MECHANISMS OF COIX SEED COMPOSITIONS IN THE TREATMENT OF SPLEEN DEFICIENCY AND WET DAMPNESS ZHENG.

BACKGROUND: Coix seed has the functions of fortifying the spleen and inhibiting the dampness. However, it remains unclear which Coix seed compositions is responsible for these functions. Previous investigations have revealed that the main compositions of Coix seed are proteins, polysaccharides, oils and starches. The objectives of this study are to explore which is the most effective compositions in fortifying the spleen and examine how Coix seed works in regulating the water transport on the spleen deficiency and wet dampness (SDWD) rat model.
MATERIALS AND METHODS: The rats used were divided into (i) control group, (ii) model group, (iii) decoction group, (iv) protein group, (v) polysaccharide group, (vi) oil group and (vii) starch group. The urine volume, the drinking volume and the water loading index in each group were calculated. Agilent 8*60K array was used for microarray-based gene expression analysis. The differential mRNAs related to the transport activity were screened. qRT-PCR was used to validate the mRNA microarray.
RESULTS: The results demonstrated that all treatment groups could decrease the dampness of SDWD rats. mRNA microarray had significant effect on the protein group and the polysaccharide group in regulating the water transport, among which the most significant mRNA was Fabp6, Slc51a, Slc51b, Slc11a2, Slc4a10 and AQP3 respectively.
CONCLUSION: The compositions of proteins and polysaccharides had the most significant effect in regulating the water transport of SDWD rat model. The contributing mRNA focused on Fabp, Slc and AQP family.

Introduction

Spleen deficiency and wet dampness ZHENG (SDWD) is one of the major syndromes of traditional Chinese medicine (TCM) (Han et al., 2015). It is due to the improper diet, over fatigue, dysfunction of spleen and stomach and disorder of water transport. Clinically SDWD ZHENG is frequently treated with fortifying the spleen and inhibiting the dampness methods (Yang et al., 2016), among which Coix seed is one of the commonly-used drug (You-Ming et al., 2011).

Microarray-based gene expression analysis can be used to diagnose ZHENG, it also helps to explain the molecular mechanism of ZHENG and evaluate the drug effect in terms of changes of mRNA level (Liu et al., 2014). It has been applied to explain the nature of ZHENG and provide certain scientific evidence for ZHENG in TCM(Liu et al., 2016).

This study establishes SDWD rat model by high fat diet and exhaustive swimming. The model has been approved by National Patent Office (No.ZL201410072183.8). The model rats demonstrate obvious symptoms such as slow action and gastrointestinal dysfunction, which are consistent with the clinical manifestations of SDWD ZHENG (Cui et al., 2016, Jie et al., 2015).

Coix seed (Coixlacroyma-jobi L. var. ma-yuenStapf, adlay), used both as both as food and drug in TCM, has the function of fortifying the spleen and inhibiting the dampness. However, the effective component and the mechanism in fortifying the spleen and inhibiting the dampness remains obscure. In this study we establishes SDWD rat model to find the effective component of Coix seed and to clarify its mechanism.

Materials and Methods

Animal model preparation

70 Wistar rats (140-160 g, 35 male and 35 female) were obtained from Weitong Lihua Experiment Animals Inc. Ltd. (Beijing, China, No. SCXK 11400700067086). It took 8 weeks to establish 60 SDWD rat models by high fat diet and exhaustive swimming (GAO et al., 2014, Han et al., 2015). 10 rats in the control group had freedom of movement and received no intervention.

Coix seed components

The components such as proteins, polysaccharides, oils and starches were extracted individually from Coix seed, according to the methods in our previous reports (Cui et al., 2015; Cui et al., 2014; Wu et al., 2015).

Administration mode and dosage

All the model rats were divided into six groups randomly based on their weight and gender. 6.25 g•kg-1 d-1 Coix seed was administrated to the decoction group based on the Chinese Pharmacopoeia (2010 Edition). 0.2813 g•kg-1 d-1 proteins component (equal to the proteins in the 6.25 g•kg-1 d-1 Coix seed) was administrated to the protein group. So did 0.9113 g•kg-1 d-1 polysaccharides component in the polysaccharide group, 0.2875 g•kg-1 d-1 oils component in the oil group, 1.7981 g•kg-1 d-1 starches component in the starch group. And the model group was given normal saline. Drug was administered by gavage once a day for 14 days, 1 mL / 100 g.

Detection index

After 2 weeks’ treatment, the urine volume and the drinking volume were observed for 24 hours. Body mass was recorded 0h, 1h, 2h, 4h, and 6h after intraperitoneal injection with normal saline(10% of body weight). Then the water loading index was calculated following the method described by Saito and Pedersen (Pedersen et al., 2003, Saito et al., 2001). The higher the water loading index was, the worse the water transport activity of the body was.

At the end of the experiment, 3 rats in each group were randomly selected for execution. Jejunum tissues from each rat were dissected and the total RNA was extracted for mixture in equal ratio. The mixed samples were subjected to microarray-based gene expression analysis (Agilent Rat Gene Expression Version 6.5, 8*60K, Shanghai Quanmai Biological Technology Co., Ltd., Design ID: 028279). The criteria for screening differentially expressed mRNA was Fold Change>2 (FC>2). Gene-ontology (GO) was performed for differential mRNA according to the enrichment analysis by EMBL-EBI (http://www.ebi.ac.uk/services). The differential mRNAs related to transport activity in molecular function of GO terms were analyzed.

Quantitative real-time PCR (qRT-PCR)

qRT-PCR was used to validate the mRNA microarray. Total RNA was reverse-transcribed to cDNA with a reverse transcription kit (PrimerScript RT reagent Kit, Takara, USA). GAPDH was used as a reference. mRNA expression was detected by real-time PCR instrument (ABI, USA, 9700HT real-time system).ΔΔCt was calculated for relative quantification of mRNA expression.

Statistical Analysis

The urine volume, the drinking volume, and the water loading index were expressed as mean±SD. One-way analysis of variance (ANOVA) and least significant difference (LSD-t) were used to compare the difference between groups. All the data were analyzed by IBM SPSS21.0 software. P<0.05 was accepted as statistical significance.

Differential mRNA related to transporter activity in molecular function was screened out from 7 groups. SIMCA-P 11.0 software was applied in the principal component analysis (PCA). The criteria for determining the number of principal components (PC) was cumulative contribution rate >80%.

Results

Covariance analysis of the urine volume in each group

The drinking volume affected the urine volume. After the influence of drinking was excluded, the urine volume in model group was lower than that of the control group (P<0.01); the urine volume in the treatment groups was higher than that of the model group, especially that of the protein group (P<0.05). (Table 1, Figure 1).

Table 1

Covariance analysis of urine volume in each group

Source	Type III Sum of	Squares	df	Mean Square	F	Sig.
Drinking		21.943	1	21.943	4.683	.034
Urine		130.285	6	21.714	4.634	.001

Figure 1

Covariance analyses of drinking volume and urine volume in each group.

The difference of the drinking volume was significant among groups (P<0.05); the urine volume decreased significantly in the model group (P<0.01); the urine volume increased significantly in the treatment groups (P<0.05).

Comparison of the water loading index in the treatment groups

The water loading index of model group (0.58) was higher than that of the control group (P<0.01). The water loading index of the treatment groups decreased compared with that of the model group (0.43, 0.41, 0.52, 0.49, 0.54) (P<0.01). (Figure 2).

Figure 2

Comparison of water loading index in each group

The difference of the water lodading index was significant among groups (P<0.05). Data was mean±SD(n=10 rats per group). *P<0.05, **P<0.01 vs control group. #P<0.05, ##P<0.01 vs model group.

PCA analysis of differential mRNA related to transport activity

The model group and the control group could be clearly distinguished in the 3D chart. Bi-plot analysis showed: (1) There were three principal components (contribution rate of PC1, PC2, PC3=61.7%, 15.3%, 13%); (2) The decoction group, the protein group and the polysaccharide group could improve the transport activity mRNA expression significantly, while the oil group had little effect (Figure 3).

Figure 3

PCA analysis of mRNA microarrays.

The analysis of the normalized coefficient of PC1-3 showed that Fabp6, Slc51a, Slc51b, Slc11a2, Slc4a10 and AQP3 were the top six genes (Table 2, Table 3).

Table 2

Coefficient of different PC.

PC1		PC2		PC3
Variable	Coefficient	Variable	Coefficient	Variable	Coefficient
Slc26a3	0.976	Slc2a2	0.931	Aqp8	0.892
Aqp7	0.938	Slc51a	0.829	Sec14l5	0.527
Slc51b	0.938	Fabp6	0.826	Slc13a5	0.515
Aqp3	0.927	Slc23a2	0.78	Fabp6	0.481
RGD1565367	0.921	Sec14l5	0.63	Slc2a2	0.324
Slc51a	0.914	Csn1s1	0.521	Pmp2	0.286
Slc5a12	0.885	Crabp1	0.479	Csn1s1	0.276
Fabp6	0.87	Pmp2	0.435	Rbp7	0.266
Abcb1b	0.867	Slc4a1	0.414	Slc51b	0.247
Fabp4	0.856	Aqp3	0.369	Abcc6	0.237
Pmp2	0.719	Abcc6	0.34	Slc4a1	0.215
Csn1s1	0.708	Aqp8	0.336	Slc51a	0.211
Slc13a5	0.559	Tap2	0.318	Slc23a2	0.174
Slco5a1	0.421	Slc13a5	0.312	Crabp1	0.17
Slc5a5	0.331	Slc51b	0.292	Abcb1b	0.063
Crabp1	0.311	Aqp7	0.144	Tap2	0.05
Rph3a	0.311	Rbp7	0.105	Aqp9	0.035
Slc5a4	0.08	Abcb1b	0.093	Slc11a2	0.016
Slc23a2	0.008	Slc5a4	-0.034	Aqp3	0.01
Sec14l5	-0.001	Slco5a1	-0.038	Slco5a1	-0.005
Slc11a1	-0.057	Slc11a1	-0.055	Slc5a4	-0.012
Slc5a1	-0.231	Fabp4	-0.197	Fabp4	-0.12
Slc4a7	-0.33	Slc5a1	-0.227	Slc26a2	-0.127
Slc2a2	-0.494	Aqp9	-0.237	Slc5a5	-0.17
Slc4a1	-0.538	Slc26a2	-0.244	Fabp12	-0.208
Slc26a2	-0.542	Fabp12	-0.246	Rph3a	-0.252
Fabp12	-0.58	Slc5a12	-0.249	RGD1565367	-0.264
Aqp9	-0.742	Rph3a	-0.251	Slc5a1	-0.292
Slc4a10	-0.815	Slc4a10	-0.368	Slc5a12	-0.35
Aqp8	-0.832	Slc4a7	-0.37	Slc26a3	-0.353
Abcc6	-0.842	RGD1565367	-0.428	Aqp7	-0.36
Rbp7	-0.862	Slc5a5	-0.474	Slc11a1	-0.554
Tap2	-0.914	Slc11a2	-0.501	Slc4a10	-0.604
Slc11a2	-0.941	Slc26a3	-0.577	Slc4a7	-0.871

Table 3

Normalized coefficient of each gene.

Variable	Coefficient	Variable	Coefficient
Fabp6	0.076456	Slc13a5	0.030665
Slc51a	0.074885	Abcc6	0.027684
Slc51b	0.062386	Fabp12	0.02592
Slc11a2	0.062317	Slc26a2	0.021884
Slc4a10	.059034	Slc4a7	0.020247
Aqp3	0.057569	Aqp8	0.017378
Abcb1b	0.045099	Crabp1	0.011981
Aqp7	0.044554	Slco5a1	0.009314
Csn1s1	0.044305	Slc4a1	0.008408
Pmp2	0.043495	Slc5a1	0.006724
Tap2	0.037581	Sec14l5	0.003918
Aqp9	0.03479	Slc23a2	0.003133
Fabp4	0.033786	Rph3a	0.002116
Rbp7	0.033618	Slc2a2	0.002099
RGD1565367	0.031859	Slc11a1	0.00194
Slc26a3	0.0318	Slc5a5	0.001744
Slc5a12	0.031047	Slc5a4	0.000263

.

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qRT-PCR Detection

qRT-PCR was used to validate the accuracy of mRNA microarrays. AQP3 and AQP8 were selected randomly. Spearman Rho correlation analysis showed that there was a significant correlation between mRNA microarrays and qRT-PCR (r= 0.956, Sig = 0.000) (Figure 4).

Figure 4

Correlation between qRT-PCR and mRNA microarrays (A:AQP3, B:AOP8)

Discussion

Spleen deficiency and wet dampness (SDWD) ZHENG is one of the major syndromes of TCM, of which excessive fatigue and high fatty diet are main causes (Lim et al., 2015). SDWD can lead to the imbalance of gastrointestinal functions, edema and diarrhea, etc. (Gao et al., 2014, Han et al., 2015), which is frequently treated with fortifying the spleen and inhibiting the dampness clinically (Dai et al., 2016).

Coix seed is frequently used to treat diseases related to SDWD in TCM (Huang et al., 2014, Zhao et al., 2014). However, the effective components of fortifying the spleen and inhibiting the dampness are not clear. In previous study four components have been extracted from Coix seed.

The results show the water load index in all treatment groups decreases and the urine volume increases, which indicates that the active components of Coix seed can regulate the water transport of SDWD rats, among which the components of proteins and polysaccharides play the major role.

Microarray-based gene expression analysis is widely used in the study of TCM. It has already been applied in the study of clinical diseases (Khraiwesh et al., 2015). It detects the whole genome of the objects, which may provide possible therapeutic effect and clarify the mechanism. A lot of researches had been done in ZHENG fields with mRNA microarrays technology (Sun et al., 2016). Fang et al. found the relationship between neuroendocrine-immune and different ZHENG in tumor-bearing mice (Fang et al., 2010). mRNA microarrays is a good choice for us to explore the nature of SDWD.

The results show that SDWD model rats have higher expression of Abcb1b, Fabp6, Aqp7, Aqp3, Fabp4, Slc26a3, Slc13a5, Slc51b, Slc51a gene and lower expression of Slc4a1, Slc2a2, Slc5a1, Slc23a2, Slc26a2, Slc4a7, Slc5a4, Slc11a1 gene, which is consistent with Ying’s research results (Ying et al., 2016). The genes are closely related to water transport, which is the mechanism of SDWD water accumulation. WK Adams also believes that long-term diet disorders cause the body’s water and salt metabolism deficiency (Adams et al., 2015). Our previous studies find that the expression of Slc and AQP abnormally in SDWD rats and the expression of Apoa5 and Apoe improves (HAN et al., 2016, Han et al., 2016), which indicates that there is abnormal water transport in model rats.

After treatment with the components of Coix seed, the rat models show improvement of SDWD ZHENG. Principal component analysis shows that the loading of differential mRNA of the protein group and the polysaccharide group was closer to that of the decoction group, and the loading of the oil group was closer to the model group. It suggests that the components of proteins and polysaccharides play a more significant role in normalizing the mRNA expression of SDWD model rats. The most significant gene is Fabp6, Slc51a, Slc51b, Slc11a2, Slc4a10 and AQP3 respectively, which indicates that the components of proteins and polysaccharides play an important role in regulating water transport via the Slc gene and AQP gene family.

It is note-worthy that the result of mRNA microarrays are not entirely consistent with the results of water loading index, which shows that the components of oils and starches may have other ways in fortifying the spleen and inhibiting the dampness, which is worthy of further study.

Conclusion

The results from the present study demonstrate that components of Coix seed have excellent effect in treating SDWD by fortifying the spleen and inhibiting the dampness. The components of proteins and polysaccharides play an important role in regulating water transport, the components of oils and starches may play a part in other way.