Proteomic screening and identification of microRNA‐128 targets in glioma cells

Brain‐enriched miR‐128 is repressed in glioma cells, and could inhibit the proliferation of gliomas by targeting genes such as E2F3a and BMI1. To identify more targets of miR‐128 in glioblastoma multiforme, the pulse stable isotope labeling with amino acids in cell culture (pSILAC) technique was used to test its impact on whole protein synthesis in T98G glioma cells. We successfully identified 1897 proteins, of which 1459 proteins were quantified. Among them, 133 proteins were downregulated after the overexpression of miR‐128. Through predictions using various bioinformatics tools, 13 candidate target genes were chosen. A luciferase assay validated that 11 of 13 selected genes were potential targets of miR‐128, and a mutagenesis experiment confirmed CBFB, CORO1C, GLTP, HnRNPF, and TROVE2 as the target genes. Moreover, we observed that the expression of CORO1C, TROVE2, and HnRNPF were higher in glioma cell lines compared to normal brain tissues and presented a tendency toward downregulation after overexpression of miR‐128 in T98G cells. Furthermore, we have validated that CORO1C, TROVE2, and HnRNPF could inhibit glioma cell proliferation. In sum, our data showed that the integration of pSILAC and bioinformatics analysis was an efficient method for seeking the targets of miRNAs, and plentiful targets of miR‐128 were screened and laid the foundation for research into the miR‐128 regulation network.     

Gel‐free mass spectrometry analysis of Drosophila melanogaster heads

Membrane proteins play key roles in several fundamental biological processes such as cell signalling, energy metabolism and transport. Despite the significance, these still remain an under‐represented group in proteomics datasets. Herein, a bottom‐up approach to analyse an enriched membrane fraction from Drosophila melanogaster heads using multidimensional liquid chromatography (LC) coupled with tandem‐mass spectrometry (MS/MS) that relies on complete solubilisation and digestion of proteins, is reported. An enriched membrane fraction was prepared using equilibrium density centrifugation on a discontinuous sucrose gradient, followed by solubilisation using the filter‐aided sample preparation (FASP), tryptic and sequential chymotryptic digestion of proteins. Peptides were separated by reversed‐phase (RP) LC at high pH in the first dimension and acidic RP‐LC in the second dimension coupled directly to an Orbitrap Velos Pro mass spectrometer. A total number of 4812 proteins from 114 865 redundant and 38 179 distinct peptides corresponding to 4559 genes were identified in the enriched membrane fraction from fly heads. These included brain receptors, transporters and channels that are most important elements as drug targets or are linked to disease. Data are available via ProteomeXchange with identifier PXD001712 ( http://proteomecentral.proteomexchange.org/dataset/PXD001712 ).     

A comprehensive Plasmodium falciparum protein interaction map reveals a distinct architecture of a core interactome

We derive a map of protein interactions in the parasite Plasmodium falciparum from conserved interactions in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Escherichia coli and pool them with experimental interaction data. The application of a clique‐percolation algorithm allows us to find overlapping clusters, strongly correlated with yeast specific conserved protein complexes. Such clusters contain core activities that govern gene expression, largely dominated by components of protein production and degradation processes as well as RNA metabolism. A critical role of protein hubs in the interactome of P. falciparum is supported by their appearance in multiple clusters and the tendencies of their interactions to reach into many distinct protein clusters. Parasite proteins with a human ortholog tend to appear in single complexes. Annotating each protein with the stage where it is maximally expressed we observe a high level of cluster integrity in the ring stage. While we find no signal in the trophozoite phase, expression patterns are reversed in the schizont phase, implying a preponderance of parasite specific functions in this late, invasive schizont stage. As such, the inference of potential protein interactions and their analysis contributes to our understanding of the parasite, indicating basic pathways and processes as unique targets for therapeutic intervention.     

In silico re-identification of properties of drug target proteins

Background

Computational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated.

Methods

Using the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins.

Results

We first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained.

Conclusions

When the newly proposed properties are integrated, the prediction performance is improved and these properties are related to drug targets. We believe that our study will provide a new aspect in inferring drug-target interactions.

     

Identification of host genes that affect acquisition of an integrative and conjugative element in Bacillus subtilis

Conjugation, a major type of horizontal gene transfer in bacteria, involves transfer of DNA from a donor to a recipient using donor‐encoded conjugation machinery. Using a high‐throughput screen (Tn‐seq), we identified genes in recipients that contribute to acquisition of the integrative and conjugative element ICEBs1 by Bacillus subtilis. We found that null mutations in some genes caused an increase, and others a decrease in conjugation efficiency. Some mutations affected conjugation only when present in recipients. Other mutations affected conjugation when present in donors or recipients. Most of the genes identified are known or predicted to affect the cell envelope. Several encode enzymes involved in phospholipid biosynthesis and one encodes a homologue of penicillin‐binding proteins. Two of the genes identified also affected conjugation of Tn916, indicating that their roles in conjugation may be general. We did not identify any genes in recipients that were essential for ICEBs1 conjugation, indicating that if there are such genes, then these are either essential for cell growth or redundant. Our results indicate that acquisition of ICEBs1, and perhaps other conjugative elements, is robust and not easily avoided by mutation and that several membrane‐related functions affect the efficiency of conjugation.     

Second-site modifiers of the split mutation of Notch define genes involved in neurogenesis in Drosophila melanogaster

Summary We have searched for dominant modifiers, i.e., enhancers and suppressors, of the compound eye phenotype of split, a recessive viable allele of Notch. Among the spl modifiers found, we have detected mutations in loci whose functions were previously known to cooperate with Notch in embryonic neurogenesis, such as daughterless, master mind, Delta and Hairless. In addition, other spl modifier mutations have been found in loci that were not previously known to interact with Notch, such as scabrous, glass, roughened eye, and several other genes that have not yet been assigned to known loci. The phenotypes associated with mutations in some of these latter loci suggest the participation of the corresponding genes in embryonic neurogenesis. We show that in some cases the observed interactions are due to genetic haplo-insufficent expression of the genes, whereas allele-specific interactions with spl are observed in master mind and Delta alleles. From this observation, we propose a direct functional association between the proteins encoded by Notch, Delta and master mind.     

Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action

A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin’s antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.     

Functional analyses of small secreted cysteine-rich proteins identified candidate effectors in Verticillium dahliae

Secreted small cysteine-rich proteins (SCPs) play a critical role in modulating host immunity in plant–pathogen interactions. Bioinformatic analyses showed that the fungal pathogen Verticillium dahliae encodes more than 100 VdSCPs, but their roles in host–pathogen interactions have not been fully characterized. Transient expression of 123 VdSCP-encoding genes in Nicotiana benthamiana identified three candidate genes involved in host–pathogen interactions. The expression of these three proteins, VdSCP27, VdSCP113, and VdSCP126, in N. benthamiana resulted in cell death accompanied by a reactive oxygen species burst, callose deposition, and induction of defence genes. The three VdSCPs mainly localized to the periphery of the cell. BAK1 and SOBIR1 (associated with receptor-like protein) were required for the immunity triggered by these three VdSCPs in N. benthamiana. Site-directed mutagenesis showed that cysteine residues that form disulphide bonds are essential for the functioning of VdSCP126, but not VdSCP27 and VdSCP113. VdSCP27, VdSCP113, and VdSCP126 individually are not essential for V. dahliae infection of N. benthamiana and Gossypium hirsutum, although there was a significant reduction of virulence on N. benthamiana and G. hirsutum when inoculated with the VdSCP27/VdSCP126 double deletion strain. These results illustrate that the SCPs play a critical role in the V. dahliae–plant interaction via an intrinsic virulence function and suppress immunity following infection.     

In silico prediction of drug targets in <Emphasis Type="Italic">Vibrio cholerae</Emphasis>

Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.     

THANATOS: an integrative data resource of proteins and post-translational modifications in the regulation of autophagy

Macroautophagy/autophagy is a highly conserved process for degrading cytoplasmic contents, determines cell survival or death, and regulates the cellular homeostasis. Besides ATG proteins, numerous regulators together with various post-translational modifications (PTMs) are also involved in autophagy. In this work, we collected 4,237 experimentally identified proteins regulated in autophagy and cell death pathways from the literature. Then we computationally identified potential orthologs of known proteins, and developed a comprehensive database of The Autophagy, Necrosis, ApopTosis OrchestratorS (THANATOS, http://thanatos.biocuckoo.org), containing 191,543 proteins potentially associated with autophagy and cell death pathways in 164 eukaryotes. We performed an evolutionary analysis of ATG genes, and observed that ATGs required for the autophagosome formation are highly conserved across eukaryotes. Further analyses revealed that known cancer genes and drug targets were overrepresented in human autophagy proteins, which were significantly associated in a number of signaling pathways and human diseases. By reconstructing a human kinase-substrate phosphorylation network for ATG proteins, our results confirmed that phosphorylation play a critical role in regulating autophagy. In total, we mapped 65,015 known sites of 11 types of PTMs to collected proteins, and revealed that all types of PTM substrates were enriched in human autophagy. In addition, we observed multiple types of PTM regulators such as protein kinases and ubiquitin E3 ligases or adaptors were significantly associated with human autophagy, and again the results emphasized the importance of PTM regulations in autophagy. We anticipated THANATOS can be a useful resource for further studies.     

Large-scale analysis of phosphorylated proteins in maize leaf

Phosphorylation is an ubiquitous regulatory mechanism governing the activity, subcellular localization, and intermolecular interactions of proteins. To identify a broad range of phosphoproteins from Zea mays, we enriched phosphopeptides from Zea mays leaves using titanium dioxide microcolumns and then extensively fractionated and identified the phosphopeptides by mass spectrometry. A total of 165 unique phosphorylation sites with a putative role in biological processes were identified in 125 phosphoproteins. Most of these proteins are involved in metabolism, including carbohydrate and protein metabolism. We identified novel phosphorylation sites on translation initiation factors, splicing factors, nucleolar RNA helicases, and chromatin-remodeling proteins such as histone deacetylases. Intriguingly, we also identified phosphorylation sites on several proteins associated with photosynthesis, and we speculate that these sites may be involved in carbohydrate metabolism or electron transport. Among these phosphoproteins, phosphoenolpyruvate carboxylase and NADH: nitrate reductase (NR) which catalyzes the rate-limiting and regulated step in the pathway of inorganic nitrogen assimilation were identified. A conserved phosphorylation site was found in the cytochrome b5 heme-binding domain of NADH: nitrate reductase, suggesting that NADH: nitrate reductase is phosphorylated by the same protein kinase or highly related kinases. These data demonstrate that the pathways that regulate diverse processes in plants are major targets of phosphorylation.     

Isolation of WDR and bHLH genes related to flavonoid synthesis in grapevine (<Emphasis Type="Italic">Vitis vinifera</Emphasis> L.)

Anthocyanins and tannins are two of the most abundant flavonoids found in grapevine, and their synthesis is derived from the phenylpropanoid pathway. As described for model species such as Arabidopsis thaliana, maize and petunia, the end-point branches of this pathway are tightly regulated by the combinatorial interaction of three families of regulatory factors; MYB, bHLH (also known as MYC) and WDR proteins. Among these, only MYB genes have been previously identified in grapes. Here, we report the isolation of the first members from the WDR and bHLH families found in Vitis vinifera, named WDR1, WDR2 and MYCA1. WDR1 contributed positively to the accumulation of anthocyanins when it was overexpressed in A. thaliana, although it was not possible to determine the function of WDR2 by ectopic expression. The sub-cellular localizations of WDR1 and MYCA1 were observed by means of GFP-fusion proteins, indicating both cytoplasm and nuclear localization, in contrast to the localization of a MYB factor exclusively in the nucleus. The expression patterns of these genes were quantified in coloured reproductive organs throughout development, and correlated with anthocyanin accumulation and the expression profiles of the flavonoid-related MYBA1-2, UFGT, and ANR genes. In vitro grapevine plantlets grown under high salt concentrations showed a cultivar-dependent response for anthocyanin accumulation, which correlated with the expression of MYBA1-2, MYCA1 and WDR1 genes. These results suggest that MYCA1 may regulate ANR and UFGT and that this last control is easier to distinguish whenever MYBA genes are absent or in low abundance. Future studies should address the specific interactions of these proteins and their quantitative contribution to flavonoid synthesis in grape berries.     

How to decide which are the most pertinent overly-represented features during gene set enrichment analysis

Background  

The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlations amongst heterogeneous data such as Gene Ontology annotations, gene expression data and genome location of genes. Despite the rapid growth of available data, very little has been proposed in terms of formalization and optimization. Additionally, current methods mainly ignore the structure of the data which causes results redundancy. For example, when searching for enrichment in GO terms, genes can be annotated with multiple GO terms and should be propagated to the more general terms in the Gene Ontology. Consequently, the gene sets often overlap partially or totally, and this causes the reported enriched GO terms to be both numerous and redundant, hence, overwhelming the researcher with non-pertinent information. This situation is not unique, it arises whenever some hierarchical clustering is performed (e.g. based on the gene expression profiles), the extreme case being when genes that are neighbors on the chromosomes are considered.