The Molecule Pages database

Using High-Throughput Measurements to Identify Principles of Transcriptional and Epigenetic Regulators

To achieve exquisite control over the epigenome, we need a better predictive understanding of how transcription factors, chromatin regulators, and their individual domain's function, both as modular parts and as full proteins. Transcriptional effector domains are one class of protein domains that regulate transcription and chromatin. These effector domains either repress or activate gene expression by interacting with chromatin-modifying enzymes, transcriptional cofactors, and/or general transcriptional machinery. Here, we discuss important design considerations for high-throughput investigations of effector domains, recent advances in discovering new domains in human cells and testing how domain function depends on amino acid sequence. For every effector domain, we would like to know the following: What role does the cell type, signaling state, and targeted context have on activation, silencing, and epigenetic memory? Large-scale measurements of transcriptional activities can help systematically answer these questions and identify general rules for how all these parameters affect effector domain activities. Last, we discuss what steps need to be taken to turn a newly discovered effector domain into a robust, precise epigenome editor. With more carefully considered high-throughput investigations, soon we will have better predictive control over the epigenome.

A cellular and bioinformatics analysis of the SENP1 SUMO isopeptidase in pancreatic cancer

Sumoylation is an important post-translational modification that involves the conjugation of the Small Ubiquitin-related Modifier (SUMO) onto target proteins. This modification is reversed through the catalytic activity of SUMO isopeptidases, known as SENPs. One of these SENPs, SENP1, was reported to be overexpressed in human pancreatic cancer cells and patient tissues. Since elevated SENP1 expression levels can be used as a prognostic marker for a subset of cancers, we set out to further explore the overexpression of SENP1 in pancreatic cancer. We found that SENP1 protein levels were not significantly different between pancreatic cancer and normal pancreas-derived cell lines. To evaluate SENP1 expression in patient samples, we analyzed large publicly available datasets and found that SENP1 mRNA levels were significantly lower in pancreatic cancer tissue as compared to normal pancreas tissue samples. Furthermore, we found that the SENP1 gene is amplified in less than 1% of sequenced pancreatic cancer patient samples and that expression levels have no association with patient survival. Based on our analysis, we conclude that SENP1 is not overexpressed in pancreatic cancer and is therefore not likely to be an effective biomarker for this disease. Through this work, we also outline a simple but powerful bioinformatics workflow for the assessment of mRNA expression levels, genomic alterations and survival analysis for putative biomarkers for common human cancers.

Analysis of the Glutamate Agonist LY404,039 Binding to Nonstatic Dopamine Receptor D2 Dimer Structures and Consensus Docking

Dopamine receptor D2 (D2R) plays an important role in the human central nervous system and is a focal target of antipsychotic agents. The D2^HighR and D2^LowR dimeric models previously developed by our group are used to investigate the prediction of binding affinity of the LY404,039 ligand and its binding mechanism within the catalytic domain. The computational data obtained using molecular dynamics simulations fit well with the experimental results. The calculated binding affinities of LY404,039 using MM/PBSA for the D2^HighR and D2^LowR targets were -12.04 and -9.11 kcal/mol, respectively. The experimental results suggest that LY404,039 binds to D2^HighR and D2^LowR with binding affinities (K_i) of 8.2 and 1640 nM, respectively. The high binding affinity of LY404,039 in terms of binding to [³H]domperidone was inhibited by the presence of a guanine nucleotide, indicating an agonist action of the drug at D2^HighR. The interaction analysis demonstrated that while Asp114 was among the most critical amino acids for D2^HighR binding, residues Ser193 and Ser197 were significantly more important within the binding cavity of D2^LowR. Molecular modeling analyses are extended to ensemble docking as well as structure-based pharmacophore model (E-pharmacophore) development using the bioactive conformation of LY404,039 at the binding pocket as a template and screening of small-molecule databases with derived pharmacophore models.

Cancer associated fibroblasts have phenotypic and functional characteristics similar to the fibrocytes that represent a novel MDSC subset

Circulating fibrocytes were reported to represent a novel myeloid-derived suppressor cell (MDSC) subset and they were also proposed to be involved in the tumor immune escape. This novel fibrocyte subset had a surface phenotype resembling non-monocytic MDSCs (CD14^-CD11c^hiCD123^-) and exhibited immunomodulatory roles. Most effector functions of fibrocytes (circulating fibroblast-progenitors) are accomplished as tissue fibroblasts, likewise in the tumor microenvironment. Therefore, fibroblasts at tumor tissues should be evaluated whether they display similar molecular/gene expression patterns and functional roles to the blood-borne fibrocytes. A chemically induced rat breast carcinogenesis model was utilized to obtain cancer associated fibroblasts (CAFs). CAFs and normal tissue fibroblasts (NFs) were isolated from cancerous and healthy breast tissues, respectively, using a previously described enzymatic protocol. Both CAFs and NFs were analyzed for cell surface phenotypes by flow cytometry and for gene expression profiles by gene set enrichment analysis (GSEA). PBMCs were cocultured with either NFs or CAFs and proliferations of PBMCs were assessed by CFSE assays. Morphological analyses were performed by immunocytochemistry stainings with vimentin. CAFs were spindle shaped cells unlike their blood-borne counterparts. They did not express CD80 and their MHC-II expression was lower than NFs. Although CAFs expressed the myeloid marker CD11b/c, its expression was lower than that on the circulating fibrocytes. CAFs did not express granulocytic/neutrophilic markers and they seemed to have developed in an environment containing T_HELPER2-like cytokines. They also showed immunosuppressive effects similar to their blood-borne counterparts. In summary, CAFs showed similar phenotypic and functional characteristics to the circulating fibrocytes that were reported to represent a unique MDSC subset.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation.

Database URL:http://causalbionet.com

Peripheral blood mononuclear cell gene expression profiles predict poor outcome in idiopathic pulmonary fibrosis

We aimed to identify peripheral blood mononuclear cell (PBMC) gene expression profiles predictive of poor outcomes in idiopathic pulmonary fibrosis (IPF) by performing microarray experiments of PBMCs in discovery and replication cohorts of IPF patients. Microarray analyses identified 52 genes associated with transplant-free survival (TFS) in the discovery cohort. Clustering the microarray samples of the replication cohort using the 52-gene outcome-predictive signature distinguished two patient groups with significant differences in TFS. We studied the pathways associated with TFS in each independent microarray cohort and identified decreased expression of "The costimulatory signal during T cell activation" Biocarta pathway and, in particular, the genes CD28, ICOS, LCK, and ITK, results confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A proportional hazards model, including the qRT-PCR expression of CD28, ICOS, LCK, and ITK along with patient's age, gender, and percent predicted forced vital capacity (FVC%), demonstrated an area under the receiver operating characteristic curve of 78.5% at 2.4 months for death and lung transplant prediction in the replication cohort. To evaluate the potential cellular source of CD28, ICOS, LCK, and ITK expression, we analyzed and found significant correlation of these genes with the PBMC percentage of CD4(+)CD28(+) T cells in the replication cohort. Our results suggest that CD28, ICOS, LCK, and ITK are potential outcome biomarkers in IPF and should be further evaluated for patient prioritization for lung transplantation and stratification in drug studies.

FNV: light-weight flash-based network and pathway viewer

MOTIVATION

Network diagrams are commonly used to visualize biochemical pathways by displaying the relationships between genes, proteins, mRNAs, microRNAs, metabolites, regulatory DNA elements, diseases, viruses and drugs. While there are several currently available web-based pathway viewers, there is still room for improvement. To this end, we have developed a flash-based network viewer (FNV) for the visualization of small to moderately sized biological networks and pathways.

SUMMARY

Written in Adobe ActionScript 3.0, the viewer accepts simple Extensible Markup Language (XML) formatted input files to display pathways in vector graphics on any web-page providing flexible layout options, interactivity with the user through tool tips, hyperlinks and the ability to rearrange nodes on the screen. FNV was utilized as a component in several web-based systems, namely Genes2Networks, Lists2Networks, KEA, ChEA and PathwayGenerator. In addition, FVN can be used to embed pathways inside pdf files for the communication of pathways in soft publication materials.

AVAILABILITY

FNV is available for use and download along with the supporting documentation and sample networks at http://www.maayanlab.net/FNV.

CONTACT

avi.maayan@mssm.edu.

Sprouty proteins inhibit receptor-mediated activation of phosphatidylinositol-specific phospholipase C

PLCγ03B3 binds Spry1 and Spry2. Overexpression of Spry decreased PLCγ03B3 activity and IP₃ and DAG production, whereas Spry-deficient cells yielded more IP₃. Spry overexpression inhibited T-cell receptor signaling and Spry1 null T-cells hyperproliferated with TCR ligation. Through action of PLCγ03B3, Spry may influence signaling through multiple receptors.

Sprouty (Spry) proteins are negative regulators of receptor tyrosine kinase signaling; however, their exact mechanism of action remains incompletely understood. We identified phosphatidylinositol-specific phospholipase C (PLC)-γ as a partner of the Spry1 and Spry2 proteins. Spry–PLCγ interaction was dependent on the Src homology 2 domain of PLCγ and a conserved N-terminal tyrosine residue in Spry1 and Spry2. Overexpression of Spry1 and Spry2 was associated with decreased PLCγ phosphorylation and decreased PLCγ activity as measured by production of inositol (1,4,5)-triphosphate (IP₃) and diacylglycerol, whereas cells deficient for Spry1 or Spry1, -2, and -4 showed increased production of IP₃ at baseline and further increased in response to growth factor signals. Overexpression of Spry 1 or Spry2 or small-interfering RNA-mediated knockdown of PLCγ1 or PLCγ2 abrogated the activity of a calcium-dependent reporter gene, suggesting that Spry inhibited calcium-mediated signaling downstream of PLCγ. Furthermore, Spry overexpression in T-cells, which are highly dependent on PLCγ activity and calcium signaling, blocked T-cell receptor-mediated calcium release. Accordingly, cultured T-cells from Spry1 gene knockout mice showed increased proliferation in response to T-cell receptor stimulation. These data highlight an important action of Spry, which may allow these proteins to influence signaling through multiple receptors.

MPSQ: a web tool for protein-state searching

MPSQ (multi-protein-states query) is a web-based tool for the discovery of protein states (e.g. biological interactions, covalent modifications, cellular localizations). In particular, large sets of genes can be used to search for enriched state transition network maps (NMs) and features facilitating the interpretation of genomic-scale experiments such as microarrays. One NM collects all the catalogued states of a protein as well as the mutual transitions between the states. For the returned NM, graph visualization is provided for easy understanding and to guide further analysis.