Potential Protein-protein Interactions Research Articles

Plasma Proteome Profiling of Patients With In-stent Restenosis by Tandem Mass Tag-Based Quantitative Proteomics Approach.

BackgroundDespite the widespread application of new drug-eluting stents, a considerable portion of patients experience in-stent restenosis (ISR). To date, the pathophysiologic mechanisms of ISR remain poorly understood.MethodsIn this study, we collected plasma samples from ISR patients (n = 29) and non-ISR patients (n = 36) after drug-eluting stent implantation, as well as from healthy controls (HCs) (n = 32). Our goal was to investigate differences in plasma protein profiles using tandem mass tag (TMT) labeling coupled with liquid chromatography and tandem mass spectrometry. The proteomic data were validated by enzyme-linked immunosorbent assay (ELISA). Bioinformatic analyses were conducted to analyze potential pathways and protein-protein interaction (PPI) involved in ISR.ResultsA total of 1,696 proteins were identified, of which 278 differed in protein abundance between non-ISR and HCs, 497 between ISR and HCs, and 387 between ISR and non-ISR, respectively. Bioinformatic analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and PPI, further demonstrated that differentially abundant proteins between ISR and non-ISR are involved in several crucial biological processes and signaling pathways, such as focal adhesion, platelet activation, Rap1 signaling, regulation of actin cytoskeleton, and cholesterol metabolism. Among the identified differentially abundant proteins in ISR, 170 were increased in abundance relative to both non-ISR patients and HCs. Some of these proteins were identified to have critical functions for atherosclerosis development and might be involved in ISR pathology. Among these proteins, 3 proteins with increased abundance including fetuin-B, apolipoprotein C-III (APOC3), and cholesteryl ester transfer protein (CETP) were confirmed by ELISA.ConclusionsThis is the first study provided a comprehensive proteomic profile to understand ISR pathology, which may help identify early diagnostic biomarkers and therapeutic targets.

Prospective Analysis of Proteins Carried in Extracellular Vesicles with Clinical Outcome in Hepatocellular Carcinoma.

Background: Extracellular vehicles (EVs) contain different proteins that relay information between tumor cells, thus promoting tumorigenesis. Therefore, EVs can serve as an ideal marker for tumor pathogenesis and clinical application. Objective: Here, we characterised EV-specific proteins in hepatocellular carcinoma (HCC) samples and established their potential protein-protein interaction (PPI) networks. Materials and Methods: We used multi-dimensional bioinformatics methods to mine a network module to use as a prognostic signature and validated the model's prediction using additional datasets. The relationship between the prognostic model and tumor immune cells or the tumor microenvironment status was also examined. Results: 1134 proteins from 316 HCC samples were mapped to the exoRBase database. HCC-specific EVs specifically expressed a total of 437 proteins. The PPI network revealed 321 proteins and 938 interaction pathways, which were mined to identify a three network module (3NM) with significant prognostic prediction ability. Validation of the 3NM in two more datasets demonstrated that the model outperformed the other signatures in prognostic prediction ability. Functional analysis revealed that the network proteins were involved in various tumor-related pathways. Additionally, these findings demonstrated a favorable association between the 3NM signature and macrophages, dendritic, and mast cells. Besides, the 3NM revealed the tumor microenvironment status, including hypoxia and inflammation. Conclusion: These findings demonstrate that the 3NM signature reliably predicts HCC pathogenesis. Therefore, the model may be used as an effective prognostic biomarker in managing patients with HCC.

The Interactions of Small Proline-Rich Proteins with Late Cornified Envelope Proteins are Involved in the Pathogenesis of Psoriasis.

PurposePsoriasis is a common cutaneous disease with multiple characteristics including inflammation and aberrant keratinocyte proliferation. However, the pathogenesis of psoriasis is not completely clear yet. The objective of this study is to perform an in-depth analysis of the association between SPRR and LCE in the pathogenesis of psoriasis.MethodsIn this study, we explore the differentially expressed genes (DEGs) in psoriasis by analyzing different gene expression profiles obtained from the Gene Expression Omnibus (GEO) database. The DEGs were examined using gene ontology (GO) functional enrichment analysis and protein–protein interactions (PPI) network. Correlation analysis in R studio software was used to analyze the association between SPRR and LCE genes. Further, potential direct protein–protein interactions between SPRR proteins and LCE3D were verified by co-localization observations and co-immunoprecipitation (CO-IP) assays in 293T cells. Also, the expression levels of SPRR and LCE genes were detected in lesional skin of the IMQ-induced psoriasiform dermatitis mice using RT-PCR.ResultsInterestingly, the small proline-rich (SPRR) and late cornified envelope (LCE) genes were identified as a module in the constructed PPI network. And the analysis of the gene expression profile GSE63684 showed that both SPRR family and LCE family genes were significantly upregulated in imiquimod (IMQ) induced psoriasiform dermatitis mice. Also, the correlation analysis in R studio software recognized the association of SPRR and LCE genes, which were further verified by co-localization and co-immunoprecipitation (CO-IP) assays in 293T cells, and the results show that the direct interactions between SPRR2 and LCE3D. Notably, we also found that the expression levels of SPRR and LCE genes were significantly increased in the IMQ-induced psoriasiform dermatitis mice, while specifically decreased under the tazarotene cream treatment, indicating that the SPRR and LCEs were regulated simultaneously in psoriasis.ConclusionIn summary, our study found that interactions between SPRR proteins and LCE proteins may provide new insights into the pathogenesis of psoriasis.

Structural organization of the intermediate and light chain complex of Chlamydomonas ciliary I1 dynein.

Axonemal I1 dynein (dynein f) is the largest inner dynein arm in cilia and a key regulator of ciliary beating. It consists of two dynein heavy chains, and an intermediate chain/light chain (ICLC) complex. However, the structural organization of the nine ICLC subunits remains largely unknown. Here, we used biochemical and genetic approaches, and cryo-electron tomography imaging in Chlamydomonas to dissect the molecular architecture of the I1 dynein ICLC complex. Using a strain expressing SNAP-tagged IC140, tomography revealed the location of the IC140 N-terminus at the proximal apex of the ICLC structure. Mass spectrometry of a tctex2b mutant showed that TCTEX2B dynein light chain is required for the stable assembly of TCTEX1 and inner dynein arm interacting proteins IC97 and FAP120. The structural defects observed in tctex2b located these 4 subunits in the center and bottom regions of the ICLC structure, which overlaps with the location of the IC138 regulatory subcomplex, which contains IC138, IC97, FAP120, and LC7b. These results reveal the three-dimensional organization of the native ICLC complex and indicate potential protein-protein interactions that are involved in the pathway by which I1 regulates ciliary motility.

A comprehensive library of fluorescent constructs of SARS-CoV-2 proteins and their initial characterisation in different cell types.

Background InformationComprehensive libraries of plasmids for SARS‐CoV‐2 proteins with various tags (e.g., Strep, HA, Turbo) are now available. They enable the identification of numerous potential protein–protein interactions between the SARS‐CoV‐2 virus and host proteins.ResultsWe present here a large library of SARS CoV‐2 protein constructs fused with green and red fluorescent proteins and their initial characterisation in various human cell lines including lung epithelial cell models (A549, BEAS‐2B), as well as in budding yeast. The localisation of a few SARS‐CoV‐2 proteins matches their proposed interactions with host proteins. These include the localisation of Nsp13 to the centrosome, Orf3a to late endosomes and Orf9b to mitochondria.Conclusions and SignificanceThis library should facilitate further cellular investigations, notably by imaging techniques.

Genes That Predict Poor Prognosis in Breast Cancer via Bioinformatical Analysis.

Background Breast cancer is one of the most commonly diagnosed cancers all over the world, and it is now the leading cause of cancer death among females. The aim of this study was to find DEGs (differentially expressed genes) which can predict poor prognosis in breast cancer and be effective targets for breast cancer patients via bioinformatical analysis. Methods GSE86374, GSE5364, and GSE70947 were chosen from the GEO database. DEGs between breast cancer tissues and normal breast tissues were picked out by GEO2R and Venn diagram software. Then, DAVID (Database for Annotation, Visualization, and Integrated Discovery) was used to analyze these DEGs in gene ontology (GO) including molecular function (MF), cellular component (CC), and biological process (BP) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. Next, STRING (Search Tool for the Retrieval of Interacting Genes) was used to investigate potential protein-protein interaction (PPI) relationships among DEGs and these DEGs were analyzed by Molecular Complex Detection (MCODE) in Cytoscape. After that, UALCAN, GEPIA (gene expression profiling interactive analysis), and KM (Kaplan–Meier plotter) were used for the prognostic information and core genes were qualified. Results There were 96 upregulated genes and 98 downregulated genes in this study. 55 upregulated genes were selected as hub genes in the PPI network. For validation in UALCAN, GEPIA, and KM, 5 core genes (KIF4A, RACGAP1, CKS2, SHCBP1, and HMMR) were found to highly expressed in breast cancer tissues with poor prognosis. They differentially expressed between different subclasses of breast cancer. Conclusion These five genes (KIF4A, RACGAP1, CKS2, SHCBP1, and HMMR) could be potential targets for therapy in breast cancer and prediction of prognosis on the basis of bioinformatical analysis.

Molecular Docking and Dynamics Simulation of a Screening Library from Life Chemicals Database for Potential Protein-Protein Interactions (PPIs) Inhibitors against SARS-CoV-2 Spike Protein

The ongoing pandemic of coronavirus 2 represents a major challenge for global public health authorities. Coronavirus disease 2019 can be fatal especially in elderly people and those with comorbidities. Currently, several vaccines against coronavirus 2 are under application in multiple countries with emergency use authorization. In the same time, many vaccine candidates are under development and assessment. It is worth noting that the design of some of these vaccines depends on the expression of receptor binding domain for viral spike protein to induce host immunity. As such, blocking the spike protein interface with antibodies, peptides or small molecular compounds can impede the ability of coronavirus 2 to invade host cells by intervention with interactions between viral spike protein and cellular angiotensin converting enzyme 2. In this virtual screening study, we have used predictive webservers, molecular docking and dynamics simulation to evaluate the ability of 3000 compounds to interact with interface residues of spike protein receptor binding domain. This library of chemicals was focused by Life Chemicals as potential protein-protein interactions inhibitor. Here, we report that hit compound 7, with IUPAC name of 3‐cyclohexyl‐N‐(4‐{[(1R,9R) ‐6‐oxo‐7,11‐ diazatricyclo [7.3.1.02,7] trideca‐2,4‐dien‐11‐yl] sulfonyl} phenyl) propenamide, may have the capacity to interact with interface of receptor binding domain for viral spike protein and thereby reduce cellular entry of the virus. However, in vitro and in vivo assessments may be required to validate these virtual findings.

De novo sequencing and native mass spectrometry revealed hetero-association of dirigent protein homologs and potential interacting proteins in Forsythia × intermedia.

The discovery of dirigent proteins (DPs) and their functions in plant phenol biochemistry was made over two decades ago with Forsythia × intermedia. Stereo-selective, DP-guided, monolignol-derived radical coupling in vitro was then reported to afford the optically active lignan, (+)-pinoresinol from coniferyl alcohol, provided one-electron oxidase/oxidant capacity was present. It later became evident that DPs have several distinct sub-families, presumably with different functions. Some known DPs require other essential enzymes/proteins (e.g. oxidases) for their functions. However, the lack of a fully sequenced genome for Forsythia × intermedia made it difficult to profile other components co-purified with the (+)-pinoresinol forming DP. Herein, we used an integrated bottom-up, top-down, and native mass spectrometry (MS) approach to de novo sequence the extracted proteins via adaptation of our initial report of DP solubilization and purification. Using publicly available transcriptome and genomic data from closely related species, we identified 14 proteins that were putatively associated with either DP function or the cell wall. Although their co-occurrence after extraction and chromatographic separation is suggestive for potential protein-protein interactions, none were found to form stable protein complexes with DPs in native MS under the specific experimental conditions we have explored. Interestingly, two new DP homologs were found and they formed hetero-trimers. Molecular dynamics simulations suggested that similar hetero-trimers were possible between Arabidopsis DP homologs with comparable sequence similarities. Nevertheless, our integrated mass spectrometry method development helped prepare for future investigations directed to the discovery of novel proteins and protein-protein interactions. These advantages can be highly beneficial for plant and microbial research where fully sequenced genomes may not be readily available.

Functional and druggability analysis of the SARS-CoV-2 proteome

The infectious coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, appeared in December 2019 in Wuhan, China, and has spread worldwide. As of today, more than 46 million people have been infected and over 1.2 million fatalities. With the purpose of contributing to the development of effective therapeutics, we performed an in silico determination of binding hot-spots and an assessment of their druggability within the complete SARS-CoV-2 proteome. All structural, non-structural, and accessory proteins have been studied, and whenever experimental structural data of SARS-CoV-2 proteins were not available, homology models were built based on solved SARS-CoV structures. Several potential allosteric or protein-protein interaction druggable sites on different viral targets were identified, knowledge that could be used to expand current drug discovery endeavors beyond the currently explored cysteine proteases and the polymerase complex. It is our hope that this study will support the efforts of the scientific community both in understanding the molecular determinants of this disease and in widening the repertoire of viral targets in the quest for repurposed or novel drugs against COVID-19.

SLC38A2 Overexpression Induces a Cancer-like Metabolic Profile and Cooperates with SLC1A5 in Pan-cancer Prognosis.

Cancer cells have dramatically increased demands for energy as well as biosynthetic precursors to fuel their restless growth. Enhanced glutaminolysis is a hallmark of cancer metabolism which fulfills these needs. Two glutamine transporters, SLC1A5 and SLC38A2, have been previously reported to promote glutaminolysis in cancer with controversial perspectives. In this study, we harnessed the proximity labeling reaction to map the protein interactome using mass spectrometry-based proteomics and discovered a potential protein-protein interaction between SLC1A5 and SLC38A2. The SLC1A5/SLC38A2 interaction was further confirmed by bimolecular fluorescence complementation assay. We further investigated the metabolic influence of SLC1A5 and SLC38A2 overexpression in human cells, respectively, and found that only SLC38A2, but not SLC1A5, resulted in a cancer-like metabolic profile, where the intracellular concentrations of essential amino acids and lactate were significantly increased as quantified by nuclear magnetic resonance spectroscopy. Finally, we analyzed the 5-year survival rates in a large pan-cancer cohort and found that the SLC1A5hi /SLC38A2lo group did not relate to a poor survival rate, whereas the SLC1A5lo /SLC38A2hi group significantly aggravated the lethality. Intriguingly, the SLC1A5hi /SLC38A2hi group resulted in an even worse prognosis, suggesting a cooperative effect between SLC1A5 and SCL38A2. Our data suggest that SLC38A2 plays a dominant role in reprogramming the cancer-like metabolism and promoting the cancer progression, whereas SLC1A5 may augment this effect when co-overexpressed with SLC38A2. We propose a model to explain the relationship between SLC1A5, SLC38A2 and SCL7A5, and discuss their impact on glutaminolysis and mTOR signaling.

--A high-throughput screen identifies inhibitors of the interaction between the oncogenic transcription factor ERG and the cofactor EWS.

Aberrant expression of the transcription factor ERG is a key driving event in approximately one-half of all of prostate cancers. Lacking an enzymatic pocket and mainly disordered, the structure of ERG is difficult to exploit for therapeutic design. We recently identified EWS as a specific interacting partner of ERG that is required for oncogenic function. In this study, we aimed to target this specific protein-protein interaction with small molecules. A high-throughput screening (HTS) strategy was implemented to identify potential protein-protein interaction inhibitors. Secondary assays verified the function of several hit compounds, and one lead compound inhibited ERG-mediated phenotypes in prostate cells. This is the first study aimed at targeting the ERG-EWS protein-protein interaction for the development of a small molecule-based prostate cancer therapy.

Abstract 4933: Nuclear Pyruvate Kinase M2 (PKM2) contributes to PSAT1-mediated cell migration in EGFR-activated lung cancer cells

Abstract Increased activity of the serine synthesis pathway (SSP) has been demonstrated in many types of cancer and can contribute to tumor growth by providing precursors for numerous anabolic reactions. Lung cancer, which is the leading cause of cancer deaths in the U.S., is one of several tumor types displaying increased expression of enzymes within the SSP, particularly PSAT1 (phosphoserine aminotransferase 1). Furthermore, increased PSAT1 expression correlates with poorer overall survival in lung cancer patients. Several previous studies have demonstrated a requirement for PSAT1 for NSCLC proliferation and lung cancer growth. Yet, understanding the complete mechanism by which PSAT1 promotes lung cancer progression requires further investigation, particularly as serine can be imported from the extracellular environment. Recent discoveries of the non-canonical functions of metabolic enzymes in tumorigenesis prompted us to explore a plausible additional function of PSAT1 that may be contributing to lung tumorigenesis. Therefore, we investigated potential PSAT1 protein-protein interactions via GST pulldown assay with mass spectrometry (MS). Among the identified peptides, PKM2 was chosen for further study due to its prior functional link to serine metabolism. In vitro co-immunoprecipitation data showed that PSAT1 interacted selectively with PKM2, but not PKM1 and site-directed mutagenesis analysis found the contribution of the PKM2-specific exon in the interaction. Although in vitro assays found that PSAT1 enhanced the kinase function of recombinant PKM2, depletion of PSAT1 by shRNA did not alter the pyruvate kinase activity and expression in NSCLC cells. Recent reports implicating EGF-induced nuclear PKM2 function in transcription led us to study the role of PSAT1 in nuclear localization of PKM2 in EGFR-activated lung cancer cells. Cell fractionation studies demonstrated that silencing of PSAT1 in EGFR-mutant PC9 or EGF-stimulated A549 cells decreased PKM2 nuclear translocation. Further, PSAT1 suppression abrogated cell migration in EGFR-mutant PC9 and EGF stimulated A549. To further elucidate the role of nuclear PKM2, we introduced PKM2 variants tagged with a nuclear localization signal (NLS) into PSAT1 silenced PC9 cells. We found that re-expression of NLS-PKM2 acetyl-mimetic mutant, but not wild-type, partially restored the cell migration in PSAT1 silenced PC9 cells. Taken together, our findings suggested that PSAT1 contributes to EGFR-driven lung cancer cell migration in part through promoting nuclear PKM2 translocation and function. Citation Format: Rumeysa Biyik-Sit, Traci Kruer, Susan M. Dougherty, James Bradley, Michael L. Merchant, John O. Trent, Brian F. Clem. Nuclear Pyruvate Kinase M2 (PKM2) contributes to PSAT1-mediated cell migration in EGFR-activated lung cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4933.

Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications.

Esophageal cancer (EC) is a type of extremely aggressive gastrointestinal cancer with high incidences in China and other Asian countries. EC does not have specific symptoms and is relatively easy to metastasize, which makes it difficult in early diagnosis. Thus, novel noninvasive diagnostic method is urgently needed in clinical practice. In this study, mass spectrometry with tandem mass tags and differential protein analysis were applied for identifying esophageal cancer-related proteins. The identified proteins were annotated based on their enrichment in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. In addition, hierarchical clustering was applied based on differentially expressed proteins. As a result, a total of 5131 quantifiable proteins were identified from our liquid chromatography-tandem mass spectrometry with tandem mass tags (LC-MS/MS-TMT) method with 63 upregulated and 97 downregulated differential proteins between esophageal cancer and controlled normal samples. The differentially expressed proteins were highly enriched in GO terms associated with mitochondrial dissemble and apoptosis, and blood vessel regulation, and the upregulated differentially expressed proteins in EC samples were significantly enriched in major histocompatibility complex MHC-class I/II pathway of immune system. The functional clustering analysis revealed potential protein-protein interactions among tetraspanin, myosin, and S-100. In summary, our study provided a practical technological procedure of proteomic analysis for discovering novel biomarkers of a specific cancer type.

Gibberellin recovers seed germination in rice with impaired brassinosteroid signalling

Seed germination is essential for ensuring grain yield and quality. Germination rate, uniformity, and post-germination growth all contribute to cultivation. Although the phytohormones gibberellin (GA) and brassinosteroid (BR) are known to regulate germination, the underlying mechanism of their crosstalk in co-regulating rice seed germination remains unclear. In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) proteomic approach was employed to identify target proteins responsive to GA during recovery of germination in BR-deficient and BR-insensitive rice. A total of 42 differentially abundant proteins were identified in both BR-deficient and BR-insensitive plants, and most were altered consistently in the two groups. Gene Ontology (GO) analysis revealed enrichment in proteins with binding and catalytic activity. A potential protein-protein interaction network was constructed using STRING analysis, and five Late Embryogenesis Abundant (LEA) family members were markedly down-regulated at both mRNA transcript and protein levels. These LEA genes were specifically expressed in rice seeds, especially during the latter stages of seed development. Mutation of LEA33 affected rice grain size and seed germination, possibly by reducing BR accumulation and enhancing GA biosynthesis. The findings improve our knowledge of the mechanisms by which GA and BR coordinate seed germination.

Integrated strategy for accurately screening biomarkers based on metabolomics coupled with network pharmacology

Screening diagnostic biomarkers can be challenging due to the complexity of traditional Chinese medicine (TCM) and ambiguous pharmacological mechanisms. In this study, we reported an integrated strategy for accurately screening diagnostic biomarkers based on metabolomics coupled with network pharmacology. First, a feasible pharmacological model was established through systems pharmacology and based on metabolomics-based techniques to explore diagnostic biomarkers. While the components satisfying the q-value < 0.05, fold change (FC) ≥ 1.2 or FC ≤ 0.8, coefficient of variance (CV) ≤ 30%(QC) and the variable importance in the project (VIP) value > 1 are considered to be diagnostic biomarkers. Second, the ingredients were retained only when oral bioavailability (OB), Caco-2 permeability, drug half-life, TPSA and drug likeness (DL) satisfied the criteria (OB ≥ 40%; Caco-2 ≥ −0.4; HL ≥ 4 h; TPSA˂140; DL ≥ 0.18) suggested by the TCMSP database. Moreover, ingredients that exhibit extensive biological activity in TCM are also retained. Third, the effect targets of TCM were screened using the TCMSP database, Swiss Target Prediction and STICH online software. Disease targets were gathered from the therapeutic target database (TTD), PharmGkb and TCMSP database. Hub genes were screened by potential protein-protein interaction (PPI) network pharmacology analysis. Finally, a metabolic network pathway is established between the diagnostic biomarker and the hub gene. In the network analysis of metabolic pathways, most of the genes involved in this pathway are the second-step-obtained hub genes, which can explain the accuracy of the identified biomarkers. The proposed integrated strategy was successfully applied to explore the mechanism of action of Pulsatilla decoction (PD) in the treatment of acute ulcerative colitis (UC). Based on this integrated strategy, 23 potential biomarkers of acute UC treated with PD were identified. In conclusion, the integrated strategy provides novel insights into network pharmacology and metabolomics as effective tools to illuminate the mechanism of action of TCM.

Association study identified biologically relevant receptor genes with synergistic functions in celiac disease

Receptors are essential mediators of cellular physiology, which facilitate molecular and cellular cross-talk with the environment. Nearly 20% of the all known celiac disease (CD) genes are receptors by function. We hypothesized that novel biologically relevant susceptibility receptor genes act in synergy in CD pathogenesis. We attempted to identify novel receptor genes in CD by re-analyzing published Illumina Immunochip dense genotype data for a north Indian and a European (Dutch) cohort. North Indian dataset was screened for 269 known receptor genes. Association statistics for SNPs were considered with minor allele frequency >15% and association P ≤ 0.005 to attend desired study power. Identified markers were tested for cross-ethnic replication in a European CD dataset. Markers were analyzed in-silico to explain their functional significance in CD. Six novel SNPs from MOG (rs29231, p = 1.21e-11), GABBR1 (rs3025643, p = 1.60e-7), OR2H2 (rs1233388, p = 0.0002), ABCF1 (rs9262119, p = 0.0005), ADRA1A (rs10102024, p = 0.003), and ACVR2A (rs7560426, p = 0.004) were identified in north Indians, of which three genes namely, GABBR1 (rs3025643, p = 5.38e-8), OR2H2 (rs1233388, p = 3.29e-5) and ABCF1 (rs9262119, p = 0.0002) were replicated in Dutch. Tissue specific functional annotation, potential epigenetic regulation, co-expression, protein-protein interaction and pathway enrichment analyses indicated differential expression and synergistic function of key genes that could alter cellular homeostasis, ubiquitination mediated phagosome pathway and cellular protein processing to contribute for CD. At present multiple therapeutic compounds/drugs are available targeting GABBR1 and ADRA1A, which could be tested for their effectiveness against CD in controlled drug trials.

Myeloid-Derived Suppressor Cells Are Regulated by Estradiol and Are a Predictive Marker for IVF Outcome.

In vitro fertilization (IVF) is an effective means to treat infertility, but the pregnancy rate is still unsatisfactory and reliable markers to predict pregnancy outcome are ill-defined. Myeloid-derived suppressor cell (MDSC) are critically involved in decisions related to the acceptance or rejection of foreign fetal antigens by the maternal immune system. However, factors that regulate peripheral blood MDSC during pre-pregnancy are poorly defined. Thus, the goal of this study was to assess the relationships among serum estradiol (E2) and endothelial growth factor (VEGF) levels, MDSC ratios, and pregnancy outcome associated with IVF. Patients undergoing IVF treatment (n = 54) were recruited from January to June 2018. Levels of E2 and VEGF were measured by ELISA, MDSC ratios among peripheral blood mononuclear cells (PBMC) were detected by flow cytometry, and the crosstalk among these parameters was analyzed. A receiver operating characteristic curve (ROC) of MDSC levels was plotted to assess this measure as an independent predictive factor for pregnancy. In addition, we analyzed the possible involvement of molecular pathways by bioinformatics. When E2 levels were <4,000 pg/ml, MDSC proportion was positively correlated with serum E2 and VEGF levels. However, when E2 levels were >4,000 pg/ml, MDSC ratio and VEGF levels were negatively correlated with E2. A ROC curve revealed that the percentage of MDSC had better sensitivity and specificity at a concentration of 8.22% (0.875 and 0.75, respectively; area under the curve (AUC) = 0.859) to predict pregnancy success, based on multiple logistic regression analysis. Furthermore, we found 12 target genes of E2 and VEGF, and also functional genes related to MDSC, indicating potential protein–protein interactions underlying these associations. In summary, we showed that E2, depending on its concentration, might play a dichotomous role in influencing the MDSC proportion by regulating VEGF. In IVF patients, an increased MDSC ratio among PBMC was highly correlated with elevated pregnancy rates, independent of the effects of E2, which might provide new insight into immune-related miscarriage and IVF failure.

Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells.

Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein–protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.

Targeting Virus-host Protein Interactions: Feature Extraction and Machine Learning Approaches.

Targeting critical viral-host Protein-Protein Interactions (PPIs) has enormous application prospects for therapeutics. Using experimental methods to evaluate all possible virus-host PPIs is labor-intensive and time-consuming. Recent growth in computational identification of virus-host PPIs provides new opportunities for gaining biological insights, including applications in disease control. We provide an overview of recent computational approaches for studying virus-host PPI interactions. In this review, a variety of computational methods for virus-host PPIs prediction have been surveyed. These methods are categorized based on the features they utilize and different machine learning algorithms including classical and novel methods. We describe the pivotal and representative features extracted from relevant sources of biological data, mainly include sequence signatures, known domain interactions, protein motifs and protein structure information. We focus on state-of-the-art machine learning algorithms that are used to build binary prediction models for the classification of virus-host protein pairs and discuss their abilities, weakness and future directions. The findings of this review confirm the importance of computational methods for finding the potential protein-protein interactions between virus and host. Although there has been significant progress in the prediction of virus-host PPIs in recent years, there is a lot of room for improvement in virus-host PPI prediction.

Examining the Metabolic Role of the Pseudomonas aeruginosa MDO Operon

Mammalian cysteine dioxygenase (CDO) is a mononuclear iron enzyme that catalyzes the oxidation of L‐cysteine to L‐cysteine sulfinic acid. It contains an amino acid‐derived cofactor formed between residues Cys93‐Tyr157. Putative CDO enzymes have been identified in several bacteria; however, all known bacterial CDO enzyme homologs lack the Cys‐Tyr amino acid‐derived cofactor. 1Although the MDO enzyme has been proposed to convert 3‐mercaptopropionate (3‐MPA) to 3‐sulfinopropionate (3‐SPA), the physiological function of either 3‐MPA or 3‐SPA remains unclear. 2,3In numerous bacteria, the MDO gene is on the same operon as an annotated sulfurtransferase, and the operon is expressed during bacterial sulfur limitation. The sulfurtransferase has amino acid sequence similarity to mercaptopyruvate sulfurtransferase enzymes.Different thiol‐containing substrates were evaluated to support a defined metabolic pathway involving both MDO and the sulfurtransferase. MDO gave similar catalytic parameters with both 3‐MPA and mercaptopyruvate, suggesting that both are viable substrates for the enzyme. However, the specificity of MDO for mercaptopyruvate correlates with the classification of the coexpressed sulfurtransferase. Therefore, MDO and the sulfurtransferase enzymes may be metabolically linked, and optimal catalytic function could involve protein‐protein interactions between the two enzymes. Potential protein‐protein interactions between MDO and the sulfurtransferase were identified by surface plasmon resonance, and hydrogen‐deuterium exchange was performed to further identify where the interaction sites of MDO and the sulfurtransferase are located. Coupling of MDO with the sulfurtransferase was also investigated to understand the functional role of the enzymes in bacteria. The proposed overall mechanism for both enzymes would result in sulfite release that could be utilized in the sulfur assimilation pathway. Based on these findings, the MDO/sulfurtransferase system represents an additional pathway for bacteria to adapt to sulfur limiting conditions that had not been previously identified.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.