WikiPathways: capturing the full diversity of pathway knowledge

A Tiered Approach for Screening and Assessment of Environmental Mixtures by Omics and In Vitro Assays

New methodology approaches with a broad coverage of the biological effects are urgently needed to evaluate the safety of the universe of environmentally relevant chemicals. Here, we propose a tiered approach incorporating transcriptomics and in vitro bioassays to assess environmental mixtures. The mixture samples and the perturbed biological pathways are prioritized by concentration-dependent transcriptome (CDT) and then used to guide the selection of in vitro bioassays for toxicant identification. To evaluate omics' screening capability, we first applied a CDT technique to test mixture samples by HepG2 and MCF7 cells. The effect recoveries of large-volume solid-phase extraction on the overall bioactivity of the mixture were 48.9% in HepG2 and 58.3% in MCF7. The overall bioactivity potencies obtained by transcriptomics were positively correlated with the panel of 8 bioassays among 14 mixture samples combined with the previous data. Transcriptomics could predict their activation status (AUC = 0.783) and the relative potency (p < 0.05) of bioassays for four of the eight receptors (AhR, ER, AR, and Nrf2). Furthermore, the CDT identified other biological pathways perturbated by mixture samples, such as the pathway related to TP53, CAR, FXR, HIF, THRA, etc. Overall, this study demonstrates the potential of concentration-dependent omics for effect-based water quality assessment.

Dynamic rewiring of the human interactome by interferon signaling

BACKGROUND

The type I interferon (IFN) response is an ancient pathway that protects cells against viral pathogens by inducing the transcription of hundreds of IFN-stimulated genes. Comprehensive catalogs of IFN-stimulated genes have been established across species and cell types by transcriptomic and biochemical approaches, but their antiviral mechanisms remain incompletely characterized. Here, we apply a combination of quantitative proteomic approaches to describe the effects of IFN signaling on the human proteome, and apply protein correlation profiling to map IFN-induced rearrangements in the human protein-protein interaction network.

RESULTS

We identify > 26,000 protein interactions in IFN-stimulated and unstimulated cells, many of which involve proteins associated with human disease and are observed exclusively within the IFN-stimulated network. Differential network analysis reveals interaction rewiring across a surprisingly broad spectrum of cellular pathways in the antiviral response. We identify IFN-dependent protein-protein interactions mediating novel regulatory mechanisms at the transcriptional and translational levels, with one such interaction modulating the transcriptional activity of STAT1. Moreover, we reveal IFN-dependent changes in ribosomal composition that act to buffer IFN-stimulated gene protein synthesis.

CONCLUSIONS

Our map of the IFN interactome provides a global view of the complex cellular networks activated during the antiviral response, placing IFN-stimulated genes in a functional context, and serves as a framework to understand how these networks are dysregulated in autoimmune or inflammatory disease.

Investigating global gene expression changes in a murine model of cherubism

Cherubism is a rare genetic disorder caused primarily by mutations in SH3BP2 resulting in excessive bone resorption and fibrous tissue overgrowth in the lower portions of the face. Bone marrow derived cell cultures derived from a murine model of cherubism display poor osteogenesis and spontaneous osteoclast formation. To develop a deeper understanding for the potential underlying mechanisms contributing to these phenotypes in mice, we compared global gene expression changes in hematopoietic and mesenchymal cell populations between cherubism and wild type mice. In the hematopoietic population, not surprisingly, upregulated genes were significantly enriched for functions related to osteoclastogenesis. However, these upregulated genes were also significantly enriched for functions associated with inflammation including arachidonic acid/prostaglandin signaling, regulators of coagulation and autoinflammation, extracellular matrix remodeling, and chemokine expression. In the mesenchymal population, we observed down regulation of osteoblast and adventitial reticular cell marker genes. Regulators of BMP and Wnt pathway associated genes showed numerous changes in gene expression, likely implicating the down regulation of BMP signaling and possibly the activation of certain Wnt pathways. Analyses of the cherubism derived mesenchymal population also revealed interesting changes in gene expression related to inflammation including the expression of distinct granzymes, chemokines, and sulfotransferases. These studies reveal complex changes in gene expression elicited from a cherubic mutation in Sh3bp2 that are informative to the mechanisms responding to inflammatory stimuli and repressing osteogenesis. The outcomes of this work are likely to have relevance not only to cherubism, but other inflammatory conditions impacting the skeleton.

The aqueous humor proteome of primary open angle glaucoma: An extensive review

BACKGROUND

We reviewed the literature on the aqueous humor (AH) proteome of primary open angle glaucoma (POAG) patients in order to obtain deeper insight into the pathophysiology of POAG.

METHODS

We searched Pubmed and Embase up to May 2019 for studies that compared AH protein composition between POAG (cases) and cataract (controls). Untargeted studies (measuring the whole proteome, by LC-MS/MS) were divided into two subgroups depending on the type of surgery during which POAG AH was collected: glaucoma filtration surgery (subgroup 1) or cataract surgery (subgroup 2). We reanalyzed the raw data (subgroup 1) or combined the reported data (subgroup 2) to perform GO enrichment (GOrilla) and pathway analysis (Pathvisio).

RESULTS

Out of 93 eligible proteomic studies, seven were untargeted studies that identified 863 AH proteins. We observed 73 differentially expressed proteins in subgroup 1 and 87 differentially expressed proteins in subgroup 2. Both subgroups were characterized by activation of the acute immune response, dysregulation of folate metabolism and dysregulation of the selenium micronutrient network. For subgroup 1 but not for subgroup 2, proteins of the complement system were significantly enriched.

CONCLUSION

AH proteome of POAG patients shows strong activation of the immune system. In addition, analysis suggests dysregulation of folate metabolism and dysregulation of selenium as underlying contributors. In view of their glaucoma surgery, POAG patients of subgroup 1 most likely are progressive whereas POAG patients in subgroup 2 most likely have stable POAG. The proteome difference between these subgroups suggests that the complement system plays a role in POAG progression.

Role of microRNA 690 in Mediating Angiotensin II Effects on Inflammation and Endoplasmic Reticulum Stress

Overactivation of the renin–angiotensin system (RAS) during obesity disrupts adipocyte metabolic homeostasis and induces endoplasmic reticulum (ER) stress and inflammation; however, underlying mechanisms are not well known. We propose that overexpression of angiotensinogen (Agt), the precursor protein of RAS in adipose tissue or treatment of adipocytes with Angiotensin II (Ang II), RAS bioactive hormone, alters specific microRNAs (miRNA), that target ER stress and inflammation leading to adipocyte dysfunction. Epididymal white adipose tissue (WAT) from B6 wild type (Wt) and transgenic male mice overexpressing Agt (Agt-Tg) in adipose tissue and adipocytes treated with Ang II were used. Small RNA sequencing and microarray in WAT identified differentially expressed miRNAs and genes, out of which miR-690 and mitogen-activated protein kinase kinase 3 (MAP2K3) were validated as significantly up- and down-regulated, respectively, in Agt-Tg, and in Ang II-treated adipocytes compared to respective controls. Additionally, the direct regulatory role of miR-690 on MAP2K3 was confirmed using mimic, inhibitors and dual-luciferase reporter assay. Downstream protein targets of MAP2K3 which include p38, NF-κB, IL-6 and CHOP were all reduced. These results indicate a critical post-transcriptional role for miR-690 in inflammation and ER stress. In conclusion, miR-690 plays a protective function and could be a useful target to reduce obesity.

Transcriptomic analysis of vitamin D responses in uterine and peripheral NK cells

Vitamin D deficiency is prevalent in pregnant women and is associated with adverse pregnancy outcomes, in particular disorders of malplacentation. The active form of vitamin D, 1,25-dihydroxyvitamin D3 (1,25(OH)2D3), is a potent regulator of innate and adaptive immunity, but its immune effects during pregnancy remain poorly understood. During early gestation, the predominant immune cells in maternal decidua are uterine natural killer cells (uNK), but the responsivity of these cells to 1,25(OH)2D3 is unknown despite high levels of 1,25(OH)2D3 in decidua. Transcriptomic responses to 1,25(OH)2D3 were characterised in paired donor uNK and peripheral natural killer cells (pNK) following cytokine (CK) stimulation. RNA-seq analyses indicated 911 genes were differentially expressed in CK-stimulated uNK versus CK-stimulated pNK in the absence of 1,25(OH)2D3, with predominant differentially expressed pathways being associated with glycolysis and transforming growth factor β (TGFβ). RNA-seq also showed that the vitamin D receptor (VDR) and its heterodimer partner retinoid X receptor were differentially expressed in CK-stimulated uNK vs CK-stimulated pNK. Further analyses confirmed increased expression of VDR mRNA and protein, as well as VDR-RXR target in CK-stimulated uNK. RNA-seq analysis showed that in CK-stimulated pNK, 1,25(OH)2D3 induced 38 and suppressed 33 transcripts, whilst in CK-stimulated uNK 1,25(OH)2D3 induced 46 and suppressed 19 genes. However, multiple comparison analysis of transcriptomic data indicated that 1,25(OH)2D3 had no significant overall effect on gene expression in either CK-stimulated pNK or uNK. These data indicate that CK-stimulated uNK are transcriptionally distinct from pNK and, despite expressing abundant VDR, neither pNK nor uNK are sensitive targets for vitamin D.

Comprehensive Immunoprofiling of Pediatric Zika Reveals Key Role for Monocytes in the Acute Phase and No Effect of Prior Dengue Virus Infection

Zika virus (ZIKV) is an emerging, mosquito-borne flavivirus responsible for recent epidemics across the Americas, and it is closely related to dengue virus (DENV). Here, we study samples from 46 DENV-naive and 43 DENV-immune patients with RT-PCR-confirmed ZIKV infection at early-acute, late-acute, and convalescent time points from our pediatric cohort study in Nicaragua. We analyze the samples via RNA sequencing (RNA-seq), CyTOF, and multiplex cytokine/chemokine Luminex to generate a comprehensive, innate immune profile during ZIKV infection. Immunophenotyping and analysis of cytokines/chemokines reveal that CD14+ monocytes play a key role during ZIKV infection. Further, we identify CD169 (Siglec-1) on CD14+ monocytes as a potential biomarker of acute ZIKV infection. Strikingly distinct transcriptomic and immunophenotypic signatures are observed at all three time points. Interestingly, pre-existing dengue immunity has minimal impact on the innate immune response to Zika. Finally, this comprehensive immune profiling and network analysis of ZIKV infection in children serves as a valuable resource.

Transcriptional profiling and therapeutic targeting of oxidative stress in neuroinflammation

Oxidative stress is a central part of innate-immune induced neurodegeneration. However, the transcriptomic landscape of the central nervous system (CNS) innate immune cells contributing to oxidative stress is unknown, and therapies to target their neurotoxic functions are not widely available. Here, we provide the oxidative stress innate immune cell atlas in neuroinflammatory disease, and report the discovery of new druggable pathways. Transcriptional profiling of oxidative stress-producing CNS innate immune cells (Tox-seq) identified a core oxidative stress gene signature coupled to coagulation and glutathione pathway genes shared between a microglia cluster and infiltrating macrophages. Tox-seq followed by a microglia high-throughput screen (HTS) and oxidative stress gene network analysis, identified the glutathione regulating compound acivicin with potent therapeutic effects decreasing oxidative stress and axonal damage in chronic and relapsing multiple sclerosis (MS) models. Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune populations and may enable the discovery of selective neuroprotective strategies.

Assessment of the Mode of Action Underlying the Effects of GenX in Mouse Liver and Implications for Assessing Human Health Risks

GenX is an alternative to environmentally persistent long-chain perfluoroalkyl and polyfluoroalkyl substances. Mice exposed to GenX exhibit liver hypertrophy, elevated peroxisomal enzyme activity, and other apical endpoints consistent with peroxisome proliferators. To investigate the potential role of peroxisome proliferator-activated receptor alpha (PPARα) activation in mice, and other molecular signals potentially related to observed liver changes, RNA sequencing was conducted on paraffin-embedded liver sections from a 90-day subchronic toxicity study of GenX conducted in mice. Differentially expressed genes were identified for each treatment group, and gene set enrichment analysis was conducted using gene sets that represent biological processes and known canonical pathways. Peroxisome signaling and fatty acid metabolism were among the most significantly enriched gene sets in both sexes at 0.5 and 5 mg/kg GenX; no pathways were enriched at 0.1 mg/kg. Gene sets specific to the PPARα subtype were significantly enriched. These findings were phenotypically anchored to histopathological changes in the same tissue blocks: hypertrophy, mitoses, and apoptosis. In vitro PPARα transactivation assays indicated that GenX activates mouse PPARα. These results indicate that the liver changes observed in GenX-treated mice occur via a mode of action (MOA) involving PPARα, an important finding for human health risk assessment as this MOA has limited relevance to humans.

A systems toxicology approach to compare the heavy metal mixtures (Pb, As, MeHg) impact in neurodegenerative diseases

Conventional toxicological risk assessment methods mainly working on single chemicals that fail to adequately address the simultaneous exposure and their potential toxicity in humans. We herein investigated the toxic heavy metals lead (Pb), arsenic (As), and methylmercury (MeHg) and their binary mixtures role in neurodegenerative diseases. To characterize the toxicity of metal mixtures at the molecular level, we established a non-animal omics-based organ relevant cell model system. The obtained experimental data was refined by using the statistical and downstream functional analysis. The protein expression information substantiates the previous findings of single metal (Pb, As, and MeHg) induced alterations to mitochondrial dysfunction, oxidative stress, mRNA splicing, and ubiquitin system dysfunction relation to neurodegenerative diseases. The functional downstream analysis of single and binary mixtures protein data is presented in a comparative manner. The heavy metals mixtures' outcome showed significant differences in the protein expression compared to single metals that indicate metal mixtures exposure is more hazardous than single metal exposure. These results suggest that more comprehensive strategies are needed to improve the mixtures risk assessment in the future.

A framework using topological pathways for deeper analysis of transcriptome data

BACKGROUND

Pathway analysis is one of the later stage data analysis steps essential in interpreting high-throughput gene expression data. We propose a set of algorithms which given gene expression data can recognize which portion of sub-pathways are actively utilized in the biological system being studied. The degree of activation is measured by conditional probability of the input expression data based on the Bayesian Network model constructed from the topological pathway.

RESULTS

We demonstrate the effectiveness of our pathway analysis method by conducting two case studies. The first one applies our method to a well-studied temporal microarray data set for the cell cycle using the KEGG Cell Cycle pathway. Our method closely reproduces the biological claims associated with the data sets, but unlike the original work ours can produce how pathway routes interact with each other above and beyond merely identifying which pathway routes are involved in the process. The second study applies the method to the p53 mutation microarray data to perform a comparative study.

CONCLUSIONS

We show that our method achieves comparable performance against all other pathway analysis systems included in this study in identifying p53 altered pathways. Our method could pave a new way of carrying out next generation pathway analysis.

Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach

The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.

BioHackathon 2015: Semantics of data for life sciences and reproducible research

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression

Welding generates and releases fumes that are hazardous to human health. Welding fumes (WFs) are a complex mix of metallic oxides, fluorides and silicates that can cause or exacerbate health problems in exposed individuals. In particular, WF inhalation over an extended period carries an increased risk of cancer, but how WFs may influence cancer behaviour or growth is unclear. To address this issue we employed a quantitative analytical framework to identify the gene expression effects of WFs that may affect the subsequent behaviour of the cancers. We examined datasets of transcript analyses made using microarray studies of WF-exposed tissues and of cancers, including datasets from colorectal cancer (CC), prostate cancer (PC), lung cancer (LC) and gastric cancer (GC). We constructed gene-disease association networks, identified signaling and ontological pathways, clustered protein-protein interaction network using multilayer network topology, and analyzed survival function of the significant genes using Cox proportional hazards (Cox PH) model and product-limit (PL) estimator. We observed that WF exposure causes altered expression of many genes (36, 13, 25 and 17 respectively) whose expression are also altered in CC, PC, LC and GC. Gene-disease association networks, signaling and ontological pathways, protein-protein interaction network, and survival functions of the significant genes suggest ways that WFs may influence the progression of CC, PC, LC and GC. This quantitative analytical framework has identified potentially novel mechanisms by which tissue WF exposure may lead to gene expression changes in tissue gene expression that affect cancer behaviour and, thus, cancer progression, growth or establishment.

Stratifying cellular metabolism during weight loss: an interplay of metabolism, metabolic flexibility and inflammation

Obesity is a global epidemic, contributing significantly to chronic non-communicable diseases, such as type 2 diabetes mellitus, cardiovascular diseases and metabolic syndrome. Metabolic flexibility, the ability of organisms to switch between metabolic substrates, is found to be impaired in obesity, possibly contributing to the development of chronic illnesses. Several studies have shown the improvement of metabolic flexibility after weight loss. In this study, we have mapped the cellular metabolism of the adipose tissue from a weight loss study to stratify the cellular metabolic processes and metabolic flexibility during weight loss. We have found that for a majority of the individuals, cellular metabolism was downregulated during weight loss, with gene expression of all major cellular metabolic processes (such as glycolysis, fatty acid β-oxidation etc.) being lowered during weight loss and weight maintenance. Parallel to this, the gene expression of immune system related processes involving interferons and interleukins increased. Previously, studies have indicated both negative and positive effects of post-weight loss inflammation in the adipose tissue with regards to weight loss or obesity and its co-morbidities; however, mechanistic links need to be constructed in order to determine the effects further. Our study contributes towards this goal by mapping the changes in gene expression across the weight loss study and indicates possible cross-talk between cellular metabolism and inflammation.

Comprehensive bioinformatics analysis of trabecular meshwork gene expression data to unravel the molecular pathogenesis of primary open-angle glaucoma

PURPOSE

Performing bioinformatics analyses using trabecular meshwork (TM) gene expression data in order to further elucidate the molecular pathogenesis of primary open-angle glaucoma (POAG), and to identify candidate target genes.

METHODS

A systematic search in Gene Expression Omnibus and ArrayExpress was conducted, and quality control and preprocessing of the data was performed with ArrayAnalysis.org. Molecular pathway overrepresentation analysis was performed with PathVisio using pathway content from three pathway databases: WikiPathways, KEGG and Reactome. In addition, Gene Ontology (GO) analysis was performed on the gene expression data. The significantly changed pathways were clustered into functional categories which were combined into a network of connected genes.

RESULTS

Ninety-two significantly changed pathways were clustered into five functional categories: extracellular matrix (ECM), inflammation, complement activation, senescence and Rho GTPase signalling. ECM included pathways involved in collagen, actin and cell-matrix interactions. Inflammation included pathways entailing NF-κB and arachidonic acid. The network analysis showed that several genes overlap between the inflammation cluster on the one hand, and the ECM, complement activation and senescence clusters on the other hand. GO analysis, identified additional clusters, related to development and corticosteroids.

CONCLUSION

This study provides an overview of the processes involved in the molecular pathogenesis of POAG in the TM. The results show good face validity and confirm findings from histological, biochemical, genome-wide association and transcriptomics studies. The identification of known points of action for drugs, such as Rho GTPase, arachidonic acid, NF-κB, prostaglandins and corticosteroid clusters, supports the value of this approach to identify potential drug targets.

Genome wide association study of incomplete hippocampal inversion in adolescents

Incomplete hippocampal inversion (IHI), also called hippocampal malrotation, is an atypical presentation of the hippocampus present in about 20% of healthy individuals. Here we conducted the first genome-wide association study (GWAS) in IHI to elucidate the genetic underpinnings that may contribute to the incomplete inversion during brain development. A total of 1381 subjects contributed to the discovery cohort obtained from the IMAGEN database. The incidence rate of IHI was 26.1%. Loci with P<1e-5 were followed up in a validation cohort comprising 161 subjects from the PING study. Summary statistics from the discovery cohort were used to compute IHI heritability as well as genetic correlations with other traits. A locus on 18q11.2 (rs9952569; OR = 1.999; Z = 5.502; P = 3.755e-8) showed a significant association with the presence of IHI. A functional annotation of the locus implicated genes AQP4 and KCTD1. However, neither this locus nor the other 16 suggestive loci reached a significant p-value in the validation cohort. The h² estimate was 0.54 (sd: 0.30) and was significant (Z = 1.8; P = 0.036). The top three genetic correlations of IHI were with traits representing either intelligence or education attainment and reached nominal P< = 0.013.

Whole-Genome Sequencing of Finnish Type 1 Diabetic Siblings Discordant for Kidney Disease Reveals DNA Variants associated with Diabetic Nephropathy

BACKGROUND

Several genetic susceptibility loci associated with diabetic nephropathy have been documented, but no causative variants implying novel pathogenetic mechanisms have been elucidated.

METHODS

We carried out whole-genome sequencing of a discovery cohort of Finnish siblings with type 1 diabetes who were discordant for the presence (case) or absence (control) of diabetic nephropathy. Controls had diabetes without complications for 15-37 years. We analyzed and annotated variants at genome, gene, and single-nucleotide variant levels. We then replicated the associated variants, genes, and regions in a replication cohort from the Finnish Diabetic Nephropathy study that included 3531 unrelated Finns with type 1 diabetes.

RESULTS

We observed protein-altering variants and an enrichment of variants in regions associated with the presence or absence of diabetic nephropathy. The replication cohort confirmed variants in both regulatory and protein-coding regions. We also observed that diabetic nephropathy-associated variants, when clustered at the gene level, are enriched in a core protein-interaction network representing proteins essential for podocyte function. These genes include protein kinases (protein kinase C isoforms ε and ι) and protein tyrosine kinase 2.

CONCLUSIONS

Our comprehensive analysis of a diabetic nephropathy cohort of siblings with type 1 diabetes who were discordant for kidney disease points to variants and genes that are potentially causative or protective for diabetic nephropathy. This includes variants in two isoforms of the protein kinase C family not previously linked to diabetic nephropathy, adding support to previous hypotheses that the protein kinase C family members play a role in diabetic nephropathy and might be attractive therapeutic targets.

Data-driven characterization of molecular phenotypes across heterogeneous sample collections

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.

Phosphoproteomics Profiling to Identify Altered Signaling Pathways and Kinase-Targeted Cancer Therapies

Phosphorylation is one of the most extensively studied posttranslational modifications (PTM), which regulates cellular functions like cell growth, differentiation, apoptosis, and cell signaling. Kinase families cover a wide number of oncoproteins and are strongly associated with cancer. Identification of driver kinases is an intense area of cancer research. Thus, kinases serve as the potential target to improve the efficacy of targeted therapies. Mass spectrometry-based phosphoproteomic approach has paved the way to the identification of a large number of altered phosphorylation events in proteins and signaling cascades that may lead to oncogenic processes in a cell. Alterations in signaling pathways result in the activation of oncogenic processes predominantly regulated by kinases and phosphatases. Therefore, drugs such as kinase inhibitors, which target dysregulated pathways, represent a promising area for cancer therapy.

EBF1 Gene mRNA Levels in Maternal Blood and Spontaneous Preterm Birth

Genetic variants of six genes (EBF1, EEFSEC, AGTR2, WNT4, ADCY5, and RAP2C) have been linked recently to gestational duration and/or spontaneous preterm birth (sPTB). Our goal was to examine sPTB in relation to maternal blood mRNA levels of these genes. We used a public gene expression dataset (GSE59491) derived from maternal blood in trimesters 2 and 3 that included women with sPTB (n = 51) and term births (n = 106) matched for maternal age, race/ethnicity, pre-pregnancy body mass index, smoking during pregnancy, and parity. T tests were used to examine mRNA mean differences (sPTB vs term) within and across trimesters, and logistic regression models with mRNA quartiles were applied to assess associations between candidate gene mRNA levels and sPTB. Based on these analyses, one significant candidate gene was used in a Gene Set Enrichment Analysis (GSEA) to identify related gene sets. These gene sets were then compared with the ones previously linked to sPTB in the same samples. Our results indicated that among women in the lowest quartile of EBF1 mRNA in the 2nd or 3rd trimester, the odds ratio for sPTB was 2.86 (95%CI 1.08, 7.58) (p = 0.0349, false discovery rate (FDR) = 0.18) and 4.43 (95%CI 1.57, 12.50) (p = 0.0049, FDR = 0.06), respectively. No other candidate gene mRNAs were significantly associated with sPTB. In GSEA, 24 downregulated gene sets were correlated with 2nd trimester low EBF1 mRNA and part of previous sPTB-associated gene sets. In conclusion, mRNA levels of EBF1 in maternal blood may be useful in detecting increased risk of sPTB as early as 2nd trimester. The potential underlying mechanism might involve maternal-fetal immune and cell cycle/apoptosis pathways.

Developmentally Engineered Callus Organoid Bioassemblies Exhibit Predictive In Vivo Long Bone Healing

Clinical translation of cell-based products is hampered by their limited predictive in vivo performance. To overcome this hurdle, engineering strategies advocate to fabricate tissue products through processes that mimic development and regeneration, a strategy applicable for the healing of large bone defects, an unmet medical need. Natural fracture healing occurs through the formation of a cartilage intermediate, termed "soft callus," which is transformed into bone following a process that recapitulates developmental events. The main contributors to the soft callus are cells derived from the periosteum, containing potent skeletal stem cells. Herein, cells derived from human periosteum are used for the scalable production of microspheroids that are differentiated into callus organoids. The organoids attain autonomy and exhibit the capacity to form ectopic bone microorgans in vivo. This potency is linked to specific gene signatures mimicking those found in developing and healing long bones. Furthermore, callus organoids spontaneously bioassemble in vitro into large engineered tissues able to heal murine critical-sized long bone defects. The regenerated bone exhibits similar morphological properties to those of native tibia. These callus organoids can be viewed as a living "bio-ink" allowing bottom-up manufacturing of multimodular tissues with complex geometric features and inbuilt quality attributes.

RNA Sequencing of Collecting Duct Renal Cell Carcinoma Suggests an Interaction between miRNA and Target Genes and a Predominance of Deregulated Solute Carrier Genes

Collecting duct carcinoma (CDC) is a rare renal cell carcinoma subtype with a very poor prognosis. There have been only a few studies on gene expression analysis in CDCs. We compared the gene expression profiles of two CDC cases with those of eight normal tissues of renal cell carcinoma patients. At a threshold of |log2fold-change| ≥1, 3349 genes were upregulated and 1947 genes were downregulated in CDCs compared to the normal samples. Pathway analysis of the deregulated genes revealed that cancer pathways and cell cycle pathways were most prominent in CDCs. The most upregulated gene was keratin 17, and the most downregulated gene was cubilin. Among the most downregulated genes were four solute carrier genes (SLC3A1, SLC9A3, SLC26A7, and SLC47A1). The strongest negative correlations between miRNAs and mRNAs were found between the downregulated miR-374b-5p and its upregulated target genes HIST1H3B, HK2, and SLC7A11 and between upregulated miR-26b-5p and its downregulated target genes PPARGC1A, ALDH6A1, and MARC2. An upregulation of HK2 and a downregulation of PPARGC1A, ALDH6A1, and MARC2 were observed at the protein level. Survival analysis of the cancer genome atlas (TCGA) dataset showed for the first time that low gene expression of MARC2, cubilin, and SLC47A1 and high gene expression of KRT17 are associated with poor overall survival in clear cell renal cell carcinoma patients. Altogether, we identified dysregulated protein-coding genes, potential miRNA-target interactions, and prognostic markers that could be associated with CDC.

Adipocyte abundances of CES1, CRYAB, ENO1 and GANAB are modified in-vitro by glucose restriction and are associated with cellular remodelling during weight regain

Long-term weight loss maintenance is a problem of overweight and obesity. Changes of gene expression during weight loss (WL) by calorie restriction (CR) are linked to the risk of weight regain (WR). However, detailed information on genes/proteins involved in the mechanism is still lacking. Therefore, we developed an in-vitro model system for glucose restriction (GR) and refeeding (RF) to uncover proteome differences between GR with RF vs normal feeding, of which we explored the relation with WR after WL. Human Simpson-Golabi-Behmel Syndrome cells were subjected to changing levels of glucose to mimic the condition of CR and RF. Proteome profiling was performed by liquid chromatography tandem mass spectrometry. This in-vitro model revealed 44 proteins differentially expressed after GR and RF versus feeding including proteins of the focal adhesions. Four proteins showed a persistent up- or down-regulation: liver carboxylesterase (CES1), mitochondrial superoxide dismutase [Mn] (SOD2), alpha-crystallin B-chain (CRYAB), alpha-enolase (ENO1). In-vivo weight loss-induced RNA expression changes linked CES1, CRYAB and ENO1 to WR. Moreover, of these 44 proteins, CES1 and glucosidase II alpha subunit (GANAB) during follow up correlated with WR. Correlation clustering of in-vivo protein expression data indicated an interaction of these proteins with structural components of the focal adhesions and cytoplasmic filaments in the adipocytes.

Multi-trait genome-wide association study identifies new loci associated with optic disc parameters

A new avenue of mining published genome-wide association studies includes the joint analysis of related traits. The power of this approach depends on the genetic correlation of traits, which reflects the number of pleiotropic loci, i.e. genetic loci influencing multiple traits. Here, we applied new meta-analyses of optic nerve head (ONH) related traits implicated in primary open-angle glaucoma (POAG); intraocular pressure and central corneal thickness using Haplotype reference consortium imputations. We performed a multi-trait analysis of ONH parameters cup area, disc area and vertical cup-disc ratio. We uncover new variants; rs11158547 in PPP1R36-PLEKHG3 and rs1028727 near SERPINE3 at genome-wide significance that replicate in independent Asian cohorts imputed to 1000 Genomes. At this point, validation of these variants in POAG cohorts is hampered by the high degree of heterogeneity. Our results show that multi-trait analysis is a valid approach to identify novel pleiotropic variants for ONH.

ADGRL4/ELTD1 Silencing in Endothelial Cells Induces ACLY and SLC25A1 and Alters the Cellular Metabolic Profile

Adhesion G Protein-Coupled Receptor L4 (ADGRL4/ELTD1) is an endothelial cell adhesion G protein-coupled receptor (aGPCR) which regulates physiological and tumour angiogenesis, providing an attractive target for anti-cancer therapeutics. To date, ADGRL4/ELTD1's full role and mechanism of function within endothelial biology remains unknown, as do its ligand(s). In this study, ADGRL4/ELTD1 silencing, using two independent small interfering RNAs (siRNAs), was performed in human umbilical vein endothelial cells (HUVECS) followed by transcriptional profiling, target gene validation, and metabolomics using liquid chromatography-mass spectrometry in order to better characterise ADGRL4/ELTD1's role in endothelial cell biology. We show that ADGRL4/ELTD1 silencing induced expression of the cytoplasmic metabolic regulator ATP Citrate Lyase (ACLY) and the mitochondria-to-cytoplasm citrate transporter Solute Carrier Family 25 Member 1 (SLC25A1) but had no apparent effect on pathways downstream of ACLY (fatty acid and cholesterol synthesis or acetylation). Silencing induced KIT expression and affected the Notch signalling pathway, upregulating Delta Like Canonical Notch Ligand 4 (DLL4) and suppressing Jagged Canonical Notch Ligand 1 (JAG1) and Hes Family BHLH Transcription Factor 2 (HES2). The effect of ADGRL4/ELTD1 silencing on the cellular metabolic profile was modest but several metabolites were significantly affected. Cis-aconitic acid, uridine diphosphate (UDP)-glucoronate, fructose 2,6-diphosphate, uridine 5-diphosphate, and aspartic acid were all elevated as a result of silencing and phosphocreatine, N-acetylglutamic acid, taurine, deoxyadenosine triphosphate, and cytidine monophosphate were depleted. Metabolic pathway analysis implicated ADGRL4/ELTD1 in pyrimidine, amino acid, and sugar metabolism. In summary, this study shows that ADGRL4/ELTD1 impacts core components of endothelial metabolism and regulates genes involved in endothelial differentiation/homeostasis and Notch signalling.

A Bioinformatic Approach for the Identification of Molecular Determinants of Resistance/Sensitivity to Cancer Thermotherapy

Application of heat above 43°C and up to 47°C, the so-called “thermal ablation” range, leads to tumor cell destruction either by apoptosis or by necrosis. However, tumor cells have developed mechanisms of defense that render them thermoresistant. Of importance, the in situ application of heat for the treatment of localized solid tumors can also prime specific antitumor immunity. Herein, a bioinformatic approach was employed for the identification of molecular determinants implicated in thermoresistance and immunogenic cell death (ICD). To this end, both literature-derived (text mining) and microarray gene expression profile data were processed, followed by functional enrichment analysis. Two important functional gene modules were detected in hyperthermia resistance and ICD, the former including members of the heat shock protein (HSP) family of molecular chaperones and the latter including immune-related molecules, respectively. Of note, the molecules HSP90AA1 and HSPA4 were found common between thermoresistance and damage signaling molecules (damage-associated molecular patterns (DAMPs)) and ICD. In addition, the prognostic potential of HSP90AA1 and HSPA4 overexpression for cancer patients' overall survival was investigated. The results of this study could constitute the basis for the strategic development of more efficient and personalized therapeutic strategies against cancer by means of thermotherapy, by taking into consideration the genetic profile of each patient.

Temporal gene expression changes after acute and delayed ventral root avulsion-reimplantation

BACKGROUND

In a model of injured spinal motor neurons where the avulsed spinal nerve is surgically reimplanted, useful regrowth of the injured nerve follows, both in animal experiments and clinical cases. This has led to surgical reimplantation strategies with subsequent partial functional motoric recovery. Still, the ideal time point for successful regeneration after reimplantation and the specific genetic profile of this time point is not known.

OBJECTIVE

To explore the temporal gene expression of the whole genome in the ventral spinal cord after reimplantation at different time points after avulsion.

METHODS

Totally 18 adult rats were subjected to avulsion of the left L5 root only (N = 3), avulsion followed by acute spinal reimplantation (N = 3), avulsion followed by 24 h (N = 3) or 48 h (N = 3) delayed reimplantation. Animals were allowed to survive 24 h after their respective surgery whereafter the ventral quadrant of the spinal cord at the operated side was harvested, processed for and analysed with Affymetrix Rat Gene ST 1.0 array followed by statistical analysis of gene expression patternsResults:Specific gene expression patterns were found at different time points after avulsion and reimplantation. Over all, early reimplantation seemed to diminish inflammatory response and support gene regulation related to neuronal activity compared to avulsion only or delayed reimplantation. In addition did gene activity after avulsion-reimplantation correspond to regeneration-associated genes typical for regeneration in the peripheral nervous system.

CONCLUSIONS

Our study reveal that genetic profiling after this kind of injury is possible, that specific and distinct expression patterns can be found with early reimplantation being favourable over late and that regenerative activity in this kind of injury bears hallmark typical for peripheral nerve regeneration. These findings can be useful in elucidating specific genetic expression typical for successful nerve regeneration, hopefully not only in this specific model but in the nervous system in general.

Circulating miRNAs and Risk of Sudden Death in Patients With Coronary Heart Disease

OBJECTIVES

This study evaluated whether plasma miRNAs were specifically associated with sudden cardiac and/or arrhythmic death (SCD) in a cohort of patients with coronary heart disease (CHD), most of whom were without primary prevention implantable cardioverter-defibrillators.

BACKGROUND

Novel biomarkers for sudden death risk stratification are needed in patients with CHD to more precisely target preventive therapies, such as implantable cardioverter-defibrillators. miRNAs have been implicated in regulating inflammation and cardiac fibrosis in cells, and plasma miRNAs have been shown to predict cardiovascular death in patients with CHD.

METHODS

We performed a nested case control study within a multicenter cohort of 5,956 patients with CHD followed prospectively for SCD. Plasma levels of 18 candidate miRNAs previously associated with cardiac remodeling were measured in 129 SCD cases and 258 control subjects matched on age, sex, race, and left ventricular ejection fraction.

RESULTS

miR-150-5p, miR-29a-3p, and miR-30a-5p were associated with increased SCD risk (odds ratios and 95% confidence intervals: 2.03 [1.12 to 3.67]; p = 0.02; 1.93 [1.07 to 3.50]; p = 0.02; 0.55 [0.31 to 0.97]; p = 0.04, respectively, for third vs. first tertile miRNA level). Unfavorable levels of all 3 miRNAs was associated with a 4.8-fold increased SCD risk (1.59 to 14.51; p = 0.006). A bioinformatics-based approach predicted miR-150-5p, miR-29a-3p, and miR-30a-5p to be involved in apoptosis, fibrosis, and inflammation.

CONCLUSIONS

These findings suggest that plasma miRNAs may regulate pathways important for remodeling and may be useful in identifying patients with CHD at increased risk of SCD.

Hypergraph-based connectivity measures for signaling pathway topologies

Characterizing cellular responses to different extrinsic signals is an active area of research, and curated pathway databases describe these complex signaling reactions. Here, we revisit a fundamental question in signaling pathway analysis: are two molecules “connected” in a network? This question is the first step towards understanding the potential influence of molecules in a pathway, and the answer depends on the choice of modeling framework. We examined the connectivity of Reactome signaling pathways using four different pathway representations. We find that Reactome is very well connected as a graph, moderately well connected as a compound graph or bipartite graph, and poorly connected as a hypergraph (which captures many-to-many relationships in reaction networks). We present a novel relaxation of hypergraph connectivity that iteratively increases connectivity from a node while preserving the hypergraph topology. This measure, B-relaxation distance, provides a parameterized transition between hypergraph connectivity and graph connectivity. B-relaxation distance is sensitive to the presence of small molecules that participate in many functionally unrelated reactions in the network. We also define a score that quantifies one pathway’s downstream influence on another, which can be calculated as B-relaxation distance gradually relaxes the connectivity constraint in hypergraphs. Computing this score across all pairs of 34 Reactome pathways reveals pairs of pathways with statistically significant influence. We present two such case studies, and we describe the specific reactions that contribute to the large influence score. Finally, we investigate the ability for connectivity measures to capture functional relationships among proteins, and use the evidence channels in the STRING database as a benchmark dataset. STRING interactions whose proteins are B-connected in Reactome have statistically significantly higher scores than interactions connected in the bipartite graph representation. Our method lays the groundwork for other generalizations of graph-theoretic concepts to hypergraphs in order to facilitate signaling pathway analysis.

Signaling pathways describe how cells respond to external signals through molecular interactions. As we gain a deeper understanding of these signaling reactions, it is important to understand how molecules may influence downstream responses and how pathways may affect each other. As the amount of information in signaling pathway databases continues to grow, we have the opportunity to analyze properties about pathway structure. We pose an intuitive question about signaling pathways: when are two molecules “connected” in a pathway? This answer varies dramatically based on the assumptions we make about how reactions link molecules. Here, examine four approaches for modeling the structural topology of signaling pathways, and present methods to quantify whether two molecules are “connected” in a pathway database. We find that existing approaches are either too permissive (molecules are connected to many others) or restrictive (molecules are connected to a handful of others), and we present a new measure that offers a continuum between these two extremes. We then expand our question to ask when an entire signaling pathway is “downstream” of another pathway, and show two case studies from the Reactome pathway database that uncovers pathway influence. Finally, we show that the strict notion of connectivity can capture functional relationships among proteins using an independent benchmark dataset. Our approach to quantify connectivity in pathways considers a biologically-motivated definition of connectivity, laying the foundation for more sophisticated analyses that leverage the detailed information in pathway databases.

Genomic alterations in high-risk chronic lymphocytic leukemia frequently affect cell cycle key regulators and NOTCH1-regulated transcription

To identify genomic alterations contributing to the pathogenesis of high-risk chronic lymphocytic leukemia (CLL) beyond the well-established role of TP53 aberrations, we comprehensively analyzed 75 relapsed/refractory and 71 treatment-naïve high-risk cases from prospective clinical trials by single nucleotide polymorphism arrays and targeted next-generation sequencing. Increased genomic complexity was a hallmark of relapsed/refractory and treatment-naïve high-risk CLL. In relapsed/refractory cases previously exposed to the selective pressure of chemo(immuno)therapy, gain(8)(q24.21) and del(9)(p21.3) were particularly enriched. Both alterations affect key regulators of cell-cycle progression, namely MYC and CDKN2A/B. While homozygous CDKN2A/B loss has been directly associated with Richter transformation, we did not find this association for heterozygous loss of CDKN2A/B. Gains in 8q24.21 were either focal gains in a MYC enhancer region or large gains affecting the MYC locus, but only the latter type was highly enriched in relapsed/refractory CLL (17%). In addition to a high frequency of NOTCH1 mutations (23%), we found recurrent genetic alterations in SPEN (4% mutated), RBPJ (8% deleted) and SNW1 (8% deleted), all affecting a protein complex that represses transcription of NOTCH1 target genes. We investigated the functional impact of these alterations on HES1, DTX1 and MYC gene transcription and found derepression of these NOTCH1 target genes particularly with SPEN mutations. In summary, we provide new insights into the genomic architecture of high-risk CLL, define novel recurrent DNA copy number alterations and refine knowledge on del(9p), gain(8q) and alterations affecting NOTCH1 signaling. This study was registered at ClinicalTrials.gov with number NCT01392079.

The UCSC Genome Browser database: 2018 update

The UCSC Genome Browser (https://genome.ucsc.edu) provides a web interface for exploring annotated genome assemblies. The assemblies and annotation tracks are updated on an ongoing basis—12 assemblies and more than 28 tracks were added in the past year. Two recent additions are a display of CRISPR/Cas9 guide sequences and an interactive navigator for gene interactions. Other upgrades from the past year include a command-line version of the Variant Annotation Integrator, support for Human Genome Variation Society variant nomenclature input and output, and a revised highlighting tool that now supports multiple simultaneous regions and colors.

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.

Interactive and coordinated visualization approaches for biological data analysis

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.

Complementation of dopaminergic signaling by Pitx3-GDNF synergy induces dopamine secretion by multipotent Ntera2 cells

Human teratocarcinoma cell line Ntera2 (NT2) expresses dopamine signals and has shown its safe profile for clinical applications. Attempts to restore complete dopaminergic (DAergic) phenotype enabling these cells to secrete dopamine have not been fully successful so far. We applied a blend of gene transfer techniques and a defined medium to convert NT2 cells to fully DAergic. The cells were primarily engineered to overexpress the Pitx3 gene product and then cultured in a growth medium supplemented with knockout serum and retinoic acid to form embroid bodies (EBs). Trypsinization of EB colonies produced single cells ready for differentiation. Neuronal/DAergic induction was promoted by applying conditioned medium taken from engineered human astrocytomas over-secreting glial cell-derived neurotrophic factor (GDNF). Immunocytochemistry, reverse-transcription and real-time polymerase chain reaction analyses confirmed significantly induced expression of molecules involved in dopamine signaling and metabolism including tyrosine hydroxylase, Nurr1, dopamine transporter, and aromatic acid decarboxylase. High-performance liquid chromatography analysis indicated release of dopamine only from a class of fully differentiated cells expressing Pitx3 and exposed to GDNF. In addition, Pitx3 and GDNF additively promoted in vitro neuroprotection against Parkinsonian toxin. One month after transplantation to the striatum of 6-OHDA-leasioned rats, differentiated NT2 cells survived and induced significant increase in striatal volume. Besides, cell implantation improved motor coordination in Parkinson's disease (PD) rat models. Our findings highlight the importance of Pitx3-GDNF interplay in dopamine signaling and indicate that our strategy might be useful for the restoration of DAergic fate of NT2 cells to make them clinically applicable toward cell replacement therapy of PD.

Ileal interposition surgery targets the hepatic TGF-β pathway, influencing gluconeogenesis and mitochondrial bioenergetics in the UCD-T2DM rat model of diabetes

Ileal interposition (IT) is a surgical procedure that increases the delivery of incompletely digested nutrients and biliary and pancreatic secretions to the distal intestinal mucosa. Here, we investigated the metabolic impact of this intervention in 2-mo-old prediabetic University of California, Davis type 2 diabetes mellitus rats by assessing liver gene expression at 1.5 mo post-IT surgery. Pathway analysis indicated decreased signaling via TGF-β/Smad (a family of proteins named mothers against decapentaplegic homologs), peroxisome proliferator-activated receptor (PPAR), and PI3K-Akt-AMPK-mechanistic target of rapamycin, likely targeting hepatic stellate cells because differentiation and activation of these cells is associated with decreased signaling via PPAR and TGF-β/Smad. IT surgery up-regulated the expression of genes involved in regulation of cholesterol and terpenoid syntheses and down-regulated those involved in glycerophospholipid metabolism [including cardiolipin (CL)], lipogenesis, and gluconeogenesis. Consistent with the down-regulation of the hepatic CL pathway, IT surgery produced a metabolic switch in liver, kidney cortex, and fat depots toward decreased mitochondrial fatty acid β-oxidation, the process required to fuel high energy-demanding pathways (e.g., gluconeogenesis and glyceroneogenesis), whereas opposite effects were observed in skeletal and cardiac muscles. This study demonstrates for the first time the presence of metabolic pathways that complement the effects of IT surgery to maximize its benefits and potentially identify similarly effective, durable, and less invasive therapeutic options for metabolic disease, including inhibitors of TGF-β signaling.-Hung, C., Napoli, E., Ross-Inta, C., Graham, J., Flores-Torres, A. L., Stanhope, K. L., Froment, P., Havel, P. J., Giulivi, C. Ileal interposition surgery targets the hepatic TGF-β pathway, influencing gluconeogenesis and mitochondrial bioenergetics in the UCD-T2DM rat model of diabetes.

Simultaneous Enrichment Analysis of all Possible Gene-sets: Unifying Self-Contained and Competitive Methods

Studying sets of genomic features is increasingly popular in genomics, proteomics and metabolomics since analyzing at set level not only creates a natural connection to biological knowledge but also offers more statistical power. Currently, there are two gene-set testing approaches, self-contained and competitive, both of which have their advantages and disadvantages, but neither offers the final solution. We introduce simultaneous enrichment analysis (SEA), a new approach for analysis of feature sets in genomics and other omics based on a new unified null hypothesis, which includes the self-contained and competitive null hypotheses as special cases. We employ closed testing using Simes tests to test this new hypothesis. For every feature set, the proportion of active features is estimated, and a confidence bound is provided. Also, for every unified null hypotheses, a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$P$\end{document}-value is calculated, which is adjusted for family-wise error rate. SEA does not need to assume that the features are independent. Moreover, users are allowed to choose the feature set(s) of interest after observing the data. We develop a novel pipeline and apply it on RNA-seq data of dystrophin-deficient mdx mice, showcasing the flexibility of the method. Finally, the power properties of the method are evaluated through simulation studies.

Genome-wide functional association networks: background, data & state-of-the-art resources

The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions. Unfortunately, the high volume of network resources makes it impossible for the intended user to select an appropriate tool for their particular research question. The aim of this paper is to provide an overview of the underlying data and representative network resources as well as to mention methods of integration, allowing a customized approach to resource selection. Additionally, this report will provide a primer for researchers venturing into the field of network integration.

Predicting instances of pathway ontology classes for pathway integration

BACKGROUND

To improve the outcomes of biological pathway analysis, a better way of integrating pathway data is needed. Ontologies can be used to organize data from disparate sources, and we leverage the Pathway Ontology as a unifying ontology for organizing pathway data. We aim to associate pathway instances from different databases to the appropriate class in the Pathway Ontology.

RESULTS

Using a supervised machine learning approach, we trained neural networks to predict mappings between Reactome pathways and Pathway Ontology (PW) classes. For 2222 Reactome classes, the neural network (NN) model generated 10,952 class recommendations. We compared against a baseline bag-of-words (BOW) model for predicting correct PW classes. A 5% subset of Reactome pathways (111 pathways) was randomly selected, and the corresponding class recommendations from both models were evaluated by two curators. The precision of the BOW model was higher (0.49 for BOW and 0.39 for NN), but the recall was lower (0.42 for BOW and 0.78 for NN). Around 78% of Reactome pathways received pertinent recommendations from the NN model.

CONCLUSIONS

The neural predictive model produced meaningful class recommendations that assisted PW curators in selecting appropriate class mappings for Reactome pathways. Our methods can be used to reduce the manual effort associated with ontology curation, and more broadly, for augmenting the curators' ability to organize and integrate data from pathway databases using the Pathway Ontology.

A chronic hypoxic response in photoreceptors alters the vitreous proteome in mice

Reduced oxygenation of the outer retina in the aging eye may activate a chronic hypoxic response in RPE and photoreceptor cells and is considered as a risk factor for the development of age-related macular degeneration (AMD). In mice, a chronically active hypoxic response in the retinal pigment epithelium (RPE) or photoreceptors leads to age-dependent retinal degeneration. To identify proteins that may serve as accessible markers for a chronic hypoxic insult to photoreceptors, we used proteomics to determine the protein composition of the vitreous humor in genetically engineered mice that lack the von Hippel-Lindau tumor suppressor (Vhl) specifically in rods (rod^ΔVhl) or cones (all-cone^ΔVhl). Absence of VHL leads to constitutively active hypoxia-inducible transcription factors (HIFs) and thus to a molecular response to hypoxia even in normal room air. To discriminate between the consequences of a local response in photoreceptors and systemic hypoxic effects, we also evaluated the vitreous proteome of wild type mice after exposure to acute hypoxia. 1'043 of the identified proteins were common to all three hypoxia models. 257, 258 and 356 proteins were significantly regulated after systemic hypoxia, in rod^ΔVhl and in all-cone^ΔVhl mice, respectively, at least at one of the analyzed time points. Only few of the regulated proteins were shared by the models indicating that the vitreous proteome is differentially affected by systemic hypoxia and the rod or cone-specific hypoxic response. Similarly, the distinct protein compositions in the individual genetic models at early and late time points suggest regulated, cell-specific and time-dependent processes. Among the proteins commonly regulated in the genetic models, guanylate binding protein 2 (GBP2) showed elevated levels in the vitreous that were accompanied by increased mRNA expression in the retina of both rod^ΔVhl and all-cone^ΔVhl mice. We hypothesize that some of the differentially regulated proteins at early time points may potentially be used as markers for the detection of a chronic hypoxic response of photoreceptors.

Identification of Cholecystokinin by Genome-Wide Profiling as Potential Mediator of Serotonin-Dependent Behavioral Effects of Maternal Separation in the Amygdala

Converging evidence suggests a role of serotonin (5-hydroxytryptamine, 5-HT) and tryptophan hydroxylase 2 (TPH2), the rate-limiting enzyme of 5-HT synthesis in the brain, in modulating long-term, neurobiological effects of early-life adversity. Here, we aimed at further elucidating the molecular mechanisms underlying this interaction, and its consequences for socio-emotional behaviors, with a focus on anxiety and social interaction. In this study, adult, male Tph2 null mutant (Tph2 -/-) and heterozygous (Tph2 +/-) mice, and their wildtype littermates (Tph2 +/+) were exposed to neonatal, maternal separation (MS) and screened for behavioral changes, followed by genome-wide RNA expression and DNA methylation profiling. In Tph2 -/- mice, brain 5-HT deficiency profoundly affected socio-emotional behaviors, i.e., decreased avoidance of the aversive open arms in the elevated plus-maze (EPM) as well as decreased prosocial and increased rule breaking behavior in the resident-intruder test when compared to their wildtype littermates. Tph2 +/- mice showed an ambiguous profile with context-dependent, behavioral responses. In the EPM they showed similar avoidance of the open arm but decreased prosocial and increased rule breaking behavior in the resident-intruder test when compared to their wildtype littermates. Notably, MS effects on behavior were subtle and depended on the Tph2 genotype, in particular increasing the observed avoidance of EPM open arms in wildtype and Tph2 +/- mice when compared to their Tph2 -/- littermates. On the genomic level, the interaction of Tph2 genotype with MS differentially affected the expression of numerous genes, of which a subset showed an overlap with DNA methylation profiles at corresponding loci. Remarkably, changes in methylation nearby and expression of the gene encoding cholecystokinin, which were inversely correlated to each other, were associated with variations in anxiety-related phenotypes. In conclusion, next to various behavioral alterations, we identified gene expression and DNA methylation profiles to be associated with TPH2 inactivation and its interaction with MS, suggesting a gene-by-environment interaction-dependent, modulatory function of brain 5-HT availability.

Metabopolis: scalable network layout for biological pathway diagrams in urban map style

Background

Biological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways.

Results

Our work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. We automatize the manual drawing process of biologists by first partitioning the map domain into multiple sub-blocks, and then building the corresponding pathways by routing edges schematically, to maintain the global and local context simultaneously. Our system incorporates constrained floor-planning and network-flow algorithms to optimize the layout of sub-blocks and to distribute the edge density along the map domain. We have developed the approach in close collaboration with domain experts and present their feedback on the pathway diagrams based on selected use cases.

Conclusions

We present a new approach for computing biological pathway maps that untangles visual clutter by decomposing large networks into semantic sub-networks and bundling long edges to create space for presenting relationships systematically.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2779-4) contains supplementary material, which is available to authorized users.

Genetic effects of welding fumes on the development of respiratory system diseases

BACKGROUND

The welding process releases potentially hazardous gases and fumes, mainly composed of metallic oxides, fluorides and silicates. Long term welding fume (WF) inhalation is a recognized health issue that carries a risk of developing chronic health problems, particularly respiratory system diseases (RSDs). Aside from general airway irritation, WF exposure may drive direct cellular responses in the respiratory system which increase risk of RSD, but these are not well understood.

METHODS

We developed a quantitative framework to identify gene expression effects of WF exposure that may affect RSD development. We analyzed gene expression microarray data from WF-exposed tissues and RSD-affected tissues, including chronic bronchitis (CB), asthma (AS), pulmonary edema (PE), lung cancer (LC) datasets. We built disease-gene (diseasome) association networks and identified dysregulated signaling and ontological pathways, and protein-protein interaction sub-network using neighborhood-based benchmarking and multilayer network topology.

RESULTS

We observed many genes with altered expression in WF-exposed tissues were also among differentially expressed genes (DEGs) in RSD tissues; for CB, AS, PE and LC there were 34, 27, 50 and 26 genes respectively. DEG analysis, using disease association networks, pathways, ontological analysis and protein-protein interaction sub-network suggest significant links between WF exposure and the development of CB, AS, PE and LC.

CONCLUSIONS

Our network-based analysis and investigation of the genetic links of WFs and RSDs confirm a number of genes and gene products are plausible participants in RSD development. Our results are a significant resource to identify causal influences on the development of RSDs, particularly in the context of WF exposure.

Elucidation of Novel Therapeutic Targets for Acute Myeloid Leukemias with RUNX1-RUNX1T1 Fusion

The RUNX1-RUNX1T1 fusion is a frequent chromosomal alteration in acute myeloid leukemias (AMLs). Although RUNX1-RUNX1T1 fusion protein has pivotal roles in the development of AMLs with the fusion, RUNX1-RUNX1T1, fusion protein is difficult to target, as it lacks kinase activities. Here, we used bioinformatic tools to elucidate targetable signaling pathways in AMLs with RUNX1-RUNX1T1 fusion. After analysis of 93 AML cases from The Cancer Genome Atlas (TCGA) database, we found expression of 293 genes that correlated to the expression of the RUNX1-RUNX1T1 fusion gene. Based on these 293 genes, the cyclooxygenase (COX), vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), and fibroblast growth factor receptor (FGFR) pathways were predicted to be specifically activated in AMLs with RUNX1-RUNX1T1 fusion. Moreover, the in vitro proliferation of AML cells with RUNX1-RUNX1T1 fusion decreased significantly more than that of AML cells without the fusion, when the pathways were inhibited pharmacologically. The results indicate that novel targetable signaling pathways could be identified by the analysis of the gene expression features of AMLs with non-targetable genetic alterations. The elucidation of specific molecular targets for AMLs that have a specific genetic alteration would promote personalized treatment of AMLs and improve clinical outcomes.

Community-driven roadmap for integrated disease maps

The Disease Maps Project builds on a network of scientific and clinical groups that exchange best practices, share information and develop systems biomedicine tools. The project aims for an integrated, highly curated and user-friendly platform for disease-related knowledge. The primary focus of disease maps is on interconnected signaling, metabolic and gene regulatory network pathways represented in standard formats. The involvement of domain experts ensures that the key disease hallmarks are covered and relevant, up-to-date knowledge is adequately represented. Expert-curated and computer readable, disease maps may serve as a compendium of knowledge, allow for data-supported hypothesis generation or serve as a scaffold for the generation of predictive mathematical models. This article summarizes the 2nd Disease Maps Community meeting, highlighting its important topics and outcomes. We outline milestones on the roadmap for the future development of disease maps, including creating and maintaining standardized disease maps; sharing parts of maps that encode common human disease mechanisms; providing technical solutions for complexity management of maps; and Web tools for in-depth exploration of such maps. A dedicated discussion was focused on mathematical modeling approaches, as one of the main goals of disease map development is the generation of mathematically interpretable representations to predict disease comorbidity or drug response and to suggest drug repositioning, altogether supporting clinical decisions.

Navigating the disease landscape: knowledge representations for contextualizing molecular signatures

Large amounts of data emerging from experiments in molecular medicine are leading to the identification of molecular signatures associated with disease subtypes. The contextualization of these patterns is important for obtaining mechanistic insight into the aberrant processes associated with a disease, and this typically involves the integration of multiple heterogeneous types of data. In this review, we discuss knowledge representations that can be useful to explore the biological context of molecular signatures, in particular three main approaches, namely, pathway mapping approaches, molecular network centric approaches and approaches that represent biological statements as knowledge graphs. We discuss the utility of each of these paradigms, illustrate how they can be leveraged with selected practical examples and identify ongoing challenges for this field of research.

A Curated Resource for Phosphosite-specific Signature Analysis

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.