Depression is one of the most pervasive, disabling, and expensive of all neuropsychiatric disorders (Porcu et al., 2020). According to the report of WHO, depression will rank as the first reason for global disease burden in 2030 (Malhi and Mann, 2018). Despite large efforts are put into developing therapies for depression, western medications are still invalid in myriad cases and regularly cause insufferable side effects (Duman and Aghajanian, 2012).

Therefore, the formulas of Traditional Chinese medicine (TCM), as an essential alternative and complementary medicine, are gaining more and more enthusiasts among the patients (Wang et al., 2017). The formulas of TCM have been widely utilized to recover the harmony disturbed in diseases through multi-target synergistic functions of its corresponding components, hence qualified and efficacious for the treatment of complicated diseases such as depression (Yeung et al., 2014). Considerably, increasing clinical evidence demonstrates the desirable efficiency of the prescription of TCM in treating depression (Peng et al., 2015; Chi et al., 2019; Wang et al., 2019). Since ancient times, Chaihu-Shugan-San, a classic TCM prescription was written in Jing Yue Quan Shu, has been extensively utilized in Chinese clinical applications for the treatment of depression (Liu et al., 2020). It consists of 7 crude herbs, namely Chai Hu (Bupleurum chinense DC.), Chen Pi (Citrus reticulata Blanco), Xiang Fu (Cyperus rotundus L.), Zhi Qiao (Citrus × aurantium L.), Chuan Xiong (Ligusticum striatum DC.), Bai Shao (Paeonia lactiflora Pall.), and Gan Cao (Glycyrrhiza uralensis Fisch.) in a specific ratio of 4: 4: 3: 3: 3: 3: 1 (Table 1). All plant names or species were validated using http://www.theplantlist.org/. Modern studies show that Chaihu-Shugan-San has significant clinical efficacy in depression (Kim et al., 2005; Li et al., 2010; Wang et al., 2012; Qiu et al., 2014a; Qiu et al., 2014b). Our previous studies suggest that regional cerebral blood flow perfusion defects and clinical symptoms of depression can be improved by Chaihu-Shugan-San, the mechanisms involve reversing the hypothalamic-pituitary-adrenal (HPA) axis hyperfunction (Qiu et al., 2014a). Other researches support that Chaihu-Shugan-San exerts antidepressant effect by increasing monoamine neurotransmitters, regulating brain-derived neurotrophic factor (BDNF), and affecting the BDNF-TrkB-ERK/Akt signalling pathway (Li et al., 2009; Qiu et al., 2014b; Liu Q. et al., 2018; Chen et al., 2018). Despite these researches, the mechanisms of the multi-component Chaihu-Shugan-San are far from being fully understood, which limits its application.

From the perspective of TCM theory, a formula is composed of several compatibility groups that exert different but synergistic functions (Zhang et al., 2015). Clinically, strive to achieve the best therapeutic effect and minimal side effects, TCM doctors would combine traditional Chinese medicinal material groups according to TCM theory. Through organic integration, the TCM prescription has applicability to deal with the disease complexity. In TCM theory, depression is considered to be Gan-Qi stagnation and further would be upgraded as Gan malnutrition (Scheid, 2013). Chaihu-Shugan-San can disperse stagnated Gan-Qi and nourish Gan to alleviate pain because consists of 2 recipes: Shu Gan, which disperses stagnated Gan-Qi; and Rou Gan, which nourishes Gan to alleviate pain (Table 1) (Qiu et al., 2014b). However, the mechanisms of the TCM theory-based synthetic effects of Rou Gan and Shu Gan subdivisions in Chaihu-Shugan-San are not reported.

Chaihu-Shugan-San improves depression outcomes via multi-targets and multi-pathways (Li et al., 2009; Qiu et al., 2014b; Li et al., 2014). Considering the complex changes in protein expression in vivo during depressive states, proteomics is considerably potent for monitoring the dynamic alternations (Zhang J. et al., 2016). The technique is a method for accurately detecting the changes of protein in disease states and after treatment by drugs (Zhang L. et al., 2016). Previous proteomic researches of postmortem depression cases and rodent depression models have shown dysfunctions of energy metabolism, synaptic plasticity, neurogenesis, and neurotransmission (Zhang et al., 2018). Collectively, proteomics provides holistic insights into the disease- and drug-driven pathway alteration, which in turn gains evidence to identify treatment targets. Thus, this strategy is hopeful to better understand the multiple mechanisms of Chaihu-Shugan-San and its decomposed recipes in depression treatment, which has not been published before.

In the current investigation, Tandem Mass Tag (TMT) labeling quantitative proteomics was carried out to explore the hippocampus proteins in the rats having chronic unpredictable mild stress (CUMS) and to analyzed the differentially expressed proteins (DEPs). With the bioinformatics method, we next elucidated the underlying mechanisms of Chaihu-Shugan-San in treating depression and compared the effects of Chaihu-Shugan-San with those of its decomposed recipes (Shu Gan and Rou Gan). Our study will highlight the synthetical anti-depressive superiority of the Chaihu-Shugan-San formula.

In TCM theory, the Gan is the center of regulating emotions (Scheid, 2013; Li XJ. et al., 2020). Chaihu-Shugan-San consists of Shu Gan (stagnated Gan-Qi dispersion) and Rou Gan (Gan nourishment to alleviate pain), treating complex emotional diseases such as depression (Qiu et al., 2014b). Modern studies have also shown that Chaihu-Shugan-San can inhibit apoptosis in liver cells and participate in phospholipid and bile acid metabolism to counteract CUMS-induced liver injury in rats (Jia et al., 2017). While for the hippocampus, which is responsible for emotion regulation (Snyder et al., 2011), a comprehensive exploration is lacking. The anti-depressive mechanisms and the compatibility advantage of Chaihu-Shugan-San in the hippocampus of CUMS-induced rats were explored by proteomics for the first time in this study.

After a 2-weeks treatment of Chaihu-Shugan-San or its decomposed recipes, behavioral data including SPT and FST demonstrated that Chaihu-Shugan-San exhibited better therapeutic effects in the CUMS models. Our proteomics data showed that Chaihu-Shugan-San controlled 110 DEPs. By mapping the PPI network of 110 DEPs, we found that Gad2 and Vamp2 were the key targets in the network. Bioinformatics analysis suggested that the signalling pathways affected by Chaihu-Shugan-San contained neurotransmitters release and transmit pathways (e.g., GABA, glutamate, serotonin, norepinephrine, dopamine, and acetylcholine), which play an important role in the pathogenesis of depression (Kraus et al., 2017; Murrough et al., 2017; Gunduz-Bruce et al., 2019). Furthermore, the 22 Chaihu-Shugan-San advanced proteins which were mainly enriched in GABA release cycle was additionally changed by Chaihu-Shugan-San treatment. The 323 proteins whose expression was changed by Shu Gan or Rou Gan treatment alone were enriched in metabolism and cellular responses to external stimuli. Finally, we used molecular biotechnology to verify the credibility of quantitative proteomics by selected proteins from DEPs including Gad2, Vamp2, and Pde2a.

TCM has extraordinary therapeutic effects owing to its complicated mechanisms, in which the compatibility of its recipes counts a great deal. Chaihu-Shugan-San, a combination of Shu Gan and Rou Gan, has been widely used as a classical antidepressant formula in TCM practice (Qiu et al., 2014b). Weight changes and appetite changes are common symptoms of depression (Fava, 2000). After 4 weeks of CUMS procedures, the bodyweight growth and food intake of the stressed rats were significantly less than the unstressed rats. Chaihu-Shugan-San or Shu Gan could increase the bodyweight growth and food intake of CUMS-induced rats, exerting a fluoxetine-like effect. We used SPT and FST to assess the antidepressant efficacy of Chaihu-Shugan-San, Shu Gan, and Rou Gan in CUSM rats. SPT evaluates sensitivity to reward. A decreased preference for consumption of sucrose reflects anhedonia (lose pleasure in rewards) that is the core symptom of depression (Moreau, 2002). In SPT, Chaihu-Shugan-San significantly improves the sucrose preference index, which is similar to fluoxetine. Neither Shu Gan nor Rou Gan increases the sucrose preference index significantly. FST is the gold standard for despair testing (Becker et al., 2021). FST assesses learned helplessness, which is a feature of depression-like behavior (Yankelevitch-Yahav et al., 2015). In FST, the Chaihu-Shugan-San and Shu Gan groups significantly lower the immobility time, which is similar to fluoxetine. CUMS-induced rats showed lacked pleasure, desperate behavior, loss of appetite, and impaired weight growth, similar to human depressive disorder (Krishnan et al., 2007; Yang et al., 2017; Xing et al., 2019). The experimental results indicated that the depression model was successfully established. After 2 weeks of treatment, all behavioral disturbances created via CUMS were correspondingly reversed, indicating that Chaihu-Shugan-San and fluoxetine possessed anti-depressive impacts. Chaihu-Shugan-San exhibited better therapeutic effects in the CUMS models as compared with its decomposed recipes.

Then, to further analyze the advantage of TCM compatibility and explore the anti-depression mechanisms of Chaihu-Shugan-San, we used quantitative proteomics and bioinformatics analysis to identify and analyze DEPs. Chaihu-Shugan-San, Shu Gan, and Rou Gan regulated 110, 12, and 407 DEPs, respectively. Although the targets of Chaihu-Shugan-San are less than the sum of Shu Gan and Rou Gan, bioinformatics analysis shows that it may affect the classic antidepressant pathway (e.g., GABA, glutamate, serotonin, norepinephrine, dopamine, and acetylcholine pathway) (Kraus et al., 2017; Murrough et al., 2017; Gunduz-Bruce et al., 2019). The GABA synthesis, release, reuptake, and degradation was the most significant pathway by 110 DEPs enriched. Compared with Shu Gan or Rou Gan alone, the expression of 22 advanced proteins was additionally changed by Chaihu-Shugan-San treatment, whereas the expression of 323 proteins whose expression was changed by Shu Gan or Rou Gan alone were not changed by Chaihu-Shugan-San treatment. Interestingly, 22 DEPs focus on GABA synthesis, release, reuptake, and degradation pathway-one of the key pathways of Chaihu-Shugan-San to treat depression. The signalling pathways regulated by Shu Gan are the transport of small molecules (cations, anions, amino acids, and oligopeptides) (Supplementary Figure S4A). The signalling pathways regulated by Rou Gan are metabolism, cellular responses to external stimuli, and transport to the Golgi (Supplementary Figure S4B). Meanwhile, based on 323 proteins, only 2 pathways were enriched: metabolism and cellular responses to external stimuli. These 323 proteins that are not enriched in the key pathway of depression are targeted by Shu Gan or Rou Gan. Accordingly, the compatibility of prescriptions is not simply increasing the number of targets, but increasing the accuracy of targets. This explains why Shu Gan and Rou Gan did not achieve the antidepressant effect of Chaihu-Shugan-San.

Our data show that Chaihu-Shugan-San treats depression potentially via influence 110 DEPs (Gad2, Vamp2, Pde2a, etc.), and neurotransmitters release and transmission cycle (e.g., GABA, glutamate, serotonin, norepinephrine, dopamine, and acetylcholine). Compared with Shu Gan and Rou Gan, the 22 Chaihu-Shugan-San advanced proteins and the affected GABA pathway may be the advantages of Chaihu-Shugan-San compatibility. Remarkably, the PPI of Chaihu-Shugan-San’s targets showed a closely linked network, Gad2 and Vamp2 are key targets in the network. Gad2 and Vamp2 also are enriched in the GABA and glutamate release pathways. GABA and glutamate are the primary inhibitory and excitatory neurotransmitters in the brain. An impaired balance of neural excitation and inhibition is one of the pathological characteristics of depression (Abdallah et al., 2014; Fee et al., 2017). Stress leads to activation of the HPA axis. Then it results in the over-release of glucocorticoid, dysfunction of glucocorticoid receptors, and subsequent the disorder of glutamate transmission and an excessive concentration of glutamate in the synaptic space. This could create excitatory toxicity to neurons, resulting in neuron degeneration, aging, and death, finally resulting in mental disorders, for instance, depression (Ferrer et al., 2018). Glutamate levels are elevated in the brains with depression in patients or rats (Hashimoto et al., 2007; De Vasconcellos-Bittencourt et al., 2011). Glutamate release inhibitors have antidepressant properties and are used in clinics widely (Deutschenbaur et al., 2016; Lener et al., 2017). Activation of the HPA axis also changes the expression of postsynaptic GABA_A receptors, then reduces GABA release in presynaptic (Luscher et al., 2011; Maguire, 2018). The studies from depression subjects indicate the GABAergic deficit in the central nervous system (Croarkin et al., 2011; Möhler, 2012). The enhancers of GABA_A receptors have been used as antidepressants (Papakostas and Shelton, 2008; Morishita, 2009). Our previous research demonstrates that the components of Chaihu-Shugan-San play an antidepressant role by regulating the HPA axis and inhibiting neurotransmitter reuptakes (e.g., norepinephrine, serotonin, and dopamine) (Zhang et al., 2011). Therefore, we speculate that Chaihu-Shugan-San affects glutamate and GABA signalling pathways to treat depression via the HPA axis. Of course, the concrete anti-depressive mechanism needs to further explore.

We chose Gad2, Vamp2, and Pde2a for western blotting. Gad2 belongs to the group II glutamate decarboxylase family that catalyzes the decarboxylation of glutamate to produce GABA. Glutamate regulates the expression of Gad2 by the autocrine effect on sensory terminal BDNF, and depletion of glutamate release lower levels of BDNF and Gad2 (Mende et al., 2016). Gad2 activity underlies enhanced release of GABA at high frequencies of stimulation, showed that this enzyme expression could regulate the efficiency of inhibitory synaptic signalling (Betley et al., 2009). However, no simple parallel exists between Gad2 and GABA content (Sonnewald et al., 2004; Benagiano et al., 2005; Freichel et al., 2006). Depression patients had Gad2 antibody positive and Gad2 mRNA expression increased (Bowers et al., 1998; Kruse et al., 2015). Our proteomics data and western blotting data show that Gad2 levels in CUMS rats were significantly increased, while the treatment of Chaihu-Shugan-San or its decomposed recipes reversed it. Interestingly, Gad2 is an indicator of diabetes (Atkinson and Eisenbarth, 2001). Ample clinical evidence shows that diabetes is associated with depression, but the internal relationship is unclear (Anderson et al., 2001; Knol et al., 2006; Mezuk et al., 2008). This finding may provide clues for depression complicated with diabetes.

Vamp2, a core soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein residing on synaptic vesicles, forms helix bundles with SNAP25 and syntaxin-1 for the SNARE assembly (Ramakrishnan et al., 2012; Wang et al., 2020). SNARE proteins were the main neurotransmitter release-associated proteins involving in the release procedure and synaptic vesicle fusion (Kiessling et al., 2013; Stratton et al., 2016). It is the crucial factor that mediates the complicated interactions between the presynaptic membrane and vesicle fusion. According to our proteomics and western blotting data, the Vamp2 expression level was up-regulated in CUMS rats, while treatment of Chaihu-Shugan-San and its decomposed recipes could counteract the change significantly. SNARE protein complex formation is considerably enhanced during depression (Katrancha and Koleske, 2015; Cao et al., 2018). Furthermore, antidepressant reboxetine, fluoxetine, and desipramine could remarkably diminish SNARE complex expression (Bonanno et al., 2005). A previous study has illustrated that acupuncture could reduce the expression of SNARE protein (Vamp2) in depressive animals (Fan et al., 2016). A recent study shows that anti-depressive TCM-paeoniflorin noticeably reduced hippocampal glutamate via inhibiting the level of SNARE complex and Vamp2 (Li YC. et al., 2020).

Pde2a, an enzyme that catalyzes the hydrolysis of cyclic guanosine monophosphate (cGMP) and cyclic adenosine monophosphate (cAMP), may become a potential pharmacological target for neuropsychiatric diseases (Conti and Beavo, 2007; Knott et al., 2017). Proteomics data and western blotting results showed Pde2a was decreased after Chaihu-Shugan-San or Chaihu-Shugan-San’s decomposed recipes treatment. Pde2a is a crucial point of compartmentalized cross-talk between cGMP and cAMP signalling (Reierson et al., 2011). cGMP/cAMP signalling pathway, being generally anti-inflammatory, could help to reduce oxidative stress (Masood et al., 2008). Inhibition of cGMP is widespread across various antidepressants such as ketamine (Li et al., 2006; Cunha et al., 2015). A study showed Pde2a mRNA expression increased in the depression cell model (Zhu et al., 2019). The most commonly characterized selective Pde2a inhibitor, namely Bay 60–7550, generates antidepressant efficacy in the depression animal model (Masood et al., 2009; Xu et al., 2013; Ding et al., 2014). Pde2a inhibitor had significant neuroprotective effects on depression by affecting the cGMP and cAMP signalling pathways, contain increasing the ratio of the expression of pCREB/CREB and BDNF (Liu L. et al., 2018).

Taken together, the curative effect of Chaihu-Shugan-San is better than those of Shu Gan and Rou Gan in behavioral evaluation, and Chaihu-Shugan-San affects the classic antidepressant pathway more focused than Shu Gan and Rou Gan in proteomics. This study suggests that Gad2, Vamp2, and Pde2a are potentially involved in depression remission treated by Chaihu-Shugan-San. Therefore, these proteins might be the antidepression targets of Chaihu-Shugan-San. Nevertheless, the present study had several limitations. First, we are still at the beginning of our understanding on how these proteins are operated and how they are regulated by Chaihu-Shugan-San. Second, modeling the full complexity of the human disorder in animals is difficult, especially mood disorders such as depression. Tests on assessing animal models of depression also lack the mechanistic specificity to be used universally to elucidate the neurobiological mechanisms of depression in humans. Data from human samples need to be supplemented in future studies.

In this study, we provide proteomic clues to explore the merit of prescription compatibility in Chaihu-Shugan-San and explores mechanisms of Chaihu-Shugan-San anti-depression. Our research reveals that Chaihu-Shugan-San treats depression via multiple targets and pathways, which may include regulations of 110 DEPs and some neurotransmitter’s transmission cycle (e.g., GABA, glutamate, serotonin, norepinephrine, dopamine, and acetylcholine). Compared with Shu Gan and Rou Gan, the 22 Chaihu-Shugan-San advanced proteins and the affected GABA pathway may be the advantages of Chaihu-Shugan-San compatibility. Those findings would contribute to revealing the prescription combination advantages of Chaihu-Shugan-San for antidepression, and also a rational way for clarifying the composition rules of TCM. Meanwhile, this research offers data and theory support for the clinical application of Chaihu-Shugan-San.