The majority of cancer evolution studies involve individual-based approaches that neglect the population dynamics necessary to build a global picture of cancer evolution for each cancer type. Here, we conducted a population-based study in breast cancer to understand the timing of malignancy evolution and its correlation to the genetic evolution of pathological stages. In an omics integrative approach, we integrated gene expression and genomic aberration data for pre-invasive  and post-invasive  samples and investigated the evolutionary role of further genetic changes in later stages compared to the early ones. We found that single gene alterations (SGAs) and copy-number alterations (CNAs) work together in forward and backward evolution manners to fine-tune the signaling pathways operating in tumors. Analyses of the integrated point mutation and gene expression data showed that (i) our proposed fine-tuning concept is also applicable to metastasis, and (ii) metastases sometimes diverge from the primary tumor at the DCIS stage. Our results indicated that the malignant potency of breast tumors is constant over the pre- and post-invasive pathological stages. Indeed, further genetic alterations in later stages do not establish de novo malignancy routes; however, they serve to fine-tune antecedent signaling pathways. Modern cancer biology, which is expanding rapidly in the light of omics approaches, has validated many aspects of Darwinian somatic evolution in cancer progression . Such evThe study of the somatic evolution of cancer relies on the dynamic genotype‒phenotype relationship of cancer cells at different stages of tumor progression . Data foStudying the evolution of malignancy in large populations of patients will solve some of the mentioned issues, and might allow new aspects of cancer evolution that are not visible in the individual-based approaches to be pinpointed. We exploited a large volume of available data on different stages of breast cancer to build a universal portrait of tumor evolution in breast cancer. The most common type of breast cancer is ductal carcinoma, which consists of two main stages, ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) . DCIS orWith the advent of high-throughput technologies, researchers can quantify cellular changes at different molecular levels. Omics data have been broadly used for disease classification and identification of molecular gene signatures, but low reproducibility is a major weakness of these approaches . HoweverIn this study, we used an omics integration approach to integrate the gene expression, copy-number alteration (CNA), and mutation data for the DCIS, IDC, and metastasis (Met) samples. Our results indicated that the malignant phenotype mostly forms in the earlier stages of tumor progression. Phylogenetic analyses depicted a global picture of breast cancer evolution that indicated early divergence of metastases at the DCIS stage. We discovered that further genetic alterations in advanced tumors do not generate new functional pathways in the tumor, but rather serve as fine-tuning effectors for antecedent changes from earlier stages. The fine-tuning happens via two different pathways, forward and backward evolution. In forward evolution, cancer cells increase the single gene alteration (SGA) burden to increase the efficiency of selected pathways. In backward evolution, tumor cells exploit CNAs in order to reverse the expression direction of unwanted inherited genetic changes, with a negative impact on the function of operating pathways. Therefore, we concluded that the malignancy fate is determined at the very early stages, and subsequent genetic changes are the fine-tuners of the evolutionary path.p-value < 0.05 for DEG1 , DEG2 , and DEG3 (DCIS vs. IDC), respectively  and hierarchical clustering to determine whether the gene expression profiles of DCIS and IDC samples were separable. We did not find a clear separation between these samples a,b. To ap < 0.0001, Pearson correlation test; Here, we applied further advanced approaches to distinguish DCIS and IDC based on their gene expression profiles. Therefore, we used machine-learning (ML) methods to define a minimal number of genes as representatives of DCIS and IDC. We optimized four different ML methods  and they successfully generated distinctive  features able to sort DCIS from IDC samples a. In ordp = 0.008, Pearson correlation test; The aggravation of chromosomal aberration is a general aspect of tumor progression in the evolutionary path toward advanced stages . We specp = 0.008 for common genes in constant CNAs and DCIS CNAs, p = 0.06 for disparate genes in constant CNAs and IDC CNAs, Wilcoxon matched-pair signed rank test; The constant malignant properties of tumors in premalignant stages raise a question about the role of the accumulation of genetic alterations in later stages. To address this question, we first explored the functions of earlier and later events during tumor evolution, as well as the possible interactions between them. We assumed that each CNA prototype is an evolutionary unit b whereinp = 0.01, Wilcoxon matched-pair signed rank test; Up to this point, our results suggested that the progression of CNAs in later stages did not increase the density of SGAs in each given CNA. Surprisingly, further genetic alterations specific to the later stages did not generate further signaling pathways in the tumor, contradicting a forward evolution model for extra genetic alterations in the later stages. Hence, we proposed two scenarios to explain the role of further genetic alterations in the later stages. The first scenario was to consider a neutral evolution model whereby further genetic alterations randomly accumulate in tumors. This scenario might be accurate, but is difficult to test. In a substitute scenario, we hypothesized a backward evolution in the later stages, serving to reverse the expression of unwanted genes inherited from earlier stages. In a backward evolutionary model, we supposed that CNAs in the later stages would function in the reverse direction to SGAs from earlier stages within that region h,i. For To better understand the role of early and late genetic alterations during tumor progression, we performed more functional analyses. Since in the late stage of tumors, genetic alterations are the accumulative results of the early (common SGAs) and late stages (disparate SGAs), we studied the function of disparate SGAs as a part of the whole running program (common + disparate) in the late stage. Therefore, we performed PPIN analyses for common SGAs and all DEG3 , independent of their chromosomal loci. Surprisingly, we found that the higher connectivity of the network suggested more intricate biological functions for the protein network of all DEG3 compared to the common SGAs . We thenp < 0.0001, chi-square test; We then investigated how further genetic alterations might affect the function of selected pathways from earlier stages. Closer inspection of PPINs suggested that highly interactive nodes in the common PPINs were more homogenous in their connections compared to the PPINs of DEG3 , which indicated that SGAs increase the function of selected pathways in a forward evolution manner. Similarly, we performed SPIA for all SGAs of common genes compared to all DEG3 . Interestingly, perturbation was detected for only seven pathways . These results indicated that further genetic alterations in later stages do not establish new paths for the operating pathways of tumor cells, but rather fine-tune and increase the function of descendant pathways, which can be explained by the forward evolution model.To investigate the functionality of the acquired complexity, we expanded our analyses by using signaling pathway impact analyses (SPIA) to track the functions of changes in the enriched pathways. The biggest advantage of SPIA is its ability to quantify the direction of changes by integrating the effect of topological positioning, gene expression values, and the impact of players’ interaction (inhibition or activation) in a given enriched pathway . Therefopathways e. Consisp = 0.03, Student’s paired t-Test; In the next step, we functionally assessed the existence of backward evolution during tumor progression. In the previous section, we showed that CNAs in later stages serve to decrease the load of SGAs inherited from earlier stages in those regions where their function was left unaddressed see j. Here, Altogether, these results indicated that SGAs in advanced stages, which are inherited from earlier stages, play a prominent role in the construction of functional signaling pathways. Those SGAs that are acquired in later stages serve as fine-tuners for the functions of SGAs that are inherited from earlier stages. These results further suggest that CNAs have no driving role in the evolution of functional signaling pathways of tumors, but, rather, are tools exploited by tumors for the fine-tuning in a forward or backward evolution model.p = 0.001, Student’s paired t-test, In cancer, metastasis is the demonstration of a malignant phenotypic evolution of primary tumors. Therefore, we tested the main aspects of our findings in metastatic (Mets) samples. For these analyses, we first generated a DEG for metastases as well as a common DEG list overlap between Met–DEG and DCIS–DEG profiles  sampling methods do not cover the entire heterogeneity of tumors ,15,16,  as the basis of cancer cell invasion were among the most perturbed pathways shared in DCIS, IDC, and Met. However, the same pathways showed three main differences in the advanced tumors as compared to their ancestral pathways from an early stage. First, the number of genes in the same pathways was higher in later stages compared to the ancestral ones, indicating the involvement of more genomic changes in the later stages. Second, the same pathways were increasingly heterogeneous in terms of the direction of the expression and regulation of their player in later stages. Third, the perturbation of enriched pathways significantly increased in the late stage, indicating fine-tuning evolution of the earlier-developed pathways by further genetic alteration in late-stage tumors.We also found that the density of SGAs in the chromosomal regions with CNAs was higher compared to the regions without CNAs. In addition, the direction of CNAs turned out to be in the direction of SGAs in each stage, which was in line with the notion that CNA is one of the mechanisms of somatic gene deregulation . We alsoWe further found that Met samples had equal similarities to DCIS and IDC in terms of their shared perturbed signaling pathways and driver genes. However, Met had more unique disturbed pathways compared to DCIS and IDC. This probably reflects a higher chance of Met samples resulting from neutral evolution, as this has been shown to be more prominent in the absence of selection pressure ,30. TherAltogether, these findings were in line with recent studies that found that metastatic dissemination of breast and colon cancer cells is higher in the earlier stages of tumor progression compared to the advanced tumors, and that these cancer cells disseminated early on are the precursors of a high proportion of metastases ,11,36. Ihttps://www.networkanalyst.ca/faces/home.xhtml) [p-values for the DEGs’ identification were obtained by using the state-combined Fisher’s method . DEGs within the mentioned states were named DEG1, DEG2, DEG3, and DEG4 for normal vs. DCIS, normal vs. IDC, DCIS vs. IDC states, and primary vs. metastasis, respectively  database (see GEO accession numbers in e.xhtml) . The comq-value < 0.01) in the metadataset  was done by the pairwise average-linkage method [In an independent analysis, all samples obtained from the GPL96 (HG-U133A) and GPL570 (HG-U133_Plus_2) platforms were preprocessed with the FRMA package  and merge method . Furthere method . The sece method . The thie method . The foue method . All modThe prognostic performance of gene signatures was assessed via the Cox model in terms of overall survival (OS) and recurrence-free survival analysis (RFS) using the Survexpress dataset , which ihttps://progenetix.org/, version 2017), including 76 DCIS and 1736 IDC samples  data were obtained from the Progenetix database  were done using NetworkAnalyst  and STRIp-value < 0.05) were considered. Moreover, signaling pathway impact analysis (SPIA) was applied to assess unusual signaling perturbations in pathways related to common or all (common + disparate) gene sets, and to analyze the fine-tuning functionality effect of backward evolution-related genes. According to the SPIA results, KEGG pathway-related genes were significantly perturbed in at least one of the common, all, and specific DCIS-related pathways (http://software.broadinstitute.org/gsea/msigdb/index.jsp).Gene-enrichment analysis of PPINs was done using the Reactome database through NetworkAnalyst. Only significantly enriched pathways , which contained 2663 and 245 samples for IDC and DCIS, respectively. Moreover, 3607 IDC, 9 DCIS, and 86 metastatic samples were retrieved from cBioPortal . MutatiWe used the DawnRank method for the detection of driver genes. In principle, this method integrates PPINs with gene expression data and DNA-based somatic alterations, which enabled us to find the unique driver genes of which changes could deeply perturb the influential pathways ,62. On tIn order to study the evolutionary relationships between different stages of tumor progression, we used a mutation map of driver genes of DCIS, IDC, and Met, and a binary  dataset was created in which 1 represented genes with a point mutation in the driver gene lists and 0 represented nonmutated genes k. This bp-values reported for survival analysis were measured by the Cox regression hazard ratio and log rank tests. Paired and unpaired Student’s t-tests were performed when the data points passed a D’Agostino‒Pearson normality test. In cases where the variables were not distributed normally according to the D’Agostino‒Pearson test (p ≤ 0.05), we applied the Wilcoxon test. To compare numbers between different groups, we applied Fisher’s exact test, or if the samples numbered at least five in each condition of the χ2 tests. All p-values are two-tailed. All p-values and statistical tests are mentioned in either the figures or legends. To test the similarity of the gene expression data of microarray and RNA-seq (http://www.nemates.org/MA/progs/overlap_stats.html).Statistical analyses and estimation of correlations in this study were performed using GraphPad Prism v.6. The significance was assessed via the Pearson correlation coefficient. The  RNA-seq  data, weAltogether, this study suggested that the differences in the gene expression profiles of pre- and postinvasive breast cancer do not present a new foundation route of malignancy. Indeed, the fundamental genetic alterations of SGAs occurring in the earlier stages of tumor development and further SGAs in later stages serve, in a forward evolution model, as a fine-tuning mechanism of those primary changes. Remarkably, we were able to apply a backward evolution model for cancer genome evolution, in which CNAs are selective events and serve as means to reverse the expression/direction of a proportion of the earlier SGAs. Our methodology introduces a new pipeline for cancer evolution studies, and our results draw a global portrait of the evolution of malignancy in breast cancer.


Pathogens hitting the plant cell wall is the first impetus that triggers the phenylpropanoid pathway for plant defense. The phenylpropanoid pathway bifurcates into the production of an enormous array of compounds based on the few intermediates of the shikimate pathway in response to cell wall breaches by pathogens. The whole metabolomic pathway is a complex network regulated by multiple gene families and it exhibits refined regulatory mechanisms at the transcriptional, post-transcriptional, and post-translational levels. The pathway genes are involved in the production of anti-microbial compounds as well as signaling molecules. The engineering in the metabolic pathway has led to a new plant defense system of which various mechanisms have been proposed including salicylic acid and antimicrobial mediated compounds. In recent years, some key players like phenylalanine ammonia lyases (PALs) from the phenylpropanoid pathway are proposed to have broad spectrum disease resistance (BSR) without yield penalties. Now we have more evidence than ever, yet little understanding about the pathway-based genes that orchestrate rapid, coordinated induction of phenylpropanoid defenses in response to microbial attack. It is not astonishing that mutants of pathway regulator genes can show conflicting results. Therefore, precise engineering of the pathway is an interesting strategy to aim at profitably tailored plants. Here, this review portrays the current progress and challenges for phenylpropanoid pathway-based resistance from the current prospective to provide a deeper understanding.  As the first cellular compartment encountered during pathogen attack, it is significant to assume the functions of cell wall in plant defense . The plaCsCCR was induced after a fungal infection [Lilium usitatissimum [AtMYC2 TFs that regulate JA reactions [Phenylpropanoid pathway providing the lignin-building monolignols is greatly triggered after the cell wall gets hit by pathogens . The firnfection . Similartissimum . Transcrtissimum ,28. To atissimum ,30,31,32tissimum . Genes teactions ,28. ThusMore recently, a link has been established for the role of key players from the phenylpropanoid pathway in broad spectrum disease resistance. A noteworthy example is the PAL genes which are found reliable for cell wall mediated immunity and involved in broad spectrum disease resistance. . The racHowever, the protective function and mechanisms, contributing to this immune homeostasis in different species are still uncovered and detailed information is required to validate the hypothesis to consider key players for a broad spectrum disease resistance (BSR) based approach to reduce yield penalties.The objective of this review is to provide detailed information about the progress and challenges in understanding the role of the major genes and transcriptome network probably involved in the biosynthesis pathway of the lignin/phenylpropanoid pathway for plant disease resistance mechanism and also provide brief information about the current hypothesis as well as open questions for future prospects in this direction. Additionally, an attempt has been made to bring all the information together for pathway based emerging players in disease response and possible models have been provided for various resistance mechanisms.The phenylpropanoid pathway has been constantly redrawn in recent decades, but now appears to be well established  36,37,3,337,38. p-coumaric acid kick start the general phenylpropanoid pathway [p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol, respectively [p-coumarate by a bifunctional phenylalanine and tyrosine ammonialyase (PTAL).The conversion activity of PAL and ammonia lyase of Phe into cinnamic acid and  pathway . The bioectively . The enzectively . Overallectively . Apart fectively  proposedArabidopsis thaliana by either silencing or deletion of functional mutations of genes in regulatory pathways. These studies were mainly focused on some gene families such as PAL, F5H. C4H, COMT, 4CL, CCR, CAD, HCT, C3H, CSE, and CCoAOMT. Some recent results related to the major genes in monolignol pathways for defense are listed in The phenylpropanoid pathway entails the biogenesis of various number of phenolics polymers and lignin, and these compounds contribute to various disease resistance mechanisms ,44,45,46It is generally assumed that transcriptionally activated genes involved in varied biosynthetic pathways result in the emergence of phenylpropanoids metabolites during the response of plants to infection . HoweverMany prediction methods including cis-regulatory elements of monolignol biosynthesis pathway genes have helped reveal the mystery of transcriptional regulation of phenylpropanoid pathways. Promoter and electrophoretic mobility shift assay (EMSA) analysis have supported the prediction and concrete results for complex transcriptional networks. There is a regulatory mechanism exhibited by the phenylpropanoid pathway at the transcriptional, post-transcriptional, and post-translational levels . The proThe key findings of the existence of AC elements in the promoters from various studies are widely accepted. Deep functional analysis of promoter region of the genes in the phenylpropanoid pathway revealed their modular organization and identified AC elements as central coordinator elements. Studies show that AC-rich elements correlating with the MYB transcription factor-binding motif are essential for coordinated pathway genes ,86,87. IPinus taeda lignifying tissue and discovered PtMYB4. In tobacco plant, the overexpression of PtMYB4 resulted in an increased expression of C3H, COMT, CCR, CCoAOMT, and CAD with the expression of 4CL and C4H genes reportedly unaffected but resulted in a decline in the expression of PAL genes. Moreover, the case was a little different in transgenic tobacco plants. Transgenic tomato plants did not respond to the PAL, C4H genes but there was a significant increase in expression of the monolignol-specific coding genes. Some transcriptional factors are found to act as repressors of lignin biogenesis [The role of MYB family is highly linked as an activator in the monolignol biosynthesis pathway. MYB46 and its homologous MYB83 were discovered to not only actively participate in lignin biosynthesis but redundantly activate the formation of secondary cell wall ,91. The ogenesis ,94,95,96ogenesis . The oveThe compounds generated by the phenylpropanoid pathways are one of the important reasons for its defensive functions. The genes in the phenylpropanoid pathway code for various compounds. Defensive properties are not only restricted to any class of phenylpropanoid, but are regulated by hydroxycinnamic acids and monolignols through various complex spectra of mechanisms. The genes responsible for the defensive compounds have been cloned in many crops. The biosynthesis pathway is governed by gene families, but the function of specific members is yet to be determined. The set of genes involved in biosynthesis pathways have some mechanisms of defense, including the role from lignification, utilization of secondary metabolites to elicitors and defense singling regulations. Important defense mechanisms are discussed below: The basal defense mechanism starts with the lignification of the cell wall innate response to plant diseases apart from its contribution to structural integrity . ComposiHeterogeneity and nature of monolignol linkages make it difficult to degrade and is reported to function as a barrier to limit the colony development or penetration process by pathogens, representing the basal defense mechanism. ,128. AftAtCAD5 was recorded higher in roots with lignification during the pathogen infection [Capsicum annuum L. [Gossypium hirsutum during pathogen infection [Furthermore, lignin-based compounds may hamper the multiplication and movement of pathogens ,132. Mannfection . DIRs  was checked on soybean after Phytophthora sojae infection and it was found that the SA level was regulated by the PAL genes [Beside the mechanism discussed above, it has been proposed that plant infestation initiates a rise in the activity of PAL, a key enzyme from the phenylpropanoid pathway. In plants, it is believed that SA formation is attained either through the isochorismate synthase (ICS) or the PAL catalyzed steps. SA is a key player in conferring resistance to disease and pathogens in various crops. SA dependent signaling regulates the activation of plant defense thereby warding off microbial pathogen attacks ,161,162 AL genes . Apart fAL genes  showed aAL genes . Duan etAL genes  revealedRac family was found to interact with OsCCR, which is a lignin pathway regulator [Xanthomonas was governed by the CCR-like gene and SNL6, which have an effect on lignin content of rice [In comparison with other resistance mechanisms, elicitor mediated signaling is of great importance. The whole sensing system relays via protein kinase or calcium depended signaling systems. It has direct relation with activation of phytohormone pathways, which in turn govern the activation of immune responses. For example, in a yeast-based experiment system, the involvement of defense regulating egulator . In a di of rice .P. syringae disturbed the expression of major enzymes of the phenylpropanoids pathways and also downregulated the ability of A. thaliana to photosynthesize [Ustilago maydis, a biotrophic fungus and causal agent of smut disease, tends to deploy effector proteins that repress the production of SA [Ralstonia solanacerum to overcome SA mediated defense [P. syringae Type III Effector (T3E), HopI1 impedes SA production by attacking the chloroplast localized chaperone [P. syringae T3E, HopZ1b, represses the phytoalexins precursor production by targeting a soybean (Glycine max) 2-hydroxyisoflavanone dehydratase. In apple, Venisse et al. [Pantoea stewartia [Generally, after penetration, pathogens exploit the metabolism of host cell penetration of the cell wall  and virunthesize . In maizon of SA  and simi defense . It was haperone . In simihaperone  revealede et al.  showed te et al. . Moreovetewartia .Crops are prone to attack by different pathogens causing various diseases and so the quest to breed for crops tolerant to diseases has never been more urgent and tasking till now. Diseases lead to an overall yield loss of about 16% globally . The utiOryzae Ssativa genome consists of nine OsPAL genes. Most of the OsPAL genes experience an upregulation during resistance interaction with R. solani, M. oryzae, and X. oryzae. Eight of the OsPAL genes are co-localized with QTLs responsible for resistant to multiple pathogens in rice. However, OsPAL9 shows no association with any QTL for resistance. For example, OsPAL1, OsPAL2, OsPAL3, and OsPAL4 are within the bounds of three QTLs associated with resistant for sheath blight qSB-2, qSBR2-2 [OsPAL5, and OsPAL6 are within the bounds of a QTL linked with bacterial blight resistance [OsPAL4, a mutant line bearing a deletion in the OsPAL4 gene was linked to a rise in susceptibility to three pathogens, X. oryzaepv. oryzae, R. solani, and M. oryzae. This revealed that contribution of OsPAL4 to broad spectrum resistance is achieved by the QTL located on chromosome no. 2, which is responsible for disease resistance in rice. In addition, OsPAL4 mutant showed an increase in susceptibility to both X. oryzaepv. Oryzae and M. oryzae as compared to the wild type, confirming that OsPAL4 mutant affects resistance to disease in a negative fashion through altering expression of other OsPAL genes, such as OsPAL6 [OsPAL6 is involved in the regulation of M. oryzae resistance invaded from roots by promoting phytoalexins and SA synthesis, which then turns out to be influential in JA- and ethylene-dependent signaling. Furthermore, beside the contribution of OsPAL06, it is likely that OsPAL1, OsPAL2, OsPAL3, OsPAL4, OsPAL5, OsPAL7, and OsPAL8 participate in the rice—M. oryzae interactions. Following the rice yellow mottle virus infection, there was an increase in the synthetization of OsPAL1 and OsPAL2 proteins During rice–Xanthomonas oryzae pv. oryzae interactions, OsPAL01 also showed distinctive expression [OsPALs do not just play a part in reactions involving resistance but also play a role in susceptible reaction and diverse OsPALs take part during various points of rice–pathogen interactions. It is suggested that OsPAL may play a key role in broad spectrum resistance. The adaptation of M. oryzae is carried out in such a way that its virulence proteins cannot be identified by the resistant gene product [OsPAL1 and OsPAL6 in rice are downstream of defense-responsive pathogen species or race-nonspecific resistance, it can also be suggested that resistance mediated by PAL may be durable due to the fact that its product does not involve pathogen recognition [The vast majority of the phenylpropanoids have been shown to confer broad spectrum antimicrobial activity and also help plants defend against microbial diseases . For exa qSBR2-2 , OsPAL5,sistance , and a ssistance . Using Isistance  identifis OsPAL6 . Duan L.s OsPAL6  used thepression ,192,193. product . Since tognition . Capsicum annum). The R gene-mediated and basal resistance to infection by Xanthomonas campestris pv. vesicatoria is contributed by the activity of PAL in pepper plants. A study carried out by Kim et al. [CaPAL gene is necessary for inducing SA-dependent defense signaling activities in plants [Xanthomonas campestris pv. vesicatoria infection, CaPAL1-silenced pepper plants displayed an increase in susceptibility. Likewise, in A. thaliana, there was an increase in resistance against Hyaloperonospora arabidopsidis and Pseudomonas syringaepv. tomato (Pst) and in plants with overexpression of CaPAL1 suggesting SA build-up in the course of Pst infection was upregulated by the constitutive overexpression of CaPAL1 in Arabidopsis. In a recent study, Shine et al. showed that SA functions in conferring resistance against oomycete pathogen P. sojae and bacterial pathogens P. syringae and the build-up of phenylalanine substrate was as a result of silencing GmPAL with ICS-catalyzed and PAL catalyzed reactions playing a combined role in soybean defense. The PAL gene family consists of three to four genes in pepper plant (m et al.  showed tn plants . This reBrachypodium with BdPAL1 and BdPAL2 both playing a major role in the biogenesis of lignin and also both being expressed at a higher rate in stem tissues that form lignin as compared to the other six BdPAL genes. The knockdown of BdPAL lead to a surge in susceptibility to M. oryzae and Fusarium culmorum [The first report of PAL gene was done in 1961 and over a decade, the number of studies in different plants have shown the wide distribution of PAL gene families in higher plants, and is also reported in yeast and some bacteria [culmorum .X. oryzae pvoryzae and Magnaporthe oryzae with no consequent effect on yield in rice. It was revealed that the mRNAs of OsPAL genes which are associated with defense in plants was bounded by bsr-k1 protein, thus, promoting their turnover. Furthermore, the OsPAL mRNA build-up in the bsr-k1 mutant was a result of decline in mRNA turnover due to the loss of function of bsr-k.Interestingly, various genes involved in BSR have been discovered in crops , only a The phenylpropanoid pathway is an important center of attraction because of its importance in the production of defense related compounds and also because it has great involvement against pathogen attempts of cell wall weakening strategies. Advances in the last decade have supported that pathway engineering in plants can bring satisfactory solutions, keeping broad spectrum disease resistance and yield security in parallel. The plethora of available research on the phenylpropanoid pathway continue to show evidence of its importance and efficiency. In this review, we discussed all the possible aspects related to the phenylpropanoid pathway which could be important elements for disease resistance mechanisms  includin


Current bans on the use of antibiotics in livestock feed have led to increasing demand for alternatives to antibiotics (ATA). One popular alternative is chestnut tannins (ChT). While there is growing evidence of the immune benefits of using phytobiotics, such as ChT, there is currently minimal information on the effect of tannins on the immune pathway of the host. A previous study discovered a large upregulation of IL-6 in broiler chicks at day 6 when provided with 1% ChT from hatch. In regard to potential immune modulation, ChT appear to influence host immunity via an IL-6 mediated response, which could be beneficial in host defenses against pathogens at the early stages of broiler growth and development. A critical pathway identified in the regulation of the immune system is the JAK-STAT signaling pathway. The role of JAK-STAT pathway is altered by the addition of ChT in the diet. By demonstrating the changes in the kinome of the broiler model, the information in this study will provide further insights into potential ATA to improve poultry health.The objective of this study was to identify the phosphorylation events associated with host immunity with the inclusion of chestnut tannins (ChT) in the diet. A total of 200 male day-of-hatch Cobb 500 chicks were randomly assigned to two treatment groups, totaling 50 chicks per pen per experiment (this study was repeated two times). The treatments were as follows: (1) control feed—normal starter feed (n = 50), and (2) 1% ChT inclusion feed (n = 50). The ceca were collected on each necropsy day for analysis via (1) a peptide array to provide tissue immunometabolism information from the host, and (2) quantitative PCR for mRNA expression. Of the top three immune pathways, the data identified the T-cell receptor signaling pathway, the chemokine signaling pathway, and the JAK-STAT signaling pathway. The results showed significantly altered phosphorylation of JAK and STAT peptides within the JAK-STAT pathway. These results support the mRNA expression data with the upregulated IL-6 response, due to the significant phosphorylation of IL6ST, JAK, and STAT peptides. In regard to immune modulation, ChT appear to influence host immunity via an IL-6 mediated response which could be beneficial in host defenses against pathogens at the early stages of broiler growth and development. Therefore, it is suggested that the role of the JAK-STAT pathway is altered by including ChT in the diet. Castanea sativa) [Antibiotic growth promoters (AGPs) were originally incorporated into livestock feed to promote better health and performance. However, with the ban of antibiotics in feed , there i sativa) ,3. Phyto sativa) . Plant-b sativa) . Tannins sativa) ,7. This  sativa) ,8,9,10.Studying phosphorylation events provides information on the mechanism of post-translational modification, which offers insight in cellular and tissue phenotypes ,12. The All experiments conducted were in accordance with guidelines set by the United States Department of Agriculture Animal Care and Use Committee (USDA ACUC #2019001), which meets all federal requirements as defined in the Animal Welfare Act, and the Humane Care and Use of Laboratory Animals. A total of 200 male day-of-hatch Cobb 500 chicks were obtained from a local commercial hatchery and assigned to two treatment groups, totaling 50 chicks per pen per experiment. The treatments were as follows: (1) control feed—corn/soy starter feed (n = 50) and (2) 1% ChT inclusion feed (n = 50). The chicks were randomly distributed into each group with fresh pine shavings, water, and the starter diet ad libitum. The chicks were kept under 96 h light and then transitioned to 18 h light and 6 h dark cycle until the end of the study. All treatments included a corn/soybean-based crumble diet, but differed in AGP or tannins inclusion. The diets were formulated to meet or exceed broiler requirements, as shown in On each necropsy day, ten birds per group were selected by random, euthanized via cervical dislocation, and necropsied on days 2, 4, 6, 8, and 10 of each separate experiment. Both ceca were removed, flushed with phosphate buffered saline (PBS), and flash frozen in liquid nitrogen to preserve the kinase enzymatic activity. The frozen tissues were stored at −80 °C until further processing. Therefore, 100 ceca were collected on each separate experimental trial, for a total of 200 ceca collected at the end of both experiments.Salmonella enterica throughout the study.During each necropsy, the cecal contents (0.25 g/bird) were collected and serially diluted to 1:100, 1:1000, 1:10,000, and 1:100,000 of 1× PBS. These contents were spread onto XLT4 for Salmonella detection for confirmation purposes. These plates were incubated at 37 °C for 24 h. Furthermore, an enrichment step was also performed for detection purposes: 100 uL of the cecal contents were pre-enriched in Rappaport-Vassiliadis broth for 24 h at 37 °C. None of the birds showed the presence of For the phenotype readout, a peptide array was utilized to provide tissue immunometabolism information from the host. At three of the timepoints , three whole ceca from three randomly selected birds—stored at −80 °C—were defrosted for analysis. Each distal end of the cecal sample was weighed to obtain a consistent 40 mg sample for the array. The samples were homogenized using an Omni International Bead Ruptor Elite  in 100 uL of lysis buffer , 1% Triton X-100, 2.5 mM sodium pyrophosphate, 1 mM Na3VO4, 1 mM NaF, 1 μg/mL leupeptin, 1 g/mL aprotinin, and 1 mM phenylmethylsulphonyl fluoride). All products were obtained from Sigma Aldrich , unless indicated. Following homogenization, the peptide array protocol was carried out with previously described alterations ,15. The ® Plus kit  and evaluated with a NanoDropTM 2000 Spectrophotometer . Ceca stored in RNALater were used for RNA isolation with the Qiagen Rneasy Plus Kit. The ceca were cut longitudinally to expose the lumen, and any remaining fecal matter was gently removed with forceps. For each group, ten ceca were processed per experiment for qRT-PCR. Cytokine mRNA expression levels were ascertained using RT-PCR TaqMan based assay with 28S as the reference gene. The RNAs were stored at −80 °C until plate setup. The cytokines IL-1β, IL-6, IL-8, IL-17, and IFN-γ were quantified utilizing a previously published method [t method [Total RNA was extracted using a Qiagen RNeasyd method . The prid method . The plat method  and exprhttp://saphire.usask.ca/saphire/piika/index.html), a tool designed for in silico analysis of phosphorylation sites [Once the peptide microarrays finished running , data normalization was performed for the kinome array using the PIIKA2 online platform  on day 6 with no change in phosphorylation state on days 4 and 10 (as indicated by the hyphen). JAK2 (p ≤ 0.01) also appeared to be a target for altered phosphorylation, as seen on days 4 and 6 in 1% ChT-fed chicks compared to the control. Another peptide of interest is the IL6ST peptide (Interleukin-6 receptor subunit beta), which had altered phosphorylation on days 4 and 10 (p < 0.05). The array also identified significant altered phosphorylation of STAT1, 3, and 5B activities on all tested days (p < 0.05). Therefore, the increased presence of JAK and STAT peptides indicated a stimulation in increased IL6 to stimulate JAK-STAT signaling pathway due to the inclusion of 1% ChT in the diet.For the kinome array, one of the major phosphorylated pathways identified to be affected by ChT was the JAK-STAT signaling pathway for all days tested. The other affected immune pathways identified on the kinome array were T-cell receptor signaling pathway and chemokine signaling pathway. The resulting phosphorylation events within these pathways are listed in Demands for alternatives to antibiotics, such as ChT, in livestock feed have increased globally in the past several years. Growing research is showing the importance of the gastrointestinal system and its role in host immune modulation ,23,24. NThe JAK family proteins are the initial receptors present to initiate the JAK-STAT pathway. In the chicken, JAK1 expression is found in the bursa and thymus at high levels, perhaps due to the post-translational modification activity of JAK1 kinase in these locations . A previThe kinome data provides further evidence of this trend with the decreasing phosphorylation events within the T-cell receptor signaling pathway and chemokine signaling pathway across all three days tested; see This study aimed to provide phosphorylation details regarding the broiler chick immune response when ChT are included into the grower diet. The ChT appear to be acting as an immune activator due to the high upregulation of IL-6 proinflammatory cytokine. In considering practical application, recent studies suggest the usage of encouraging proinflammatory states for beneficial purposes of stimulating the immune system at early stages to improve resistance against pathogens . As a keSupplementing broiler diets on day 6 with 1% ChT provided evidence of modulation based on the alteration of JAK-STAT signaling pathway in the host. Based on the kinome array, the JAK-STAT pathway was one of the most altered signaling pathways involved in the immune response. This was further evidenced by the significant upregulation of IL-6 proinflammatory cytokine on day 6. This suggests a role of the JAK-STAT pathway in altered immunomodulation via IL-6 signal transduction pathway. However, more research will need to be conducted to further elucidate the effects of ChT on immunity and its role.


Thousands of pathway diagrams are published each year as static figures inaccessible to computational queries and analyses. Using a combination of machine learning, optical character recognition, and manual curation, we identified 64,643 pathway figures published between 1995 and 2019 and extracted 1,112,551 instances of human genes, comprising 13,464 unique NCBI genes, participating in a wide variety of biological processes. This collection represents an order of magnitude more genes than found in the text of the same papers, and thousands of genes missing from other pathway databases, thus presenting new opportunities for discovery and research.The online version contains supplementary material available at (doi:10.1186/s13059-020-02181-2). The molecular mechanisms underlying biology are often outlined as pathway diagrams. In textbooks and on whiteboards, these depictions are fundamental to a biologist’s training. As mental models for practitioners, they serve as scaffolds for hypotheses and integrating new knowledge. And in the scientific literature, pathway figures are the pinnacle of communication for published work, synthesizing diverse sources and types of data spanning decades into a coherent model. Though often published only as static images, pathways express dynamic interactions. Common examples include metabolic cycles, gene regulation, and signaling cascades. Depicted interactions play out over a spectrum of electrochemical, enzymatic, and developmental timescales.each month in recent years and less than 3% of these are sourced from a pathway database [When properly modeled as an interaction network and annotated with standard identifiers, pathway knowledge can be conveyed with greater precision in formats amenable to computational analysis. Distinct from static images, pathway models can be used in enrichment analyses , enhancedatabase .In this study, we have identified pathway figures published over the past 25 years and characterized their content in terms of recognized gene symbols by optical character recognition (OCR). While it is more common to process text from the abstract and body of papers in order to extract genes and other biological concepts including interactions, knowledge extraction from published pathway figures is relatively rare and incomplete –22. In aThe goal of this work was to identify the human gene content in a comprehensive collection of published pathway figures, to characterize its biological relevance, and to increase meaningful, FAIR  access tWe identified and characterized 64,643 pathway figures published between the years 1995 and 2019. Starting with 235,081 figures from a PMC image query that specified the 25-year date range and keywords covering diverse types of pathways, machine learning was applied to more precisely distinguish figures containing molecular interaction diagrams from those depicting other types of pathways  or pathway-related content .diluted set of figures containing a high proportion of non-pathways. Two rounds of machine learning effectively concentrated actual pathway figures. The second and final round relied on a set of 15,406 figures manually classified by a domain expert to train a model distinguishing pathway figures from other figures with 91.88% precision, 91.88% recall, and a Matthews Correlation Coefficient [Relying solely on the linearly ranked PMC results  would have resulted a relatively fficient  of 0.82.Prior to any gene detection by OCR, the papers containing the 65k set of pathway figures were characterized by publicly available annotations. The pathway figures came from 56,095 papers authored by 216,542 unique authors and are published in 3,453 journals. Obviously, not all co-authors are involved in preparing a pathway figure in a given paper, but for comparison, the most successful effort to crowdsource pathway knowledge by the WikiPathways database has fewer than 800 unique authors.The papers containing pathway figures can be characterized by paper-level annotations, for example disease ontology terms from Europe PMC and genes recognized in the text by PubTator. A subset of 29,187 (52%) pathway-figure containing papers had at least one disease ontology terms annotation from Europe PMC. The top 10 most frequent disease ontology terms annotating these papers are Cancer , Infection (19%), Defects (15%), Tumor (9.3%), Diabetes (4.3%), Hypoxia (2.0%), Depression (1.3%), Obesity (0.8%), Ischemia (0.7%), Atherosclerosis (0.4%), and Other (9.2%). PubTator extracts genes and other concepts from the abstract and body text of PMC-indexed papers by natural language processing . While fHaving identified and characterized a set of papers containing pathway figures, the primary goal of this study was to extract their human gene content by an OCR pipeline customized for pathway figures , 23. TheOf the 64,643 pathway figures identified by image classification, 58,962 (91%) figures had at least one human gene recognized by our pathway figure OCR pipeline. A total of 1,112,551 instances of human genes were recognized, consisting of 13,464 unique human NCBI Genes. On average, there were 18.9 genes recognized per figure, compared to only 3.4 genes recognized in the text of the same papers by PubTator. PubTator found a tenth as many genes  in the text of these same papers overall; only half of the papers (53.5%) mentioning one or more genes in the text. In our pathway figure OCR results, there were over 600 figures with more than 100 genes each. While many of the largest figures are interaction networks, the largest with 385 recognized genes is an augmented KEGG pathway where the authors properly listed the individual gene family and paralog members referenced generically in the original . At the The top 10 human genes identified in pathway figures representing unique families are MAPK1 , AKT1 (14%), PIK3CA (10%), NFKB1 (8.9%), KRAS (7.6%), MTOR (7.5%), MAP2K1 (6.2%), TNF (5.6%), RAF1 (5.3%), and TP53 (5.1%). Compared to genes extracted from the text of the same set of papers containing pathway figures, the same trend of cancer-related biology dominates the content. In more detail, this top 10 set includes four of the top five genes found in the text of the same papers by PubTator: MAPK1, AKT1, MTOR, and TP53. Figure Seeking to optimize across coverage, performance, and interpretability, we defined a subset of figures with at least seven distinct NCBI Genes. Compared to the overall set, these 28,836 pathway figures contained 13,216 (98%) unique genes, thus retaining the coverage and novelty of the collection. Among these 28,836 pathway figures, 28,520 (99%) were significantly associated with at least one Gene Ontology  term by enrichment analysis, indicating general biological relevance. In terms of disease relevance, we found 20,227 (70%) pathway figures significantly associated with at least one disease ontology term , and 98%The initial characterization of published pathway figures and their gene content revealed a novel resource of relevant pathway knowledge that is practically inaccessible to researchers. The following examples demonstrate how this resource could be utilized in a variety of applications.With over 600,000 papers added to PMC in the last year, researchers are resigned to merely sampling the work most relevant to them via search engines, feeds, subscriptions, and recommendations. While figure captions are accessible to text-based processing and indexing, the actual contents of figures remain hidden to any commonly available search engine . The systematic identification of genes in pathway figures enables access to this content through new and existing tools.https://europepmc.org/annotations). While these typically derive from text-based processing, the same deposition and integration system could be used to accept gene-paper mappings based on figures. Querying one or more genes at Europe PMC would then return paper results containing both text and figure references to those genes.Search engines commonly index papers by the genes found in the abstract, body, and caption text. Europe PMC goes further by supporting community-contributed mappings between genes and papers  that processes the latest publications and preprints on a daily basis. The gene-paper mappings from pathway figures would be a natural fit for an indexing system that links papers via their contents. Furthermore, the characterization of gene sets as demonstrated above could provide mappings from papers to disease ontology terms and other gene-based and pathway-based annotations. A feed service that could produce a regularly updated set of papers that contained relevant pathway figures would be a welcome innovation to researchers attempting to stay abreast of scientific literature.As another example, the Chan Zuckerberg Initiative is working on a new literature feed service called Meta (https://gladstone-bioinformatics.shinyapps.io/shiny-25years) to enable filtering, searching, and viewing the full collection of 65k pathway figures by enriched disease terms, genes, date, and various publication metadata fields . There are 221 pathway figures in this collection that can be rapidly queried and viewed by the same three-stage procedure described above and in Fig. http://covid.wikipathways.org) as part of the COVID-19 Disease Map initiative (https://covid.pages.uni.lu/map_curation) [As a topical demonstration of the tool, a second version was produced focusing on COVID-19 related pathways as defined by the COVID-19 Open Research Dataset (uration) .https://biothings-explorer.readthedocs.io) [drugs that bind components of pathways associated with a disease of interest. By defining an API that recognizes standard paper and gene identifiers in a JSON file export of pathway figure-based gene sets, the 1.1M gene-paper links from this study can be used to bridge query paths to other content in the knowledge graph. The addition of disease annotations and future extraction of metabolites, drugs, and concepts from the OCR results will establish additional bridges and reinforce paths inferred by computational reasoning. This work is in active development as part of the NCATS Biomedical Data Translator program, targeting critical use cases, such as drug repurposing (https://ncats.nih.gov/tidbit/tidbit_04.html).This source of annotated pathway information is also finding utility in an advanced platform for distributed knowledge integration. The BioThings Explorer platform includes a collection of APIs semantically defining inputs and outputs that comprise a knowledge graph (docs.io) . The plaGiven the 25-year span of this new pathway resource, it was natural to reflect on the role of pathway figures in scientific discovery. The R Shiny app previously described can be used by any researcher or historian to investigate the story of particular diseases and genes from a pathway perspective. Tracing the development of the Hippo signaling pathway as one example demonstrates this potential Fig. .Fig. 3Mβ, Notch, and Wnt signaling. The Wts gene (LATS1 in humans) was discovered in Drosophila in 1995 [The Hippo signaling pathway controls organ size in animals by regulation of cell proliferation and apoptosis. The components of the Hippo signaling pathway are highly conserved , and man in 1995 , 34, and in 1995 , 36, ini in 1995 .In our 65k pathway figure collection, the first published figures representing the Hippo signaling pathway appeared in 2007 , 39, morhttps://reactome.org/content/detail/R-HSA-2028269). Even with the advent of pathway databases, evolving and emerging pathway knowledge can be accessed via our pathway figure OCR pipeline once published and publicly indexed, whereas traditional database curation might lag by months, by years or indefinitely. In the next section, this example is also used to demonstrate the utility of having access to this history in a computational format for the first time, enabling clustering, visualization, and other applications.Access to pathway diagrams and their gene contents provides a new way to track the discovery and depiction of key molecules and interactions for a given pathway over time; many of these pathway figures predate any pathway database. For the Hippo pathway example, there were 31 representations of the pathway in published literature spanning the 13 years prior to its first entry in a database in 2012  pathway figures can be defined for use in enrichment analysis. By contrast, only 1072 (1.9%) papers had 10 or more genes identified in the text by PubTator. Also of note, this set of 49% of the largest pathway figures retains 97%  of the unique human genes found in the overall 65k collection. Among the set of 32,277 pathway figures identified for use in enrichment analysis, there were 878 figures that shared the exact same gene content with at least one other figure and 4,937 figures entirely contained by one or more other pathway figures.In order to assess the redundancy and hierarchical structure among pathway figures in more detail, a sample subset of 55 Hippo signaling pathway figures was clustered by gene overlaps Fig. . The oveFor the purpose of an enrichment analysis, any of these pathways have the potential to provide a highly specific result with greater context and interpretability than a single, so-called canonical, Hippo signaling pathway. This potential argues against additional pre-filtering of the pathway figure set. Furthermore, many enrichment tools already employ post-filtering of results by, for example, a Jaccard distance measure to handle ontologies with even greater redundancy and higher degree of nesting. The same approach could optionally be applied to enrichment results from these pathway figure-based gene sets as part of a researcher’s exploratory analysis.There is a vast resource of pathway knowledge trapped in the form of published pathway figures. We have identified these figures and extracted their gene content to make this resource accessible and to demonstrate its potential to enhance biomedical research. We found 64,643 pathway figures in publications dating from 1995 to 2019 and identified 1,112,551 occurrences of human genes in total . Much of this content represents novel pathway knowledge that is present neither in the text of papers, nor in pathway databases. The extraction of drugs, metabolites, and disease terms from these same pathway figures is now a more tractable project, as is the identification of genes from other species, by expanding the lexicon used to match against the OCR results. A greater challenge lies in the extraction of interactions, subcellular compartments, and other graphical representations of biology beyond just the molecules. While the OCR of text from images is a well-studied problem with widely available solutions, a more customized machine learning approach will be required for these non-standard graphics. Adding to the challenge, the process of modeling interactions in a pathway involves more than simply retracing what is typically provided in a pathway figure. A certain level of domain expertise is required for curators of pathway databases as their task requires independent interpretation and investigation. Nevertheless, the refined collection of gene-characterized pathway figures presented here can be used as a reference dataset by researchers interested in this challenge.Oh, the figures we have seen! Having scanned many thousands of pathway figures as a collection, the most obvious point to make is that standardization is desperately needed. Standards for pathway models have been around for decades [Despite unlocking the basic contents of published pathway figures, this work only partially mitigates gross deficiencies in current pathway knowledge representation and communication.  decades –52 and h decades –57. Like decades .post hoc extraction of knowledge from published pathway figures can serve to make this content more findable, accessible, interoperable, and reusable. The gene sets extracted from these figures can be indexed to enhance literature searches, they can create and reinforce links in knowledge graphs, they can inform the historiography of gene and pathway discovery, and they can enable pathway figure-based enrichment analysis. We are currently working with NDEx to host the initial set of gene-annotated pathway figures for enrichment analysis (https://home.ndexbio.org). The annotated pathway figures are also being prioritized by their novel gene content and disease associations for manual curation as proper models in pathway databases. Finally, the interactive pathway figure tool allows anyone to explore the complete set of 65k figures by various metrics and metadata (https://gladstone-bioinformatics.shinyapps.io/shiny-25years).In the meantime, the pathway: signaling, signaling, regulatory, disease, drug, metabolic, biosynthetic, synthesis, cancer, response, and cycle. These were determined based on exploratory queries and referencing the first two levels of pathway ontology terms [A PMC image query URL was composed, specifying a date range starting at 1995-01-01. Exploratory queries previously identified 1995 as the first year with accurately indexed pathway figures. Keywords in the query were specified as an OR set of the following pathway types together with the word gy terms . The queactual pathway figures at three points: the first thousand figures (of 235k) contained 66.3% pathways, the middle thousand contained 35%, and the final thousand contained fewer than 10% . Of the 18 figures classified as non-pathways, two were composite figures that included a pathway as a minor panel in figure that contained a lot of non-pathway content. Composite figures were typically excluded from the “pathway” training sets in our manual classification in order to avoid recognizing gene occurrences in figure elements unrelated to pathways, so these were conservatively included in the false positive count. Of the remaining 16 non-pathways, only three had three or more genes subsequently detected by our pathway figure OCR pipeline (see next section), suggesting the majority of false positives could be effectively ignored.https://github.com/wikipathways/bioentities). The pipeline output is a table of pathway figures associated with sets of recognized genes with human NCBI Gene identifiers. Paper and figure metadata including titles and captions are maintained along with additional information such as the raw OCR results, the normalized and transformed symbols, and the lexicon source that was matched.The set of pathway figures was then fed into our pathway figure OCR pipeline , 23. BriThere were three non-composite false positive cases that contained three or more human genes: a diagram of nerve fibers with gene markers , a meta-Annotations on the 56,095 papers containing pathway figures were retrieved from the PMC query site and web services, including authors, journal titles, paper titles, paper identifiers, publication dates, figure titles, hyperlinks, and captions.europepmc R package [Disease annotations for 29,187 papers were available from Europe PMC and collected using the  package . A less Gene associations for 30,036 papers were available from PubTator and downloaded as NCBI Gene-to-PMID mappings from the PubTator FTP Service. A PMID-to-PMCID mapping file from the PMC FTP Service enabled comparison with our PMCID-indexed pathway figures and extracted gene sets.Gene Ontology and disease annotations for pathway figures were determined by performing enrichment analysis on the sets of figure-extracted genes against ontology-associated gene sets. The source of disease annotations was the “knowledge” channel of the DISEASES database  filteredAdditional file 1 Review history.


Qi She Pill (QSP) is a traditional prescription for the treatment of neuropathic pain (NP) that is widely used in China. However, no network pharmacology studies of QSP in the treatment of NP have been conducted to date.  To verify the potential pharmacological effects of QSP on NP, its components were analyzed via target docking and network analysis, and network pharmacology methods were used to study the interactions of its components.  Information on pharmaceutically active compounds in QSP and gene information related to NP were obtained from public databases, and a compound-target network and protein-protein interaction network were constructed to study the mechanism of action of QSP in the treatment of NP. The mechanism of action of QSP in the treatment of NP was analyzed via Gene Ontology (GO) biological process annotation and Kyoto Gene and Genomics Encyclopedia (KEGG) pathway enrichment, and the drug-like component-target-pathway network was constructed. β2-adrenergic receptor, HTR2A, and calcitonin gene-related peptide. In total, 53 GO entries, including 35 biological process items, 7 molecular function items, and 11 cell related items, were identified. In addition, eight relevant (KEGG) pathways were identified, including calcium, neuroactive ligand-receptor interaction, and cAMP signaling pathways.  The compound-target network contained 60 compounds and 444 corresponding targets. The key active compounds included quercetin and beta-sitosterol. Key targets included PTGS2 and PTGS1. The protein-protein interaction network of the active ingredients of QSP in the treatment of NP featured 48 proteins, including DRD2, CHRM,  Network pharmacology can help clarify the role and mechanism of QSP in the treatment of NP and provide a foundation for further research. Neuropathic pain (NP) is a common condition globally . With a Qi She Pill (QSP) has been approved by the China Food and Drug Administration , and it is widely available in China . QSP is Preclinical pharmacological studies reported that QSP has analgesic effects and obvious anti-inflammatory effects against acute and chronic inflammation . PatholoThe development of network pharmacology  has beenAlthough the analgesic effects and chemical profiling of QSP have been reported, the active compounds in QSP and the specific molecular mechanisms of QSP in treating NP are unclear, and network pharmacology-based prediction of the bioactive components and their target pathways has not been performed. Therefore, the present study explored the pharmacological mechanisms by which QSP alleviates NP and investigated the relationships among herbs, compounds, and target genes by employing QSP-based network pharmacology. First, we collected information on the bioactive compounds in QSP and retrieved candidate target genes from public databases. Network analysis was then performed to connect compounds in QSP with their target genes and related signaling pathways. Finally, based on the results of network analysis, multicompound, multitarget, and multipathway mechanisms related to QSP were predicted. The workflow is shown in The chemical components of CS, BC, CR, STR, and HMM meeting the criteria of oral bioavailability (OB) >30% and drug likeness (DL) >0.18 were selected as candidate active components using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database , and thePotential protein targets of QSP were screened using the TCMSP database, and all retrieved target proteins were corrected to the official symbols using the UniProt database. The network diagram of “active component-biological target” was constructed using Cytoscape 3.2.1 software . Nodes iIn this study, “neuropathic pain” was used as the search term to retrieve recognized biological targets using various databases , HTR7, OPRM1, HTR2A, SLC6A4, HTR2C, CHRM1, and calcitonin gene-related peptide (CALCA). The interaction between the target and the target is 18 sides. Analysis of the network of active ingredient-target interactions revealed that the network map contained 90 nodes and 296 edges. The 90 nodes included 42 active components of QSP in blood and 48 targets of QSP. The active ingredients of QSP and NP target network are shown in Using the GO bioprocess enrichment analysis function of the DAVID platform, the functions of the 48 proteins in the PPI network of QSP in the treatment of NP were studied, and 53 GO entries were determined using a false discovery rate (FDR) of <0.05. The 53 GO entries are listed in Supplementary KEGG pathway enrichment analysis was performed using DAVID. The pathways of 48 proteins involved in PPI network of NP-related targets of QSP were analyzed via pathway enrichment, and 24 signaling pathways were obtained. According to the principle of FDR <0.05, eight signaling pathways, including calcium signaling and neural active ligand-receptor interaction signaling pathways, were identified, indicating that the active components of QSP can act on these signaling pathways in the treatment of NP. The drug-active ingredient-target-pathway network model map of QSP was constructed using Cytoscape 3.2.1 software. The map included 103 nodes, including 5 drugs, 42 active components, and 48 target proteins. The metabolic pathways were connected by 444 edges to form a complete network. TCMSP is a system-level pharmacological database of TCM that provides systematic TCM information, and it is a platform for the development of new drugs for the treatment of human diseases. After a critical review of pharmacological and clinical knowledge, the TCMSP collected all 499 herbs registered in the 2010 edition of the Chinese Pharmacopoeia, totaling 12,144 compounds . BATMAN-QSP can relieve pain and promote blood circulation. The drug has been widely used in China. Clinical studies revealed that QSP can significantly improve mild-to-moderate NP and improve the quality of life of patients with mild-to-moderate NP, especially concerning physiological function, social function, emotional function, vitality, and other aspects. In a number of randomized, double-blind, placebo-controlled studies, improvements in dysfunction associated with mild-to-moderate NP were observed in both the QSP and placebo group, although the improvement was significantly better in the QSP group . To studPPI networks are composed of individual proteins interacting with each other to participate in biological signal transmission, gene expression regulation, energy and substance metabolism, cell cycle regulation, and other aspects of life processes. It is of great significance to understand the functional connection between proteins . EnrichmNetwork pharmacology combines the concepts of systems biology and multidirectional pharmacology . It explThe network pharmacology analysis of QSP identified 444 compounds in six herbs, and 48 of the compounds in the six herbs were screened to identify NP-related target genes. This study demonstrated that network pharmacology studies can reveal close interactions between multiple components and multiple targets. The network pharmacology approach of this study provides another research strategy for a comprehensive understanding of the mechanism by which QSP treats NP.


Meanwhile, the corresponding metabonomic profiles were used to explore differentially induced metabolic markers thus providing the metabolic mechanism of HLJDT in treating MI. The results demonstrated the myocardial protection effect of HLJDT on ischemia by a multicomponent-multitarget mode. This study highlights the reliability and effectiveness of a network pharmacology-based approach that identifies and validates the complex of natural compounds in HLJDT for illustrating the mechanism for the treatment of MI.Myocardial ischemia (MI) is one of the most common cardiovascular diseases with high incidence and mortality. Huang-Lian-Jie-Du-Tang (HLJDT) is a classic traditional Chinese prescription to clear “heat” and “poison”. In this study, we used a deliberate strategy integrating the methods of network pharmacology, pharmacodynamics, and metabonomics to investigate the molecular mechanism and potential targets of HLJDT in the treatment of MI. Firstly, by a network pharmacology approach, a global view of the potential compound-target-pathway network based on network pharmacology was constructed to provide a preliminary understanding of bioactive compounds and related targets of HLJDT for elucidating its molecular mechanisms in MI. Subsequently,  Acute myocardial ischemia (AMI) refers to a pathological state in which blood perfusion is reduced due to coronary artery occlusion, insufficient blood flow, or oxygen supply. It is one of the most common cardiovascular diseases with a high incidence rate and high mortality rate . StudiesNetwork pharmacology is one of the emerging strategies based on multi-disciplinary technologies such as system biology, multi-directional pharmacology, computational biology, and network analysis, which systematically reveals the core molecular targets and pharmacodynamics methods of TCM . In thisCoptis chinensis Franch (Huanglian 9 g), the radix of Scutellaria baicalensis Georgi (Huangqin 6 g), the cortex of Phellodendron chinense C.K. Schneid (Huangbo 6 g) and the fructus of Gardenia jasminoides J. Ellis  (Coptis chinensis Franch and the cortex of Phellodendron chinense C.K. Schneid. Berberine and Phellodendron amurense are the focuses of current studies. 2) Flavonoids: mainly from the radix of Scutellaria baicalensis Georgi. The representative components are baicalein, scutellarin, and baicalin. 3) Iridoids: mainly from the fructus of Gardenia jasminoides J. Ellis and its representative component is gardenside (Huang-Lian-Jie-Du-Tang (HLJDT) is a classic traditional Chinese prescription to clear “heat” and “poison”, which was first published in Gehong’s “elbow reserve emergency prescription”. It consists of the rhizoma of zi, 9 g) . Modern zi, 9 g) . Recent zi, 9 g)  Studies rdenside . Althougin vivo experimental verification of the efficacy was performed in a rat MI model by ligation of the coronary artery. The metabonomics approach was applied to explore differentially induced metabolic markers, thus providing the metabolic mechanism of HLJDT in treating MI. This study highlights the reliability and effectiveness of a network pharmacology-based approach that identifies and validates the complexity of natural compounds in HLJDT for illustrating the mechanism of action in the treatment of MI. The overall flowchart for elucidating the mechanism of HLJDT in the treatment of MI is illustrated in In this study, we used a deliberate strategy integrating the methods of network pharmacology, pharmacodynamics, and metabonomics to investigate the molecular mechanism and potential target of HLJDT for treatment of MI. Firstly, an MI-related “potential compounds-target-pathway” regulatory network was generated by network pharmacology to identify potential bioactive compounds and related targets of HLJDT. Subsequently, http://lsp.nwu.edu.cn/)  , which iedu.cn/)  were useedu.cn/) .http://www.genecards.org, a database providing a detailed genome, proteome, transcription, genetic, and functional overview of all known and predicted human genes) and the Online Mendelian Inheritance in Man database (OMIM) to collect target genes related to MI. The common target genes were screened out as the target of HLJDT in the treatment of MI.The target gene number (PDB ID number) was converted into a gene name corresponding to the Genecards database through the UniProt database. The key words “myocardial ischemia” or “myocardial infarction” were input into the Genecards database  to analyze the KEGG pathways of the predicted targets. The results of KEGG enrichment analysis were visualized using the Omicshare online analysis platform. The components-targets-pathway (C-P-T) network of HLJDT for treating MI was constructed by utilizing the network-visualization software Cytoscapev3.6.1.Male Sprague–Dawley (SD) rats (180–200 g) were purchased from the SLAC Laboratory Animal Co., Ltd. . The animals were housed in standard pathogen-free cages in a climate-controlled environment with a 12 h light/12 h dark cycle. Sterile food and water were naturally provided. All procedures were conducted in accordance with the guidelines for care and use of laboratory animals from the Second Military Medical University and government.in vivo MI rat model is shown in The experimental procedure of the The 50 experimental rats were anesthetized with isoflurane inhalation and needle electrodes were inserted into the subcutaneous limbs. A catheter containing 0.1% heparin saline was inserted into the left ventricle through the left common carotid artery. Electrocardiograph (ECG) and left ventricular hemodynamic changes were recorded by a BL-410 biological function experiment system and the changes of the S-T segment were used to determine the success of modeling. Endotracheal intubation and artificial ventilators were used for mechanical ventilation. The MI model was established by ligating the left anterior descending coronary artery (LADCA) . After tThe experimental rats were sacrificed 30 min after modeling. Immediately, blood was collected from the abdominal aorta. The supernatant serum obtained was collected and stored at −20°C for analysis of the biochemical indexes including CK, MDA, SOD, LDH and IL-1β, IL-6, IL-17, and TNF-α. The remaining serum was stored at −80°C for metabonomic analysis. Simultaneously, the hearts were rapidly removed for 2,3,5-triphenyltetrazolium chloride (TTC) immersion to determine the myocardial infarct size.Metabonomic analysis was performed by the Agilent 1,290 Infinity Ⅱ UHPLC system coupled to an Agilent 6545 UHD and Accurate-Mass Q-TOF/MS. Mobile phase: A: aqueous solution. B: acetonitrile solution. Flow rate: 0.35 ml/min. Column temperature: 25°C. Injection volume: 2 μL. Gradient elution condition optimized: 0–2 min, 1% B; 2–7 min, 1–15% B; 7–9 min, 15–50% B; 9–13 min, 50–95% B; 13–15 min, 95% B. Post time was set as 5 min. Mass spectrometry was operated in both positive and negative ion modes. Differential metabolites were further identified by MS/MS with collision energy of 10 v, 20 v, and 40 v. Raw data were converted by the self-contained software of the Agilent system. Then the peak was identified by the XCMS program in the R software platform. The peel data were subjected to internal standard normalization and weight normalization and the flesh data were subjected to internal standard normalization. Visualization matrices containing sample name, m/z-RT pair, and peak area were obtained. For the peel simples, 1,428 features were obtained in the positive mode. After editing, the data matrices were imported into SIMCA-P 13.0 After preprocessing, the data were analyzed by Orthogonal Partial Least Square Discriminate Analysis (OPLS-DA).p value (threshold <0.05) of Student’s t-test were used to find differentially expressed metabolites.The metabolites were qualitatively analyzed by searching the self-built standard substance database according to the results of the secondary spectrum and then the METLIN, HMDB, HMDB-SERUM, KEGG, CHEBI, LIPID, and other public databases were searched to provide alternative substances. In our study, the Variable Importance in Projection  of the first principal component of the OPLS-DA model and the p < 0.05 was considered a significant difference.Data were analyzed by one-way analysis of variance (ANOVA) followed by a Dunnett's test or a Kruskal-Wallis ANOVA on Ranks followed by a Dunn’s test for multiple comparisons and expressed as the means ± SEM. *Rhizoma coptidis, 143 were in Radix scutellariae, 140 were in Cortex phellodendri, and 98 were in Fructus gardenia. With the criteria of OB larger than 30% and DL larger than 0.18, 106 chemical ingredients were screened out, where 14 were in Rhizoma coptidis, 36 were in Radix scutellariae, 37 were in Cortex phellodendri, and 15 were in Fructus gardenia. After taking out the duplicated parts, 84 chemical constituents were accepted, and their structures were retrieved from the PubChem database  in the fructus of Gardenia jasminoides J. Ellis; oroxylin (RS21), wogonin (RS22), and baicalein (RS25) in the radix of Scutellaria baicalensis Georgi, and β-sitosterol (CP7) in the cortex of Phellodendron chinense C.K. Schneid. Meanwhile, some of the target genes were involved in diverse pathways, for example, MAPK8 participated in diverse pathways, including apoptosis, the PI3K-Akt pathway, the TNF pathway, and the MAPK pathway, while IL-17 was involved in the IL-17 signaling pathway, Th17 cell differentiation, and apoptosis, etc. These results indicated that HLJDT probably acted on MI in a multi-target, multi-pathway, and overall integrative mode.A global view of the potential compound–target–pathway (C-T-D) network including 114 nodes  and 270 edges was constructed  to furthThe rat MI model was established to evaluate the potential myocardial protection of HLJDT. Representative photographs of TTC-stained heart slices and the corresponding quantitative statistical analysis of myocardial infarct size obtained after MI are shown in Meanwhile, the MI group exhibited elevated levels of cardiac markers such as creatine kinase (CK), CM-KB, aspartate aminotransferase (AST), lactate dehydrogenase (LDH), anti-oxidant enzymes superoxide dismutase (SOD), inflammation, and immune related factors: interleukin-6 (IL-6), IL-1β, IL-17, and TNF-α, while the MI group exhibited reduced levels of malondialdehyde (MDA). Oral administration of HLJDT could significantly improve the above related levels . The resp values less than 0.05, and VIP values larger than 2.0. They were PA (20:1 (11Z)/0:0), phytosphingosine, spermic acid 2, phenylacetaldehyde, prostaglandin E1, heptadecanoic acid, thromboxane, piperidine, carbamic acid, sphingosine, acetamide, ethionamide sulphoxide, PA (15:0/22:1 (13Z)), and cis-3-Chloroallyl aldehyde. The distribution of 14 metabolites were visually displayed by heatmap  of serum were extracted from the sham and MI groups. The OPLS score plot proved that the sham group were significantly different from the MI group  metabolism /0:0), phytosphingosine, spermic acid 2, phenylacetaldehyde, prostaglandin E1, heptadecanoic acid, thromboxane, piperidine, carbamic acid, sphingosine, acetamide, ethionamide sulphoxide, PA (15:0/22:1 (13Z)), and tabolism . The exitabolism . An abnotabolism . Ceramidtabolism . The AA tabolism .Notably, in the main target genes and differentially regulated makers, the sphingolipid signaling pathway was found to be the only shared pathway. According to the literature, sphingolipids, the critical composition of the cell membrane, regulates cellular growth, differentiation, and aging . It inclCoptis chinensis Franch, kaempferol in the fructus of Gardenia jasminoides J. Ellis, oroxylin, wogonin, and baicalein in the radix of Scutellaria baicalensis Georgi, and β-sitosterolin in the cortex of Phellodendron chinense C.K. Schneid. The results demonstrated the myocardial protection effect of HLJDT on ischemia with a multicomponent-multitarget mode. This study highlights the reliability and effectiveness of a network pharmacology-based approach that identifies and validates the complex of natural compounds in HLJDT for illustrating the mechanism of action in the treatment of MI.The present study demonstrated the myocardial protection of HLJDT. An integrative approach of network pharmacology and metabonomic was performed to investigate the biological mechanisms of HLJDT for treating MI. By comprehensive analysis of the potential compound–target–pathway network and metabolic pathway enrichment, we speculated that the action mechanisms of HLJDT were attributed to the biological process of oxidative stress, apoptosis, and immune and inflammatory responses by regulating the sphingolipid pathway, PI3K-Akt pathway, and IL-17 signaling pathway. Meanwhile, the integrated network indicated that the top ingredients with the highest number of connections to target nodes were quercetin in the rhizoma of