Interaction Of Different Proteins Research Articles

A hydrophobic groove in secretagogin allows for alternate interactions with SNAP-25 and syntaxin-4 in endocrine tissues

Vesicular release of neurotransmitters and hormones relies on the dynamic assembly of the exocytosis/trans-SNARE complex through sequential interactions of synaptobrevins, syntaxins, and SNAP-25. Despite SNARE-mediated release being fundamental for intercellular communication in all excitable tissues, the role of auxiliary proteins modulating the import of reserve vesicles to the active zone, and thus, scaling repetitive exocytosis remains less explored. Secretagogin is a Ca2+-sensor protein with SNAP-25 being its only known interacting partner. SNAP-25 anchors readily releasable vesicles within the active zone, thus being instrumental for 1st phase release. However, genetic deletion of secretagogin impedes 2nd phase release instead, calling for the existence of alternative protein-protein interactions. Here, we screened the secretagogin interactome in the brain and pancreas, and found syntaxin-4 grossly overrepresented. Ca2+-loaded secretagogin interacted with syntaxin-4 at nanomolar affinity and 1:1 stoichiometry. Crystal structures of the protein complexes revealed a hydrophobic groove in secretagogin for the binding of syntaxin-4. This groove was also used to bind SNAP-25. In mixtures of equimolar recombinant proteins, SNAP-25 was sequestered by secretagogin in competition with syntaxin-4. Kd differences suggested that secretagogin could shape unidirectional vesicle movement by sequential interactions, a hypothesis supported by in vitro biological data. This mechanism could facilitate the movement of transport vesicles toward release sites, particularly in the endocrine pancreas where secretagogin, SNAP-25, and syntaxin-4 coexist in both α- and β-cells. Thus, secretagogin could modulate the pace and fidelity of vesicular hormone release by differential protein interactions.

Pan-cancer analysis revealing the multidimensional expression and prognostic and immunologic roles of TGFB1 in cancer.

This study aimed to perform an integrated pan-cancer analysis to characterize the expression patterns, prognostic value, genetic alterations, and immunologic roles of transforming growth factor beta 1 (TGFB1) across diverse human cancer types. Bioinformatics analyses were conducted using multiple public databases including The Cancer Genome Atlas, Genotype-Tissue Expression, Clinical Proteomic Tumor Analysis Consortium, TIMER2, GEPIA2, cBioPortal, StringDB, and others. Differential expression, survival, immune correlation, and protein interaction network analyses were performed. TGFB1 was overexpressed in several tumor types compared with that in normal tissues. High TGFB1 expression was associated with an advanced stage and poorer prognosis in certain cancers. TGFB1 mutations occurred in 1.3% of 10,967 cases surveyed. TGFB1 expression correlated with tumor-infiltrating immune cells and immunotherapy-related genes. This comprehensive multi-omics analysis revealed the complex expression and prognostic landscape of TGFB1 across cancers. TGFB1 is emerging as a potential immunotherapeutic target in certain contexts. Further research should elucidate its multifaceted tumor-promoting and tumor-suppressive mechanisms. Our pan-cancer analysis provides new insights into TGFB1 as a prognostic biomarker and immunotherapeutic target in human cancers, and our findings may guide future preclinical and clinical investigations of TGFB1-directed therapies.

Transcriptomic characterization of Trichoderma harzianum T34 primed tomato plants: assessment of biocontrol agent induced host specific gene expression and plant growth promotion

In this study, we investigated the intricate interplay between Trichoderma and the tomato genome, focusing on the transcriptional and metabolic changes triggered during the late colonization event. Microarray probe set (GSE76332) was utilized to analyze the gene expression profiles changes of the un-inoculated control (tomato) and Trichoderma-tomato interactions for identification of the differentially expressed significant genes. Based on principal component analysis and R-based correlation, we observed a positive correlation between the two cross-comaparable groups, corroborating the existence of transcriptional responses in the host triggered by Trichoderma priming. The statistically significant genes based on different p-value cut-off scores [(padj-values or q-value); padj-value < 0.05], [(pcal-values); pcal-value < 0.05; pcal < 0.01; pcal < 0.001)] were cross compared. Through cross-comparison, we identified 156 common genes that were consistently significant across all probability thresholds, and showing a strong positive corelation between p-value and q-value in the selected probe sets. We reported TD2, CPT1, pectin synthase, EXT-3 (extensin-3), Lox C, and pyruvate kinase (PK), which exhibited upregulated expression, and Glb1 and nitrate reductase (nii), which demonstrated downregulated expression during Trichoderma-tomato interaction. In addition, microbial priming with Trichoderma resulted into differential expression of transcription factors related to systemic defense and flowering including MYB13, MYB78, ERF2, ERF3, ERF5, ERF-1B, NAC, MADS box, ZF3, ZAT10, A20/AN1, polyol sugar transporter like zinc finger proteins, and a novel plant defensin protein. The potential bottleneck and hub genes involved in this dynamic response were also identified. The protein–protein interaction (PPI) network analysis based on 25 topmost DEGS (pcal-value < 0.05) and the Weighted Correlation Gene Network Analysis (WGCNA) of the 1786 significant DEGs (pcal-value < 0.05) we reported the hits associated with carbohydrate metabolism, secondary metabolite biosynthesis, and the nitrogen metabolism. We conclude that the Trichoderma-induced microbial priming re-programmed the host genome for transcriptional response during the late colonization event and were characterized by metabolic shifting and biochemical changes specific to plant growth and development. The work also highlights the relevance of statistical parameters in understanding the gene regulatory dynamics and complex regulatory networks based on differential expression, co-expression, and protein interaction networks orchestrating the host responses to beneficial microbial interactions.

Proteomics analysis of serum from thymoma patients

Thymoma is the most common malignant tumor in thymic epithelial tumors (TETS). This study aimed to identify the changes in serum proteomics in patients with thymoma. Proteins were extracted from twenty patients with thymoma serum and nine healthy controls and prepared for mass spectrometry (MS) analysis. Data independent acquisition (DIA) quantitative proteomics technique was used to examine the serum proteome. Differential proteins of abundance changes in the serum were identified. Bioinformatics was used to examine the differential proteins. Functional tagging and enrichment analysis were conducted using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The string database was used to assess the interaction of different proteins. In all, 486 proteins were found in all samples. There were differences in 58 serum proteins between patients and healthy blood donors, 35 up-regulated and 23 down-regulated. These proteins are primarily exocrine and serum membrane proteins involved in controlling immunological responses and antigen binding, according to GO functional annotation. KEGG functional annotation showed that these proteins play a significant role in the complement and coagulation cascade and the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signal pathway. Notably, the KEGG pathway (complement and coagulation cascade) is enriched, and three key activators were up-regulated: von willebrand factor (VWF), coagulation factor v (F5) and vitamin k-dependent protein c (PC). Protein–protein interaction (PPI) analysis showed that six proteins ((VWF, F5, thrombin reactive protein 1 (THBS1), mannose-binding lectin-associated serine protease 2 (MASP2), apolipoprotein B (APOB), and apolipoprotein (a) (LPA)) were up-regulated and two proteins (Metalloproteinase inhibitor 1(TIMP1), ferritin light chain (FTL)) were down-regulated. The results of this study showed that several proteins involved in complement and coagulation cascades were up-regulated in the serum of patients.

Identification and verification of the temozolomide resistance feature gene DACH1 in gliomas.

The most important chemotherapy treatment for glioma patients is temozolomide. However, the development of drug resistance severely restricts the use of temozolomide. Therefore, elucidating the mechanism of temozolomide resistance, enhancing temozolomide sensitivity, and extending patient survival are urgent tasks for researchers. Temozolomide resistance hub differential genes were identified using differential analysis and protein interaction analysis from the GEO datasets (GSE100736 and GSE113510). These genes were further studied in glioma patients treated with temozolomide in the TCGA and CGGA databases. Patients from the mRNAseq_325 dataset (CGGA) were considered as the training set to construct a risk model for predicting glioma sensitivity to temozolomide, while patients from the mRNAseq_693 dataset (CGGA) and TCGA-GBM dataset were considered as the validation set to evaluate the performance of models. PCR and western blot were performed to determine the difference in expression of the feature gene DACH1 between glioma cells and temozolomide-resistant glioma cells. The alterations in the sensitivity of tumor cells to temozolomide were also observed after DACH1 was silenced. The patients were then divided into two groups based on the expression of DACH1, and the differences in patient survival rates, molecular pathway activation, and level of immune infiltration were compared. Based on four signature genes (AHR, DACH1, MGMT, and YAP1), a risk model for predicting glioma sensitivity to temozolomide was constructed, and the results of timeROC in both the training and validation sets showed that the model had good predictive performance. The expression of the signature gene DACH1 was significantly downregulated in temozolomide-resistant cells, according to the results of the PCR and western blot experiments. The sensitivity of tumor cells to temozolomide was significantly reduced after DACH1 was silenced. DACH1 probably regulates temozolomide resistance in glioblastoma through the transcriptional dysregulation in cancer and ECM. This study constructs a risk model that can predict glioma susceptibility to temozolomide and validates the function of the feature gene DACH1, which provides a promising target for the research of temozolomide resistance.

Computational evaluation of marine demospongiae sponges metabolites activity as mycolic acid biosynthesis inhibitors in Mycobacterium tuberculosis.

Mycobacterium tuberculosis is a bacterium that has historically had a substantial impact on human health. Despite advances in understanding and management of tuberculosis (TB), the disease remains a crucial problem that necessitates ongoing work to discover effective drugs, minimize transmission, and improve global health outcomes. The purpose of this study is to use molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses to explore the molecular interactions of different proteins that are involved in mycolic acid biosynthesis (HadAB, InhA, KasA, FabD, and beta-ketoacyl-acyl carrier protein synthase III) of M. tuberculosis with Demospongiae metabolites. The docking findings were evaluated using the glide gscore, and the top 10 compounds docked against each protein receptor were chosen. Furthermore, the selected compounds underwent ADMET analysis, indicating that they have the potential for therapeutic development. Among the selected compounds, makaluvamine G showed the highest binding affinity against HadAB, psammaplysin E showed highest binding affinity against InhA, pseudotheonamide D showed the highest binding affinity against KasA protein, dinordehydrobatzelladine B showed the highest binding affinity against FabD, and nagelamide X showed the highest binding affinity against beta-ketoacyl-acyl carrier protein synthase III. Additionally, molecular mechanics generalized born surface area (MM-GBSA) binding free energy and molecular dynamics simulations were used to support the docking investigations. The results of the study suggest that these compounds may eventually be used to treat TB. However, computer validations were included in this study, and more in vitro research is required to turn these prospective inhibitors into clinical drugs.

Biomarkers Associated with Immune Checkpoint, N6-Methyladenosine, and Ferroptosis in Patients with Restenosis.

This study aimed to identify potential diagnostic markers of restenosis after stent implantation and to determine their association with immune checkpoint, ferroptosis, and N6-methyladenosine (m6A). Microarray data were downloaded from the National Center for Biotechnology Information (NCBI: GSE46560 and GSE48060 datasets) to identify differentially expressed genes (DEGs) between in-stent restenosis and no-restenosis samples. We then conducted systematic functional enrichment analyses of the DEGs based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and further predicted the interactions of different proteins using the Search Tool for the Retrieval of Interacting Genes (STRING). We used the MCC and MCODE algorithms in the cytoHubba plug-in to screen three key genes in the network, and employed receiver operating characteristic (ROC) curves to determine their diagnostic significance using a multiscale curvature classification algorithm. Next, we investigated the relationships between these target genes, immune checkpoint, ferroptosis, and m6A. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the above results. We identified 62 upregulated genes and 243 downregulated genes. Based on GO, KEGG, and screening results, EEF1D, RPL36, and RPSA are promising genes for predicting restenosis. In addition, the methylation of YTHDF2, the ferroptosis-related gene GLS2, and the immune checkpoint-related gene CTLA4 were observed to be associated with restenosis. The qRT-PCR test confirmed that RPSA and RPL36 are useful diagnostic markers of the restenosis that can provide new insights for future studies on its occurrence and molecular mechanisms. We found that RPSA and RPL36, as useful diagnostic markers of restenosis, can provide new insights for future studies on its occurrence and molecular mechanisms.

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues:An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength and caused a veritable collapse in health infrastructure. The molecular modeling of the novel coronavirus research sounds promising and equips more evidence about the pragmatic therapeutic options. This article proposes a machine-learning framework for identifying potential COVID-19 transcriptomic signatures. The transcriptomics data contains immune-related genes collected from multiple tissues (blood, nasal, and buccal) with accession number: GSE183071. Extensive bioinformatics work was carried out to identify the potential candidate markers, including differential expression analysis, protein interactions, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes)pathway enrichment studies. The overlapping investigation found SERPING1, the gene that encodes a glycosylated plasma protein C1-INH, in all three datasets. Furthermore, the immuno-informatics study was conducted on the C1-INH protein. 5DU3, the protein identifier of C1-INH, was fetched to identify the antigenicity, major histocompatibility(MHC) Class I and II binding epitopes, allergenicity, toxicity, and immunogenicity. The screening of peptides satisfying the vaccine-design criteria based on the metrics mentioned above is performed. The drug-gene interaction study reported that Rhucin is strongly associated with SERPING1. HSIC-Lasso (Hilbert-Schmidt independence criterion-least absoluteshrinkage and selection operator), a model-free biomarker selection technique, was employed to identify the genes having a nonlinear relationship with the target class. The gene subset is trained with supervised machine learning models by a leave-one-out cross-validation method. Explainable artificial intelligencetechniques perform the model interpretation analysis.

Application value of plasma proteomics in the diagnosis and pathogenesis of high altitude polycythemia

Objective: To explore the application value of plasma proteomics in the diagnosis and pathogenesis of high altitude polycythemia (HAPC). Methods: Ten patients with HAPC in Qinghai Provincial People's Hospital from January 2020 to January 2021 were selected as the experimental group, including 4 males and 6 females, aged (46±4) years. Ten healthy controls at the same altitude in the same period were selected as the control group, including 5 males and 5 females, aged (44±4) years. The differential proteins were identified and quantified by high performance liquid chromatography-mass spectrometry (HPLC-MS), and the gene ontology (GO) functional enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis and interaction network analysis were conducted for the selected differential proteins. Results: A total of 117 differential proteins with quantitative values were screened from the experimental group and the control group, 45 significantly up-regulated proteins with quantitative values only in the experimental group, 40 significantly down-regulated proteins with quantitative values only in the control group, and 32 differentially expressed proteins with quantitative values in both experimental and control groups were detected. Compared with the control group, 11 of the 32 differentially expressed proteins in the experimental group were down-regulated and 21 were up-regulated. The results of GO functional enrichment analysis showed that the biological processes involved by differential proteins mainly included immune response, complement activation, activated protein cascade and coagulation system. The results of KEGG function enrichment analysis showed that the main biochemical metabolic pathways and signal transduction pathways involved by differential proteins were axon guidance, lysosomes, cell adhesion molecules, lipid and atherosclerosis, hematopoietic cell lineage and cholesterol metabolism. The abundant domains are mainly in immunoglobulin-like domain, EGF-like domain, fibronectin type Ⅲ superfamily, serine proteases, Sushi/SCR/CCP superfamily. The results of differential protein interaction analysis showed that the interaction score was>700, and the top 10 differential proteins with the largest number of nodes were MPO, RPS27A, ARG1, GM2A, TIMP1, CRP, FABP5, HBB, S100A7 and RHOA, respectively. Conclusion: Plasma proteomics analysis technique is helpful to identify the related protein markers in the development of HAPC, and provide reference for the diagnosis and pathogenesis of HAPC.

MYC Influences mRNA Processing and Nuclear Export to Initiate Acute Myeloid Leukemia

Background: Although MYC is a potent oncogene that is frequently associated with poor outcomes in many solid tumors, its precise role in Acute Myeloid Leukemia (AML) pathogenesis and outcomes are not clear. We recently discovered that intermediate-risk AML patients with long first remissions with standard chemotherapy have an unexpectedly high frequency of pathogenic MYC mutations in the dominant leukemia clone at diagnosis (6 of 26 [23%] cases, versus 1.8% of all AML patients, p=0.002). An analysis of all MYC mutations reported in AML, revealed that they are nearly always single base substitutions that localize to a hotspot in the MYC Box I domain (MBI - AAs hotspot 73-74); this stands in distinct contrast to other hematopoietic malignancies, where MYC mutations are scattered throughout the entire gene. In this study, we engineered mouse hematopoietic stem and progenitor cells (HSPCs) to express AML-associated MYC missense mutations and characterized their in-vitro and in-vivo cellular and molecular phenotypes. Results: We observed that constitutive expression of MYC MBI mutant proteins in mouse HSPCs significantly prolonged Myc half-life and conferred different degrees of growth advantage over both wild type MYC overexpression and overexpression of non-MBI mutant proteins. To determine whether these mutations are AML drivers, HSPCs expressing MYCWT or the MBI mutants MYCP74Q and MYCT73N were transplanted into lethally irradiated syngeneic recipient mice, which were then evaluated for the development of leukemia. Primary recipient mice transplanted with MYCWT-expressing cells developed leukemia with a median survival of 58 days for whereas mice transplanted with MYCP74Q- or MYCT73N-expressing cells displayed a median survival of 42 and 41.5 days, respectively (p<0.001). Furthermore, secondary recipient mice transplanted with MYCWT-, MYCP74Q- or MYCT73N-expressing AML cells from primary recipient mice also developed AML, indicating that expression of WT and MBI-MUT Myc leads to the development of frank leukemia in mice. Next, we investigated the impact of these point mutations on the transcriptional targets of Myc by comparing single-cell RNA-seq profiles of murine HSPCs expressing wild type, P74Q, or T73N Myc versus an empty vector control. From these analyses, we found that while each of these mutants retain many of the transcriptional activities of wild type Myc, they also display unique transcriptional signatures. To better understand how these mutations affect the transcriptional output of MYC, we performed ChIP-seq analysis of primary murine HSPCs expressing MYCWT-, MYCcP74Q- or MYCT73N. Despite MBI mutations causing persistent MYC protein expression (due to prolonged half-life), we detected an overall decrease in chromatin binding of MBI-MUT MYC, with preserved binding to transcriptional start sites of a core sets of genes involved in splicing and translation. Importantly, MBI mutations did not affect the canonical E-box Myc binding site, nor create novel binding sites, indicating that these mutations lead to an overall decrease in Myc occupancy at target promoters. Immunofluorescent staining for WT vs. MBI mutant MYC showed that despite their overall decrease in chromatin binding, Myc mutant proteins localized predominantly to the nucleus. However, a substantial number of nuclei showed a ring-like morphology of MBI-MUT MYC, suggesting that MBI mutations might enrich protein localization at the nuclear periphery. To determine whether the changes in staining pattern observed for MBI-MUT were associated with alterations in the ability of MYC to interact with its regulatory proteins, we employed a modified BioID proximity labeling system, "TurboID", to screen for differential protein interactions in murine HSPCs. This analysis showed that MBI mutations resulted in several gained interactions over WT MYC - most prominently with components of the nuclear pore complex (NUP98, NUP107, NUP133, XPOT, RAE1) supporting the idea that MBI-MUT might accelerate transformation by controlling translation and mRNA nuclear export. Conclusions: Collectively, these data indicate that AML-associated MYC mutations support leukemogenesis through non-canonical (transcription-independent) MYC proprieties. More broadly, these data suggest that aberrant mRNA processing and nuclear export might play an important role in the initiation of AML by MYC mutations.

Proteomic and phosphorylated proteomic landscape of injured lung in juvenile septic rats with therapeutic application of umbilical cord mesenchymal stem cells.

Acute lung injury (ALI) is the most common complication of sepsis. Intravenous injection of HUMSCs can regulate the level of circulating endothelial cytokines and alleviate lung injury in juvenile septic rats. In this study, we performed proteomic and phosphorylated proteomic analysis of lung tissue of juvenile septic rats after Human Umbilical Cord Mesenchymal Stem Cells (HUMSCs) intervention for the first time, and screened the potential proteins and pathways of HUMSCs for therapeutic effect. The 4D proteome quantitative technique was used to quantitatively analyze the lung tissues of septic rats 24 hours (3 biological samples) and 24 hours after HUMSCs intervention (3 biological samples). A total of 213 proteins were identified as differentially expressed proteins, and 971 phosphorylation sites changed significantly. Based on the public database, we analyzed the functional enrichment of these proteins and phosphorylated proteins. In addition, Tenascin-C may be the key differential protein and ECM receptor interaction pathway may be the main signal pathway by using various algorithms to analyze the protein-protein interaction network. Phosphorylation analysis showed that tight junction pathway was closely related to immune inflammatory reaction, and EGFR interacted most, which may be the key differential phosphorylated protein. Finally, 123 conserved motifs of serine phosphorylation site (pS) and 17 conserved motifs of threonine (pT) phosphorylation sites were identified by motif analysis of phosphorylation sites. Results from proteomics and phosphorylated proteomics, the potential new therapeutic targets of HUMSCs in alleviating lung injury in juvenile septic rats were revealed.

S-Palmitoylation and Sterol Interactions Mediate Antiviral Specificity of IFITMs.

Interferon-induced transmembrane proteins (IFITM1, 2, and 3) are important antiviral proteins that are active against many viruses, including influenza A virus (IAV), dengue virus (DENV), Ebola virus (EBOV), Zika virus (ZIKV), and severe acute respiratory syndrome coronavirus (SARS-CoV). IFITM proteins exhibit specificity in activity, but their distinct mechanisms of action and regulation are unclear. Since S-palmitoylation and cholesterol homeostasis are crucial for viral infections, we investigated IFITM interactions with cholesterol by photoaffinity cross-linking in mammalian cells along with molecular dynamic simulations and nuclear magnetic resonance analysis in vitro. These studies suggest that cholesterol can directly interact with S-palmitoylated IFITMs in cells and alter the conformation of IFITMs in membrane bilayers. Notably, we discovered that the S-palmitoylation levels regulate differential IFITM protein interactions with cholesterol in mammalian cells and specificity of antiviral activity toward IAV, SARS-CoV-2, and EBOV. Our studies suggest that modulation of IFITM S-palmitoylation levels and cholesterol interaction influence host susceptibility to different viruses.

Differential mitochondrial protein interaction profile between human translocator protein and its A147T polymorphism variant.

The translocator protein (TSPO) has been implicated in mitochondrial transmembrane cholesterol transport, brain inflammation, and other mitochondrial functions. It is upregulated in glial cells during neuroinflammation in Alzheimer's disease. High affinity TSPO imaging radioligands are utilized to visualize neuroinflammation. However, this is hampered by the common A147T polymorphism which compromises ligand binding. Furthermore, this polymorphism has been linked to increased risk of neuropsychiatric disorders, and possibly reduces TSPO protein stability. Here, we used immunoprecipitation coupled to mass-spectrometry (IP-MS) to establish a mitochondrial protein binding profile of wild-type (WT) TSPO and the A147T polymorphism variant. Using mitochondria from human glial cells expressing either WT or A147T TSPO, we identified 30 WT TSPO binding partners, yet only 23 for A147T TSPO. Confirming that A147T polymorphism of the TSPO might confer loss of function, we found that one of the identified interactors of WT TSPO, 14-3-3 theta (YWHAQ), a protein involved in regulating mitochondrial membrane proteins, interacts much less with A147T TSPO. Our data presents a network of mitochondrial interactions of TSPO and its A147T polymorphism variant in human glial cells and indicate functional relevance of A147T in mitochondrial protein networks.

A new biomarker neuropeptide Y and bioinformatics analysis of intrahepatic cholestasis of pregnancy.

To explore the expression of neuropeptide Y (NPY) and bioinformatics characteristics of intrahepatic cholestasis of pregnancy (ICP). Gene chip data of intrahepatic cholestasis of pregnancy were searched from the GEO database with bioinformatics method, and GSE46157 gene chip was downloaded. Differentially expressed genes in normal pregnant placenta tissue and ICP pregnant placenta tissue (bile acid concentration > 40 μmol/L) were screened by GEO2R. Functional annotation (GO) and pathway analysis (KEGG) were performed with DAVID. STRING online database and Cytoscape software were used for protein interaction network analysis. Maternal serum NPY level of 63 cases of ICP pregnant women and 20 normal pregnant women were investigated by ELISA. After screening 3896 differential genes and protein interaction, the top 14 hub genes were selected with nine up-regulated and five down-regulated genes. ICP patients were divided into three subgroups according to serum TBA and ALT levels. Maternal serum NPY levels of pregnant women in ICP subgroups 1, 2, and 3 were significantly higher than those in the normal pregnant women. The number of premature births, meconium-staining amniotic fluid, neonatal asphyxia, and NICU admission was significantly higher in the ICP subgroup 1 than in the ICP subgroups 2 and 3, and than in the normal pregnant women. This study indicates that many differentially expressed genes and signaling pathways are involved in the pathophysiological procedure of ICP. NPY could be a new biomarker of ICP.

Analysis of Sepsis Markers and Pathogenesis Based on Gene Differential Expression and Protein Interaction Network.

Objective The purpose of the present study is to screen the hub genes associated with sepsis, comprehensively understand the occurrence and progress mechanism of sepsis, and provide new targets for clinical diagnosis and treatment of sepsis. Methods The microarray data of GSE9692 and GSE95233 were downloaded from the Gene Expression Omnibus (GEO) database. The dataset GSE9692 contained 29 children with sepsis and 16 healthy children, while the dataset GSE95233 included 102 septic subjects and 22 healthy volunteers. Differentially expressed genes (DEGs) were screened by GEO2R online analysis. The DAVID database was applied to conduct functional enrichment analysis of the DEGs. The STRING database was adopted to acquire protein-protein interaction (PPI) networks. Results We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233. After the intersection of DEGs of the two datasets, a total of 98 co-DEGs were obtained. DEGs associated with sepsis were involved in inflammatory responses such as T cell activation, leukocyte cell-cell adhesion, leukocyte-mediated immunity, cytokine production, immune effector process, lymphocyte-mediated immunity, defense response to fungus, and lymphocyte-mediated immunity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that sepsis was connected to bacterial and viral infections. Through PPI network analysis, we screened the most important hub genes, including ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK. Conclusions In conclusion, the present study revealed an unbalanced immune response at the transcriptome level of sepsis and identified genes for potential biomarkers of sepsis, such as ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK.

Proteomic characteristics of PM2.5-induced differentially expressed proteins in k-ras-silenced HBE cells

The human bronchial epithelial cells (HBE) and K-ras-silenced HBE cells were treated with fine particulate matter (PM2.5) samples from Taiyuan for 24 h. To screen the proteomic characteristics of PM2.5-induced differentially expressed proteins (DEPs), the Q Exactive mass spectrometer was used. Gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) analysis, functional prediction, protein–protein interaction (PPI) network analysis, and visualization of differential protein interactions were performed. 251 DEPs in K-ras silenced cells and 535 DEPs in normal HBE cells were identified, respectively. KEGG analysis showed that the differentially expressed proteins of PM2.5-treated cells were related to the biosynthesis of ribosomes, antibiotics, and amino acids. On the other hand, K-ras silenced cells were related to metabolic pathways, RNA transport, and DNA replication. Through the construction of a PPI network, the top 10 hub proteins were screened from the two cell groups, among which MRPL13, RPS20, and EIF1AX were of great significance. Our results indicated that the K-ras gene plays an important role in PM2.5-induced DEPs, and the findings provide a scientific basis for the further study of PM2.5 toxic mechanisms and biomarkers.

A quasispecies in a BHK-21 cell-derived virulent Tembusu virus strain contains three groups of variants with distinct virulence phenotypes

Previous studies resulted in the isolation of a low-virulence plaque-purified variant from the third passage (P3) in BHK-21 cells of a Tembusu virus (TMUV) isolate, suggesting the presence of viral quasispecies in the P3 culture. To confirm this notion, the fourth passage virus (P4) was prepared by infecting BHK-21 cells with P3 for isolation of more variants. We isolated 10 plaque-purified viruses. Comparative genome sequence analysis identified six of the 10 viruses as genetically different variants, which harbored a total of eight amino acid differences in the envelope, NS1, NS3, and NS5 proteins. When tested in a 2-day-old Pekin duck model, P4 caused 80 % mortality, belonging to a high-virulence TMUV strain. Out of the six genetically different variants, two presented high-virulence, one exhibited moderate-virulence, and three displayed low-virulence, causing 60 %–70 %, 40 %, and 10 % mortalities, respectively. These results demonstrate that P4 contains at least three groups of variants with distinct virulence phenotypes. Analysis of links between the eight residues and virulence of the six variants identified NS1 protein residue 183 and NS5 protein residues 275 and/or 287 as novel determinants of TMUV virulence. The analysis also provided a new clue for future studies on the molecular basis of TMUV virulence in terms of genetic interaction of different proteins. Overall, our study provides direct evidence to suggest that TMUV exists in in vitro culture of a virulent isolate as a quasispecies, which may enhance our understanding of molecular mechanism of TMUV virulence.

Survival Is Related to Estrogen Signal Transduction Pathway Activity in Postmenopausal Women Diagnosed with High-Grade Serous Ovarian Carcinoma.

Simple SummaryAll cells have a complex internal network of ‘communication chains’ called signal transduction pathways (STPs). Through interaction of different proteins in STPs, they are partly responsible for the behavior of a cell. In our study, we investigated the activity of six STPs in 85 women with advanced stage high-grade serous ovarian cancer (HGSC). To investigate the relation between and differences in survival and STP activity, women with a short disease-free survival (below 12 months) and a long disease-free survival (above 24 months) were included. We found no differences in mean STP activity between short-term survivors (52 women) and long-term survivors (33 women). However, when we analyzed postmenopausal women, we found that both disease-free and overall survival were related to estrogen receptor (ER) pathway signaling. This indicates that a better survival outcome was related to a more active ER pathway in this subgroup.High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, has a high mortality rate. Although there are some factors associated with survival, such as stage of disease, there are remarkable differences in survival among women diagnosed with advanced stage disease. In this study, we investigate possible relations between survival and signal transduction pathway (STP) activity. We assessed the functional activity of the androgen receptor (AR), estrogen receptor (ER), phosphoinositide-3-kinase (PI3K), Hedgehog (HH), transforming growth factor beta (TGF-β) and canonical wingless-type MMTV integration site (Wnt) pathway in 85 primary tumor samples of patients with FIGO stage IIIC to IVB HGSC and disease-free survival (DFS) below 12 (n = 52) or over 24 months (n = 33). There were no significant differences in median pathway activity between patients with a short and long DFS. In univariate Cox proportional hazards analysis, ER pathway activity was related to a favorable DFS and overall survival (OS) in postmenopausal women (p = 0.033 and p = 0.041, respectively), but not in premenopausal women. We divided the postmenopausal group into subgroups based on ER pathway activity quartiles. Survival analysis revealed that postmenopausal women in the lowest ER quartile had a shorter DFS and OS (log-rank p = 0.006 and p < 0.001, respectively). Furthermore, we were able to form subgroups of patients based on an inverse relation between ER and PI3K pathway activity. In conclusion, in postmenopausal patients with advanced stage HGSC, a poorer survival outcome was associated with low functional ER pathway activity.

Controlling the kinetics of visible-light-induced photocatalytic performance of gold decorated graphitic carbon nitride nanocomposite using different proteins

In this work, the interaction of different proteins with two dimensional (2D) graphitic carbon nitride (GCN) nanosheets decorated with gold nanoparticles (Au NP) is reported along with their influence in controlling the visible-light-induced photocatalytic activity. The decoration of Au NP on 2D GCN nanosheets improves the photocatalytic activity as Au NP plays an important role in trapping and storing the conduction band electrons of GCN nanosheets. The structural, morphological and optical properties of Au-GCN (AGCN) nanocomposite have been investigated using scattering and spectroscopic techniques. Methylene blue (MB) dye was chosen as a representative system for the studying of visible-light-induced photocatalytic activity of AGCN nanocomposite in the presence of different proteins. Bovine serum albumin (BSA), trypsin and cytochrome C having different chain lengths and physicochemical properties were used to control the kinetics of the photocatalytic activity of GCN and AGCN nanocomposites. Due to the simultaneous competitive adsorption of MB and proteins, the photocatalytic activity of the nanocomposites got enhanced in the presence of BSA, while it got inhibited or slowed down in the presence of trypsin and cytochrome C, respectively. The observed photocatalytic activity could be correlated with the surface charges present on the proteins and the mechanistic understanding developed in this study can be beneficial in controlling the kinetics of the photocatalytic activity of semiconductor-based photocatalysts using proteins as activators or inhibitors.

Changes in gene expression of adipose tissue CD14+ cells in patients with Type 2 diabetes mellitus and their relationship with environmental factors.

To study the gene expression of adipose tissue CD14+ cells in patients with Type 2 diabetes mellitus (T2DM) based on chip data, screen differentially expressed genes, and analyze their relationship with the environmental factors. The data of GSE54350 were obtained from the public database of gene expression profiling. The data were pre-processed by Network Analyst, String 11.0, Cytoscape 3.7.1, and other analytical software. The differentially expressed genes were analyzed by gene ontology biological function and kyoto encycopedia of genes and genomes (KEGG) signaling pathway to establish differential gene protein interaction network, transcription factor-gene regulatory network, microRNA-gene regulatory network, environmental factors-gene regulatory network, and other interaction systems. The gene expression pattern of CD14+ cells in adipose tissue of obese T2DM patients was significantly different from that of obese non-T2DM patients. There were 19 differentially expressed genes with up-regulation. The differentially expressed genes were mainly involved in ARP2/3 complex regulation of actin cytoskeleton, positively associated with biological processes such as protein complex assembly, and involved in the phagocytic Fcγ receptor signaling pathways and receptor family signaling pathways. The protein-protein interaction networks showed that TNF was the core protein node. The microRNA-gene regulatory network showed that hsa-mir-124-3p interacted with differentially expressed genes; TNF, KYNU, RCAN1 and other related genes all interacted with environmental factors. The gene expression of adipose tissue CD14+ cells are significantly changed in obese T2DM patients. TNF may play an important role in the process of obesity affecting the immune status of T2DM patients. Multiple microRNAs, transcription factors, and environmental factors also play a role in the above process. This study provides new material and new ideas for further exploration of the impact of obesity on T2DM patients.