloride (15 mg/ml in pyridine) was added to the residue and incubated at 37°C for 90 min for methoxyamination. Subsequently, the sample was trimethylsilylated by adding 80 μl BSTFA (with 1% TMCS) and incubated at 70°C for 60 min. The derivatized samples were cooled to room temperature before being analyzed (Jaeger, 2008).

 

GC/MS conditions

 

For each cultivar, three biological replicates were independently analyzed. In total, 15 samples were randomly analyzed to reduce analysis bias. Under the adjusted initial pressure, all samples were analyzed in randomized order by a 7890B gas chromatography coupled with a 5977B mass spectrometer (Agilent Inc., CA, USA). A DB-5ms capillary column (30 m ×250 μm inner diameter, 0.25 μm film thickness; J&W Scientific, Folsom, CA, USA) was used to separate compounds. The injector port was heated to 280°C and injections (1 μl) were performed with a split ratio of 5:1. Helium (purity?99.999%) was used as the carrier gas at a constant flow of approximately 1 ml/min. The column temperature was held at 60°C for 1 min, then increased to 300°C at 5°C/min, and held for 11 minutes. The total run time was 60 min. The temperatures of the transfer line, ion source and quadruple were maintained at 280, 230 and 150°C, respectively. Electron impact ionization mass spectra were recorded with an ionization energy of 70 eV and EM voltage of 970 V. Mass spectra were scanned from 33 to 600 amu in total ion chromatogram mode after a solvent delay of 6.5 min (Weckwerth et al., 2004).

 

Data processing and statistical analysis

 

Metabolite identification was performed by the National Institute of Standards and Technology (NIST) mass spectral library (2017) in MSD ChemStation (version E.02.02.1431; Agilent Inc., CA, USA). The raw data acquired by Agilent GC/MS were imported into ChromaTOF (version 4.50.8.0; Leco Corporation, MI, USA) in NetCDF format. ChromaTOF could automatically compute baseline, find peaks above a signal to noise (S/N) of 100:1, deconvolute (identify overlapped peaks), integrate using specific masses, and align the same compound in different samples. The resulting three-dimensional dataset comprised sample information, peak retention time, and peak intensity. Some artificial peaks generated by noise, column bleed, and by-products in the silylation procedure were removed manually from the dataset. The resulting data were normalized to the area of the IS (L-2-chlorophenylalanine) for further statistical analysis. L-2-chlorophenylalanine was also utilized to assess process variability during sample preparation and data processing (Weckwerth et al., 2004).

 

For differential metabolites, we usually screen through VIP, such as screening out variables with VIP greater than 1.5, then calculating p-value, further screening out variables less than 0.05, and then observing these folds change was 2.0. Metabolites have been used for principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) by R (www.r-project.org/) to study metabolite cultivars-specific accumulation according to the described (Wang et al., 2018).

 

To further illustrate the biological significance associated with bitter/sweet taste, we used the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to link differential metabolites to metabolic pathways in the SBGs compared with those in BBGs. Enrichment P-values were computed from a hypergeometric distribution. A p-value < 0.01 was selected to reduce the false discovery rate. The software used for drawing and data analysis was GraphPad Prism 7 (GraphPad Software Inc., La Jolla, CA, USA).


 RESULTS

Differences in morphologies among the fruits of the five bottle gourd cultivars

 

These bottle-gourd cultivars were divided into two groups based on their taste and flavor. One group had two members, BG27 and BG32, which tasted lightly bitter (BBGs). The other had three ones, BG33, BG56, and BG58, which tasted thick sweet (SBGs). Though the two groups of bottle gourd cultivars were planted simultaneously and grown in the same field and under the same conditions, not only the taste of the fruits was distinct, but the shape and peel color also appeared different. The shape of BG27 was like Corbel. BG32 had a round body with a long neck. The shape of BG33 was like a long gun. Both BG56 and BG58 were like Cylinders. The peel color of the five bottle gourd cultivars belonged to a different degree of green (Figure 1).

 

 

 

 

 

Figure 1. Five bottle gourd cultivars.

Source: Authors

 

 

Metabolic profiling

 

As is mentioned above, a few differences in tastes and shape between the two groups of bottle gourd cultivars existed. While as we all know the soluble solids content and acid-base titration method, which were referred to rough judgments, sometimes cannot exactly respond to the real ones. To make sure the differences in total contents and also in composition, we applied a newly developed GC–MS-based widely untargeted metabolomics method (German et al., 2005). A total of 155 metabolites (16 differential metabolites and 139 non-differential metabolites) were identified/annotated (Table 1; Supplementary Table S1). The results of all detected metabolites are shown in an Excel file (Supplementary S1), which indicates the differences in the metabolite levels of the five cultivars. To gain more insight into the metabolic differences between BBG and SBG, differential metabolite screening was performed among all 155 metabolites identified/annotated according to the fold-change and the variables determined to be important in the projection (VIP) scores. A fold-change score ≥2 or ≤0.5 among the metabolites with a VIP value>1 was used as an identification criterion. The screening results have been illustrated using volcano plots (Figure 2A). The overall situation of relative expression of 16 differential metabolites is shown by heat map visualization (Figure 2B).

 

 

 

 

 

 

 

 

 

 

 

Table 1. The relative content of 24 differential metabolites.

 

Compounds

The relative content

BG27

BG32

BG33

BG56

BG58

2-αMannobiose

459.87

352.78

363.16

87.38

91.00

73.70

32.42

55.09

28.14

50.26

44.90

30.92

47.34

47.05

49.27

3-αMannobiose

200.69

186.40

148.10

198.84

172.34

162.70

156.40

131.58

123.52

123.09

118.84

120.39

84.18

82.79

86.01

4-Aminobutanoic acid

181.59

109.49

107.54

133.09

73.87

69.59

110.05

60.91

67.38

27.37

23.73

27.72

13.04

21.09

22.60

Butanedioic acid

52.94

49.10

42.59

123.90

56.07

55.39

38.38

37.90

29.60

45.74

39.86

39.58

19.05

28.10

25.49

D-(+)-Talose (anti)

2632.77

2300.85

1993.33

2134.59

2021.71

2060.50

2166.18

1754.75

1894.00

2105.26

1900.43

1890.99

1761.29

2029.89

1807.46

D-(+)-Talose (syn)

7807.93

6821.00

5884.16

5030.32

7568.70

5960.85

6328.20

5023.23

5057.73

5979.91

5299.36

5760.43

4924.17

5206.41

5036.75

D-(+)-Trehalose

677.82

448.57

508.57

132.17

139.13

136.96

41.22

57.68

35.15

65.88

48.78

41.60

58.44

69.41

71.15

D-Fructose

5640.66

5483.04

4405.97

5300.11

4915.11

4897.13

4886.84

3969.96

3903.63

5037.39

4518.13

4525.44

4148.26

4649.78

4209.55

Ethylene glycol

12.94

24.95

22.21

24.03

23.21

24.80

10.76

9.37

9.72

12.14

10.94

10.56

9.80

10.91

10.53

L-Aspartic acid

559.20

370.52

220.61

164.57

132.99

72.69

134.96

181.02

141.14

9.93

60.20

51.33

35.85

0.00

46.32

Myo-Inositol

1279.23

1005.94

1024.71

906.18

757.21

681.04

849.35

770.92

689.59

641.46

548.95

547.97

467.68

524.90

493.87

Oxalic acid

71.85

66.80

66.44

129.19

108.93

114.91

63.32

74.12

73.01

75.13

65.83

72.50

72.18

91.65

67.18

Phosphoric acid

74.15

45.08

63.60

56.06

42.03

38.87

34.72

32.06

21.90

20.32

18.38

18.03

14.55

15.43

18.34

Propane

129.42

86.12

112.60

23.26

26.66

23.45

8.93

18.78

10.16

15.29

13.94

10.66

18.62

16.91

18.57

Propanedioic acid

1995.95

1175.56

1681.84

1022.72

945.90

914.86

512.12

401.78

422.33

462.35

399.81

381.46

405.02

558.61

475.54

Shikimic acid

578.15

244.78

325.48

163.80

164.65

246.22

162.64

81.80

93.43

141.68

128.51

136.30

109.35

112.45

145.47

Ethylene

434.32

347.13

432.77

74.59

54.23

45.20

17.64

26.94

14.05

24.84

20.02

14.63

21.05

24.90

20.79

 

 

Source: Authors

 

 

 

 

Figure 2. The volcano plot (A) shows the differential metabolite expression levels between BBGs and SBGs. Blue dots represent downregulated differentially expressed metabolites; red spots represented upregulated differentially expressed metabolites; and gray represented non-differentially expressed metabolites. Heat map visualization (B) shows the overall situation of relative expression of 16 differential metabolites.

Source: Authors

 

 

 

We detect 6 different metabolites of saccharides, namely, 2α- mannobiose, 3α-mannobiose, D-(+)-talose (anti), D-(+)-talose (syn), D-(+)-trehalose, D-fructose (Figure 3A–F). The MNB content of two kinds of group BBGs is obviously higher than that of SBGs group (Figure 3A and B). The contents of D-tal(anti) and D-tal (syn) in a gourd with different taste and flavor are distinct, and their content in BBGs are higher than SBGs (Figure 3C and D). The content of trehalose in BBGs is higher than SBGs (Figure 3E). In these battle gourds of this study, in BBGs, the relative content of D-fru is 5176 and 5037, respectively, whereas in SBGs, it is 4252, 4693, and 4335 (Table 1, Figure 3F).

 

 

 

 

 

Figure 3. Saccharides content in the five bottle gourd cultivars. Data represent mean values ± SE of three independent measurements. * and ** indicate a significant difference from that of BG27 at p< 0.05 and p < 0.01, respectively, by the Dunnett’s test.

Source: Authors

 

 

 

In this research, there are two kinds of amino acids that are different in the metabolism of two groups of gourds with different flavors, namely 4-aminobutanoic acid and L-aspartic acid. The relative content of 4-aminobutanoic acid or L-Asp in BBGs is significantly more than the group SBGs (Figure 4A and B).

 

 

 

 

Figure 4. Amino acids content in the five bottle gourd cultivars. Data represent mean values ± SE of three independent measurements. * and ** indicate a significant difference from that of BG27 at p < 0.05 and p< 0.01, respectively, by the Dunnett’s test.

Source: Authors

 

 

 

In this study, it was found that there were significant differences in the contents of butanedioic acid, phosphoric acid, propanedioic acid and shikimic acid in two different tastes and flavors of bottle gourd (Figure 5A-D). The content of these four acids in BBG cultivars is higher than that in SBG cultivars (Figure 5A-D).

 

 

 

 

Figure 5. Organic acids and inorganic acidscontent in the five bottle gourd cultivars. Data represent mean values ± SE of three independent measurements. * and ** indicate a significant difference from that of BG27 at p < 0.05 and p < 0.01, respectively, by the Dunnett’s test.

Source: Authors

 

 

 

In addition to the above-mentioned metabolites, there are significant differences in the content of various bottle gourds between the two groups, and there are also four metabolites, namely myo-Inositol, ethylene, ethylene glycol and propane. Similarly, BBGs have significantly larger levels of these four substances than SBGs (Figure 6A-D).

 

 

 

 

 

 

 

 

Figure 6. Other metabolites in the five bottle gourd cultivars. Data represent mean values ± SE of three independent measurements ** indicate a significant difference from that of BG27 at p< 0.01, by the Dunnett’s test.

Source: Authors

 

 

 

 

Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal differences in the metabolite profiles

 

In the PCA plot (Figure 7A), the duplicate samples were grouped together, indicating that the duplicate samples had similar metabolic profiles and that the entire analysis was stable and repeatable. Pairwise comparisons are carried out between BBG and SBG to identify the metabolites that are responsible for the taste differences. PLS-DA models are used to generate pairwise comparisons of the metabolite contributions. The predictability (Q2) and goodness of fit (R2X, R2Y) of the PLS-DA models were observed in the comparison between BBG and SBG (Q2=0.767, R2X=0.723, R2Y=0.981; Figure 7B).

 

 

 

 

 

Figure 7. PCA and PLS-DA of the relative differences in secondary metabolites in BBGs and SBGs cultivars. BG27: Jan-27, Feb-27, Mar-7; BG32: Jan-32, Feb-32, Mar-32; BG33: Jan-33, Feb-33, Mar-33; BG56: Jan-56, Feb-56, Mar-56; BG58: Jan-58, Feb-58, Mar-58.

Source: Authors

 

 

 

 

Differential metabolic pathways between BBG and SBG

 

To obtain detailed pathway information, all metabolites and the differential metabolites were mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/) (Figure 8A and B). In the mapping of KEGG, there were 12 different metabolites involved in metabolisms, 1 involved in genetic information processing and 1 involved in environmental information processing (Figure 8A). The differential metabolites were mainly involved in beta-alanine metabolism, indole alkaloid biosynthesis, galactose metabolism, ect (Figure 8B).

 

 

 

 

 

Figure 8. Enrichment of the differential metabolites to distinct KEGG pathways.

Source: Authors


 DISCUSSION

Bottle gourd fruit varies in shape, size and flavor (Wu et al., 2017; Zhang et al., 2020). Previous studies have revealed the root causes of these differences at the genome and transcriptome levels (Konan et al., 2020). However, there is no research on the difference of metabonomics of gourd with different tastes. The metabolites of different gourd fruits are different. The metabolism of fruits with different tastes was different. GC-MS-based untargeted metabolomics of two groups of bottle gourd accessions yielded 16 differential metabolites. In previous reports, sugars were the  main factor affecting sweetness (Cameron, 2011). The sweetness of the saccharides differs. Furthermore, the sweetness of some saccharides varies with the solution concentration, while the sweetness of others does not (Cameron, 2011). Mannobiose, composed of D-mannose units, is a nondigestible disaccharide and rich in Cucurbitaceae crops. MNB can modulate intestinal and systemic immune responses in mice and prevent LPS-induced immune suppression as well as directly stimulate innate immune mechanisms in vitro as a TLR4 agonist (Kovacs-Nolan et al., 2013). Therefore, the difference in MNB contained in bottle gourds with different tastes will play a certain role in cultivating bottle gourds with high MNB content. D-talose is a variety of rare monosaccharides, different from the exception of isomers such as D-glucose and D-fructose, which exist in great abundance and showed considerable growth inhibition upon the nematode (Sakoguchi et al., 2016). Trehalose is a nonreducing disaccharide with two glucose units linked in an α, α-1,1 configuration, widespread in plant kingdoms and its phosphorylation forms play a vital role in the integration of plant metabolism and development (Richards et al., 2002). Evidence showed that exogenously-supplied trehalose can make winter wheat better cope with heat stress (Luo et al., 2018). D-fru is one of the most common and also the sweetest monosaccharide, but it is not the substance with the highest sweetness in nature. For example, protein thaumatin, first isolated from the katemfe fruit, Thaumatococcus daniellii, is 1600 times sweeter than sucrose on a weight basis (Wel and Loeve, 1972). Therefore, it is probably not only sugar that determines the strong sweet taste of the gourd.

 

4-Aminobutanoic acid was also known as the name of gamma-Aminobutyric acid (GABA), was a non-proteinogenic amino acid and was first isolated from potato tubers in 1949 (Ramesh et al., 2017). In plants, GABA acts as a signal substance to regulate plant growth, development and response to stress. In mammals, its action has been mainly described in the nervous system, where GABA receptors regulate brain function and development. L-aspartic acid is one of the 20 types of amino acids that make up a protein's structural unit (Akcay et al., 2012). Free amino acids have been found as the main umami ingredients in many vegetables, especially free glutamate and free aspartate are the two main umami ingredients (Zhang et al., 2013). Previous data has shown that free glutamic acid is the major factor affecting umami taste in bottle gourds (Wu et al., 2017). However, our data found that there were significant differences in aspartic acid metabolism, but there was no significant difference in glutamic acid content in different flavors of bottle gourd.

 

Besides sugars and amino acids, sour ingredients have an important influence on the flavor of fruits. Whether the taste of the fruit is sour or sweet depends on the ratio of sweet substances to sour substances. Shikimic acid is widely found in higher plants, with high content in the fruit of Illicium verum, which has an anti-tumor effect and is also an important synthetic raw material of Tamiflu, an anti-influenza drug (Coleman, 2005). Myo-Inositol belongs to B vitamins and is the precursor of various biological functional compounds containing inositol phosphate and lipid. Inositol and phosphatidylinositol play a key role in many metabolic pathways, and if affected, they will have adverse effects on human health (Benvenga and Antonelli, 2016). Ethylene is a plant hormone that can regulate fruit ripening. Ethylene glycol and Propane also exist in the flesh of bottle gourd, but their unique roles are not clear.

 

Multivariate statistics are used to further assess the differences in metabolic profiles among the two gourd groups. PCA is one of the most widely used chemometric tools to reveal the internal structure of several variables by a few principal components and extract and rationalize information from any multivariate description of a biological system (Park et al., 2013). The results showed that the samples from the two cultivars were grouped into two areas in the plot, indicating that different flavors had relatively distinct metabolic profiles. Especially, the dots of a gourd with sweet taste are more concentrated than the dots of a gourd with slightly bitter taste, which indicates that the metabolic regulation leading to the sweet taste of the gourd is more consistent, while the metabolic regulation related to bitter taste is more complex. The plot suggests that the differences in metabolic profiles detected in our study correlated with fruit flavors. In the PLS-DA models, BBGs are clearly separated from SBGs, indicating major distinctions in the metabolic profiles between the different fruit tastes of bottle guards. For BG32 and SBGs, there was some overlap in PCA (Figure 7A), but a clear difference was obtained in the PLS-DA score plots (Figure 7B), indicating that the BG32 with a slightly bitter taste could be grouped from the guard with a sweet taste.

 

The roles of carbohydrates, and their metabolism, in plants have a vast influence on both plant growth and development. During the storage of coffee beans in the pod, the change of flavor is related to the metabolism of sugars and free amino acids in coffee beans (Hinneh et al., 2018). Previous evidence has found that, free glutamate content was a key factor conferring umami taste in the bottle gourd (Wu et al., 2017).


 CONCLUSION

However, in the study, we found that there were differences in metabolic substances and metabolic pathways between the two different tastes of bottle gourd, which lay the foundation to discover the metabolic architecture of the sweety/bitter taste in bottle gourd and facilitate the breeding of new varieties with better taste and quality.


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interests.


 ACKNOWLEDGMENTS

This research was funded by the Shanghai Science and Technology Agriculture Promotion Project (2022-02-08-00-12-F01105). Thanks to the Instrumental analysis center, Shanghai Jiao Tong University for its instrument service.Thanks to the Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences for providing the germplasm materials for the bottle gourd. Thanks to Guangzhou Gene Denovo Biotechnology Co., Ltd. for its Omicsmart cloud analysis platform.



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