Systems biology approaches in the study of Chinese herbal formulae

Commonly used research methods in genomics include DNA sequencing and bioarray technology. According to different sequencing objects, DNA sequencing technology can be divided into the following categories. (1) Genome-wide association study (GWAS) typically focuses on associations between single-nucleotide polymorphisms (SNPs) or copy-number variations (CNVs) and traits [14]. (2) Exome sequencing uses sequence capture technology to capture and enrich genome-wide exon-region DNA for high-throughput sequencing [15], which can be used to find pathogenic and susceptible genes of complex diseases. (3) Methylated DNA immunoprecipitation sequencing (MeDIP-Seq) can quickly and effectively find the methylation regions in the genome, thus enabling a comparison of the differences in DNA methylation modification patterns between samples [16]. (4) Chromatin immunoprecipitation (ChIP) is used to investigate the interaction between proteins and DNA within cells and to determine the specific location in the genome with which various histone modifications are associated, indicating the targets of histone modifiers [17]. Genomics involves chip technology, including the single-nucleotide polymorphism array (SNP-A), array-based comparative genomic hybridization chip (aCGH), and methylated DNA immunoprecipitation chip (MeDIP-Chip). In addition to high-throughput sequencing and microarray chip technology, low-throughput technology, such as real-time fluorescence quantitative polymerase chain reaction (RT-PCR) and the TaqMan probe, are also needed for verification of genomics research.

Genomics technology has the characteristics of being high-throughput, multifactorial, rapid and sensitive [18], and it can be used to systematically study the multicomponent, multipathway and multitarget effects of CHF systematically.

Current studies have reported that genomics is used to evaluate the efficacy of CHF and to reveal the mechanism of action of CHF at multiple levels. Wen et al. [19] used microarray technology to compare the differences in gene expression between the Siwu decoction and estradiol in the human breast cancer cell line MCF-7, using a microarray and a connectivity map to evaluate the efficacy of the Siwu decoction and explore its molecular mechanism of action. The authors found that the Nrf2-mediated oxidative stress pathway might explain the mechanism of Siwu decoction’s cancer defense by using IPA software, and RT-PCR confirmed the overexpression of five genes in this pathway. This study demonstrates the feasibility of microarray technology in combination with other techniques for the evaluation of therapeutic efficiencies and mechanism studies of CHF. Wang et al. [20] reported the mechanism of the Danqi pill (DQP) in myocardial ischemia treatment by measuring gene microarrays in a rat model. After evaluating the effects of signaling pathways and metabolism, the authors found that DQP can reverse energy metabolic disorders to recover cardiac function.

In addition, genomics has been used to analyze therapeutic targets of CHF and to predict other potential drugs. Tang et al. [21] examined therapy using Sini decoction (SND) on kidney yang deficiency in a rat model. Using an mRNA microarray with enrichment analysis, Wang et al. found that SND treatment can improve hypothalamic–pituitary–adrenal axis hormones. Kim et al. [22] connected GWAS diseases to CM by analyzing microarray gene expression and constructing disease-gene networks. The authors analyzed 14,713 GWAS disease-CM-target gene pairs to propose potential drugs from CM. Considering that molecular docking technology may lead to omitted or incorrect information, Zhang et al. [23] proposed the GEPSI method to identify the target proteins of CM by calculating the similarities of gene expression.

These reports are promising for the application of DNA microarray technology in the research of CM. However, other high-throughput technologies such as exome sequencing, MeDIP-Seq, ChIP, aCGH and SNP-A have not been used extensively to date in the study of CHF and, hence, need further research. It is expected that genomics or genomics combined with other omics analyses will offer comparatively high practical value with a systematic flow in the study of CHF.

Targeted methods are used to analyze the expression of individual RNA sequences, including gene expression profiling chips, mi-RNA microarrays, long noncoding RNA microarrays (LncRNA Microarray), cDNA-amplified fragment length polymorphism (cDNA-AFLP), Northern blotting and in situ hybridization. The advantages of cDNA-AFLP technology are its repeatability, low false-positive rate and ability to detect the expression of mRNA in low abundance, while the associated difficulty is the selection of suitable endonuclease combinations [25]. Northern blotting is mainly applied to studies of the dynamic expression of specific trait genes at the mRNA level. Using in situ hybridization technology to detect the expression of miRNA can provide a more intuitive display of the spatial and temporal expression patterns of miRNA.

Cui et al. [26] identified differentially expressed genes in Buyang Huanwu decoction intracerebral hemorrhage treatment with lncRNA and mRNA microarray technology and verified the results by qRT-PCR. The biological functions and signal transduction pathways of the differentially expressed genes were analyzed and were found to be related to hemoglobin complexes, oxygen transporters, oxygen transporters, and pyruvate metabolism. Wang et al. [27] confirmed that the Jian-Pi-Zhi-Dong decoction could effectively inhibit the abnormal behavior of mice with Tourette syndrome and increase the levels of dopamine transporter proteins and mRNA in striatum by immunohistochemistry and in situ hybridization. Dai et al. [28] identified microRNAs-223-3p as the key microRNAs in Qi-Shen-Yi-Qi dripping pills that regulate the angiogenesis of ischemic myocardial microvascular endothelial cells by miRNA chip and real-time PCR techniques.

Untargeted methods analyze the expression of a large number of different RNA sequences and perform extensive screening, including expressed sequence tags (EST), serial analysis of gene expression (SAGE), massively parallel signature sequencing (MPSS), and RNA sequencing (RNA-seq). EST can analyze a large sample number and can be used for cross-species comparative analysis; however, the data volume is large, and the error rate is high. SAGE is not only qualitative but also quantitative for gene differences, but one significant drawback of this technique is that it requires a large amount of mRNA. MPSS is simple and efficient and can provide information on terminal sequences, and it is suitable for any organism; however, the detection cost is high. RNA-seq with digital signaling has high sensitivity and quantitative accuracy.

The transcriptome is characterized by time specificity, tissue specificity and spatial specificity. In a transcriptional analysis of changes in Candida albicans gene expression due to treatment with a Huanglian Jiedu decoction (HLJDD) performed by an RNA-seq technique, Yang et al. [29] found that 735 differentially expressed genes were identified through gene expression analysis, including 700 upregulated genes and 35 downregulated genes. Through the functional annotation analysis of differentially expressed genes, 26 important pathways for HLJDD inhibition of Candida albicans infection were identified, especially those occurring through DNA replication and transporter activity pathways. However, to enable the transcriptome to play a greater role in the study of CHF, more attention should be paid to the study of gene modification and protein modification to deepen the understanding of the function and structure of functional genes and regulatory genes.

The separation techniques in proteomics research include two-dimensional gel electrophoresis (2DGE), fluorescence two-dimensional differential gel electrophoresis (2-D DIGE), multidimensional liquid chromatography (MDLC), and capillary electrophoresis (CE). Among these techniques, 2DGE is the most widely used separation technology in proteomics research. The technique can solve the problem of repeatability and reduce the human error associated with gel contrast analysis. 2DGE is suitable for comparing the differences in protein expression between two samples with high sensitivity, but it is expensive [32]. MDLC can be directly linked to mass spectrometry (MS), easily realizing automation and high throughput and avoiding limitations associated with the molecular weight and isoelectric point. However, MDLC is not as intuitive as gel electrophoresis for visualizing protein spots, and its resolution and reproducibility are not as good as those of 2DGE. CE combines electrophoretic separation with chromatographic separation technology. The technique has advantages in sensitivity, separation efficiency and cost, but it is difficult to analyze proteins with high molecular weights using this approach.

Proteomics detection methods include MS, stable isotope labeling, tandem affinity purification (TAP), yeast two-hybrid assays (YTH), protein chips, X-ray crystallography (XRC), and nuclear magnetic resonance (NMR). Among these methods, MS includes matrix-assisted laser desorption ionization (MALDI), surface-enhanced laser desorption ionization (SELDI), and electrospray ionization (ESI). MALDI is suitable for detecting the molecular mass of peptide segments but not peptide sequences. ESI–MS has a shorter detection time and higher sensitivity and resolution than MALDI, but it requires higher sample purity and more complex data acquisition and analysis. SELDI-TOF–MS is a surface-enhanced MS based on MALDI and is an analytical chip used for expression spectrum analysis. Stable isotope labeling includes stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tags (ICAT), and isobaric tags for relative and absolute quantification (iTRAQ). The limitation of SILAC is that it can only be used for cells. ICAT can only detect cysteine-containing proteins, while iTRAQ can only achieve relative quantification.

According to the occurrence and development of diseases, CHF mostly function at the protein level [33]. Proteomics research overcomes the nonlinear relationship between protein expression and genes and studies the mechanism and target of CHF action directly at the protein level. Proteomics technology, as the main method of large-scale research on proteins, is applied mainly in two respects: to protein expression profile differences and to protein structure, function and interaction analysis.

NMR enables noninvasive, unbiased detection of samples and is responsive to hydrogen-containing compounds; thus, the technique can detect as many compounds as possible in a sample. However, the sensitivity of NMR is lower than that of mass spectrometry. Wei et al. [45] studied the therapeutic effect of the HLJDD decoction on acute pancreatitis by comparing two models of cholestasis injury induced by bile duct ligation and thioacetamide. NMR-based metabolomic and pathological studies showed that Coptis chinensis and its main alkaloid, berberine, could inhibit inflammatory factors and protect the liver. Combining these methods with ¹H-NMR and network analysis, Zhang et al. successfully revealed that the three main compounds in HLJDD, berberine, baicalin and jasmine, can improve metabolic disorders of ischemic stroke by improving metabolic abnormalities and regulating oxidative stress, neuronal autophagy and inflammatory responses [46]. The therapeutic effect of HLJDD and its four variants on a septic cecum ligation and perforation (CLP) model was studied by ¹H-NMR, histological examination, biochemical examination and molecular biology. The results showed that HLJDD had a better therapeutic effect in the CLP model than its four variants and that the HMGB-1/TLR4/NF-kappa B signaling pathway may be involved in HLJDD’s ability to reduce tissue damage and improve metabolic disorders in septic rats [47].

It is difficult to simultaneously determine the metabolites coexisting in biological systems at very different concentrations. Commonly used separation techniques include gas chromatography (GC), liquid chromatography (LC) and CE. Analytes in metabolomics samples contain highly complex mixtures. By separating some analytes from others, complex mixtures can be simplified before testing. The separation procedure is not mandatory and is usually omitted in NMR. Because existing analytical techniques each have their own advantages and scope of application, the strategy for metabolomics comprehensive analysis is to combine separation and analytical techniques. GC–MS is suitable for the analysis of metabolites with low molecular weights, low polarity and low boiling points or volatile substances after derivatization.

GC–MS is a feasible way to systematically study the therapeutic effect of CHF. The Xuefu Zhuyu Decoction (XFZY) has a distinct therapeutic effect on traumatic brain injury (TBI) in rats. Feng et al. used GC–MS to analyze the plasma metabolomics of sham, vehicle and XFZY groups by univariate and multivariate statistical analysis to illustrate the therapeutic approach of XFZY in TBI. The authors concluded that XFZY treatment can alleviate neurological impairment and cortical lesion volume on the third day after brain injury and reverse the abnormalities of plasma metabolites such as glutamate, lactic acid, 3-hydroxybutyric acid and ribitol [48]. GC-TOF–MS was used to evaluate the efficacy and mechanism of the Shenfu decoction in the treatment of chronic heart failure induced by coronary artery ligation in rats. Unsupervised principal component analysis showed that CHF significantly altered the fingerprint of urinary metabolites. After SFD treatment, the metabolomic profiles of CHF rats were significantly reversed, and the pathways of fatty acid biosynthesis, fatty acid elongation, steroid biosynthesis, galactose metabolism and amino acid metabolism in rats were significantly altered [49].

LC–MS is suitable for the analysis of high-molecular-weight, thermally instable and high-boiling-point compounds. Based on LC-TOF/MS and LC-QqQ/MS, a nontarget metabolomics-driven method for the rapid screening and identification of xenobiotics and related metabolites in vitro was developed. Using this method, Wu et al. [50] found that iridoid glycosides, monoterpenoids, flavonoid glycosides, and anthraquinones are the main absorbed chemical components of the Zhi-Zi-Da-Huang decoction and that hydrolysis, glucuronidation and sulfation are the main metabolic pathways in vivo. Yan et al. [51] applied UHPLC-LTQ-Orbitrap MS combined with a spike-in method to the study of Danqi Tongmai tablets for the preconditioning of acute myocardial ischemia (AMI) rats, which indicated that pretreatment with this CHF can partially regulate disordered TCA circulation and amino acid and nucleotide metabolism, thereby reducing injury from AMI. In addition, the effect and mechanism of Jinxin oral liquid in treating viral pneumonia caused by the respiratory syncytial virus via improving lipid metabolism disorders [52], the protective effect of low-dose Sini decoction against myocardial injury induced by isoproterenol [53], the inhibitory effect of the Yinchenhao decoction toward dimethylnitrosamine-induced liver fibrosis in rats [54], and the improvement from the modified Jiu Wei Qiang Huo decoction on H1N1-virus pneumonia in mice [55] have all been well verified by LC–MS technology.

Regardless of which analytical technology is adopted, no single technique can completely cover all metabolomics compounds [56]. In recent years, researchers have tried to integrate various analytical techniques to give full play to the advantages of various methods. LC–MS and GC–MS analyses were performed to quantitatively evaluate the compatibility of CHF from the perspective of overall metabolic profiles and specific metabolites [57, 58]. These studies suggest that appropriate analytical techniques need to be selected before metabolomics studies on CHF can be carried out so that the results can be more comprehensive and accurate. Metabolites are not confined to the substrates and products of certain enzymes in the metabolic pathway. Instead, metabolites act as structural units, signaling molecules, and regulatory factors and play many other roles and interact in the form of a metabolic network in life activities.

At present, the main application of metagenomics in-clinic is based on gene sequence analysis of microbial species and compositions. 16S rRNA gene cloning and sequencing, PCR-denaturing gradient gel electrophoresis (PCR-DGGE), PCR-temperature gradient gel electrophoresis (PCR-TGGE), terminal restriction fragment length polymorphism (T-RFLP), and next-generation sequencing technology such as 454 and Illumina have been widely used in metagenomics research. High-throughput, large-scale, in-depth sequencing combined with multivariate statistical methods can provide more direct information on the composition and function of microorganisms and identify specific bacterial groups closely related to the physiological and pathological state of the organism. 16S rRNA gene cloning and sequencing can not only analyze the species of bacteria in a sample but can also reflect the proportion of various bacteria and provide relative quantitative analysis [59]. PCR-DGGE has a high resolution and can detect mutant individuals with single-base differences. However, when the length of DNA fragments detected by PCR-DGGE exceeds 500 bp, the resolution will decrease [60]. Similarly to DGGE, TGGE can only analyze DNA fragments shorter than 500 base pairs, and there are only ten to twenty bands in the map reflecting the dominant flora in the community, while the disadvantaged flora cannot be detected. T-RFLP was established based on PCR but without the isolation and cultivation of bacteria. However, when two distinct sequences share a terminal restriction site, they cannot be distinguished and only show one peak on an electropherogram.

One of the main methods for the application of metagenomics in CM research is to construct a 16S rRNA gene library for flora analysis based on the species specificity of the 16S rRNA gene. Another common method is to extract the total nucleic acid from bacteria and amplify the 16S rRNA gene by PCR, then analyze the data by molecular biology techniques such as fingerprinting combined with multivariate statistical analysis. To study the effect of Xiexin Tang on the distribution of intestinal flora in rats with type 2 diabetes mellitus (T2DM), Wei et al. [61] utilized high-throughput 16S rRNA gene sequencing to detect the cecum samples of the rats. Sequencing analysis showed that certain short-chain fatty acid-producing and anti-inflammatory bacteria in the intestinal microflora of T2DM rats were significantly altered after Xiexin Tang intervention, and these microbiotas were closely related to the changes in related indices of T2DM. Tong et al. [62] proved the effect of metformin and a specially designed CHF on T2DM with hyperlipidemia through a randomized clinical trial. Then, Illumina sequencing and multivariate statistical methods were used to analyze the V3 and V4 regions of 16S rRNA genes to evaluate changes in the intestinal microbial structure. The results suggest that the combination of metformin and CHF may improve T2DM with hyperlipidemia by enriching Brucella and fecal bacilli and other beneficial bacteria. To verify that oil tea can induce changes in intestinal microbes and play an anti-diabetic role, Lin et al. [63] carried out 16S rRNA gene sequencing on fecal samples of db/db mice fed oral salt, metformin and oil tea. The results showed that Lachnospiraceae were significantly enriched after oil tea treatment and correlated with decrease indicators related to diabetes. Gao et al. [64] studied the effects of S-3-1, a homogeneous polysaccharide purified from the Sijunzi decoction, on human intestinal microflora and short-chain fatty acids by a GC technique, analyzing the V3 and V4 regions of 16S rRNA after Illumina MiSeq sequencing. It appeared that S-3-1 could regulate the abundance of 9 intestinal flora, while S-3-1 incubated in gastric and intestinal juice enhanced the ability to regulate the composition of intestinal flora and regulated 13 types of bacteria genera to play an immunoregulatory role.

The number of microorganisms in the human body is more than ten times that of body cells, and the corresponding genetic code is 100 times the size of the human genome [65]. Most existing studies have focused on the distribution of intestinal microorganisms. We should pay more attention to the impact of intestinal microecological changes on human health and disease; that is, we should pay more attention to the functions of microorganisms. There is a great challenge and opportunity in the deeper and wider application of metagenomics in CHF research to connect the functional changes of intestinal flora with the influence of CHF on microflora.