Network-Based Protein Biomarker Discovery Platforms

The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms

The Rice Oligonucleotide Array Database: an atlas of rice gene expression

BACKGROUND: Microarray technologies facilitate high-throughput gene expression analysis. However, the diversity of platforms for rice gene expression analysis hinders efficient analysis. Tools to broadly integrate microarray data from different platforms are needed. RESULTS: In this study, we developed the Rice Oligonucleotide Array Database (ROAD,http://www.ricearray.org) to explore gene expression across 1,867 publicly available rice microarray hybridizations. The ROAD’s user-friendly web interface and variety of visualization tools facilitate the extraction of gene expression profiles using gene and microarray element identifications. The ROAD supports meta-analysis of genes expressed in different tissues and at developmental stages. Co-expression analysis tool provides information on co-regulation between genes under general, abiotic and biotic stress conditions. Additionally, functional analysis tools, such as Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthology, are embedded in the ROAD. These tools facilitate the identification of meaningful biological patterns in a list of query genes. CONCLUSIONS: The Rice Oligonucleotide Array Database provides comprehensive gene expression profiles for all rice genes, and will be a useful resource for researchers of rice and other grass species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1939-8433-5-17) contains supplementary material, which is available to authorized users

Attenuating MKRN1 E3 ligase-mediated AMPKα suppression increases tolerance against metabolic stresses in mice

The 5′ adenosine monophosphate-activated protein kinase (AMPK) is an essential energy sensor in the cell, which, at low energy levels, instigates the cellular energy-generating systems along with suppression of the anabolic signaling pathways. The activation of AMPK through phosphorylation is a well-known process; however, activation alone is not sufficient, and knowledge about the other regulatory networks of post-translational modifications connecting the activities of AMPK to systemic metabolic syndromes is important, which is still lacking. The recent studies on Makorin Ring Finger Protein 1 (MKRN1) mediating the ubiquitination and proteasome-dependent degradation of AMPKa implicate that the post-translational modification of AMPK, regulating its protein homeostasis, could impose significant systemic metabolic effects (Lee et al. Nat Commun 9:3404). In this study, MKRN1 was identified as a novel E3 ligase for both AMPKα1 and α2. Mouse embryonic fibroblasts, genetically deleted for Mkrmn1, and Ampkα1 and α2, became stabilized with the suppression of lipogenesis pathways and an increase in nutrient consumption and mitochondria regeneration. Of note, the Mkrn1 knockout mice fed normal chow displayed no obvious phenotypic defects or abnormality, whereas the Mkrn1-null mice exhibited strong tolerance to metabolic stresses induced by high-fat diet (HFD). Thus, these mice, when compared with the HFD-induced wild type, were resistant to obesity, diabetes, and non-alcoholic fatty liver disease. Interestingly, in whole-body Mkrn1 knockout mouse, only the liver and white and brown adipose tissues displayed anincrease in the active phosphorylated AMPK levels, but no other organs, such as the hypothalamus, skeletal muscles, or pancreas, displayed such increases. Specific ablation of MKRN1 in the mouse liver using adenovirus prevented HFD-induced lipid accumulation in the liver and blood, implicating MKRN1 as a possible therapeutic target for metabolic syndromes, such as obesity, type II diabetes, and fat liver diseases. This study would provide a crucial perspective on the importance of post-translational regulation of AMPK in metabolic pathways and will help researchers develop novel therapeutic strategies that target not only AMPK but also its regulators

Transcriptional regulatory networks underlying the reprogramming of spermatogonial stem cells to multipotent stem cells

Spermatogonial stem cells (SSCs) are germline stem cells located along the basement membrane of seminiferous tubules in testes. Recently, SSCs were shown to be reprogrammed into multipotent SSCs (mSSCs). However, both the key factors and biological networks underlying this reprogramming remain elusive. Here, we present transcriptional regulatory networks (TRNs) that control cellular processes related to the SSC-to-mSSC reprogramming. Previously, we established intermediate SSCs (iSSCs) undergoing the transition to mSSCs and generated gene expression profiles of SSCs, iSSCs and mSSCs. By comparing these profiles, we identified 2643 genes that were up-regulated during the reprogramming process and 15 key transcription factors (TFs) that regulate these genes. Using the TF-target relationships, we developed TRNs describing how these TFs regulate three pluripotency-related processes (cell proliferation, stem cell maintenance and epigenetic regulation) during the reprogramming. The TRNs showed that 4 of the 15 TFs (Oct4/Pou5f1, Cux1, Zfp143 and E2f4) regulated cell proliferation during the early stages of reprogramming, whereas 11 TFs (Oct4/Pou5f1, Foxm1, Cux1, Zfp143, Trp53, E2f4, Esrrb, Nfyb, Nanog, Sox2 and Klf4) regulated the three pluripotency-related processes during the late stages of reprogramming. Our TRNs provide a model for the temporally coordinated transcriptional regulation of pluripotency-related processes during the SSC-to-mSSC reprogramming, which can be further tested in detailed functional studies.111Ysciescopuskc

Prequips—an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data

Summary: We describe an integrative software platform, Prequips, for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)-based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies. Availability: http://prequips.sourceforge.net Contact: [email protected]

MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis

Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples. Availability: MS-BID source codes, binaries and documentations are freely available under LGPL from http://tools.proteomecenter.org/msBID.php. Contact: [email protected]

The chromatin remodeler Ino80 mediates RNAPII pausing site determination

Background Promoter-proximal pausing of RNA polymerase II (RNAPII) is a critical step for the precise regulation of gene expression. Despite the apparent close relationship between promoter-proximal pausing and nucleosome, the role of chromatin remodeler governing this step has mainly remained elusive. Results Here, we report highly confined RNAPII enrichments downstream of the transcriptional start site in Saccharomyces cerevisiae using PRO-seq experiments. This non-uniform distribution of RNAPII exhibits both similar and different characteristics with promoter-proximal pausing in Schizosaccharomyces pombe and metazoans. Interestingly, we find that Ino80p knockdown causes a significant upstream transition of promoter-proximal RNAPII for a subset of genes, relocating RNAPII from the main pausing site to the alternative pausing site. The proper positioning of RNAPII is largely dependent on nucleosome context. We reveal that the alternative pausing site is closely associated with the + 1 nucleosome, and nucleosome architecture around the main pausing site of these genes is highly phased. In addition, Ino80p knockdown results in an increase in fuzziness and a decrease in stability of the + 1 nucleosome. Furthermore, the loss of INO80 also leads to the shift of promoter-proximal RNAPII toward the alternative pausing site in mouse embryonic stem cells. Conclusions Based on our collective results, we hypothesize that the highly conserved chromatin remodeler Ino80p is essential in establishing intact RNAPII pausing during early transcription elongation in various organisms, from budding yeast to mouse.This work was supported by a National Research Foundation (NRF) of Korea Grant funded by the Ministry of Science and ICT (MSIT) (2018R1A5A1024261, SRC), and the Collaborative Genome Program for Fostering New Post-Genome Industry of the NRF funded by the MSIT (2018M3C9A6065070)

MicroRNA-143 and-145 modulate the phenotype of synovial fibroblasts in rheumatoid arthritis

Fibroblast-like synoviocytes (FLSs) constitute a major cell subset of rheumatoid arthritis (RA) synovia. Dysregulation of microRNAs (miRNAs) has been implicated in activation and proliferation of RA-FLSs. However, the functional association of various miRNAs with their targets that are characteristic of the RA-FLS phenotype has not been globally elucidated. In this study, we performed microarray analyses of miRNAs and mRNAs in RA-FLSs and osteoarthritis FLSs (OA-FLSs), simultaneously, to validate how dysregulated miRNAs may be associated with the RA-FLS phenotype. Global miRNA profiling revealed that miR-143 and miR-145 were differentially upregulated in RA-FLSs compared to OA-FLSs. miR-143 and miR-145 were highly expressed in independent RA-FLSs. The miRNA-target prediction and network model of the predicted targets identified insulin-like growth factor binding protein 5 (IGFBP5) and semaphorin 3A (SEMA3A) as potential target genes downregulated by miR-143 and miR-145, respectively. IGFBP5 level was inversely correlated with miR-143 expression, and its deficiency rendered RA-FLSs more sensitive to TNFα stimulation, promoting IL-6 production and NF-κB activity. Moreover, SEMA3A was a direct target of miR-145, as determined by a luciferase reporter assay, antagonizing VEGF165-induced increases in the survival, migration and invasion of RA-FLSs. Taken together, our data suggest that enhanced expression of miR-143 and miR-145 renders RA-FLSs susceptible to TNFα and VEGF165 stimuli by downregulating IGFBP5 and SEMA3A, respectively, and that these miRNAs could be therapeutic targets. © 2017 KSBMB4

Multi-dimensional histone methylations for coordinated regulation of gene expression under hypoxia

Hypoxia increases both active and repressive histone methylation levels via decreased activity of histone demethylases. However, how such increases coordinately regulate induction or repression of hypoxia-responsive genes is largely unknown. Here, we profiled active and repressive histone tri-methylations (H3K4me3, H3K9me3, and H3K27me3) and analyzed gene expression profiles in human adipocyte-derived stem cells under hypoxia. We identified differentially expressed genes (DEGs) and differentially methylated genes (DMGs) by hypoxia and clustered the DEGs and DMGs into four major groups. We found that each group of DEGs was predominantly associated with alterations in only one type among the three histone tri-methylations. Moreover, the four groups of DEGs were associated with different TFs and localization patterns of their predominant types of H3K4me3, H3K9me3 and H3K27me3. Our results suggest that the association of altered gene expression with prominent single-type histone tri-methylations characterized by different localization patterns and with different sets of TFs contributes to regulation of particular sets of genes, which can serve as a model for coordinated epigenetic regulation of gene expression under hypoxia.111Ysciescopu

Expression and functional profiling reveal distinct gene classes involved in fatty acid metabolism

Cells respond to fatty acid exposure by metabolic reorganization and proliferation of peroxisomes. Described here is the development and application of a genome-wide screen to identify nonessential yeast genes necessary for efficient metabolism of myristic and oleic acids. Comparison of the resultant fitness data set with an integrated data set of genes transcriptionally responsive to fatty acids revealed very little overlap between the data sets. Furthermore, the fitness data set enriched for genes involved in peroxisome biogenesis and other processes related to cell morphology, whereas the expression data set enriched for genes related to metabolism. These data suggest that in response to fatty acid exposure, transcriptional control is biased towards metabolic reorganization, and structural changes tend to be controlled post-transcriptionally. They also suggest that fatty acid responsive metabolic networks are more robust than those related to cell structure. Statistical analyses of these and other global data sets suggest that the utilization of distinct control mechanisms for the execution of morphological versus metabolic responses is widespread