Reactome (http://www.reactome.org) is an expert-authored, peer-reviewed knowledgebase of human reactions and pathways that functions as a data mining resource and electronic textbook. Its current release includes 2975 human proteins, 2907 reactions and 4455 literature citations. A new entity-level pathway viewer and improved search and data mining tools facilitate searching and visualizing pathway data and the analysis of user-supplied high-throughput data sets. Reactome has increased its utility to the model organism communities with improved orthology prediction methods allowing pathway inference for 22 species and through collaborations to create manually curated Reactome pathway datasets for species including Arabidopsis, Oryza sativa (rice), Drosophila and Gallus gallus (chicken). Reactome's data content and software can all be freely used and redistributed under open source terms.

Psoriasis is a chronic, immune-mediated and inflammatory skin disease. Although various biological drugs are available for psoriasis treatment, some patients have poor responses or do not respond to treatment. The aim of the present study was to highlight the molecular mechanism of responsiveness to current biological drugs for psoriasis treatment. To this end, we reviewed previously published articles that reported genes associated with treatment response to biological drugs in psoriasis, and gene ontology analysis was subsequently performed using the Cytoscape platform. Herein, we revealed a statistically significant association between NF-kappaB signaling (p value = 3.37 × 10-9), regulation of granulocyte macrophage colony-stimulating factor production (p value = 6.20 × 10-6), glial cell proliferation (p value = 2.41 × 10-5) and treatment response in psoriatic patients. To the best of our knowledge, we are the first to directly associate glial cells with treatment response. Taken together, our study revealed gene ontology (GO) terms, some of which were previously shown to be implicated in the molecular pathway of psoriasis, as novel GO terms involved in responsiveness in psoriatic disease patients.

Histone H2AK119 mono-ubiquitination (H2AK119Ub) is a relatively abundant histone modification, mainly catalyzed by the Polycomb Repressive Complex 1 (PRC1) to regulate Polycomb-mediated transcriptional repression of downstream target genes. Consequently, H2AK119Ub can also be dynamically reversed by the BAP1 complex, an evolutionarily conserved multiprotein complex that functions as a general transcriptional activator. In previous studies, it has been reported that the BAP1 complex consists of important biological roles in development, metabolism, and cancer. However, identifying the BAP1 complex's regulatory mechanisms remains to be elucidated due to its various complex forms and its ability to target non-histone substrates. In this review, we will summarize recent findings that have contributed to the diverse functional role of the BAP1 complex and further discuss the potential in targeting BAP1 for therapeutic use.

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene-gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as "bait" to "fish out" (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I (GLO1) as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that GLO1 knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for GLO1 in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications.

Constraint-based reconstruction and analysis (COBRA) is used for modeling genome-scale metabolic networks (MNs). In a COBRA model, extreme pathways (ExPas) are the edges of its conical solution space, which is formed by all viable steady-state flux distributions. ExPa analysis has been successfully applied to MNs to reveal their phenotypic capabilities and properties. Recently, the COBRA framework has been extended to transcriptional regulatory networks (TRNs) and transcriptional and translational networks (TTNs), so efforts are needed to determine whether ExPa analysis is also effective on these two types of networks.

Despite our expanding knowledge about the mechanism underlying atrial fibrillation (AF), the interplay between the biological events underlying AF remains incompletely understood. This study aimed to identify the functionally enriched gene-sets in AF and capture their interconnection via pivotal factors, that may drive or be driven by AF. Global abundance of the proteins in the left atrium of AF patients compared to control patients (n = 3/group), and the functionally enriched biological processes in AF were determined by mass-spectrometry and gene set enrichment analysis, respectively. The data were validated in an independent cohort (n = 19-20/group). In AF, the gene-sets of innate immune system, metabolic process, cellular component disassembly and ion homeostasis were up-regulated, while the gene-set of ciliogenesis was down-regulated. The innate immune system was over-represented by neutrophil degranulation, the components of which were extensively shared by other gene-sets altered in AF. In the independent cohort, an activated form of neutrophils was more present in the left atrium of AF patients with the increased gene expression of neutrophil granules. MYH10, required for ciliogenesis, was decreased in the atrial fibroblasts of AF patients. We report the increased neutrophil degranulation appears to play a pivotal role, and affects multiple biological processes altered in AF.

MicroRNAs (miRs) have emerged as important gene silencers affecting many target mRNAs. Here, we report the identification of 244 miRs that target the 3'-untranslated regions of different cholinesterase transcripts: 116 for butyrylcholinesterase (BChE), 47 for the synaptic acetylcholinesterase (AChE-S) splice variant, and 81 for the normally rare splice variant AChE-R. Of these, 11 and 6 miRs target both AChE-S and AChE-R, and AChE-R and BChE transcripts, respectively. BChE and AChE-S showed no overlapping miRs, attesting to their distinct modes of miR regulation. Generally, miRs can suppress a number of targets; thereby controlling an entire battery of functions. To evaluate the importance of the cholinesterase-targeted miRs in other specific biological processes we searched for their other experimentally validated target transcripts and analyzed the gene ontology enriched biological processes these transcripts are involved in. Interestingly, a number of the resulting categories are also related to cholinesterases. They include, for BChE, response to glucocorticoid stimulus, and for AChE, response to wounding and two child terms of neuron development: regulation of axonogenesis and regulation of dendrite morphogenesis. Importantly, all of the AChE-targeting miRs found to be related to these selected processes were directed against the normally rare AChE-R splice variant, with three of them, including the neurogenesis regulator miR-132, also directed against AChE-S. Our findings point at the AChE-R splice variant as particularly susceptible to miR regulation, highlight those biological functions of cholinesterases that are likely to be subject to miR post-transcriptional control, demonstrate the selectivity of miRs in regulating specific biological processes, and open new venues for targeted interference with these specific processes.

Optogenetic tools allow regulation of cellular processes with light, which can be delivered with spatiotemporal resolution. By combining the chemical versatility of photoremovable protecting groups with the biological specificity of self-labeling tags, we developed a series of chemi-optogenetic tools that enable protein recruitment with precise spatiotemporal control. To this end, we created a modular platform for chemically inducible proximity (CIP), a technique in which two proteins of interest are brought together by the presence of a small molecule to induce a biological effect. The local proximity of a protein and its substrate has been shown to be sufficient to initiate a desired biological effect, making CIP a valuable technique towards probing cellular processes. The high affinity and specificity of these tags result in rapid initiation of dimerization, allowing biochemical processes to be studied on a biologically relevant timescale. In this chapter, we describe the synthesis and application of chemi-optogenetic probes for spatiotemporal control of protein proximity.

Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

Kawasaki disease (KD) is an acute self-limited vasculitis and the leading cause of acquired heart disease in children in developed countries. No etiologic agent(s) has been identified, and the processes that mediate formation of coronary artery aneurysms and abatement of fever following treatment with intravenous immunoglobulin (IVIG) remain poorly understood.

High quality functional annotation is essential for understanding the phenotypic consequences encoded in a genome. Despite improvements in bioinformatics methods, millions of sequences in databanks are not assigned reliable functions. The curation of protein functions in the context of biological processes is a way to evaluate and improve their annotation.

Ischemic cardiomyopathy (ICM) and nonischemic dilated cardiomyopathy (DCM) are the two most common causes of heart failure. However, our understanding of the specific proteins and biological processes distinguishing DCM from ICM remains insufficient.

We describe a method for addressing redox enzymes adsorbed on a carbon electrode using synchrotron infrared microspectroscopy combined with protein film electrochemistry. Redox enzymes have high turnover frequencies, typically 10-1000 s(-1), and therefore, fast experimental triggers are needed in order to study subturnover kinetics and identify the involvement of transient species important to their catalytic mechanism. In an electrochemical experiment, this equates to the use of microelectrodes to lower the electrochemical cell constant and enable changes in potential to be applied very rapidly. We use a biological cofactor, flavin mononucleotide, to demonstrate the power of synchrotron infrared microspectroscopy relative to conventional infrared methods and show that vibrational spectra with good signal-to-noise ratios can be collected for adsorbed species with low surface coverages on microelectrodes with a geometric area of 25 × 25 μm(2). We then demonstrate the applicability of synchrotron infrared microspectroscopy to adsorbed proteins by reporting potential-induced changes in the flavin mononucleotide active site of a flavoenzyme. The method we describe will allow time-resolved spectroscopic studies of chemical and structural changes at redox sites within a variety of proteins under precise electrochemical control.

MicroRNAs are frequently dysregulated in human neoplasms, including gastrointestinal cancers. Nevertheless, the global influence of microRNA dysregulation on cellular signaling is still unknown. Here we sought to elucidate cellular signaling dysregulation by microRNAs in gastrointestinal cancers at the systems biology level followed by experimental validation. Signature dysregulated microRNAs in gastric, colorectal and liver cancers were defined based on our previous studies. Targets of signature dysregulated miRNAs were predicted using multiple computer algorithms followed by gene enrichment analysis to identify biological processes perturbed by dysregulated microRNAs. Effects of microRNAs on endocytosis were measured by epidermal growth factor (EGF) internalization assay. Our analysis revealed that, aside from well-established cancer-related signaling pathways, several novel pathways, including axon guidance, neurotrophin/nerve growth factor signaling, and endocytosis, were found to be involved in the pathogenesis of gastrointestinal cancers. The regulation of EGF receptor (EGFR) endocytosis by two predicted miRNAs, namely miR-17 and miR-145, was confirmed experimentally. Functionally, miR-145, which blocked EGFR endocytosis, prolonged EGFR membrane signaling and altered responsiveness of colon cancer cells to EGFR-targeting drugs. In conclusion, our analysis depicts a comprehensive picture of cellular signaling dysregulation, including endocytosis, by microRNAs in gastrointestinal cancers.

Aging is a complex process affecting different species and individuals in different ways. Comparing genetic variation across species with their aging phenotypes will help understanding the molecular basis of aging and longevity. Although most studies on aging have so far focused on short-lived model organisms, recent comparisons of genomic, transcriptomic, and metabolomic data across lineages with different lifespans are unveiling molecular signatures associated with longevity. Here, we examine the relationship between genomic variation and maximum lifespan across primate species. We used two different approaches. First, we searched for parallel amino-acid mutations that co-occur with increases in longevity across the primate linage. Twenty-five such amino-acid variants were identified, several of which have been previously reported by studies with different experimental setups and in different model organisms. The genes harboring these mutations are mainly enriched in functional categories such as wound healing, blood coagulation, and cardiovascular disorders. We demonstrate that these pathways are highly enriched for pleiotropic effects, as predicted by the antagonistic pleiotropy theory of aging. A second approach was focused on changes in rates of protein evolution across the primate phylogeny. Using the phylogenetic generalized least squares, we show that some genes exhibit strong correlations between their evolutionary rates and longevity-associated traits. These include genes in the Sphingosine 1-phosphate pathway, PI3K signaling, and the Thrombin/protease-activated receptor pathway, among other cardiovascular processes. Together, these results shed light into human senescence patterns and underscore the power of comparative genomics to identify pathways related to aging and longevity.

The processes and mechanisms of virus infection fate decisions that are the result of a dynamic virus-immune system interaction with either an efficient effector response and virus elimination or an alleviated immune response and chronic infection are poorly understood. Here, we characterized the host response to acute and chronic lymphocytic choriomeningitis virus (LCMV) infections by gene coexpression network analysis of time-resolved splenic transcriptomes. First, we found an early attenuation of inflammatory monocyte/macrophage prior to the onset of T cell exhaustion, and second, a critical role of the XCL1-XCR1 communication axis during the functional adaptation of the T cell response to the chronic infection state. These findings not only reveal an important feedback mechanism that couples T cell exhaustion with the maintenance of a lower level of effector T cell response but also suggest therapy options to better control virus levels during the chronic infection phase.

Aging is intimately linked to system-wide metabolic changes that can be captured in blood. Understanding biological processes of aging in humans could help maintain a healthy aging trajectory and promote longevity. We performed untargeted plasma metabolomics quantifying 770 metabolites on a cross-sectional cohort of 268 healthy individuals including 125 twin pairs covering human lifespan (from 6 months to 82 years). Unsupervised clustering of metabolic profiles revealed 6 main aging trajectories throughout life that were associated with key metabolic pathways such as progestin steroids, xanthine metabolism, and long-chain fatty acids. A random forest (RF) model was successful to predict age in adult subjects (≥16 years) using 52 metabolites (R2  = .97). Another RF model selected 54 metabolites to classify pediatric and adult participants (out-of-bag error = 8.58%). These RF models in combination with correlation network analysis were used to explore biological processes of healthy aging. The models highlighted established metabolites, like steroids, amino acids, and free fatty acids as well as novel metabolites and pathways. Finally, we show that metabolic profiles of twins become more dissimilar with age which provides insights into nongenetic age-related variability in metabolic profiles in response to environmental exposure.

Despite the discovery of heterotrimeric αβγ G proteins ∼25 years ago, their selective perturbation by cell-permeable inhibitors remains a fundamental challenge. Here we report that the plant-derived depsipeptide FR900359 (FR) is ideally suited to this task. Using a multifaceted approach we systematically characterize FR as a selective inhibitor of Gq/11/14 over all other mammalian Gα isoforms and elaborate its molecular mechanism of action. We also use FR to investigate whether inhibition of Gq proteins is an effective post-receptor strategy to target oncogenic signalling, using melanoma as a model system. FR suppresses many of the hallmark features that are central to the malignancy of melanoma cells, thereby providing new opportunities for therapeutic intervention. Just as pertussis toxin is used extensively to probe and inhibit the signalling of Gi/o proteins, we anticipate that FR will at least be its equivalent for investigating the biological relevance of Gq.

The transcription factor ZBED1 is highly expressed in trophoblast cells, but its functions in the processes of trophoblast and placental biology remain elusive. Here, we characterized the role of ZBED1 in trophoblast cell differentiation using an in vitro BeWo cell model. We demonstrate that ZBED1 is enhanced in its expression early after forskolin-induced differentiation of BeWo cells and regulates many of the genes that are differentially expressed as an effect of forskolin treatment. Specifically, genes encoding markers for the differentiation of cytotrophoblast into syncytiotrophoblast and factors essential for trophoblast cell fusion and invasion were negatively regulated by ZBED1, indicating that ZBED1 might be important for maintaining a steady pool of cytotrophoblast cells. In addition, ZBED1 affected genes involved in the regulation of trophoblast cell survival and apoptosis, in agreement with the observed increase in apoptosis upon knockdown of ZBED1 in forskolin-treated BeWo cells. In addition, genes implicated in the differentiation, recruitment, and function of innate immune cells by the placenta were affected by ZBED1, further suggesting a role for this protein in the regulation of maternal immune tolerance. In conclusion, our study implicates ZBED1 in major biological processes of placental biology.