Screening and bioinformatics analysis of key autophagy-related genes in alcoholic hepatitis / 器官移植

Objective To screen key autophagy-related genes in alcoholic hepatitis (AH) and investigate potential biomarkers and therapeutic targets for AH. Methods Two AH gene chips in Gene Expression Omnibus (GEO) and autophagy-related data sets obtained from MSigDB and GeneCards databases were used, and the key genes were verified and obtained by weighted gene co-expression network analysis (WGCNA). The screened key genes were subject to gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) and immune infiltration analyses. Messenger RNA (mRNA)- microRNA (miRNA) network was constructed to analyze the expression differences of key autophagy-related genes during different stages of AH, which were further validated by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) in the liver tissues of AH patients and mice. Results Eleven autophagy-related genes were screened in AH (EEF1A2, CFTR, SOX4, TREM2, CTHRC1, HSPB8, TUBB3, PRKAA2, RNASE1, MTCL1 and HGF), all of which were up-regulated. In the liver tissues of AH patients and mice, the relative expression levels of SOX4, TREM2, HSPB8 and PRKAA2 in the AH group were higher than those in the control group. Conclusions SOX4, TREM2, HSPB8 and PRKAA2 may be potential biomarkers and therapeutic targets for AH.

Identification of key immune related genes in diabetes retinopathy based on weighted gene co-expression network / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To explore the key genes related to immunity and immune cell infiltration levels in diabetes retinopathy(DR)using bioinformatics.METHODS: Differential expression genes(DEGs)were obtained by “limma” R from Gene Expression Omnibus(GEO)data from September to October 2022, Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)were analyzed, and the infiltration of immune cell types in each sample was calculated based on CIBERSORT algorithm. Weighted gene co-expression network analysis(WGCNA)was used to screen for DEGs in immune-related gene modules. The protein-protein interaction(PPI)network was established by STRING online database and Cytoscape, and the hub genes were screened by MCODE and cytoHubba plug-ins.RESULTS: The results showed that 1 426 up-regulated and 206 down-regulated differential genes were screened, where 7 immune cell types, including B cell naive, Plasma cells, CD4+T cells, T cells regulatory(Tregs), Macrophages M0, Macrophages M1 and Neutrophils were significantly overexpressed(P<0.05), while others were low expressed(P<0.05). After WGCNA, a total of 820 DEGs were found in the modules most related to immunity. After constructing the PPI network, 10 key genes were screened using plug-ins, and two key genes were further screened using the expression amount of each differential gene in PPI: DLGAP5 and AURKB.CONCLUSION: This study used bioinformatics to screen the infiltration of immune cells and key genes related to immunity in patients with DR. These findings may provide evidences for future research, diagnosis, and treatment of DR.

Identification of M1 macrophage-related genes in rejection after kidney transplantation based on weighted gene co-expression network analysis / 器官移植

Objective To identify M1 macrophage-related genes in rejection after kidney transplantation and construct a risk prediction model for renal allograft survival. Methods GSE36059 and GSE21374 datasets after kidney transplantation were downloaded from Gene Expression Omnibus (GEO) database. GSE36059 dataset included the samples from the recipients with rejection and stable allografts. Using this dataset, weighted gene co-expression network analysis (WGCNA) and differential analysis were conducted to screen the M1 macrophage-related differentially expressed gene (M1-DEG). Then, GSE21374 dataset (including the follow-up data of graft loss) was divided into the training set and validation set according to a ratio of 7∶3. In the training set, a multivariate Cox's model was constructed using the variables screened by least absolute shrinkage and selection operator (LASSO), and the ability of this model to predict allograft survival was evaluated. CIBERSORT was employed to analyze the differences of infiltrated immune cells between the high-risk group and low-risk group, and the distribution of human leukocyte antigen (HLA)-related genes was analyzed between two groups. Gene set enrichment analysis (GSEA) was used to further clarify the biological process and pathway enrichment in the high-risk group. Finally, the database was employed to predict the microRNA (miRNA) interacting with the prognostic genes. Results In the GSE36059 dataset, 14 M1-DEG were screened. In the GSE21374 dataset, Toll-like receptor 8 (TLR8), Fc gamma receptor 1B (FCGR1B), BCL2 related protein A1 (BCL2A1), cathepsin S (CTSS), guanylate binding protein 2(GBP2) and caspase recruitment domain family member 16 (CARD16) were screened by LASSO-Cox regression analysis, and a multivariate Cox's model was constructed based on these 6 M1-DEG. The area under curve (AUC) of receiver operating characteristic of this model for predicting the 1- and 3-year graft survival was 0.918 and 0.877 in the training set, and 0.765 and 0.736 in the validation set, respectively. Immune cell infiltration analysis showed that the infiltration of rest and activated CD4+ memory T cells, γδT cells and M1 macrophages were increased in the high-risk group (all P < 0.05). The expression level of HLA I gene was up-regulated in the high-risk group. GSEA analysis suggested that immune response and graft rejection were enriched in the high-risk group. CTSS interacted with 8 miRNA, BCL2A1 and GBP2 interacted with 3 miRNA, and FCGR1B interacted with 1 miRNA. Conclusions The prognostic risk model based on 6 M1-DEG has high performance in predicting graft survival, which may provide evidence for early interventions for high-risk recipients.

Exploring biological connotation of blood stasis syndrome of rheumatoid arthritis and establishment of improved animal models based on syndrome-symptom mapping / 药学学报

Blood stasis syndrome is one of the core clinical syndrome of rheumatoid arthritis (RA), but the biological connotation of this syndrome is not clear, and there is a lack of disease improved animal models that match the characteristics of this disease and syndrome. The aim of this study was to screen the candidate biomarker gene set of blood stasis syndrome of RA, reveal the biological connotation of this syndrome, and explore and evaluate the preparation method of the improved animal model based on the characteristics of "disease-syndrome-symptom". The study was approved by the ethics committee of Guang'anmen Hospital, Chinese Academy of Traditional Chinese Medicine (No. 2019-073-KY-01) and the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine (No. TYLL2021[K]018), and the study subjects gave their informed consent. Animal welfare and experimental procedures followed the regulations of the Experimental Animal Ethics Committee of the Chinese Academy of Traditional Chinese Medicine (No. IBTCMCACMS21-2207-01). The whole blood samples were collected clinically from RA patients with blood stasis syndrome (3 cases) or other syndromes (7 types, 3 cases/type), and healthy volunteers (4 cases), and then transcriptome sequencing, KEGG, gene set enrichment analysis (GSEA) and weighted correlation network analysis (WGCNA) analysis were performed. 126 pivotal genes were screened, and their functional annotation results were significantly enriched in "immune-inflammation" related pathways and lipid metabolism regulation (sphingolipids, ether lipid metabolism and steroid biosynthesis). Syndrome-symptom mapping of hub gene set to the TCM primary and secondary symptoms, Western phenotypic symptoms and pathological links showed that joint tingling, abnormal joint morphology, petechiae and abnormal blood circulation are representative of blood stasis syndrome of RA. The results of the improved animal model showed that the rats in the collagen-induced arthritis + adrenaline hydrochloride (CIA+Adr) 3 model group had increased blood rheology, coagulation, platelet function and endothelial function abnormalities compared with the CIA-alone model group, suggesting that the rats with blood stasis syndrome of RA may be in a state of "blood stasis". The results of the study can help to advance the objective study of the evidence of blood stasis syndrome in RA, and provide new ideas for the establishment of an animal model that reflects the clinical characteristics of the disease and syndrome.

Identification of hub genes in airway epithelial cells of asthma patients by WGCNA and PPI network

Bronchial asthma is a common chronic disease of airway inflammation, high mucus secretion and airway hyper responsiveness. The pathogenetic mechanisms of asthma remain unclear. In this study, we aimed at identifying genes playing an import role in disease-related pathways in airway epithelial cells of asthma patients. Microarray data GSE41861 of asthma airway epithelial cells was used to screen differentially expressed genes (DEGs) through GEO2R analysis. The weighted gene co-expression network analysis (WGCNA) was performed to identify gene co-expression network modules in bronchial asthma. The DAVID database was then used to perform functional and pathway enrichment analysis of these DEGs. In addition, we have conducted protein-protein interaction (PPI) network of DEGs by STRING, and eventually found key genes and significant modules. A total of 315 DEGs (111 up-regulated and 204 down-regulated) were identified between severe asthma and healthy individual, which were mainly involved in pathways of cilium assembly, cilium morphogenesis, axon guidance, positive regulation of fat cell differentiation, and positive regulation of cell substrate adhesion. A total of 60 genes in the black module and green module were considered to be correlated with the severity of asthma. Combining PPI network, several key genes were identified, such as BP2RY14, PTGS1, SLC18A2, SIGLEC6, RGS13, CPA3, and HPGDS. Our findings revealed several genes that may be involved in the process of development of bronchial asthma and potentially be candidate targets for diagnosis or therapy of bronchial asthma.

Comparative molecular analysis of oral submucous fibrosis and other organ fibrosis based on weighted gene co-expression network analysis / 中南大学学报(医学版)

OBJECTIVES@#There is currently a lack of economic and suitable animal models that can accurately recapitulate the oral submucous fibrosis (OSF) disease state for indepth study. This is one of the primary reasons for the limited therapeutic methods available for OSF. Based on the underlying logic of pan-cancer analysis, this study systematically compares OSF and the other four types of organ fibrosis from the aspects of molecules, signaling pathways, biological processes, etc. A comprehensive analysis of the similarities and differences between OSF and other organ fibrosis is helpful for researchers to discover some general rules of fibrosis disease and may provide new ideas for studying OSF.@*METHODS@#Microarray data of the GSE64216, GSE76882, GSE171294, GSE92592, and GSE90051 datasets were downloaded from GEO. Differentially expressed mRNAs (DEmRNAs) of each type of fibrosis were identified by Limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify each type of fibrosis-related module. The similarities and differences of each fibrosis-related-module genes were analyzed by function and pathway enrichment analysis.@*RESULTS@#A total of 6 057, 10 910, 27 990, 10 480, and 4 801 DEmRNAs were identified in OSF, kidney intestinal fibrosis (KIF), liver fibrosis (LF), idiopathic pulmonary fibrosis (IPF), and skin fibrosis (SF), respectively. By using WGCNA, each type of fibrosis-related module was identified. The co-expression networks for each type of fibrosis were constructed respectively. Except that KIF and LF have 5 common hub genes, other fibrotic diseases have no common hub genes with each other. The common pathways of OSF, KIF, LF, IPF, and SF mainly focus on immune-related pathways.@*CONCLUSIONS@#OSF and the other 4 types of fibrotic diseases are tissue- and organ-specific at the molecular level, but they share many common signaling pathways and biological processes, mainly in inflammation and immunity.

Effects of sodium iodide symporter co-expression on proliferation and cytotoxic activity of chimeric antigen receptor T cells in vitro / 南方医科大学学报

OBJECTIVE@#To investigate the effects of co-expression of sodium iodide symporter (NIS) reporter gene on the proliferation and cytotoxic activity of chimeric antigen receptor (CAR)-T cells in vitro.@*METHODS@#T cells expressing CD19 CAR (CAR-T cells), NIS reporter gene (NIS-T cells), and both (NIS-CAR-T cells) were prepared by lentiviral infection. The transfection rates of NIS and CAR were determined by flow cytometry, and the cell proliferation rate was assessed using CCK-8 assay at 24, 48 and 72 h of routine cell culture. The T cells were co-cultured with Nalm6 tumor cells at the effector-target ratios of 1∶2, 1∶1, 2∶1 and 4∶1 for 24, 48 and 72 h, and the cytotoxicity of CAR-T cells to the tumor cells was evaluated using lactate dehydrogenase (LDH) assay. ELISA was used to detect the release of IFN-γ and TNF-β in the co-culture supernatant, and the function of NIS was detected with iodine uptake test.@*RESULTS@#The CAR transfection rate was 91.91% in CAR-T cells and 99.41% in NIS-CAR-T cells; the NIS transfection rate was 47.83% in NIS-T cells and 50.24% in NIS- CAR-T cells. No significant difference in the proliferation rate was observed between CAR-T and NIS-CAR-T cells cultured for 24, 48 or 72 h (P> 0.05). In the co-cultures with different effector-target ratios, the tumor cell killing rate was significantly higher in CAR-T group than in NIS-CAR-T group at 24 h (P < 0.05), but no significant difference was observed between the two groups at 48 h or 72 h (P>0.05). Higher IFN-γ and TNF-β release levels were detected in both CAR-T and NIS-CAR-T groups than in the control group (P < 0.05). NIS-T cells and NIS-CAR-T cells showed similar capacity of specific iodine uptake (P>0.05), which was significantly higher than that in the control T cells (P < 0.05).@*CONCLUSION@#The co-expression of the NIS reporter gene does not affect CAR expression, proliferation or tumor cell-killing ability of CAR-T cells.

Association of CDH11 with Autism Spectrum Disorder Revealed by Matched-gene Co-expression Analysis and Mouse Behavioral Studies / 神经科学通报·英文版

A large number of putative risk genes for autism spectrum disorder (ASD) have been reported. The functions of most of these susceptibility genes in developing brains remain unknown, and causal relationships between their variation and autism traits have not been established. The aim of this study was to predict putative risk genes at the whole-genome level based on the analysis of gene co-expression with a group of high-confidence ASD risk genes (hcASDs). The results showed that three gene features - gene size, mRNA abundance, and guanine-cytosine content - affect the genome-wide co-expression profiles of hcASDs. To circumvent the interference of these features in gene co-expression analysis, we developed a method to determine whether a gene is significantly co-expressed with hcASDs by statistically comparing the co-expression profile of this gene with hcASDs to that of this gene with permuted gene sets of feature-matched genes. This method is referred to as "matched-gene co-expression analysis" (MGCA). With MGCA, we demonstrated the convergence in developmental expression profiles of hcASDs and improved the efficacy of risk gene prediction. The results of analysis of two recently-reported ASD candidate genes, CDH11 and CDH9, suggested the involvement of CDH11, but not CDH9, in ASD. Consistent with this prediction, behavioral studies showed that Cdh11-null mice, but not Cdh9-null mice, have multiple autism-like behavioral alterations. This study highlights the power of MGCA in revealing ASD-associated genes and the potential role of CDH11 in ASD.

Identification of core genes related to severity of respiratory syncytial virus bronchiolitis based on RNA sequencing data / 中华微生物学和免疫学杂志

Objective:To identify the core genes related to the disease severity of respiratory syncytial virus (RSV) bronchiolitis in children using RNA sequencing (RNA-seq) and weighted gene co-expression network analysis (WGCNA), aiming to provide reference for predicting the condition of RSV infection.Methods:Twenty-two patients admitted to the Second Affiliated Hospital of Wenzhou Medical University with RSV bronchiolitis from October 1, 2019 to February 29, 2020 were enrolled as the case group. They were divided into three groups based on the severity of the disease: mild group, moderate group and severe group. Twenty-two healthy children were selected as the control group. Total RNA was extracted from whole blood leukocytes and analyzed by RNA-seq to compare the differentially expressed genes (DEGs) between children with RSV bronchiolitis and healthy children. The gene co-expression modules related to disease severity and biological indicators for disease severity assessment were identified.Results:The median age of the 22 patients (19 males and 3 females) was 3 months. The median age of the 22 healthy children (14 males and 8 females) was 4 months. There was no significant difference in age or gender between the two groups. There were 8 cases in the mild group, 7 cases in the moderate group and 7 cases in the severe group. Through significance analysis, 416 DEGs were found in the mild group, 586 in the moderate group and 846 in the severe group. According to WGCNA analysis, 10 co-expression modules were found, among which brown module ( r=0.62, P<0.001) was significantly correlated with disease severity. The protein-protein interaction network of DEGs in brown module was constructed and the top 30 core genes were selected according to the connectivity of gene nodes, among which the genes with high correlation were RBX1 and PSMA7. The expression of RBX1 and PSMA7 genes was up-regulated in the severe group, but their expression in the mild and moderate groups was not significantly different from that in the control group. Conclusions:RBX1 and PSMA7 genes might be biological predictors of disease severity in RSV bronchiolitis.

Identification of key genes in nonarteritic anteriorischemic optic neuropathy through weighted gene co-expression network analysis / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: We sought to identify key genes related to nonarteritic anterior ischemic optic neuropathy(NAION)and provide bioinformatics support for elucidating the pathogenesis of NAION.METHODS: Based on rat GSE43671 dataset, which was acquired from GEO, we identified modular genes with highly correlated clinical phenotype by WGCNA package in the R language. Then Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)analysis were performed with ClusterProfiler package. In addition, Cytoscape was used to screen potential key genes and establish miRNA-key genes network.RESULTS: There were 22 modules identified from the GSE43671 dataset by the WGCNA method, among which the blue module has the highest correlation coefficient. GO enrichment analysis suggested that the genes in the module mainly manifest in the epithelial tube morphogenesis and other biological processes, receptor complex and other cell components, and structural constituent of eye lens and other molecular functions. KEGG suggested that the genes in the module mainly relate to signaling pathways including neuroactive ligand-receptor interaction, human papillomavirus, MAPK and PI3K/Akt. There were 10 key genes screened by PPI network and Cytoscape including Psmb9, Psma7, Map3k14, Psme1, Nfkb1, Rela, Psma5, Relb, Psmb4 and Nfkb2, and 6 miRNA were predicted as miR-383-5p, miR-9a-5p, miR-155-5p, miR-223-3p, miR-495 and miR-325-3p.CONCLUSION: Using the WGCNA method to screen out the relevant pathways, key genes, and microRNA for NAION, it provides a theoretical basis for exploring pathogenesis and treatment methods of NAION, however, more animal and cell experiments are needed to further validate.

Dysregulation of MAD2L1/CAMK2A/PTTG1 Gene Cluster Maintains the Stemness Characteristics of Uterine Corpus Endometrial Carcinoma / 中国医学科学院学报

Objective To study the stemness characteristics of uterine corpus endometrial carcinoma(UCEC)and its potential regulatory mechanism.Methods Transcriptome sequencing data of UCEC was obtained from The Cancer Genome Atlas.Gene expression profile was normalized by edgeR package in R3.5.1.A one-class logistic regression machine learning algorithm was employed to calculated the mRNA stemness index(mRNAsi)of each UCEC sample.Then,the prognostic significance of mRNAsi and candidate genes was evaluated by survminer and survival packages.The high-frequency sub-pathways mining approach(HiFreSP)was used to identify the prognosis-related sub-pathways enriched with differentially expressed genes(DEGs).Subsequently,a gene co-expression network was constructed using WGCNA package,and the key gene modules were analyzed.The clusterProfiler package was adopted to the function annotation of the modules highly correlated with mRNAsi.Finally,the Human Protein Atlas(HPA)was retrieved for immunohistochemical validation.Results The mRNAsi of UCEC samples was significantly higher than that of normal tissues(

Integration-based co-expression network analysis to investigate tumor-associated modules across three cancer types / 生物工程学报

In case/control gene expression data, differential expression (DE) represents changes in gene expression levels across various biological conditions, whereas differential co-expression (DC) represents an alteration of correlation coefficients between gene pairs. Both DC and DE genes have been studied extensively in human diseases. However, effective approaches for integrating DC-DE analyses are lacking. Here, we report a novel analytical framework named DC&DEmodule for integrating DC and DE analyses and combining information from multiple case/control expression datasets to identify disease-related gene co-expression modules. This includes activated modules (gaining co-expression and up-regulated in disease) and dysfunctional modules (losing co-expression and down-regulated in disease). By applying this framework to microarray data associated with liver, gastric and colon cancer, we identified two, five and two activated modules and five, five and one dysfunctional module(s), respectively. Compared with the other methods, pathway enrichment analysis demonstrated the superior sensitivity of our method in detecting both known cancer-related pathways and those not previously reported. Moreover, we identified 17, 69, and 11 module hub genes that were activated in three cancers, which included 53 known and three novel cancer prognostic markers. Random forest classifiers trained by the hub genes showed an average of 93% accuracy in differentiating tumor and adjacent normal samples in the TCGA and GEO database. Comparison of the three cancers provided new insights into common and tissue-specific cancer mechanisms. A series of evaluations demonstrated the framework is capable of integrating the rapidly accumulated expression data and facilitating the discovery of dysregulated processes.

Screening and identifying genes associated with malignant pleural mesothelioma based on public database / 中国职业医学

OBJECTIVE: To explore the related signaling pathways, biomarkers and prognostic genes of malignant pleural mesothelioma(MPM) based on the gene chip and second-generation sequencing datasets in public database by bioinformatics-related method. METHODS: MPM microarray expression datasets GSE51024 and GSE2549, with 82 and 49 MPM patients, respectively, were downloaded from the Gene Expression Omnibus database. The RNA sequencing data of 86 MPM patients were downloaded from the The Cancer Genome Atlas(TCGA). The weighted gene co-expression network analysis(WGCNA) and differentially expressed genes(DEGs) screening were used to screen and identify hub genes in the GSE51024 dataset by RStudio 4.0 software. The gene set enrichment analysis(GSEA) was used to explore relevant signaling pathways. Finally, a total of 135 MPM gene expression data from GSE2549 dataset and TCGA database were used to verify the hub genes. RESULTS: The green key gene module identified by the WGCNA was highly correlated with MPM, with a correlation coefficient of 0.83(P<0.01). A total of 3 245 DEGs were screened by DEGs analysis. Among them, 1 229 genes were up-regulated and 2 016 genes were down-regulated. GSEA results showed that the genes were significantly enriched in the areas of G2/M cell cycle checkpoint, epithelial-mesenchymal transition, E2 F target gene, and mitotic spindle pathways. Three hub genes were screened, including the proliferating cell nuclear antigen-associated factor(PCLAF), nucleolar and spindle-associated protein 1(NUSAP1) and topoisomerase Ⅱ-α(TOP2 A). Compared with para-cancerous tissues, normal pleural tissues or lung tissues, the relative expression of PCLAF, NUSAP1 and TOP2 A were increased in the MPM tissues(all P<0.05). Downregulation of these three genes was correlated with good prognosis, and upregulation of these three genes was correlated with poor prognosis in the patients. CONCLUSION: G2/M checkpoint, epithelial-mesenchymal transition, E2 F target gene and mitotic spindle pathway are the key signaling pathways in the occurrence and development of MPM. PCLAF, TOP2 A and NUSAP1 genes could be the biomarkers for the prognosis of MPM.

Differential mRNA expression in C57BL/6 mice with bleomycin-induced pulmonary fibrosis and its association with LncRNA co-expression network / 南方医科大学学报

OBJECTIVE@#To study the changes in mRNA and long non-coding RNA (lncRNA) expression profiles in a mouse model of bleomycin-induced lung fibrosis and identify lung fibrosis-related mRNA for coding-noncoding coexpression (CNC) bioinformatics analysis of the differential lncRNAs.@*METHODS@#Lung fibrosis was induced by intratracheal injection of bleomycin in 10 C57BL/6 mice and another 10 mice with intratracheal injection of saline served as the control group. Lung tissues were harvested from the mice at 14 days after the injections and lung fibrosis was assessed using Masson and HE staining. LncRNA chip technology was used to screen the differentially expressed mRNAs and lncRNAs in mice with lung fibrosis, and GO and KEGG pathway analyses of the differential mRNAs were performed using NCBI database and UCSC database to identify possible fibrosis-related mRNAs, which were validated by qRT-PCR to construct a coding and non-coding co- expression network with the differential lncRNAs.@*RESULTS@#Compared with the control mice, the mice with intratracheal injection of bleomycin showed obvious lung fibrosis. The results of gene chip analysis showed that 127 mRNAs were upregulated and 184 mRNAs were down-regulated in the model group as compared with the control group. GO and pathway analysis suggested that the differentially expressed genes participated mainly in immune response, cell differentiation, and cytoskeletons; the involved signal pathways were associated mainly with cytokine and cytokine receptor interaction and chemokine signal transduction. Bioinformatics analysis identified a significant coexpression network between the fibrosisrelated mRNA and the differentially expressed lncRNA.@*CONCLUSIONS@#In mice with lung fibrosis, the differential expressions of fibrosis-related mRNAs in the lung tissues are closely correlated with the co- expressions of a large number of differential lncRNAs, which points to a new direction for investigation of the pathogenesis of pulmonary fibrosis.

Transcriptomic markers in pediatric septic shock prognosis: an integrative analysis of gene expression profiles

The goal of this study was to identify potential transcriptomic markers in pediatric septic shock prognosis by an integrative analysis of multiple public microarray datasets. Using the R software and bioconductor packages, we performed a statistical analysis to identify differentially expressed (DE) genes in pediatric septic shock non-survivors, and further performed functional interpretation (enrichment analysis and co-expression network construction) and classification quality evaluation of the DE genes identified. Four microarray datasets (3 training datasets and 1 testing dataset, 252 pediatric patients with septic shock in total) were collected for the integrative analysis. A total of 32 DE genes (18 upregulated genes; 14 downregulated genes) were identified in pediatric septic shock non-survivors. Enrichment analysis revealed that those DE genes were strongly associated with acute inflammatory response to antigenic stimulus, response to yeast, and defense response to bacterium. A support vector machine classifier (non-survivors vs survivors) was also trained based on DE genes. In conclusion, the DE genes identified in this study are suggested as candidate transcriptomic markers for pediatric septic shock prognosis and provide novel insights into the progression of pediatric septic shock.

Analysis of sepsis-related genes through weighted gene co-expression network / 中华危重病急救医学

Objective:To identify the Key genes in the development of sepsis through weighted gene co-expression network analysis (WGCNA).Methods:The gene expression dataset GSE154918 was downloaded from the public database Gene Expression Omnibus (GEO) database, which containes data from 105 microarrays of 40 control cases, 12 cases of asymptomatic infection, 39 cases of sepsis, and 14 cases of follow-up sepsis. The R software was used to screen out differentially expressed genes (DEG) in sepsis, and the distributed access view integrated database (DAVID), search tool for retrieval of interacting neighbouring genes (STRING) and visualization software Cytoscape were used to perform gene function and pathway enrichment analysis, Protein-protein interaction (PPI) network analysis and key gene analysis to screen out the key genes in the development of sepsis.Results:Forty-six candidate genes were obtained by WGCNA and combined with DEG expression analysis, and these 46 genes were analyzed by gene ontology (GO) and Kyoto City Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to obtain gene functions and involved signaling pathways. The PPI network was further constructed using the STRING database, and 5 key genes were selected by the PPI network visualization software Cytoscape, including the mast cell expressed membrane protein 1 gene (MCEMP1), the S100 calcium-binding protein A12 gene (S100A12), the adipokine resistance factor gene (RETN), the c-type lectin structural domain family 4 member gene (CLEC4D), and peroxisome proliferator-activated receptor gene (PPARG), and differential expression analysis of each of these 5 genes showed that the expression levels of the above 5 genes were significantly upregulated in sepsis patients compared with healthy controls.Conclusion:In this study, 5 key genes related to sepsis were screened by constructing WGCNA method, which may be potential candidate targets related to sepsis diagnosis and treatment.

X-Module: A novel fusion measure to associate co-expressed gene modules from condition-specific expression profiles

A gene co-expression network (CEN) is of biological interest, since co-expressed genes share commonfunctions and biological processes or pathways. Finding relationships among modules can reveal inter-modularpreservation, and similarity in transcriptome, functional, and biological behaviors among modules of the sameor two different datasets. There is no method which explores the one-to-one relationships and one-to-manyrelationships among modules extracted from control and disease samples based on both topological andsemantic similarity using both microarray and RNA seq data. In this work, we propose a novel fusion measureto detect mapping between modules from two sets of co-expressed modules extracted from control and diseasestages of Alzheimer’s disease (AD) and Parkinson’s disease (PD) datasets. Our measure considers bothtopological and biological information of a module and is an estimation of four parameters, namely, semanticsimilarity, eigengene correlation, degree difference, and the number of common genes. We analyze the consensus modules shared between both control and disease stages in terms of their association with diseases. Wealso validate the close associations between human and chimpanzee modules and compare with the state-ofthe-art method. Additionally, we propose two novel observations on the relationships between modules forfurther analysis.

Analysis of differentially expressed genes in bacterial and fungal keratitis

Purpose: This study was aimed at identifying differentially expressed genes (DEGs) in bacterial and fungal keratitis. The candidate genes can be selected and quantified to distinguish between causative agents of infectious keratitis to improve therapeutic outcomes. Methods: The expression profile of bacterial or fungal infection, and normal corneal tissues were downloaded from the Gene Expression Omnibus. The limma package in R was used to screen DEGs in bacterial and fungal keratitis. The Co-Express tool was used to calculate correlation coefficients of co-expressed genes. The "Advanced network merge" function of Cytoscape tool was applied to obtain a fusional co-expression network based on bacterial and fungal keratitis DEGs. Finally, functional enrichment analysis by DAVID software and KEGG analysis by KOBAS of DEGs in fusion network were performed. Results: In total, 451 DEGs in bacterial keratitis and 353 DEGs in fungal keratitis were screened, among which 148 DEGs were found only in bacterial keratitis and 50 DEGs only in fungal keratitis. Besides, 117 co-expressed gene pairs were identified among bacterial keratitis DEGs and 87 pairs among fungal keratitis DEGs. In total, nine biological pathways and seven KEGG pathways were screened by analyzing DEGs in the fusional co-expression network. Conclusion: TLR4 is the representative DEG specific to bacterial keratitis, and SOD2 is the representative DEG specific to fungal keratitis, both of which are promising candidate genes to distinguish between bacterial and fungal keratitis.

Synthesis of L-2-aminobutyric acid by leucine dehydrogenase coupling with an NADH regeneration system / 生物工程学报

In this study, Escherichia coli BL21 (DE3) was used as the host to construct 2 recombinant E. coli strains that co-expressed leucine dehydrogenase (LDH, Bacillus cereus)/formate dehydrogenase (FDH, Ancylobacter aquaticus), or leucine dehydrogenase (LDH, Bacillus cereus)/alcohol dehydrogenase (ADH, Rhodococcus), respectively. L-2-aminobutyric acid was then synthesized by L-threonine deaminase (L-TD) with LDH-FDH or LDH-ADH by coupling with two different NADH regeneration systems. LDH-FDH process and LDH-ADH process were optimized and compared with each other. The optimum reaction pH of LDH-FDH process was 7.5, and the optimum reaction temperature was 35 °C. After 28 h, the concentration of L-2-aminobutyric acid was 161.8 g/L with a yield of 97%, when adding L-threonine in batches for controlling 2-ketobutyric acid concentration less than 15 g/L and using 50 g/L ammonium formate, 0.3 g/L NAD+, 10% LDH-FDH crude enzyme solution (V/V) and 7 500 U/L L-TD. The optimum reaction pH of LDH-ADH process was 8.0, and the optimum reaction temperature was 35 °C. After 24 h, the concentration of L-2-aminobutyric acid was 119.6 g/L with a yield of 98%, when adding L-threonine and isopropanol (1.2 times of L-threonine) in batches for controlling 2-ketobutyric acid concentration less than 15 g/L, removing acetone in time and using 0.3 g/L NAD⁺, 10% LDH-ADH crude enzyme solution (V/V) and 7 500 U/L L-TD. The process and results used in this paper provide a reference for the industrialization of L-2-aminobutyric acid.

Optimization of enterokinase secretion in Pichia pastoris / 生物工程学报

Enterokinase is a class of serine proteases that specifically recognize the cleavage DDDDK sequences. Therefore, enterokinase has been widely used as a tool enzyme in the field of biomedicine. Currently, the expression level of enterokinase in Pichia pastoris is low, which hinders related practical applications. In this study, the effects of six different signal peptides SP1, SP2, SP3, SP4, SP7 and SP8 on the secretory expression of enterokinase in Pichia pastoris were studied. Compared with α-factor, SP1 significantly increased the secretory expression of enterokinase (from 6.8 mg/L to 14.3 mg/L), and the enterokinase activity increased from (2 390±212) U/mL to (4 995±378) U/mL in shaking flask cultures. On this basis, the enterokinase activity was further enhanced to (7 219±489) U/mL by co-expressing the endogenous protein Kex2. Moreover, the activity that the mutant strain with N-terminal fusion of three amino acids of WLR was increased to (15 145±920) U/mL with a high specific activity of (1 174 600±53 100) U/mg. The efficient secretory expression of enterokinase laid a foundation for its applications in near future.