Hippophae rhamnoides L. It is widely studied for its ability to modulate inflammatory responses. In this study, we evaluated the potential of isorhamnetin to prevent gram-negative sepsis. We investigated its efficacy using an Escherichia coli-induced sepsis model. Our study reveals that isorhamnetin treatment significantly enhances survival and reduces proinflammatory cytokine levels in the serum and lung tissue of E. coli-infected mice. Further, isorhamnetin treatment also significantly reduces the levels of aspartate aminotransferase, alanine amino transferase and blood urea nitrogen, suggesting that it can improve liver and kidney function in infected mice. Docking studies reveal that isorhamnetin binds deep in the hydrophobic binding pocket of MD-2 via extensive hydrophobic interactions and hydrogen bonding with Tyr102, preventing TLR4/MD-2 dimerization. Notably, binding and secreted alkaline phosphatase reporter gene assays show that isorhamnetin can interact directly with the TLR4/MD-2 complex, thus inhibiting the TLR4 cascade, which eventually causes systemic inflammation, resulting in death due to cytokine storms. We therefore presume that isorhamnetin could be a suitable therapeutic candidate to treat bacterial sepsis. Isorhamnetin is a flavonoid that is abundant in the fruit of  Inflammation is an innate immune response against microbial infection. However, if it persists for a long time, it can cause several fatal diseases, including sepsis. Sepsis is a clinical condition defined as a systemic inflammation in the body in response to microbial infection, which eventually leads to multiple organ failure. Sepsis is reported to be the leading cause of mortality across the globe, and thus the World Health Organization (WHO) devoted the year 2017 to prioritize this disease and its treatment strategies . The orgTLRs are transmembrane receptors present in major immune cells, and are composed of an extracellular leucine-rich repeat domain, a transmembrane region and an intracellular toll-interleukin-1 receptor (TIR) domain ,6. In total, 10 and 12 TLRs are identifiable in human beings and mice, respectively, and each of them recognizes specific pathogen-associated molecular patterns . HoweverHippophae rhamnoides L.; it exerts various biological effects, including anti-inflammatory [Mycobacterium tuberculosis H37Rv and multi-drug- and extensively drug-resistant clinical isolates [Flavonoids are naturally-occurring polyphenols that are found in a variety of edible plants. Chemically, they exist in glycosylated (conjugated with sugar) or aglycone forms (free form) . The rolammatory , anticanammatory  and antiammatory . Furtherisolates . Importaisolates . Thus, tEscherichia coli-induced sepsis by establishing a murine model. Furthermore, based upon binding affinity and a molecular docking examination, we show for the first time, to our knowledge, that isorhamnetin can bind TLR4/MD-2 directly, thus preventing the activation of the TLR4 cascade, which is responsible for sepsis progression. The outcomes of our study might provide further insights into the natural flavonoid isorhamnetin and its role in sepsis prevention and treatment. In the present study, we explored the potential of isorhamnetin to protect against E. coli-induced sepsis. To establish a bacterial sepsis model, we used a virulent E. coli K1 strain to infect isorhamnetin-pretreated mice for 96 h for survival assays and 18 h to examine inflammation. As depicted in E. coli-treated mice died within 24 h of infection. Further, we assessed the bacterial burden in the visceral organs of the mice  and found that isorhamnetin treatment significantly reduced the bacterial population in all organs compared to that in the E. coli only group (It was previously reported that isorhamnetin can reduce inflammation by downregulating nitric oxide (NO) and cytokine production . Therefoly group B. AlthouE. coli-induced myeloperoxidase (MPO) and proinflammatory cytokines (TNF-α and IL-6) was then examined. As depicted in E. coli, whereas treatment with isorhamnetin decreased MPO activity in the kidney, liver and lung. However, the best results were obtained in the lung tissue , alanine amino transferase (ALT) and blood urea nitrogen (BUN) assays were carried out to evaluate liver and kidney function, and the results of these assays reveal that untreated mice infected with function E. Howeve and BUN E. Notabl and BUN E, clearlreatment F.E. coli-infected mice and ameliorate inflammation, we next determined its probable mechanism of action. Isorhamnetin was previously reported to downregulate the TLR4 pathway [As we observed that isorhamnetin could successfully promote the survival of  pathway , which h pathway , which e−6 M  assay using HEK-Blue™-hTLR4 cells to confirm the selectivity of isorhamnetin for the TLR4 receptor. SEAP is a protein secreted after the translocation of NF-κB from the cytosol to the nucleus; the amount of SEAP secreted into the medium correlates with the activation of the TLR4 pathway. Results of this experiment reveal that isorhamnetin could reduce SEAP activity in a concentration-dependent manner, with a 52% inhibition rate, indicating its specificity for the TLR4 receptor B.E. coli treatment group is significantly higher than those of the isorhamnetin treatment group (p < 0.001), suggesting that isorhamnetin treatment causes the reduction of the E. coli count, thus the level of LPS is decreased. However, the in vitro assessment of LPS neutralization reveals that isorhamnetin has no effect on the neutralization of LPS, as the level of LPS is similar in both the isorhamnetin treatment group as well as the LPS-only-treated group  assay to examine the level of LPS in the mice serum and the in vitro LPS neutralizing efficacy of isorhamnetin. As, depicted in ed group D, implyiTo understand the interaction between isorhamnetin and MD-2 at the molecular level, a binding model of isorhamnetin to MD-2 was determined by a docking simulation. A model of the binding between isorhamnetin and MD-2 shows that isorhamnetin was inserted into the hydrophobic binding pocket of MD-2, which is a part of the LPS-binding site a. IsorhaIsorhamnetin, a natural flavonoid and metabolite of quercetin, has gained much scientific attention due to its broad range of biological activities. Specifically, it is reported to exert anti-inflammatory , anti-gaBrassica vegetables, is reported to stabilize mast cells and protect the gastrointestinal tract; moreover, its potent anti-inflammatory and antioxidant activity was also reported [Natural products isolated from plants and herbs are categorized in complementary and alternative medicine, and are now replacing synthetic drugs. A report published by the National Health Interview Survey (NHIS) reveals that approximately 38% of adults in America use complementary and alternative medicine , which sreported . Howeverreported ; howeverreported .E. coli-induced sepsis using a mouse model. We observed a significantly high survival rate in mice treated with isorhamnetin compared with that in the E. coli only group. Moreover, the bacterial load in the visceral organs  is greatly decreased in the isorhamnetin-treated group, suggesting that this compound protects mice from E. coli infection. Further, the secretion of IL-6 and TNF-α is reduced significantly in the sera and lung lysates from the isorhamnetin-treated mice, whereas this is predominantly high in the E. coli only group, suggesting that isorhamnetin suppresses E. coli-induced inflammation in mice.The exaggerated production of cytokines is a major cause of systemic inflammation, often referred to as septic shock. Septic shock or sepsis is the most fatal condition, and here the mortality rate is predominantly high with very few treatment options . As we oCordyceps species, is found to suppress LPS-induced inflammatory signaling by inactivating the MAPK and NF-κB pathways and inhibiting TLR4-mediated signaling [To induce systemic inflammation or sepsis, bacteria or their byproducts target TLR signaling, and more specifically, the TLR4 pathway. Natural compounds, and precisely, flavonoids, represent principal candidates that target the TLR4 pathway. For example, epigallocatechin gallate, a polyphenolic flavonoid found in green tea, has been identified as a potent antagonist of the TLR4 pathway . Therefoignaling .In addition, curcumin, sulforaphane, 6-shagaol, glycyrrhizin, isoliquiritigenin, caffeic acid phenethyl ester, cinnamaldehyde, paclitaxel, morphine, naloxone, chitohexose and xanthohumol are natural small molecular inhibitors that target TLR4 activation and signaling . Among tIn this study, we examined the binding efficacy of isorhamnetin to MD-2 in order to regulate the TLR4/MD-2 interaction, which eventually leads to the induction of TLR4 pathway. We carried out the SEAP assay using HEK-Blue™-hTLR4 cells, as the translocation of NF-κB from the cytosol to the nucleus tends to release the SEAP protein in cell supernatant, and is directly associated with the activation of the TLR4 pathway. From this experiment, we observed that isorhamnetin treatment reduces the activation of TLR4 pathway as the secretion of SEAP protein is drastically reduced even at the 1 μM concentration, suggesting that isorhamnetin may inhibit TLR4-inflammatory signaling pathway.Isorhamnetin, a flavonoid, has potent anti-inflammatory potential ; therefoE. coli-infected group and the isorhamnetin-treated group, suggesting that isorhamnetin treatment exerts the reduction of the bacterial load in blood, and thus decreases the level of LPS. Taken together both in vitro and in vivo, LAL assay results indicate that isorhamnetin does not target LPS neutralization, instead it might give a competition to the LPS while binding with MD-2 in order to inhibit the TLR4/MD-2-LPS interaction which eventually downregulates the activation of the TLR4 pathway. Moreover, it is reported that treatment of isorhamnetin significantly decreases the expression of TLR4 and MyD88 in the LPS-treated cell [Additionally, we carried out the LAL assay to examine whether isorhamnetin neutralizes the LPS, because that might also be another way to block the TLR4 pathway. However, our results of this in vitro LAL assay demonstrate that there is no neutralizing effect of isorhamnetin against LPS. On the other hand, there is significant difference in the amount of LPS present in the serum of the ted cell . Similarted cell ,41. TherE. coli-induced sepsis in a mouse model. Moreover, our study, for the first time, reports that from binding affinity, molecular docking and SEAP assay experiments, isorhamnetin directly interacts with MD-2, implying that this compound could be a potent therapeutic candidate for the treatment of TLR4-mediated inflammation and sepsis.In conclusion, this is the first study, to our knowledge, to report that isorhamnetin, a natural flavonoid, protects against All chemicals, unless otherwise stated, were of the highest quality  and were used as supplied. Isorhamnetin (95.0% purity) was purchased from Sigma-Aldrich . We further purified it to 99% purity using high performance liquid chromatography in Korea Basic Science Institute . Compounds were dissolved in dimethyl sulfoxide (DMSO) to produce a 10-mg/mL stock solution.E. coli-induced sepsis model. All mice used in this study were purchased from Orient  and were housed under specific pathogen-free conditions in a temperature- and humidity-controlled environment for one week prior to the experiments. All procedures were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of Konkuk University, South Korea (IACUC number: KU18163-1).Female BALB/c (six weeks old) mice were used for the NF-κB promoter. HEK-Blue™ hTLR4 cells were seeded in 96-well plates at 2.5 × 104 per well, using HEK-Blue detection media  and these were treated with isorhamnetin. After 1 h, LPS at 20 ng/mL was added for stimulation. After 16 h, SEAP production was determined based on the absorbance of the supernatant, measured at 630 nm, as described previously.HEK-Blue™-hTLR4 cells (toll-like receptors (TLRs)), obtained via the co-transfection of human TLR4, MD-2 and CD14 co-receptor genes and an inducible SEAP reporter gene into HEK293 cells, were purchased from Invitrogen . HEK293 cells that stably expressed TLR4 contained a secreted alkaline phosphatase reporter gene (SEAP) located downstream of the D) values for the binding affinity were measured using a 1:1 binding assay with BIA Evaluation 2.0 software .The binding affinity between isorhamnetin and MD-2 was determined by SPR using a Biacore T100 . Briefly, MD-2 protein was immobilized onto a CM5 chip using a standard EDS/NHS amine coupling method with sodium acetate . MD-2 protein at 30 μg/mL was injected onto the surface of the CM5 chip at a resonance value of 2300. To analyze the kinetics, we used a running buffer composed of phosphate-buffered saline (PBS) , 0.05% Tween 20 and 1% DMSO. The chip was regenerated with 5 mM sodium hydroxide (NaOH) after the analysis of every sample. Equilibrium dissociation constant (Khttp://www.yasara.org) [E. coli LPS Ra complex was obtained from the protein data bank (PDB ID: 3FXI). The structure of isorhamnetin was acquired from the PubChem compound database (PCID:5281654), and the structure was subjected to energy optimization before docking. Water molecules and hetero atoms were removed from the protein, and polar hydrogen atoms were added. One hundred docking cycles with 500,000 evaluation steps were performed. Based on the cluster information, binding energy, molecular interactions such as hydrogen bonds and hydrophobic interactions, the best docked pose was selected.To analyze the TLR4/MD-2/isorhamnetin interaction, molecular docking was carried out using AutoDock Vina implemented by Yasara software (ara.org) . The cryE. coli (1 × 107 CFU/mouse). For the third group, mice were administered an i.p. injection of isorhamnetin (1 mg/kg) with 0.2 mL of E. coli (1 × 107 CFU/mouse). For the fourth group, mice were administered an i.p. injection of isorhamnetin (1 mg/kg) without E. coli. Survival in each group was observed for up to four days .Survival tests were carried out as described previously . BrieflyE. coli (1 × 107 CFU/mouse) injection, and the mice were housed for 12 h. After 12 h, the mice were sacrificed, and blood and lung tissues were collected to examine inflammatory cytokines (TNF-α and IL-6) in the serum or lung lysates, using respective ELISA kits (R&D system), according to the manufacturer’s instructions.Isorhamnetin (1 mg/kg) was injected 60 min before the The detection of aspartate aminotransferase (AST), alanine amino transferase (ALT) and blood urea nitrogen (BUN) in the serum was performed using a standard kit available from Asan Pharmaceutical,  as per the manufacturer’s instructions. The levels of AST, ALT and BUN were determined relative to a standard provided by the kit after subtracting the background levels. PBS was used as the negative control and a standard solution was used as the positive control to calculate the rates.E. coli colonies, which were used to assess the relative abundances of E. coli.At the time of sacrifice, the lungs, liver and kidneys were removed aseptically and placed separately in 1 mL of sterile PBS. The tissues were then homogenized on ice using a tissue homogenizer under a vented hood. The lung, liver and kidney homogenates were diluted with PBS to 1:1000. After plating 10 µL of each diluted sample onto Luria Bertani (LB) agar, the plates were incubated at 37 °C for 24 h. We then counted the numbers of To determine the endotoxin concentration in mice serum we have carried out the LAL assay. The assay was carried out using Pierce LAL Chromogenic Endotoxin Quantification Kit  according to the manufacturer’s instruction. Similarly, to examine the LPS neutralizing efficacy of isorhamnetin in vitro, we incubated the different concentrations of isorhamnetin  with 1ng/mL of LPS at 37 °C in a 96-well plate which was then analyzed by a Pierce LAL Chromogenic Endotoxin Quantification Kit  according to the manufacturer’s instruction.For histopathological examination, all samples were fixed in 10% formalin buffer and dehydrated with graded alcohol. The tissues were then embedded in paraffin blocks, and pathological sections were sliced along the longitudinal axis. From each sample, 5-mm thick sections were obtained, and staining with hematoxylin and eosin was performed to evaluate lung tissue morphology.p < 0.05. The error bars represent the mean ± standard error of the mean (SEM) .All statistical analyses were carried out using GraphPad Prism software. Dunnett’s multiple comparisons test  was used for the comparisons of multiple groups. Values were considered statistically significant at


Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Describing the biological function of computationally annotated genes in non-model assemblies and the molecular pathways formed by these genes’ products is critical for identifying the genetic basis of the various unique biological attributes  of the species in question. Computational search against DNA/protein databases, e.g., NCBI Blast (Kyoto Encyclopedia of Genes and Genomes (KEGG) provide comprehensive web services (KAAS (KEGG Automatic Annotation Server) web services to annotate the complete or random set of genes to describe their molecular function and map them into identified molecular pathways. The annotation results consist of KO numbers for each gene, genes mapped to KEGG pathway database, and genes mapped to BRITE. Nonetheless, the resulting complete set of pathways and BRITE hierarchy can only be viewed through the temporary URL provided by KEGG, which are only available for several days after the analyses are completed. Although these results are organized through either curated KEGG pathways or BRITE hierarchy, KAAS does not provide an integrative gene-centered view of gene function and pathways, i.e., the complete summary of gene function and all associated molecular pathways for each gene.For mapping genes into known molecular pathways, theAs can be envisioned, integrating the gene function annotation based on KEGG orthology and KEGG pathways can provide an efficient way to characterize both the predicted genes and associated pathways for a newly assembled genome or metagenomics dataset. Despite numerous computational packages for retrieving KEGG pathways using the API interface provided by KEGG database e.g.,. MEGAN cAssuming that the KEGG ortholog number is known for a single gene, the KO information can be retrieved from KEGG database by utilizing KEGG REST-style API. GAEV uses the ‘get’ operation of the KEGG API to extract data on the gene and linked pathways of every K number provided in the input file. The data extracted from KEGG database are stored in data files that can be loaded into GAEV to skip the data extraction step .mapno]&multi_query=%23bfffbf%0d%0a[k-num1]+%23bfffbf%0d%0a[k-num2]+... %23bfffbf%0d%0a[k-num_interest]+%23[node_color],%23[font_color].Some genes will not have a KO number associated with them. Before data extraction, GAEV will trim the input file to remove all genes that do not have a KO number or have a KO number that cannot be searched in the KEGG database. Once data extraction from KEGG’s database is complete and the data file is generated, GAEV helps the user handle and visualize the data by exporting the data as a table in an HTML file. GAEV populates the table with the user defined gene ID provided in the input file and the associated K number provided in the input file, as well as the gene name, definition, and linked pathways that have been retrieved from the KEGG database. The linked pathway map URLs that highlight identified genes in the genome assembly are created using the following formula: http://www.kegg.jp/kegg-bin/show_pathway?map=[[mapno] represents the pathway accession number. represents the K number for each gene in the pathway that is present in the provided genome assembly, and[k-num_interest] represents the K number of the focal gene that will be highlighted with a unique color.[node_color] and[font_color] represent the desired color of the focal gene’s node and font on the pathway map, respectively. By default, the node color of the focal gene is dark red, whereas the node color of other genes in the same pathway that are present in the genome assembly is light green.In the above URL,https://github.com/UtaDaphniaLab/kegg_path_generator. This software requires Python 3 or newer to run. It is recommended that this software be used as a standalone program simply by double clicking on GAEV.py or by using the ‘python 3 GAEV.py’ command.The most up-to-date version of this software can be downloaded atDaphnia pulex genome  to assign KO numbers to each of the queried genes. The Daphnia protein fasta file can be found athttps://figshare.com/articles/PA42_3_0_protein_new_txt/6653297. With a gff/gtf genome annotation file, users can also use tools such as gff2sequence , we see strong conservation betweenDaphnia andDrosophila, with only 1 gene  in this pathway missing an identified homolog in theDaphnia assembly  in mind, we have developed GAEV to provide a fast, easily accessible summary for KEGG gene annotation results. We expect that GAEV will find its use in many bioinformatic analyses, especially those involving non-model species. https://github.com/UtaDaphniaLab/Gene_Annotation_Easy_ViewerSoftware source code available from:https://zenodo.org/record/2549592 . So it would be better if the authors could be clearer what problems GAEV tries to solve.The first sentence of the manuscript confuses me about what problem the GAEV tries to solve. It provides a new and better way to annotate a given genome with pathways, but I don’t think it tries to helpI have tested GAEV using the example data provided by the authors. It worked without any errors. However, I found two typos in the first two options of the menu popping up from typing “python GAEV.py”. Is it supposed to be “Create and generate a new data file and table from a new dataset of KO numbers”? Please fix it if it is the case.GAEV provides an interactive interface to walk the users through the entire procedure. Such a design gives the users certain degree of flexibility. However, if some users need to try GAEV using different parameters or filters , such an interactive design can be overwhelming. I am wondering if the authors have plans to have an end-to-end automatic version of GAEV? By providing enough options from command line, I think GAEV can be both flexible and efficient. The likely problem with relative/absolute path to input files can also be naturally solved, and the requirement of putting the input files together with GAEV.py is not necessary as well. I am not asking the authors to have an implementation for this publication, but it would be nice to know the authors’ thoughts on this.GAEV implements a Trimming method. However, I cannot find some descriptions of this step. Such information is very important to users to understand what has been done internally and how it has been done.GAEV also supports “BATCH” mode. Could the authors provide some use cases and let the users know what they should expect in terms of the final HTML report?One typo: “MEGAN can achieve overall functional analysisof microbiome …” should be “MEGAN can achieve overall functional analysis of microbiome …”.In the URL formula, it seems that there are extra spaces after “www”. Please fix it if it is the case.Huynh and Xu present a new approach, GAEV, to annotate gene models of a given non-model genome assembly. It maps genes to their associated pathway counterpart of model species. GAEV specializes on improving the conventional KEGG analyses and focuses on providing a gene centric view of gene function and pathways. Overall, I think GAEV can be a good addition to the current bioinformatics research community. I recommend indexing of this manuscript once the authors could address my following questions/suggestions. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. I have no further comments to make.We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This is a review of the manuscript “Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways” by Huynh and Xu. The authors present a method via a python script that can take KEGG IDs and output three tables of useful annotation information in the context of the molecular pathways. The manuscript is well written and is easy to read. I envision that the tool developed will be useful, although see the comments below. With corrections I think this manuscript will be a good contribution to the resources available to researchers working in genomics/transcriptomics in non-model organisms. Major Comments Although I can start the python script running using python3, the example_input.txt file cannot be found when I enter the relative path or the absolute path. This is despite the input file being in the same folder as the script. My bioinformatics technician also encountered the same problem. Thus it seems there is an error in the script that would need to be corrected prior to acceptance of the manuscript. Minor Comments This tool is presented as accessible and user-friendly, and the authors use the example from Ye et al. 2017 of  “the query protein sequences in a fasta file”. But a protein sequence file is not provided with that paper (that I could find). Thus there an assumed knowledge gap that your reader needs to be able to use this tool as you describe. I suggest you provide additional information on how users can go from a genome with predicted genes (i.e. a .gtf or .gff3 file) to obtain those query sequences for input into the KEGG.  You may also want to mention that researchers working with non-model organisms could start with a de novo transcriptome or as an input file.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Dear Dr. Schwartz, Thanks very much for your comments on our manuscript. Please see below for how we revised our manuscript to address your concerns.1. Although I can start the python script running using python3, the example_input.txt file cannot be found when I enter the relative path or the absolute path. This is despite the input file being in the same folder as the script. My bioinformatics technician also encountered the same problem. Thus it seems there is an error in the script that would need to be corrected prior to acceptance of the manuscript.Response: We have found the bug in our code that prevented the script from finding files on Linux and Mac OS properly. This bug has been fixed as of version 1.1.1.2. This tool is presented as accessible and user-friendly, and the authors use the example from Ye et al. 2017 of  “the query protein sequences in a fasta file”. But a protein sequence file is not provided with that paper (that I could find). Thus there an assumed knowledge gap that your reader needs to be able to use this tool as you describe. I suggest you provide additional information on how users can go from a genome with predicted genes (i.e. a .gtf or .gff3 file) to obtain those query sequences for input into the KEGG. Response: We provide a fasta file of Daphnia protein sequence through the github page for GAEV. Moreover, in the manuscript we recommend users to use tools such as gff2sequence to create query sequences using information from gtf/gff files. See 2nd paragraph of Use Cases.3. You may also want to mention that researchers working with non-model organisms could start with a de novo transcriptome or as an input file.Response: Addressed accordingly. See 2nd paragraph of Use Cases. The authors of this article present a new tool, compiled as a single Python script, that aids in visualizing the gene annotation analysis results of the webserver-based KEGG services. The function of this tool is to generate an html-based view of the genes analyzed by KEGG tools and the appropriate pathways with which they are linked. The html view provides also an overview of the total existing pathways per associated genes, a task which can be useful for whole genome and metagenome annotation queries. The authors provide a thorough explanation about how the tool works and communicates with KEGG API by generating the appropriate links and exporting the generated data. The authors also provide some test datasets which can be used to generate the results mentioned in the manuscript. Nevertheless this reviewer considers this endeavour to have already been covered by other bioinformatic tools with which a comparison would be necessary to underline the importance of the new tool. For example tools like MEGAN can provide a thorough investigation of the existing KEGG pathways in a genome/metagenome . Furthermore MinPath can be also used in combination with KEGG generated datasets in order to provide a similar pathway reconstruction analysis. Maybe the authors could elaborate a little bit more about what makes their tool more suitable than these already published tools. Moreover during the Conclusions section the authors do not seem to explain the methodology in order to examine the differences between Daphnia and Drosophila and how that  can be achieved solely (or more intuitively) by exploiting this particular tool. In general this tool seems like a good addition to a bioinformatic pipeline for genomic or metagenomic analysis but this reviewer thinks that the author must emphasize more on the differences and/or improvements regarding similar tools.We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. Dear Dr. Kolisis, Thanks very much for your comments on our manuscript. Please see below for how we revised our manuscript to address your concerns.Nevertheless this reviewer considers this endeavour to have already been covered by other bioinformatic tools with which a comparison would be necessary to underline the importance of the new tool. For example tools like MEGAN can provide a thorough investigation of the existing KEGG pathways in a genome/metagenome . Furthermore MinPath can be also used in combination with KEGG generated datasets in order to provide a similar pathway reconstruction analysis. 1.Response: Our goal with our new tool is to provide a gene-centric view of molecular pathways, where each gene is accompanied by all the pathways where this gene is predicted to play a role. This is different from the purposes of MEGAN and Minpath. We emphasized this idea in the last paragraph of Introduction and drew comparison with MEGAN and Minpath.. Moreover during the Conclusions section the authors do not seem to explain the methodology in order to examine the differences between Daphnia and Drosophila and how that  can be achieved solely (or more intuitively) by exploiting this particular tool. 2Response: This example ofDaphnia circadian pathway is to demonstrate using this tool for initial exploration of non-model organisms’ genomes to understand the conservation of specific pathways compared to established model systems . The Drosophila circadian pathway is provided through KEGG database. Users can directly examine their interested pathways from the results of GAEV (click on the link in the generated html file) and view the pathways and mapped genes on KEGG website. We provide a brief explanation of how to technically view the pathway on KEGG server in Discussion.


The purpose of this work was to investigate the bioactive compounds, core genes, and pharmacological mechanisms and to provide a further research orientation of Erzhi pill (EZP) on drug-induced liver injury (DILI).  At first, we collected information of bioactive compounds of EZP from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and previous studies. And then, the targets related to bioactive compounds and DILI were obtained from 4 public databases. At last, Cytoscape was used to establish a visual network. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and network analysis were performed to investigate potential mechanism of EZP against DILI.  A total of 23 bioactive compounds and 89 major proteins of EZP were screened out as potential players against DILI. Association for bioactive compounds, core targets, and related pathways was analyzed, implying that core targets related to these pathways are ALB, AKT1, MAPK1, EGFR, SRC, MAPK8, IGF1, CASP3, HSP90AA1, and MMP9, and potential mechanisms of EZP acting on DILI are closely related to negative regulation of apoptosis process, improvement of lipid metabolism, and positive regulation of liver regeneration process.  This study demonstrated the multicompound, multitarget, and multichannel characteristics of EZP, which provided a novel approach for further research the mechanism of EZP in the treatment of DILI. Drug-induced liver injury (DILI), which is defined as a liver injury due to medications, xenobiotics, and herbs that leads to liver dysfunction or abnormal liver serology, has been an important health concern around the world . Crude aLigustri lucidi fructus (LLF) and Ecliptae herba (EH) on the ratio of 1 : 1, is a classic TCM formula and widely used to treat hepatic disease with a long history in China. The history of EZP treating hepatic disease can be traced back to Wu Minji's series “Fu shou Jing Fang” in the Ming Dynasty. In TCM theory, EZP can tonify liver and kidney, nourish Yin, and stop bleeding, [Erzhi pill (EZP), which is composed of leeding,  which isleeding, . HoweverNetwork pharmacology, first proposed in 2007 , has becHowever, studies about the liver-protective effect of EZP on DILI are absenct. For the first time, this study explored the protective effect of EZP on DILI through network pharmacology and bioinformatic analysis. Workflow of this work is shown in detail in http://lsp.nwu.edu.cn/tcmsp.php, Version: 2.3), a website that can provide information of herbal ingredients and structures. In addition, TCMSP also provides absorption, distribution, metabolism, and excretion (ADME)-related parameters of herbal ingredients, such as oral bioavailability (OB), drug-likeness (DL), and half-life [Information of compounds of EZP was collected from Traditional Chinese Medicine Systems Pharmacology Database  and Swiss TargetPrediction  by uploading the structure of bioactive compounds, which was acquired from The PubChem Compound Database (https://www.ncbi.nlm.nih.gov/pccompound) or drawn by Chem3D 16.0. PharmMapper and Swiss TargetPrediction are web servers for potential drug target prediction by reversed pharmacophore matching query compound against an in-house pharmacophore model database [All the targets related to bioactive compounds of EZP were collected from PharmMapper  and GeneCards (https://www.genecards.org/). These two databases illuminate relationship between targets and disease from different perspectives. DrugBank is a comprehensive, freely available database, from which the user can obtain information on detailed drug, drug target, drug action, and drug interaction of FDA-approved drugs or experimental drugs going through the FDA approval process [The targets related to DILI were acquired form DrugBank ( process . GeneCar process . By searhttps://www.uniprot.org/) before the establishment of network. The networks were established by Cytoscape 3.7.1, an open-source software project that is used for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework [https://david.ncifcrf.gov/home.jsp, Vision 6.8), and KEGG . The results of GO and KEGG pathway enrichment were considered to have statistically significant and necessary functional mechanisms of DILI, when P < 0.05.In order to investigate the possible mechanisms of EZP on DILI, common targets that related to DILI and putative targets of bioactive compounds were selected as EZP's targets against DILI. The nodes of network are bioactive compounds of LLF and EH networked with relevant disease targets . All theramework . The pathttps://string-db.org/) was used to collect possible protein-protein interactions (PPI) by uploading 89 common targets that related to DILI and putative targets of active compounds. Species was limited to “Homo sapiens” with a confidence score >0.4.Search Tool for the Retrieval of Interacting Genes , were identified as bioactive compounds of EZP Figures . Further311 putative targets of LLF and 249 putative targets of EH were predicted by PharmMapper and Swiss TargetPrediction. After removing duplicated putative targets of LLF and EH, 318 putative targets linked to 23 compounds of EZP were collected. A visual EZP compounds-targets network with 341 nodes and 2691 edges was established by Cytoscape . QuercetAt last, 582 targets related to DILI were obtained (267 targets from DrugBank and 357 targets from GeneCards with 42 targets duplicated). Detailed information on DILI-related targets is presented in Supplementary Homo sapiens” was selected. And then, we established PPI network, which had 84 nodes and 811 edges by Cytoscape. In this network, the protein with greater degree was described by larger node and darker color, and the edge with greater combined score was described by thicker and darker line . In addition, 86 KEGG pathways were recognized as P < 0.05. Top 20 KEGG pathways' enrichment analysis is shown in In order to explore possible mechanism of EZP against DILI, we analyzed GO term and KEGG pathway enrichment results executed by DAVID. GO term enrichment results were divided into biological process (BP), cell compound (CC), and molecular function (MF). Top 10 enriched conditions in BP and top 5 in CC and MF were shown in DILI, which carries a high mortality rate,  has beenP < 0.05. Necrosis and apoptosis of hepatocytes, cholangiocytes, and endothelial cells are typical features of DILI. IGF1, SRC, ALB, MMP9, CASP3, EGFR, AKT1, and MAKP8, which are involved in this biological process, are included in the top ten targets of the PPI network with highest degree. As we know, CASP3 is a key enzyme in the execution of apoptosis. Evidence has shown that there is a significant upregulation of CASP3 in DILI [N-terminal kinase 1, JNK1) has diverse functions in cell cycle, such as cell death, regeneration, and differentiation [According to GO term enrichment results, negative regulation of apoptotic process was the biological process with most targets (22 targets) involved with  in DILI . In addi in DILI . MAPK8 (ntiation . These 3ntiation . MAPK sintiation .β-oxidation; and increased mobilization and uptake of fatty acids [By analyzing the results of KEGG pathway enrichment, we also found that insulin signaling pathway and insulin resistance have a significant result in KEGG pathway enrichment analysis as shown in ty acids –31. Thesty acids .α, which ultimately leads to attenuated regeneration [PPI network analysis, as well as GO and KEGG pathway analysis indicated that there were 1 core target and 2 pathways closely associated with liver regeneration, namely VEGF, VEGF signaling pathway, and PI3K-Akt signaling pathway. The liver is an organ with strong ability to regenerate. There are three phases, priming stage, proliferative phase, and termination phase, involved in the overall process of liver regeneration . The VEGneration . Hence, In this work, we investigate the potential mechanism of EZP against DILI; however, network pharmacology is just a prediction. Whether EZP acts against DILI by regulating these pathways and proteins needs further experimental verification.In summary, this study explored the protective effect of EZP on DILI through network pharmacology and bioinformatic analysis for the first time. 23 bioactive compounds of EZP and 89 targets associated with DILI were identified, and 10 core targets were identified by analyzing PPI network analysis. GO and KEGG pathway enrichment analysis indicates that the mechanisms of EZP against DILI may be related to negative regulation of apoptosis process, improvement of lipid metabolism, and positive regulation of liver regeneration process through PI3K-Akt, MAPK, Foxo, VEGF, and insulin signaling pathways, as well as insulin resistance.


Illumina-based RNA-seq of 786-O cells with or without As2O3 treatment was performed, and differentially expressed genes (DEGs) were identified using Cuffdiff software. TargetMine was utilized to perform Gene Ontology (GO) pathway and Disease Ontology enrichment analyses. Furthermore, TRANSFAC database and LPIA method were applied to select differentially expressed transcription factors (TFs) and pathways related to Wnt/β-catenin signaling pathway, respectively. Additionally, transcriptional regulatory and pathway crosstalk networks were constructed. In total, 1684 DEGs and 69 TFs were screened out. The 821 up-regulated DEGs were mainly enriched in 67 pathways, 70 GO terms, and 46 disease pathways, while only 1 pathway and 5 GO terms were enriched for 863 down-regulated DEGs. A total of 18 DEGs (4 up-regulated and 14 down-regulated genes) were involved in the Wnt/β-catenin signaling pathway. Among the 18 DEGs, 4 ones were TFs. Furthermore, 211 pathways were predicted to be linked to the Wnt/β-catenin signaling pathway. In conclusion, As2O3 may have a significant effect on the Wnt/β-catenin signaling pathway for renal cancer treatment. The potential key DEGs are expected to be used as therapeutic targets.We aimed to investigate the effect of As Renal cell carcinoma (RCC) is one of leading malignant condition in both males and females, with 62,700 estimated new cases and 14,240 estimated deaths in the United States in 2016  and 14 down-regulated genes  participated in the Wnt signaling pathway.According to SMAD3 and FOSL1) and two down-regulated TFs (NFATC3 and TCF7L1) were involved in the Wnt signaling pathway. Additionally, there were 238 nodes (112 up- and 126 down-regulated DEGs) and 247 edges in the transcriptional regulatory network. Among the 238 DEGs, there were 27 TFs, and TCF7L1 was the hub, regulating a set of genes and other TFs   .PSMA7, PSMB1 and PSMB3. The up-regulated genes SMAD3 was enriched in multiple pathways, such as cell cycle (hsa04110), pathways in cancer (hsa05200), and adherens junction (hsa04520)  was most closely linked to the Wnt signaling pathway (hsa04310) . A seriesa04520) . Based ond FOSL1 .2O3, as a treatment for cancers, has been studied for several decades. However, the molecular mechanisms of As2O3 treatment in renal cancer remains not clear, especially the effect of As2O3 on the Wnt signaling pathway. In this study, 1684 DEGs between As2O3 treatment samples and controls were identified, including 821 up- and 863 down-regulated genes. Among those DEGs, SMAD3, FOSL1, NFATC3 and TCF7L1 were identified as TFs and predicted to be associated with the Wnt signaling pathway.AsSMAD3 encodes a member of the smad family. SMAD proteins are signal transducers and transcriptional modulators that are activated by TGF-β and mediate multiple signaling pathways [SMAD3 was enriched in the functions of cell death and apoptotic process and a set of Disease Ontology terms about cancer. TGF-β acts as a tumor suppressor during the early stages of tumorigenesis, and the ability of TGF-β/SMAD3 signal in tumor suppression has been demonstrated by multiple studies [2O3 may play an anti-apoptosis role in renal cancer by up-regulating the expression of SMAD3 as well as the pathway crosstalk between TGF-β/SMAD3 and Wnt signaling pathway.pathways . Crosstapathways , as wellpathways . In this studies . A recen studies . Taken tFOSL1 encodes fos-like antigen 1, also known as Fra1, a member of Fos gene family, which regulates cell proliferation, differentiation, and transformation [FOSL1 can function as either an activator or a repressor to control the equilibrium between migration and adhesion in sprouting angiogenesis, which is critical in tumorigenesis [FOSL1 was up-regulated in the 786-O cells with As2O3 treatment, while a study has reported that Fosl1 induces transformation and invasiveness of human epithelial adenocarcinoma cells [2O3 treatment, the expression of FOSL1 is not effectively influenced, and with the prolonged time of As2O3 treatment, the expression of FOSL1 may be decreased, which is needed to be further investigated.ormation . FOSL1 cigenesis ,32. In tma cells , which iNFATC3 encodes a member of the nuclear factors of activated T cells DNA-binding transcription complex, and it is important for T-cell development and essential for cancer chemoresistance [NFATC3 is abundantly expressed in the metanephric mesenchyme [de novo renal allograft recipients, expression levels of NFAT-regulated genes are closely related to the clinical outcomes [NFATC3 with renal cancer so far, while the increased NFATC3 expression has been detected in human angiosarcoma that was induced by secreted frizzle-related protein 2 (SFRP2) [2O3 treatment may affect the Wnt/β-catenin pathway through decreasing the expression of NFATC3 in renal cancer.sistance . NFAT prsistance ,36. Studsenchyme . In de noutcomes . Furtheroutcomes . There i (SFRP2) . CollectTCF7L1  encodes a member of the T-cell factor/lymphoid enhancer factor family of TFs, which are activated by β-catenin and mediate the Wnt signaling pathway [TCF1 that is the homolog of TCF7L1 is significantly higher in clear cell RCC than in normal tissue [TCF7L1 regulated other TFs, such as SMAD3 and NFATC3. Taken together, the Wnt signaling pathway may be affected by As2O3 in renal cancer via the reduced expression of TCF7L1. pathway . A previl tissue . BesidesPSMA7 and PSMB1. Proteasomes, along with ubiquitin (Ub), are essential components of the energy-dependent, nonlysosomal proteolytic pathway. β-catenin in the Wnt signaling pathway exerts functions in cells depending on the proteasome [PSMB1 is highly expressed in RCCs, comparing with the normal kidney tissues [2O3 in renal cancer through the proteasome pathway.Furthermore, in this study, the pathway of proteasome (hsa03050) was most closely related to the Wnt signaling pathway, and the proteasome pathway was significantly enriched by a set of up-regulated DEGs that encode subunits of proteasome, such as oteasome . The levoteasome . Besides tissues . TherefoDespite the aforementioned results, there were still some limitations in this study. The predicted results, such as expression of the discussed genes, and the associations between genes and Wnt signaling pathway, were required to be confirmed by experiments in renal cancer tissues, which would be conducted in our future study and reported separately.2O3 treatment samples and controls were identified. Among them, SMAD3, FOSL1, NFATC3 and TCF7L1 were identified as TFs and predicted to be correlated with the Wnt signaling pathway. Furthermore, the pathway of proteasome was most closely linked to the Wnt signaling pathway. These genes and pathways may play pivotal roles in the As2O3 treatment of renal cancer. These findings may provide new information for the molecular mechanisms of As2O3 treatment on renal cancer, especially the influence of As2O3 on the Wnt signaling pathway in renal cancer.In conclusion, 1684 DEGs (821 up- and 863 down-regulated genes) between As


In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases.The application of multi-output regression machine learning methodologies to predict the potential effect of external proteins over the signaling circuits that trigger Fanconi anemia related cell functionalities, inferred with a mechanistic model, allowed us to detect over 20 potential therapeutic targets.The use of artificial intelligence methods for the prediction of potentially causal relationships between proteins of interest and cell activities related with disease-related phenotypes opens promising avenues for the systematic search of new targets in rare diseases.The online version of this article (10.1186/s12859-019-2969-0) contains supplementary material, which is available to authorized users. With the extraordinarily fast increase in throughput that sequencing technologies underwent in the last years , 2, genoAn especially interesting use of genomic data is related with the application of ML to model the function of the cell . Such moHere we plan to use a mechanistic model of the molecular mechanism of a disease, Fanconi anemia (FA) (ORPHA:84), a rare condition that causes genomic instability and a range of clinical features that include developmental abnormalities in major organ systems, early-onset bone marrow failure, and a high predisposition to cancer . SignaliSolid tumors, usually with poor prognosis as tumor resection is the only therapeutic option given that patients do not tolerate chemotherapy or radiation, constitute one of the most relevant hallmarks of FA. With improved hematopoietic stem cell transplant protocols, FA patient survival has increased, leading to a progressively increased number of solid malignancies in adult patients. Therapeutic research is currently focused in targeted therapies for solid tumors as well as in preventive options in the context of drug repurposing .At present, a detailed map of FA signaling is available in the Kyoto Encyclopedia of Genes and Genomes, KEGG, 03460) that can be used to derive a mechanistic model that relate gene expression to the activity of signaling circuits within the FA pathway that trigger cell activities related to FA hallmarks. These models can be used to investigate other molecules that could affect the activity of such circuits and therefore, presumably, to FA hallmarks. Therefore, these molecules are potential therapeutic targets. Since we are dealing with a rare disease, which typically are not considered as attractive business niches by pharmaceutical companies , we will60 that cThe attainment of the relationships between candidate proteins for a new indication and the FA hallmarks poses a challenge that can be addressed with the appropriate ML method.Here we take advantage of the biological knowledge available on FA, as represented in the FA pathway. The FA pathway describes the functional interaction among genes that finally trigger, from six different circuits, cell functionalities related with DNA repair see Fig. , a knownHipathia . The a method , as impl package , was use samples .scikit-learn general Machine Learning library [scikit-learn [hyperopt [2 score averaged across a K-fold cross-validation partition of the data (k = 10) is used as objective function. Finally, to evaluate the performance of the model in an unbiased way, the previously found optimal hyperparameters were fixed and a repeated (N = 10) k-fold cross-validation is performed.Here, a Multi-Output Random Forest (MORF) regressor that predicts the circuit activity across the whole disease pathway has been implemented using the  library . In the it-learn  and hypehyperopt . Since thyperopt , the hyphyperopt  method, The same cross-validation can be used to obtain a distribution of the relevance values that can be used to set a threshold beyond which the relevance values obtained by the ML keep their positions in the rank of relevance .enrichR algorithm using GO Biological Processes as well as Rare Diseases with AutoRIF (Automatic Reference into Function) and GeneRIF (Gene Reference into Function) from ARCHS4 mining of publicly available data tool to predict enrichment in rare diseases terms [Those genes with a relevance confirmed by the cross-validation procedure were considered relevant and were used to perform an enrichment analysis to evaluate their possible impact on the circuits of the FA pathway triggering FA hallmarks. An enrichment analysis was performed by using es terms –106.Additional file 1:Table S1. All gene drug targets studied obtained from DrugBank database version 5.1.2, ranked by their relevance obtained from MORF modelling. First column: gene name; second column: gene symbol: third column: Entrez ID; fourth column: relevance; fifth column: DrugBank ID of the drugs targeting the gene. (XLS 200 kb)Additional file 2:Table S2. Genes in the KEGG FA pathway (hsa03460). First column: gene name; second column: KEGG ID; third column: gene symbol; fourth column: ENSEMBL ID; fifth column: OMIM ID. (DOCX 19 kb)Additional file 3:Figure S3. Distribution of circuit activities in the FA KEGG pathway. Distribution of activities in the seven circuits of the FA KEGG pathway observed in the comparison between healthy and FA bone marrow cells. (TIF 218 kb)Additional file 4:Table S4. Drugs targeting most relevant genes (relevance> 0.005) in Fanconi Anemia extended pathway, obtained from DrugBank database. First column: DrugBank ID; second column: drug name; third column: drug description; fourth column: drug status; sixth column: drug Indication. (XLSX 69 kb)Additional file 5:Table S5. Enrichment analysis of the most relevant genes. First column: term detected in the enrichment analysis; second column: overlap; third column: p-value; fourth column: adjusted p-value; fifth column: Z score; sixth column combined score; seventh column genes annotated to the term. (XLSX 199 kb)


Erigeron breviscapus (Vaniot) Hand.-Mazz. used for the treatment of cerebrovascular diseases. However, due to overexploitation and overuse, E. breviscapus is facing the problems of extinction and habitat degradation. In this study, a correlation analysis between the transcript and metabolite profiles of methyl jasmonate (MeJA)-treated E. breviscapus at different time points indicated that chalcone isomerase (EbCHI) was the primary contributor to scutellarin accumulation during flavonoid biosynthesis. EbCHI was then further characterized as a chalcone isomerase that efficiently converted chalcone to naringenin in vitro. Optimal parameters derived by comparing different culture conditions were successfully used to establish hairy root cultures of E. breviscapus with a maximum transformation rate of 60% in B5 medium. Furthermore, overexpression of EbCHI significantly enhanced scutellarin accumulation in E. breviscapus hairy roots with a maximum content of 2.21 mg g-1 (dw), 10-fold higher than that of natural roots (0.21 mg g-1 dw). This study sheds new light on a method of effective gene-based metabolic engineering by accurate and appropriate strategies and provides a protocol for hairy root cultures that accumulate high levels of scutellarin, providing a promising prospect for relieving the overexploitation and unavailability of E. breviscapus in the future.Scutellarin, a flavonoid 7-O-glucuronide, is an essential bioactive compound of  Erigeron breviscapus (Vaniot) Hand.-Mazz., an important traditional Chinese herbal medicine, is broadly used for the treatment of cerebrovascular diseases and diabetes   based on previous studies , flavanones, dihydroflavones, dihydroflavonols, and isoflavones according to their structures and the modifications to the A, B, and C rings known as the flavonoid backbone . The biogure 1A) . Compare studies . On the Isatis indigotica  or 0.1% acetone (negative control). After treatment, the plants were harvested at distinct time points for RNA isolation  and chemical analysis . All time points contained three independent plants as biological repetitions.Methyl jasmonate (95%), apigenin 7-O-glucuronide, scutellarin, apigenin, scutellarein, apigenin 7-O-glucoside, naringenin chalcone, naringenin (98%), and acetosyringone were all purchased from Sigma (United States). The antibiotics cefotaxime and hygromycin B were purchased from Sangon (China). The plant hormones 1-naphthaleneacetic acid (NAA) and 6-benzylaminopurine (6-BA) were purchased from Phytechnology Laboratories (United States). Ammonium acetate was purchased from Thermo Fisher Scientific (United States) and methanoic acid from Aladdin (China). Methanol and acetonitrile of high performance liquid chromatography (HPLC) grade were from Merck Company (Germany). A Milli-Q Reagent Water System was used to produce ultrapure water .To assess the response of the flavonoid pathway to MeJA, quantitative reverse transcription PCR (qPCR) was used to analyze the gene transcripts at different time points after MeJA treatment. Total RNA was extracted using TRIzol Reagent  according to the manufacturer’s instructions. The quality and concentration of RNA were examined by agarose gel electrophoresis and a NanoDrop 2000 . A sample of 1 μg RNA was used for reverse transcription by First-Strand cDNA Synthesis SuperMix Reagent .Supplementary Table S1. The ubiquitin C gene (ubc) was amplified as a housekeeping gene according to a previous study  are listed in us study . The qPCE. breviscapus, the metabolites were extracted and analyzed after MeJA treatment at different time points. Plants were dried at 50°C in an oven until they reached a constant dry weight (DW). The dried plant samples (2.0 mg) were ground into fine powder and extracted twice with 1 mL of 70% methanol under sonication for 30 min. The solutions were then merged and centrifuged at 15000 rpm for 30 min. The supernatant was diluted with 70% methanol to 2 ml. Before analysis, the extract solution was filtered through a 0.2 μm organic membrane .To determine the responses of flavonoid metabolites to MeJA in -1. The column temperature was maintained at 30°C. The injection volume was 10 μL. The ESI source in negative mode was chosen for five compounds. To obtain the richest relative abundance of precursor ions and product ions, the best parameters were chosen, and they are listed in Supplementary Figure S1A. Supplementary Figure S1B shows the full scan product ion spectra of the precursor ions of the five analytes. The MRM chromatograms of five standard compounds are shown in Supplementary Figure S1C. The standard sample concentration was 1 μg ml-1, and the injection volume was 10 μl for all samples. An untreated plant (day one) sample was used as a reference to calculate the relative content.All samples were analyzed on an Agilent 1200 series HPLC interfaced to an Agilent 6410 triple-quadrupole mass spectrometer equipped with an electrospray ionization (ESI) source . A Zorbax SB-C18 column  and a C18 guard column  were used to separate the compounds. A mobile phase consisting of acetonitrile and 5 mM ammonium acetate solution  was used at a flow rate of 0.3 ml minR, based on the principle of co-occurrence between mRNA and metabolite levels  were performed with three independent replications. The standard errors were based on the biological triplicates.t-test, and the errors of different samples were used in a one-way analysis of variance (ANOVA) using SPSS 11.5 software . Transcripts from untreated plants were used as references at each time point to analyze the statistical significance of the changes in MeJA-treated plants, and the metabolite content of WT was used as a reference to analyze the statistical significance of the changes in EbCHI-overexpressing hairy roots.The statistical significance of the metabolite and expression differences were analyzed by Student’s EbCHI (JF694272.1) was amplified by polymerase chain reaction, subcloned into the pBlunt-Zero vector according to the sequences published on National Center for Biotechnology Information (NCBI)  and transformed into the E. coli. Trans1-T1 cell line , which was employed for sequencing. All primers used in this study are listed in Supplementary Table S1.The full-length cDNA of EbCHI was aligned with those of CmCHI (AEP37358.1), CtCHI (ALG75881.1), AtCHI (AEE79342.1), NtCHI (NP_001312216.1), ZmCHI (NP_001149585.1), and LsCHI (BAS69315.1) by MEGA v5.05.1 A phylogenetic tree was also constructed using the neighbor-joining method implemented in MEGA. The chalcone isomerase domain of EbCHI was analyzed on NCBI.2 Secondary structure prediction was performed with SOPMA.3 The 3-D modeling and homology-based structural modeling were performed by Phyre2 online.4The deduced polypeptide sequence of EbCHI, the full-length EbCHI coding sequence was fused in-frame to the N-terminus of enhanced green fluorescent protein (GFP) through the NcoI and BglII restriction sites of the p1301-GFP vector. Using polyethylene-glycol-mediated transformation, the vectors p1301-EbCHI-GFP and p1301-GFP were individually introduced into protoplasts isolated from 14-day-old etiolated rice stems . The PCR product was cloned into pET-32a through the BamHI and EcoRI restriction sites to express a recombinant 6 × His-EbCHI protein. After confirmation by sequencing , the recombinant plasmid and empty vector pET-32a were separately transformed into the E. coli. cell line BL21 (DE3)  by the heat shock method. The transformed cells were used to inoculate 200 mL of LB medium containing ampicillin (75 μg mL-1), grown at 37°C to an OD600 of 0.6, and then induced with 1.0 mM Isopropyl β-D-thiogalactoside (IPTG) at 16°C for 12 h. The His-tagged EbCHI protein was purified at 4°C using nickel-chelate affinity chromatography according to the manufacturer’s instructions . The protein concentration was determined using bovine serum albumin (BSA) as a standard and visualized on 12% acrylamide gel stained with Coomassie Blue. Western blotting verified that the recombinant proteins had a His-tag in the N-terminus. The proteins were detected with the anti-rabbit mAb His antibody , and a secondary antibody -linked antibody).To clone in vitro enzyme assay, the reaction mixture contained: 85 μL Tris-HCl buffer , 5 μL purified recombinant EbCHI protein (0.3 μg μL-1), and 10 μl naringenin chalcone (1.0 mM) dissolved in methanol  under optimal conditions, sterile leaf sections were pre-cultured on solid medium  supplemented with 1 mg L-1 6-BA, 1 mg L-1 NAA, 30% sucrose and 0.8% agar (pH 5.8) for 2 days. Then, the pre-cultured explants were submerged in a bacterial suspension  supplemented with 100 μM acetosyringone for several minutes , blot-dried on sterile filter paper and then placed on the corresponding solid medium  supplemented with 30% sucrose and 0.8% agar (pH 5.8) at 25°C in darkness for several days of co-cultivation .To induce hairy roots with the disarmed -1 cefotaxime and 10 mg mL-1 hygromycin in darkness. After 2 weeks, hairy roots were derived from the sterile leaves. The hairy roots that exceeded 2 cm were excised and cultivated individually on the corresponding solid medium supplemented with 30% sucrose, 0.8% agar (pH 5.8), 10 mg mL-1 hygromycin and different concentrations of cefotaxime for 4 weeks (the concentration of cefotaxime changed from 300 to 100 mg mL-1 after 2 weeks). Rapidly growing root lines that showed hygromycin resistance with no bacterial contamination were used to establish hairy root lines in 250-mL Erlenmeyer flasks containing 200 mL of the corresponding liquid medium supplemented with 30% sucrose and 10 mg mL-1 hygromycin on an orbital shaker at 100 rpm in darkness at 25°C.After co-cultivation, the induced explants were washed with 60 mL sterilized water three times and blot-dried on sterile filter paper, then transferred to the corresponding solid medium supplemented with 30% sucrose, 0.8% agar (pH 5.8), 500 mg LThe fresh weight (FW) of root tissues from the culture flasks (determined as the difference in flask weight with and without the harvested root tissues) was recorded every week after inoculation, and the information was used to draw growth rate curves. At week 10, the hairy roots were harvested for DNA and RNA extraction and metabolite analysis.EbCHI overexpression vector, the full-length EbCHI cDNA without a stop codon was cloned into the plasmid pHB-flag using the BamHI and SpeI restriction sites to generate the pHB-EbCHI-flag construct. The primers pHB-EbCHI-F and pHB-EbCHI-R were used and are listed in Supplementary Table S1. The plasmids pHB-EbCHI-flag and pHB-flag were separately transformed into the A. tumefaciens strain C58C1 by the heat shock method. Using the plant transformation method mentioned above, pHB-EbCHI-flag (EbCHI-OVX), pHB-flag (CK) introduced and non-plasmid-introduced (WT) A. tumefaciens were separately introduced into E. breviscapus to generate transgenic hairy root cultures. At week 10, the hairy roots were harvested for DNA extraction and RNA extraction. Genomic DNA was isolated and then used in a PCR analysis for the detection of the presence of the exogenous EbCHI. The primer pHB-EbCHI-1F and Rbcs-R were specifically designed to cover the 3′ terminus of the EbCHI sequence and the vector sequence (EbCHI+vector: 243 bp + 506 bp) for detecting exogenous EbCHI transformations. Primers for the rolB gene in the A. tumefaciens genomic DNA and the hygromycin resistance gene (hyg) in the plasmid pHB-flag were also used together to make sure that the transformations were successful.To construct the EbCHS, EbCHI, EbFNS, and EbF3H was quantified in the total RNA isolated from different organs  through qPCR using gene-specific primers (Supplementary Table S1). The relative expression levels are shown in Figure 2A, which indicated that all genes were highly expressed in leaves except for the similar expression of EbCHI in the three tissues. In addition, the contents of total flavones and scutellarin were both highest in leaves and lowest in roots. The content of scutellarin was 7.7-fold higher in leaves than in roots .Since the expression profile of a gene is often correlated with its function, the relative expression of the four genes p < 0.01). The transcript levels of EbCHS, EbCHI, EbF3H, and EbFNS were gradually stimulated . The expression of EbCHI, EbCHS, and EbF3H reached the highest levels at 3 h after treatment, but that of EbFNS was at 12 h after treatment, followed by a reduction. The maximum mRNA transcript levels of EbCHS, EbCHI, EbF3H, and EbFNS were 15.9-, 4.9-, 5.8-, and 19.9-fold higher than those of the control (untreated plants), respectively.MeJA treatment significantly induced the expression of genes involved in the biosynthesis of scutellarin .To examine the response of metabolites to MeJA treatment, a liquid chromatography – tandem mass spectrometry (LC-MS/MS) method was established to determine the levels of five metabolites involved in scutellarin biosynthesis in Figure 4, the relative contents of these five compounds were induced to varying degrees. The content of scutellarin was increased by 1.86-fold by MeJA treatment. Apigenin was increased more than six-fold in MeJA-induced cultures compared with control. As shown in Figure 1B, apigenin, as a common precursor, could be separated into two different pathways to produce apigenin 7-O-glucuronide and scutellarin. The content of apigenin reached its highest level at day two, and most apigenin was converted to apigenin-7-glucoside at day three, not scutellarin. The contents of apigenin-7-glucuronide, scutellarein, and apigenin-7-glucoside were most increased, by 1.5, 2.1, and 5.4, respectively. The absolute DW contents are listed in Supplementary Table S2, which shows a higher content of the two major active compounds (scutellarin and apigenin 7-O-glucuronide) than of the other three.As shown in Figure 5. The first pair of canonical correlation variables (U and V) revealed a clear correlation between gene transcripts and the target metabolites: the canonical correlation coefficient was 0.916. Details of the correlation coefficients between the raw variables (gene or metabolite) and the canonical correlation variables (U or V) are listed in Supplementary Table S3. Variable correlation coefficient cutoff values (0.5 in this study) were applied to draw the edges as part of the exploratory study of gene-to-metabolite correlation structure. For example, the variable correlation coefficients between the EbCHI transcript and the five compound accumulations were 0.719, 0.642, 0.895, -0.041, and 0.105, respectively, which indicated that EbCHI, as an upstream gene, was correlated with apigenin 7-O-glucuronide, scutellarin and apigenin, and most closely with apigenin, but was not obviously correlated with scutellarein or apigenin 7-O-glucoside. In conclusion, the observations were as follows:The accumulation profiles of the five compounds were combined with the expression profiles of four genes involved in the scutellarin biosynthesis pathway for an integrated analysis. To explore the correlation structure of the data, a canonical correlation analysis was performed, as shown in (1)EbCHI and EbCHS) both showed strong correlations with scutellarin, apigenin 7-O-glucuronide and apigenin;two upstream genes ((2)EbF3H, as a alternative pathway gene, showed very little correlation with any compounds involved in the biosynthesis of scutellarin;(3)EbFNS showed a correlation with only the accumulation of scutellarein.EbCHI is a promising candidate for metabolic engineering to increase the content of the bioactive metabolite scutellarin.According to the results of the integrated analysis, the upstream enzyme EbCHI contains an ORF of 714 nucleotides corresponding to a 238-amino-acid protein with a calculated molecular mass of 25.64 kDa and a pI of 4.99 (Supplementary Table S4). Using the neighbor-joining method, a phylogenetic analysis was performed. The phylogenetic tree indicated that EbCHI was clustered with other CHIs from the Compositae . EbCHI had high homology to orthologues in other plants, which showed high conservation of the CHI enzyme during its evolutionary process . Like the CHIs in other plants, EbCHI had only one chalcone isomerase domain . The secondary structure estimation showed that the EbCHI peptide contained 36.55% alpha helices, 21.43% extended strands, 12.18% beta turns and 29.83% random coils. Alpha helices and random coils were the most abundant structural elements, penetrating through most of the EbCHI secondary structure, while extended strands and beta turns were intermittently distributed in the protein . The 3-D structure of EbCHI was predicted by Phyre2 using sequence-homology-based structural modeling5 . As shown in Supplementary Figure S2F, similar to that of GFP alone , the fluorescence of the fusion protein EbCHI-GFP was distributed in the cytoplasm , which indicated that the conversion of chalcone to naringenin by EbCHI should take place in the cytoplasm, in accordance with previous reports , were separately introduced into the E. coli. cell line BL21 (DE3). Upon induction by IPTG, a fusion protein, EbCHI-His, was represented as the main soluble protein product . The purified EbCHI-His protein presented a single distinct band . Figure 6A, lane 4, contained the crude enzyme extract from E. coli with the pET-32a vector. Western blotting of the purified recombinant EbCHI-His protein confirmed its immune reactivity to anti-His antibodies . We used naringenin chalcone as a substrate to test its enzyme activity. The reaction products of recombinant EbCHI-His were detected by HPLC monitored at 254 nm and identified by comparison to naringenin and naringenin chalcone standards . On the one hand, the HPLC elution profiles of reaction products showed that EbCHI yielded naringenin. On the other hand, the control produced a very low abundance of spontaneous product and left a majority of residual substrate. As predicted, EbCHI converted naringenin chalcone into naringenin.To test the function of the E. breviscapus was first established. Based on the results of preliminary experiments, sterile leaf sections were optimally provided as donor explants for genetic transformation with the disarmed A. tumefaciens strain C58C1 (pRiA4). Successful transformation was indicated by the submergence of wounded leaves in the bacterial suspension  for 5, 10, and 15 min. The optimal transformation rate (reaching a maximum of 60%) was observed when explants were induced in the bacterial suspension (OD600 = 0.6) for 10 min and co-cultured in B5 medium supplemented with 125 μM acetosyringone for 2 days (Supplementary Table S5). Established E. breviscapus hairy root cultures exhibited the typical morphological characteristics, with vigorous growth on phytohormone-free medium, extensive lateral branching and lack of geotropism . In addition to these morphological characteristics, the rolB gene (located in the Ri T-DNA segment) was amplified from the genome of hairy roots, which confirmed the transformation of the hairy root cultures at the molecular level . As shown in Figure 8, the growth rates varied in different media. The growth rate of hairy root in B5 medium was significantly higher than that in the other media . Meanwhile, the highest yield was also produced in B5 medium within 10 weeks.In this research, the hairy root culture of EbCHI cDNA without a stop codon was successfully subcloned into the plasmid pHB-flag using the BamHI and SpeI restriction sites to generate the pHB-EbCHI-flag construct . The EbCHI overexpression vector pHB-EbCHI-flag and the vector control pHB-flag were separately introduced into E. breviscapus to generate EbCHI-OVX and CK hairy root cultures; meanwhile, hairy root lines generated through transformation with the blank C58C1 strain produced WT cultures.The full-length rolB, the hygromycin resistance gene (hyg) and the exogenous EbCHI gene in EbCHI-OVX lines . The rolB gene in the genome of A. tumefaciens indicated that the hairy roots had been induced by A. tumefaciens. The hyg gene indicated that the plasmid pHB-flag or pHB-EbCHI-flag had been transformed into the hairy roots. The PCR product consisting of the EbCHI 3′ fragment and vector fragment indicated that exogenous EbCHI had been successfully introduced into the genome of the E. breviscapus hairy roots.PCR analyzes showed that these hairy root cultures contained EbCHI expression levels in all the five independent EbCHI-OVX lines  were significantly enhanced . No significant difference was observed between the WT and CK lines . These results indicated that the exogenous EbCHI gene had been successfully integrated and was highly expressed in E. breviscapus hairy root cultures.A qPCR analysis indicated that, in comparison with the levels of the WT control, the EbCHI-OVX lines were significantly higher than those in the WT and CK lines, and the scutellarin accumulations in different independent lines were closely correlated with the corresponding EbCHI expression levels . Line OVX-2, with the highest EbCHI expression, produced the most abundant scutellarin , which was ∼2.4- and 3.1-fold higher than that in its WT  and CK  counterparts, respectively.Metabolite analysis showed that the contents of scutellarin in the Metabolic pathways are very complex. It is therefore difficult to exactly target the best intervention points to obtain the best outcome. However, biotechnological advances in data mining are taking away much of the guesswork by allowing the impact of modifications to be predicted more accurately (Saito and Matsuda). In particular, gene-metabolite network analysis is a powerful tool for decoding the functions of genes and screening rate-limiting enzymes . This knE. breviscapus and repressed JA-regulated flavonoid accumulation. Then, exogenous MeJA induced the degradation of JAZ proteins through the SCFCOI1-26S proteasome pathway, and the released MBW complexes activated early biosynthetic genes (EBGs) of the flavonoid pathway, including CHS, CHI, F3H, FNS, and F3′H , is a powerful plant hormone that regulates many developmental processes and stress tolerance and resistance through secondary metabolism, including flavonoid biosynthesis . The jasand F3′H .I. indigotica . In previous studies, a 12-fold higher level of apigenin was accumulated in CHI-overexpressing Saussurea medusa hairy roots than in WT hairy roots  has been achieved successfully in many pharmaceutically valuable metabolic pathways, such as the screening of AP2/ERF transcription factors and key enzymes involved in lignan biosynthesis in digotica , the chaiorrhiza , 2015 anbidopsis . In thisry roots . The ovecalensis . To valiE. breviscapus under optimal conditions to produce the bioactive compound scutellarin. To produce a high concentration of scutellarin, EbCHI-overexpressing hairy root cultures were established for metabolic engineering to enhance scutellarin accumulation. Compared with the 2.6 mg g-1 (dw) and 0.21 mg g-1 (dw) in natural whole plant and root, 2.21 mg g-1 (dw) was found in these transgenic hairy root cultures.Plants accumulate very rich and diverse bioactive metabolites, so the consumption of herbal medicines and medicinal plants is widespread and increasing. Because the main source of raw materials is from natural and wild fields, the problems of quality stability and overexploitation need to be addressed urgently. In recent years, significant progress has been made in the use of tissue and cell culture . With thE. breviscapus as a source of variation of gene expression and metabolites provided new insights into scutellarin biosynthetic genes. EbCHI is undoubtedly a key rate-limiting step in the scutellarin biosynthetic pathway. EbCHI-overexpressing hairy root cultures accumulated high levels of scutellarin, providing a promising method to relieve the overexploitation and shortage of E. breviscapus in the future.In conclusion, the current study selects more suitable intervention points to engineer the production of target metabolites effectively through a knowledge-driven approach combining gene expression and metabolite accumulation data. The method of integrating transcript and metabolite data using MeJA-elicited RC, TZ, JL, LZ, and WC conceived and designed the study. RC, TZ, and JY performed the experiments. HT conducted the experiment of subcellular localization. RC, JL, and QL contributed to data analysis and bioinformatics analysis. RC, TZ, and SG analyzed the accumulation of compounds through HPLC-MS/MS and HPLC-UV. RC, TZ, and JL wrote the final manuscript. All authors read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In this era of precision medicine, the DNA damage response (DDR) pathway has been shown to be a viable target of intervention in metastatic castration-resistant prostate cancer (CRPC) as approximately one-third of CRPC patients harbor DDR pathway mutations. To determine whether DDR pathway is a potential therapeutic target in localized disease, we analyzed The Cancer Genome Atlas (TCGA) in the present study.TCGA is a publically available cancer genome database that is sponsored by the United States National Cancer Institute. Total of 455 cases were available in the database at the time of this analysis.p = 0.0291).DDR pathway gene mutations or copy number alterations were present in 136 (29.9%) of the 455 cases. On a univariate analysis, DDR pathway status did not correlate with serum prostate specific antigen, tumor stage or grade. However, among patients with high-risk features post-operatively , DDR pathway alteration was associated with a lower overall survival (Collectively these results suggest that DDR pathway alterations may also be significant in localized prostate cancer and agents such as PARP inhibitors should be considered in patients with a high-risk disease. Prostate cancer (PCa) remains the most common malignancy among men in the United States . Due to With regards to PCa specifically, approximately 30% of metastatic castration-resistant prostate cancer (CRPC) have been reported to contain an aberrant DDR pathway . Howeverhttp://www.cbioportal.org/index.do?session_id=5b8fc998498eb8b3d567b2ac). Three sets of data were extracted and compiled based on the following criteria: pathologic Gleason score and stage, pre-operative PSA, and survival. The Provisional data was used for the pathologic Gleason score and stage, the Cell 2015 data was used for pre-operative PSA, and both the Provisional and Cell 2015 data were merged for the survival.Both the Provisional and Cell 2015 TCGA data were initially extracted as TSV files. At the time of this analysis, there were 455 patients in the Provisional TCGA database  vs non-organ confined (≥ T3a).Pre-operative PSA, divided into ranges [0–10], [10–20], and greater than or equal to 20, which was extracted by cross-referencing the given sample ID from the Provisional data to the Cell 2015 data.The programming language Python was used to extract the samples in which the Neoplasm American Joint Committee on Cancer Clinical Distant Metastasis M Stage was M0. These samples were first separated into two categories, the first being normal (unaffected) and the second being altered . Within these categories, the samples were then placed into sets based on three factors:The attributes that were recorded and placed into the respective Excel files that included the sample ID, the months that the patient was disease free, months of overall survival, and overall survival status.p < 0.05 was considered to indicate statistical significance. All analyses were performed by Python and SAS 9.4 .Baseline patient and clinical characteristics were summarized using descriptive statistics. Fisher’s exact test was performed to test the association between two categorical variables. Student’s t-test was used to compare mean age between the affected and unaffected group. The association of DDR mutation status with time from diagnosis to death from any cause was evaluated using log-rank tests and Kaplan-Meier curve estimates were plotted. All statistical tests were two-sided and The overall incidence of DDR pathway alterations in localized prostate cancer approaches 30%. To assess the potential pathologic significance of DDR pathway in localized prostate cancer, we analyzed the TCGA prostate cancer database for mutations or copy number alterations of the following twelve genes . The results revealed that 136 of the 455 cases were affected (29.9%), with 54 containing mutations and 92 copy number alterations (CNAs) . The summary statistics of the patients with DDR pathway alterations are shown in Table p = 0.57). With respect to pathologic Gleason score 6, 7, and ≥ 8, the proportion affected was 6.6, 49.3, and 44.1% (p = 0.61).Figure DDR pathway alterations associated with poor prognosis in men with high-risk prostate cancer. Next, we stratified the data based on pre-operative PSA and pathologic Gleason score and stage and investigated the potential prognostic value of DDR pathway alterations. Of the 455 cases in the database, survival data was available in 371 while pre-operative PSA in 164. The results were not significant for pre-operative PSA and pathologic Gleason score. However, in patients with pT3 or higher disease, DDR pathway alterations was associated with a lower overall survival (OS) . In addition, in men with features of high-risk of recurrence following radical prostatectomy , DDR pathway alterations again correlated with a shorter OS .In the present study, we investigated DDR pathway alterations in localized prostate cancer using the TCGA database. We found that DDR pathway alteration rate is surprisingly high and occurred in approximately 30% of the cases. In addition, DDR pathway alteration was associated with a shorter OS in men with high-risk features post-operatively. These results suggest that a dysregulated DDR pathway may occur earlier during prostate cancer progression than previously thought and that available inhibitors of DDR pathway may have a therapeutic role in localized prostate cancer.The observed DDR pathway alterations rate in localized prostate cancer was significantly higher than expected based on the reported range of 8–20% . PreviouThe present finding also has therapeutic implications. Currently, there are multiple agents such as olaparib, niraparib, and rucaparib , 13, 14 It should be noted that a recent manuscript also investigated the DDR pathway in localized prostate cancer using the same TCGA database . HoweverThis study has limitations. First, TCGA database does not contain all the relevant clinical information. Second, the biological significance of DDR pathway alterations cannot be assessed. Indeed, as indicators of altered DDR pathway, both mutations and CNAs were included. It is entirely possible that these various types of genetic changes may have different pathologic implications. Nevertheless, the present results suggest that DDR pathway alterations in localized prostate cancer is similar to that of heavily treated mCRPC, which supports further investigations into therapeutic strategies in this population.DDR pathway alterations in localized prostate cancer in the TCGA database was approximately 30%. Such high rate suggests that agents such as PARP inhibitors may be an effective part of the treatment armamentarium in localized prostate cancer.


To identify pathways associated with survival phenotypes using gene expression data, we recently proposed the hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE) method. The HisCoM-PAGE software can consider hierarchical structural relationships between genes and pathways and analyze multiple pathways simultaneously. It can be applied to various types of gene expression data, such as microarray data or RNA sequencing data. We expect that the HisCoM-PAGE software will make our method more easily accessible to researchers who want to perform pathway analysis for survival times. Availability: HisCoM-PAGE is available on the website (http://statgen.snu.ac.kr/software/HisCom-PAGE/).Transcriptome profiling is a common approach to the study of human diseases . The traMany previous pathway analyses have mainly focused on binary phenotypes. Thus, not many methods and software programs are available to analyze the survival phenotype. In addition, many pathway methods perform single-pathway analyses, but do not consider correlations between pathways.Recently, we proposed the hierarchical structural component model for the pathway analysis of gene expression data (HisCoM-PAGE) method  based onThe workflow of the HisCoM-PAGE software is shown in The HisCoM-PAGE software takes the following three inputs: (1) a gene expression file, where the rows represent the sample names, the columns represent the pathway-matched gene name, and each cell represents the normalized gene expression value; (2) a trait file, in which each line consists of two columns for the sample’s survival time and censoring status, respectively; and (3) a pathway annotation file consisting of two columns for pathway and gene names, respectively. Users can optionally make their own gene-pathway pair list for analysis.path), permutation p-value, and the false discovery rate (FDR) corrected q-value, respectively; (2) a ‘gene result-1.csv’ file containing five columns showing the pathway name, gene name, gene coefficient (wgene), p-value, and FDR-corrected q-value, respectively ; and (3) a ‘gene result-2.csv’ file that also contains five columns showing the pathway name, gene name, gene coefficient, p-value, and FDR-corrected q-value, respectively. The coefficients contained in this result file are calculated using the wgene× βpath value for each gene, which represents the effect of the gene on the phenotype.The HisCoM-PAGE software can generate the following three output files: (1) a ‘pathway results.csv’ file, which contains four columns for the pathway name, pathway coefficient (βIn this paper, we introduce the HisCoM-PAGE software for pathway analysis of the survival phenotype using gene expression data. The HisCoM-PAGE software may be a useful tool for the identification of pathways associated with the survival phenotype. The software is freely available on the website, along with a detailed tutorial.