GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent, and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understanding their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together, these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

TCF19 Impacts a Network of Inflammatory and DNA Damage Response Genes in the Pancreatic β-Cell

Transcription factor 19 (TCF19) is a gene associated with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in genome-wide association studies. Prior studies have demonstrated that Tcf19 knockdown impairs β-cell proliferation and increases apoptosis. However, little is known about its role in diabetes pathogenesis or the effects of TCF19 gain-of-function. The aim of this study was to examine the impact of TCF19 overexpression in INS-1 β-cells and human islets on proliferation and gene expression. With TCF19 overexpression, there was an increase in nucleotide incorporation without any change in cell cycle gene expression, alluding to an alternate process of nucleotide incorporation. Analysis of RNA-seq of TCF19 overexpressing cells revealed increased expression of several DNA damage response (DDR) genes, as well as a tightly linked set of genes involved in viral responses, immune system processes, and inflammation. This connectivity between DNA damage and inflammatory gene expression has not been well studied in the β-cell and suggests a novel role for TCF19 in regulating these pathways. Future studies determining how TCF19 may modulate these pathways can provide potential targets for improving β-cell survival.

Molecular Human Targets of Bioactive Alkaloid-Type Compounds from Tabernaemontana cymose Jacq

Alkaloids are a group of secondary metabolites that have been widely studied for the discovery of new drugs due to their properties on the central nervous system and their anti-inflammatory, antioxidant and anti-cancer activities. Molecular docking was performed for 10 indole alkaloids identified in the ethanol extract of Tabernaemontana cymosa Jacq. with 951 human targets involved in different diseases. The results were analyzed through the KEGG and STRING databases, finding the most relevant physiological associations for alkaloids. The molecule 5-oxocoronaridine proved to be the most active molecule against human proteins (binding energy affinity average = −9.2 kcal/mol) and the analysis of the interactions between the affected proteins pointed to the PI3K/ Akt/mTOR signaling pathway as the main target. The above indicates that indole alkaloids from T. cymosa constitute a promising source for the search and development of new treatments against different types of cancer.

The Participation of the Intrinsically Disordered Regions of the bHLH-PAS Transcription Factors in Disease Development

The basic helix–loop–helix/Per-ARNT-SIM (bHLH-PAS) proteins are a family of transcription factors regulating expression of a wide range of genes involved in different functions, ranging from differentiation and development control by oxygen and toxins sensing to circadian clock setting. In addition to the well-preserved DNA-binding bHLH and PAS domains, bHLH-PAS proteins contain long intrinsically disordered C-terminal regions, responsible for regulation of their activity. Our aim was to analyze the potential connection between disordered regions of the bHLH-PAS transcription factors, post-transcriptional modifications and liquid-liquid phase separation, in the context of disease-associated missense mutations. Highly flexible disordered regions, enriched in short motives which are more ordered, are responsible for a wide spectrum of interactions with transcriptional co-regulators. Based on our in silico analysis and taking into account the fact that the functions of transcription factors can be modulated by posttranslational modifications and spontaneous phase separation, we assume that the locations of missense mutations inducing disease states are clearly related to sequences directly undergoing these processes or to sequences responsible for their regulation.

Identification of key pathways and genes responsible for aggressive behavior

Aggression is a complex behavior, underpinned by cross talk between several biomolecules. To date a composite molecular network of the behavioral disorder has not been constructed. The present study aims to develop the same from the system network analyses recruiting genes with empirical evidence demonstrating their role in the incidence and progression of aggression. In short, 327 genes were recruited in the study after extensive literature survey and subsequent shortlisting by sieving out the comorbidities like cancer and other pathological and physiological ailments, other languages and repeated citations. Subsequent String network analysis coalesces 275 genes in a network with 2223 edges. The developed network was then subjected to delineate modules using MCODE which via gene clustering on the basis of gene ontology segregate all genes into 14 modules. Of these, as expected top 5 modules involved entailing of neuronal signaling pathways with redundant repetitions. Finally, 10 genes (known) were picked randomly, accounting average module size, and subjected to the network analysis with 100,000 bootstrap replicates. This results in the detection of certain novel genes that lacks empirical evidence for their association with the aggression. Amongst those, most notable are genes involved in protein turnover regulation like UBC, UBA, mitogenic proteins such as Rho and Myc, transcription factors like Tp53. The findings in turn fill caveats in the molecular resolution of cross talk that underscore the development of aggressive behavior and may then be exploited as screening biomarker and/or therapeutic intervention for aggression.

STRING data mining of GWAS data in canine hereditary pigment-associated deafness

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Genome-wide association studies may fail to identify significant associations between a disorder and causative genes in complex hereditary disorders.

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STRING software is a bioinformatics data mining tool that identifies known and predicted physical and functional relationship networks among the proteins of candidate genes.

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STRING analysis provides a mechanism to identify gene-gene interactions that might not otherwise have been recognized.

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Relationships identified from STRING analysis can uncover function-based gene-gene relationships that may not be easily extracted from literature, thereby providing genes for pursuit as a cause of a complex hereditary disorder.

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In this study STRING analysis was applied to identification of candidate genes to pursue as the cause of pigment-associated hereditary deafness in dogs.

Most canine deafness is linked to white pigmentation caused by the piebald locus, shown to be the gene MITF (melanocyte inducing transcription factor), but studies have failed to identify a deafness cause. The coding regions of MITF have not been shown to be mutated in deaf dogs, leading us to pursue genes acting on or controlled by MITF. We have genotyped DNA from 502 deaf and hearing Australian cattle dogs, Dalmatians, and English setters, breeds with a high deafness prevalence. Genome-wide significance was not attained in any of our analyses, but we did identify several suggestive associations. Genome-wide association studies (GWAS) in complex hereditary disorders frequently fail to identify causative gene variants, so advanced bioinformatics data mining techniques are needed to extract information to guide future studies.

STRING diagrams are graphical representations of known and predicted networks of protein-protein interactions, identifying documented relationships between gene proteins based on the scientific literature, to identify functional gene groupings to pursue for further scrutiny. The STRING program predicts associations at a preset confidence level and suggests biological functions based on the identified genes.

Starting with (1) genes within 500 kb of GWAS-suggested SNPs, (2) known pigmentation genes, (3) known human deafness genes, and (4) genes identified from proteomic analysis of the cochlea, we generated STRING diagrams that included these genes. We then reduced the number of genes by excluding genes with no relationship to auditory function, pigmentation, or relevant structures, and identified clusters of genes that warrant further investigation.

Defense Response in Chickpea Pod Wall due to Simulated Herbivory Unfolds Differential Proteome Profile

The pod wall of legumes is known to protect the developing seeds from pests and pathogens. However, the mechanism of conferring defense against insects has not yet been deciphered. Here, we have utilized 2-dimensional gel electrophoresis (2D-GE) coupled with mass spectrometry (MS/MS) to identify over expressed proteins in the pod wall of two different cultivars (commercial cultivar: JG 11 and tolerant cultivar: ICC 506-EB) of chickpea after 12 h of application of Helicoverpa armigera oral secretions (simulated herbivory). The assays were performed with a view that larvae are a voracious feeder and cause substantial damage to the pod within 12 h. A total of 600 reproducible protein spots were detected on gels, and the comparative analysis helped identify 35 (12 up-regulated, 23 down-regulated) and 20 (10 up-regulated, 10 down-regulated) differentially expressed proteins in JG 11 and ICC 506-EB, respectively. Functional classification of protein spots of each cultivar after MS/MS indicated that the differentially expressed proteins were associated with various metabolic activities. Also, stress-related proteins such as mannitol dehydrogenase (MADH), disease resistance-like protein-CSA1, serine/threonine kinase (D6PKL2), endoglucanase-19 etc. were up-regulated due to simulated herbivory. The proteins identified with a possible role in defense were further analyzed using the STRING database to advance our knowledge on their interacting partners. It decoded the involvement of several reactive oxygen species (ROS) scavengers and other proteins involved in cell wall reinforcement. The biochemical analysis also confirmed the active role of ROS scavengers during simulated herbivory. Thus, our study provides valuable new insights on chickpea-H.armigera interactions at the protein level.

Hepatic proteome analysis reveals altered mitochondrial metabolism and suppressed acyl-CoA synthetase-1 in colon-26 tumor-induced cachexia

Cachexia is a life-threatening complication of cancer traditionally characterized by weight loss and muscle dysfunction. Cachexia, however, is a systemic disease that also involves remodeling of nonmuscle organs. The liver exerts major control over systemic metabolism, yet its role in cancer cachexia is not well understood. To advance the understanding of how the liver contributes to cancer cachexia, we used quantitative proteomics and bioinformatics to identify hepatic pathways and cellular processes dysregulated in mice with moderate and severe colon-26 tumor-induced cachexia; ~300 differentially expressed proteins identified during the induction of moderate cachexia were also differentially regulated in the transition to severe cachexia. KEGG pathway enrichment revealed representation by oxidative phosphorylation, indicating altered hepatic mitochondrial function as a common feature across cachexia severity. Glycogen catabolism was also observed in cachexic livers along with decreased pyruvate dehydrogenase protein X component (Pdhx), increased lactate dehydrogenase A chain (Ldha), and increased lactate transporter Mct1. Together this suggests altered lactate metabolism and transport in cachexic livers, which may contribute to energetically inefficient interorgan lactate cycling. Acyl-CoA synthetase-1 (ACSL1), known for activating long-chain fatty acids, was decreased in moderate and severe cachexia based on LC-MS/MS analysis and immunoblotting. ACSL1 showed strong linear relationships with percent body weight change and muscle fiber size (R² = 0.73-0.76, P < 0.01). Mitochondrial coupling efficiency, which is compromised in cachexic livers to potentially increase energy expenditure and weight loss, also showed a linear relationship with ACSL1. Findings suggest altered mitochondrial and substrate metabolism of the liver in cancer cachexia, and possible hepatic targets for intervention.

Bioinformatics to Tackle the Biological Meaning of Human Cerebrospinal Fluid Proteome

Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high-throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation to biological meaning is a challenge. Several bioinformatic tools have emerged to help handling this data into systems biology comprehensively. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using (1) ClueGO+CluePedia tool to perform cluster-based analysis envisioning the characterization of the biological processes dysregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (2) Cytoscape to map disease-specific proteins; (3) SecretomeP to inquire the secretion pathway of CSF proteins; and (4) STRING to identify biological processes modulated by secreted CSF proteins based on protein-protein interaction analysis. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers.

Protein-Protein interaction network analyses of human WNT proteins involved in neural development

WNT proteins are involved from initial of neural tissue specification to the end of cell fate determination and organ development. The present work was carried out to understand the involvement of different WNT isoforms (WNT3a, WNT5a and WNT7b) in neural development. A total of 718, 546 and 1004 PPIs for WNT3a, WNT5a and WNT7b respectively, were predicted by STRING database with confidence score more than 0.400. A network carrying all the selected PPIs of targeted proteins was constructed by using Cytoscape by assigning source node, target node and combined score as edge attribute. A total 2268 interactions of WNT3a, WNT5a and WNT7b were predicted to be involved in multiple signaling pathways and developmental processes. 43 of 2268 PPIs were refined after analyzing role of targeted proteins specifically in brain and neural development. WNT3a, WNT5a and WNT7a were predicted to be interacting with 18, 17 and 11 proteins, respectively, with average node degree score of 1.89, 2.12 and 1.82 respectively. The CytoHubba algorithm identified WNT3a, WNT5a, and WNT7b as hub proteins in neural development ranked on the basis of EPC (Edge Percolated Component) score of 9.352, 9.258 and 8.387.

Analysis of Caenorhabditis elegans phosphoproteome reveals the involvement of a molecular chaperone, HSP-90 protein during Salmonella enterica Serovar Typhi infection

Being a primary and prerequisite Post Translational Modification (PTM), protein phosphorylation mediates the defense mechanisms that presides host defense against a pathogen attack. Hence, the current study was intended to uncover the role of regulatory proteins and their PTMs with special attention to phosphorylation during pathogen attack, using C. elegans as a host and S. Typhi as an interacting pathogen. The study was initiated with the identification of differential regulation of the crucial immune regulatory kinases such as PMK-1, JNK-1 and SGK-1 through immunoblotting analysis, which revealed up-regulation of kinases during 48 h of S. Typhi infection. Subsequent the phosphoproteome profiling of S. Typhi infected C. elegans, using TiO₂ Column Chromatography followed by MALDI-ToF-ToF-MS, uncovered the regulated phosphoprotein players resulting in the identification of 166 and 54 proteins from gel-free and gel-based analysis, respectively. HSP-90 was found to be a central player from the interactome analyses and its role during pathogenic defense was validated using immunoblotting. Furthermore, the protein disorders of the identified phosphoproteins have been extensively analysed in silico. This study suggests that S. Typhi interferes with the homeostasis of chaperone molecules by kinetically interfering with the phosphorylation of the downstream pathway players of MAPK and JNK.

The construction and analysis of the aberrant lncRNA-miRNA-mRNA network in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is the most common cancer and the pathogenesis remain unclear. According to the competing endogenous RNA (ceRNA) theory, long noncoding RNA (lncRNA) have a competition with mRNAs for the connecting with miRNAs that affecting the level of mRNA. In this work, the ceRNA network and the important genes to predict the survival prognosis were explored.

Methods

In the study, we recognized differently expressed genes (mRNAs, lncRNAs and miRNAs) between NSCLC and normal tissues from The Cancer Genome Atlas database (fold change >2, P<0.01) using edgeR. Then, the interaction between lncRNA and miRNA or mRNA and miRNA was explored by miRcode, miRDB, TargetScan, and miRanda. Furthermore, the functions and KEGG pathway were analyzed with DAVID and KOBAS. The connections of these mRNAs were explored by STRING online database. The relation between genes in the network and survival time were further explored by survival package in R.

Results

By bioinformatics tools, we explored 155 lncRNAs, 30 miRNAs and 68 mRNAs and constructed ceRNA network. The functions and KEGG pathway of 68 mRNAs were further analyzed. AQP2, EGF, SLC12A1, TRPV5 and AVPR2 was in the center of network and may play key roles in the development of NSCLC. And mRNA (CCNB1, COL1A1, E2F7, EGLN3, FOXG1 and PFKP), miRNA (miR-31, miR-144 and miR-192) and lncRNA (AC080129.1, AC100791.1, AL163952.1, AP000525.1, AP003064.2, C2orf48, C10orf91, FGF12-AS2, HOTAIR, LINC00518, LNX1-AS1, MED4-AS1, MIG31HG, MUC2, TTTY16 and UCA1) were closely related with overall survival (OS).

Conclusions

In summary, the present study provides a deeper understanding of the lncRNA-related ceRNA network in NSCLC and some genes may be new target to treat for NSCLC patients.

Proteome profiling of carbapenem-resistant K. pneumoniae clinical isolate (NDM-4): Exploring the mechanism of resistance and potential drug targets

The emergence of carbapenem resistance has become a major problem worldwide. This has made treatment of K. pneumoniae infections a difficult task. In this study, we have explored the whole proteome of the carbapenem-resistant Klebsiella pneumonia clinical isolate (NDM-4) under the meropenem stress. Proteomics (LC-MS/MS) and bioinformatics approaches were employed to uncover the novel mystery of the resistance over the existing mechanisms. Gene ontology, KEGG and STRING were used for functional annotation, pathway enrichment and protein-protein interaction (PPI) network respectively. LC-MS/MS analysis revealed that 52 proteins were overexpressed (≥10 log folds) under meropenem stress. These proteins belong to four major groups namely protein translational machinery complex, DNA/RNA modifying enzymes or proteins, proteins involved in carbapenems cleavage, modifications & transport and energy metabolism & intermediary metabolism-related proteins. Among the total 52 proteins 38 {matched to Klebsiella pneumonia subsp. pneumoniae (strain ATCC 700721/MGH 78578)} were used for functional annotation, pathways enrichment and protein-protein interaction. These were significantly enriched in the "intracellular" (14 of 38), "cytoplasm" (12 of 38) and "ribosome" (10 of 38). We suggest that these 52 over expressed proteins and their interactive proteins cumulatively contributed in survival of bacteria and meropenem resistance through various mechanisms or enriched pathways. These proteins targets and their pathways might be used for development of novel therapeutics against the resistance; therefore, the situation of the emergence of "bad-bugs" could be controlled.

Ribosomal maturation factor (RimP) is essential for survival of nontuberculous mycobacteria Mycobacterium fortuitum under in vitro acidic stress conditions

Mycobacterium fortuitum is an important human pathogenic NTM, which resists stress conditions inside macrophages by exploitation of specific genes. TnphoA-based transposon mutagenesis was employed to identify membrane genes responsible for survival of M. fortuitum under such stress conditions. A library of about 450 mutants was constructed after electroporation of vector pRT291 into wild-type M. fortuitum. On the basis of blue color development and alkaline phosphatase assay, 20 mutants were shortlisted to screen for growth and survival under acidic stress at pH 6.5, 5.5, 4.5, and 3.5. Mutant MT727 showed reduced growth and survival under acidic stress. The acid susceptible mutant MT727 was subjected to other in vitro stress conditions prevalent inside macrophages including oxidative, nutrient starvation and nitrosative stress. However, the mutant showed no appreciable difference in growth behavior under oxidative, nutrient starvation and nitrosative stress conditions in comparison to the wild type. Genomic and bioinformatics analysis of MT727 led to identification of putative ribosomal maturation factor RimP of M. fortuitum to be affected by mutagenesis, showing closest homology to M. abscessus RimP. In silico functional interaction of RimP protein using STRING database showed its interaction with proteins of ribosomal assembly and maturation. Results indicate role of rimP gene in survival of M. fortuitum under acidic stress conditions which may be further explored for use as a potential drug target against M. fortuitum and other mycobacterial infections.

The Importance of Se-Related Genes in the Chondrocyte of Kashin-Beck Disease Revealed by Whole Genomic Microarray and Network Analysis

Kashin-Beck disease (KBD) is an endemic, chronic, and degenerative osteoarthropathy. Selenium (Se) deficiency plays important role in the pathogenesis of KBD. We aimed to screen Se-related gene from chondrocytes of patients with KBD. Whole-genome oligonucleotide microarrays were used to detect differentially expressed genes. qRT-PCR was used to confirm the microarray results. Comparative Toxicogenomics Database (CTD) was used to screen Se-related genes from differentially expressed genes. Gene Ontology (GO) classifications and network analysis of Se-related genes were constituted by STRING online system. Three hundred ninety-nine differentially expressed genes were obtained from microarray. Among them, 54 Se-related genes were identified by CTD. The qRT-PCR validation showed that four genes expressed similarly with the ones in the microarray transcriptional profiles. The Se-related genes were categorized into 6 cellular components, 8 molecular functions, 44 biological processes, 10 pathways, and 1 network by STRING. The Se-related gene insulin-like growth factor binding protein 2 (IGFBP2), insulin-like growth factor binding protein 3 (IGFBP3), interleukin 6 (IL6), BCL2, apoptosis regulator (BCL2), and BCL2-associated X, apoptosis regulator (BAX), which involved in many molecular functions, biological processes, and apoptosis pathway may play important roles in the pathogenesis of KBD.

Identification of target gene and prognostic evaluation for lung adenocarcinoma using gene expression meta-analysis, network analysis and neural network algorithms

BACKGROUND

Lung adenocarcinoma (LUAD) is a heterogeneous disease with poor survival in the advanced stage and a high incidence rate in the world. Novel drug targets are urgently required to improve patient treatment. Therefore, we aimed to identify therapeutic targets for LUAD based on protein-protein and protein-drug interaction network analysis with neural network algorithms using mRNA expression profiles.

RESULTS

A comprehensive meta-analysis of selective non-small cell lung cancer (NSCLC) mRNA expression profile datasets from Gene Expression Omnibus were used to identify potential biomarkers and the molecular mechanisms related to the prognosis of NSCLC patients. Using the Network Analyst tool, based on combined effect size (ES) methods, we recognized 6566 differentially expressed genes (DEGs), which included 3036 downregulated and 3530 upregulated genes linked to NSCLC patient survival. ClueGO, a Cytoscape plugin, was exploited to complete the function and pathway enrichment analysis, which disclosed "regulated exocytosis", "purine nucleotide binding", "pathways in cancer", and "cell cycle" between exceptionally supplemented terms. Enrichr, a web tool examination, demonstrated "early growth response protein 1 (EGR-1)", "hepatocyte nuclear factor 4α (HNF4A)", "mitogen-activated protein kinase 14 (MAP3K14)", and "cyclin-dependent kinase 1 (CDK1)" to be among the most prevalent TFs and kinases associated with NSCLC. Our meta-analysis identified that MAPK1 and aurora kinase (AURKA) are the most obvious class of hub nodes. Furthermore, protein-drug interaction network and neural network algorithms identified candidate drugs such as phosphothreonine and 4-(4-methylpiperazin-1-yl)-n-[5-(2-thienylacetyl)-1,5-dihydropyrrolo[3,4-c]pyrazol-3-yl] benzamide and for the targets MAPK1 and AURKA, respectively.

CONCLUSION

Our study has identified novel candidate biomarkers, pathways, transcription factors (TFs), and kinases associated with NSCLC prognosis, as well as drug candidates, which may assist treatment strategy for NSCLC patients.

Application of Ferulic Acid for Alzheimer's Disease: Combination of Text Mining and Experimental Validation

Alzheimer's disease (AD) is an increasing concern in human health. Despite significant research, highly effective drugs to treat AD are lacking. The present study describes the text mining process to identify drug candidates from a traditional Chinese medicine (TCM) database, along with associated protein target mechanisms. We carried out text mining to identify literatures that referenced both AD and TCM and focused on identifying compounds and protein targets of interest. After targeting one potential TCM candidate, corresponding protein-protein interaction (PPI) networks were assembled in STRING to decipher the most possible mechanism of action. This was followed by validation using Western blot and co-immunoprecipitation in an AD cell model. The text mining strategy using a vast amount of AD-related literature and the TCM database identified curcumin, whose major component was ferulic acid (FA). This was used as a key candidate compound for further study. Using the top calculated interaction score in STRING, BACE1 and MMP2 were implicated in the activity of FA in AD. Exposure of SHSY5Y-APP cells to FA resulted in the decrease in expression levels of BACE-1 and APP, while the expression of MMP-2 and MMP-9 increased in a dose-dependent manner. This suggests that FA induced BACE1 and MMP2 pathways maybe novel potential mechanisms involved in AD. The text mining of literature and TCM database related to AD suggested FA as a promising TCM ingredient for the treatment of AD. Potential mechanisms interconnected and integrated with Aβ aggregation inhibition and extracellular matrix remodeling underlying the activity of FA were identified using in vitro studies.

Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems

Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investigated. The topological properties of PPI network were examined by 'Network analyzer' a cytoscape plugin app and STRING database. The key enriched biological processes and the molecular functions of Mtb TA systems were analyzed by STRING. Manual curation of the PPI data identified four proteins (i.e. Rv2762c, VapB14, VapB42 and VapC42) to possess the highest number of interacting partners. The top 15% hub proteins were identified in the PPI network by employing two statistical measures, i.e. betweenness and radiality by employing cytohubba. Insights gained from the molecular protein models of VapC9 and VapC10 are also documented.

Serum Proteomic Variability Associated with Clinical Phenotype in Familial Transthyretin Amyloidosis (ATTRm)

Transthyretin (TTR), normally a plasma circulating protein, can become misfolded and aggregated, ultimately leading to extracellular deposition of amyloid fibrils usually targeted to heart or nerve tissues. Referred to as TTR-associated amyloidoses (ATTR), this group of diseases is frequently life threatening and fatal if untreated. ATTR, caused by amyloid-forming variant TTR proteins (ATTRm) that arise from point mutations in the TTR gene, were classically referred to as familial amyloid cardiomyopathy (FAC) or familial amyloid polyneuropathy (FAP), reflecting the clinical phenotype. FAC and FAP are pathologies that can be challenging to diagnose as there are no definitive biomarkers of disease; moreover, disease-specific measures of progression are lacking, and treatment options are limited. Thus, the discovery of sensitive and specific indicators of disease has the potential to improve recognition, enable accurate measurement of amyloid progression and response to treatment, and reveal key information regarding FAC and FAP pathobiological mechanisms. In this study, the goal was to investigate serum proteomic features unique to FAC and FAP types of ATTRm. Multiple-reaction monitoring mass spectrometry (MRM-MS), a powerful technique in profiling proteomes, was used to measure the serum concentrations of 160 proteins in samples from FAC and FAP patients. Results were compared to data from healthy control sera obtained from individuals matched to age (≥60 years), gender (male), and race (Caucasian). Proteomic analyses of ATTRm (FAC and FAP) and control samples showed significant concentration differences in 107 of 192 (56%) of the serum proteins that were studied. In comparing FAC to FAP, differences in concentrations as well as interactions and functions of several proteins were identified as unique to each disease; significantly lower levels of TTR were specific to FAC, but not to FAP. Annotated functional clustering identified extracellular region, signal, and signal peptide as terms common to FAC and FAP. Conversely, disulfide bond was unique to FAC; secreted, glycosylation site: N-linked, glycosylation, glycoprotein, polymorphism, and sequence variant were associated solely with FAP. Predicted protein-protein associations in FAC were seen for reaction, binding, and activation processes; no associations were found in FAP. This study demonstrates significant proteomic differences between ATTRm patient and control sera, as well as ATTRm phenotype-associated variations in the circulating levels of several proteins including TTR. The identification of serum proteins unique to FAC and FAP may have diagnostic and prognostic utility and could possibly provide important clues about disease mechanisms.

Bioinformatics Tools for Proteomics Data Interpretation

Biological systems function via intricate cellular processes and networks in which RNAs, metabolites, proteins and other cellular compounds have a precise role and are exquisitely regulated (Kumar and Mann, FEBS Lett 583(11):1703-1712, 2009). The development of high-throughput technologies, such as the Next Generation DNA Sequencing (NGS) and DNA microarrays for sequencing genomes or metagenomes, have triggered a dramatic increase in the last few years in the amount of information stored in the GenBank and UniProt Knowledgebase (UniProtKB). GenBank release 210, reported in October 2015, contains 202,237,081,559 nucleotides corresponding to 188,372,017 sequences, whilst there are only 1,222,635,267,498 nucleotides corresponding to 309,198,943 sequences from Whole Genome Shotgun (WGS) projects. In the case of UniProKB/Swiss-Prot, release 2015_12 (December 9, 2015) contains 196,219,159 amino acids that correspond to 550,116 entries. Meanwhile, UniProtKB/TrEMBL (release 2015_12 of December 9 2015) contains 1,838,851,8871 amino acids corresponding to 555,270,679 entries. Proteomics has also improved our knowledge of proteins that are being expressed in cells at a certain time of the cell cycle. It has also allowed the identification of molecules forming part of multiprotein complexes and an increasing number of posttranslational modifications (PTMs) that are present in proteins, as well as the variants of proteins expressed.

Effects of bone marrow on the microenvironment of the human pancreatic islet: A Protein Profile Approach

Stem cells are a new therapeutic modality that may support the viability and function of human organs and tissue. Our previous studies have revealed that human allogeneic bone marrow (BM) sustains pancreatic β cell function and survival. This paper examines whether BM creates a microenvironment that supports human pancreatic islets in vitro by evaluating 107 proteins in culture media from BM, islet, and islet/bone marrow (IB) with mass spectrometry. Proteins were considered up- or down-regulated if p-values < 0.05 and fold change was greater than 2 fold I VS. IB. In addition, proteins identified that were uniquely found in islets co-cultured with bone marrow, but not in islets or bone marrow. A 95% protein probability was used as a threshold. Twenty three proteins were upregulated, and sixteen proteins were downregulated. The function of each protein is listed based on the protein database, which include structural proteins (9 upregulated, 4 downregulated); anti-protease and anti-endopeptidase enzymes (8 upregulated); cation binding proteins (6 up-regulated). Six proteins were uniquely identified in islet co-cultured with bone marrow. Three are anti-proteases or anti-endopeptidases, and 1 is a structural protein. These findings suggest that BM, by changing culture media proteins, may be one of mechanisms to maintain human islet function and survival.

Differential proteome profiling in the hippocampus of amnesic mice

Amnesia or memory loss is associated with brain aging and several neurodegenerative pathologies including Alzheimer's disease (AD). This can be induced by a cholinergic antagonist scopolamine but the underlying molecular mechanism is poorly understood. This study of proteome profiling in the hippocampus could provide conceptual insights into the molecular mechanisms involved in amnesia. To reveal this, mice were administered scopolamine to induce amnesia and memory impairment was validated by novel object recognition test. Using two-dimensional gel electrophoresis coupled with MALDI-MS/MS, we have analyzed the hippocampal proteome and identified 18 proteins which were differentially expressed. Out of these proteins, 11 were downregulated and 7 were upregulated in scopolamine-treated mice as compared to control. In silico analysis showed that the majority of identified proteins are involved in metabolism, catalytic activity, and cytoskeleton architectural functions. STRING interaction network analysis revealed that majority of identified proteins exhibit common association with Actg1 cytoskeleton and Vdac1 energy transporter protein. Furthermore, interaction map analysis showed that Fascin1 and Coronin 1b individually interact with Actg1 and regulate the actin filament dynamics. Vdac1 was significantly downregulated in amnesic mice and showed interaction with other proteins in interaction network. Therefore, we silenced Vdac1 in the hippocampus of normal young mice and found similar impairment in recognition memory of Vdac1 silenced and scopolamine-treated mice. Thus, these findings suggest that Vdac1-mediated disruption of energy metabolism and cytoskeleton architecture might be involved in scopolamine-induced amnesia.

How to use and integrate bioinformatics tools to compare proteomic data from distinct conditions? A tutorial using the pathological similarities between Aortic Valve Stenosis and Coronary Artery Disease as a case-study

Nowadays we are surrounded by a plethora of bioinformatics tools, powerful enough to deal with the large amounts of data arising from proteomic studies, but whose application is sometimes hard to find. Therefore, we used a specific clinical problem - to discriminate pathophysiology and potential biomarkers between two similar cardiovascular diseases, aortic valve stenosis (AVS) and coronary artery disease (CAD) - to make a step-by-step guide through four bioinformatics tools: STRING, DisGeNET, Cytoscape and ClueGO. Proteome data was collected from articles available on PubMed centered on proteomic studies enrolling subjects with AVS or CAD. Through the analysis of gene ontology provided by STRING and ClueGO we could find specific biological phenomena associated with AVS, such as down-regulation of elastic fiber assembly, and with CAD, such as up-regulation of plasminogen activation. Moreover, through Cytoscape and DisGeNET we could pinpoint surrogate markers either for AVS (e.g. popeye domain containing protein 2 and 28S ribosomal protein S36, mitochondrial) or for CAD (e.g. ankyrin repeat and SOCS box protein 7) which deserve future validation. Data recycling and integration as well as research orientation are among the main advantages of resorting to bioinformatics analysis, hence these tutorials can be of great convenience for proteomics investigators.

BIOLOGICAL SIGNIFICANCE

As we saw for aortic valve stenosis and coronary artery disease, it can be of great relevance to perform preliminary bioinformatics analysis with already published proteomics data. It not only saves us time in the lab (avoiding work duplication) as it points out new hypothesis to explain the phenotypical presentation of the diseases as well as new surrogate markers with clinical relevance, deserving future scrutiny. These essential steps can be easily overcome if one follows the steps proposed in our tutorial for STRING, DisGeNET, Cytoscape and ClueGO utilization.

Blood Proteomic Profiling in Inherited (ATTRm) and Acquired (ATTRwt) Forms of Transthyretin-Associated Cardiac Amyloidosis

Transthyretin-associated forms of cardiac amyloidosis are fatal protein misfolding diseases that can be inherited (ATTRm) or acquired (ATTRwt). An accurate diagnosis of ATTR amyloidosis can be challenging as biopsy evidence, usually from the affected organ, is required. Precise biomarkers for ATTR disease identification and monitoring are undiscovered, disease-specific therapeutic options are needed, and the current understanding of ATTR molecular pathogenesis is limited. The aim of this study was to investigate and compare the serum proteomes in ATTRm and ATTRwt cardiac amyloidosis to identify differentially expressed blood proteins that were disease-specific. Using multiple-reaction monitoring mass spectrometry (MRM-MS), the concentrations of 160 proteins were analyzed in serum samples from ATTRm and ATTRwt patients, and a healthy control group. Patient and control sera were matched to age (≥60 years), gender (male), and race (Caucasian). The circulating concentrations of 123/160 proteins were significantly different in patient vs control sera; TTR and retinol-binding protein (RBP4) levels were significantly decreased (p < 0.03) in ATTRm compared to controls. In ATTRm, 14/123 proteins were identified as unique to that group and found generally to be lower than controls; moreover, the concentrations of RBP4 and 6 other proteins in this group were significantly different (p < 0.04) compared to ATTRwt. Predicted interactions among the 14 proteins unique to ATTRm were categorized as reaction and binding associations. Alternatively, 27 proteins were found to be unique to ATTRwt with associated interactions defined as activation, catalysis, and inhibition, in addition to reaction and binding. This study demonstrates significant proteomic differences between ATTR patient and control sera, and disease-associated variations in circulating levels of several proteins including TTR and RBP4. The identification of serum proteins unique to ATTRm and ATTRwt cardiac amyloidosis may have diagnostic and prognostic utility, and may provide important clues about disease mechanisms.

Protein kinase A signalling in Schistosoma mansoni cercariae and schistosomules

Cyclic AMP (cAMP)-dependent protein kinase/protein kinase A regulates multiple processes in eukaryotes by phosphorylating diverse cellular substrates, including metabolic and signalling enzymes, ion channels and transcription factors. Here we provide insight into protein kinase A signalling in cercariae and 24h in vitro cultured somules of the blood parasite, Schistosoma mansoni, which causes human intestinal schistosomiasis. Functional mapping of activated protein kinase A using anti-phospho protein kinase A antibodies and confocal laser scanning microscopy revealed activated protein kinase A in the central and peripheral nervous system, oral-tip sensory papillae, oesophagus and excretory system of intact cercariae. Cultured 24h somules, which biologically represent the skin-resident stage of the parasite, exhibited similar activation patterns in oesophageal and nerve tissues but also displayed striking activation at the tegument and activation in a region resembling the germinal 'stem' cell cluster. The adenylyl cyclase activator, forskolin, stimulated somule protein kinase A activation and produced a hyperkinesia phenotype. The biogenic amines, serotonin and dopamine known to be present in skin also induced protein kinase A activation in somules, whereas neuropeptide Y or [Leu(31),Pro(34)]-neuropeptide Y attenuated protein kinase A activation. However, neuropeptide Y did not block the forskolin-induced somule hyperkinesia. Bioinformatic investigation of potential protein associations revealed 193 medium confidence and 59 high confidence protein kinase A interacting partners in S. mansoni, many of which possess putative protein kinase A phosphorylation sites. These data provide valuable insight into the intricacies of protein kinase A signalling in S. mansoni and a framework for further physiological investigations into the roles of protein kinase A in schistosomes, particularly in the context of interactions between the parasite and the host.