Biomolecular Pathways Research Articles

Cardiac remodeling in aortic and mitral valve disease: a simulation study with clinical validation.

Remodeling is an important long-term determinant of cardiac function throughout the progression of heart disease. Numerous biomolecular pathways for mechanosensing and transduction are involved. However, we hypothesize that biomechanical factors alone can explain changes in myocardial volume and chamber size in valve disease. A validated model of the human vasculature and the four cardiac chambers was used to simulate aortic stenosis, mitral regurgitation, and aortic regurgitation. Remodeling was simulated with adaptive feedback preserving myocardial fiber stress and wall shear stress in all four cardiac chambers. Briefly, the model used myocardial fiber stress to determine wall thickness and cardiac chamber wall shear stress to determine chamber volume. Aortic stenosis resulted in the development of concentric left ventricular hypertrophy. Aortic and mitral regurgitation resulted in eccentric remodeling and eccentric hypertrophy, with more pronounced hypertrophy for aortic regurgitation. Comparisons with published clinical data showed the same direction and similar magnitudes of changes in end-diastolic volume index and left ventricular diameters. Changes in myocardial wall volume and wall thickness were within a realistic range in both stenotic and regurgitant valvular disease. Simulations of remodeling in left-sided valvular disease support, in both a qualitative and quantitative manner, that left ventricular chamber size and hypertrophy are primarily determined by preservation of wall shear stress and myocardial fiber stress. NEW & NOTEWORTHY Cardiovascular simulations with adaptive feedback that normalizes wall shear stress and fiber stress in the cardiac chambers could predict, in a quantitative and qualitative manner, remodeling patterns seen in patients with left-sided valvular disease. This highlights how mechanical stress remains a fundamental aspect of cardiac remodeling. This in silico study validated with clinical data paves the way for future patient-specific predictions of remodeling in valvular disease.

Reactome - Pathway Context and Visualisation for Omics Data

Reactome (https://reactome.org) is a free, open-source, open-data, curated and peer-reviewed knowledge base of biomolecular pathways, currently covering 2,106 Pathways; 10,712 protein coding genes; 11,302 reactions; 27,452 literature references and 1,800 small molecules. Pathways are arranged in a hierarchical structure, allowing the user to navigate from high level concepts like immune system to detailed pathway diagrams showing biomolecular events like membrane transport or phosphorylation. The Reactome curation strategy focuses on the annotation of “normal” pathways in human. However, we increasingly annotate disease-specific pathway modifications, grouped in three major classes: loss of function (typically metabolic disease phenotypes), gain of function (typically cancer phenotypes), and host-pathogen interactions. Here, we present new developments in the multi-scale Reactome visualization system that facilitate navigation through the pathway hierarchy and enable efficient reuse of Reactome visualizations for users' own research presentations and publications. For the higher levels of the hierarchy, Reactome now provides scalable, interactive textbook-style diagrams in SVG format, which are also freely downloadable and editable. Repeated diagram elements like ‘mitochondrion’ or ‘receptor’ are freely available as a library of graphic elements at https://reactome.org/icon-lib. Detailed lower-level diagrams are now downloadable in editable PPTX format as sets of interconnected objects, as well as in standard png format.

Reactome and ORCID-fine-grained credit attribution for community curation.

Reactome is a manually curated, open-source, open-data knowledge base of biomolecular pathways. Reactome has always provided clear credit attribution for authors, curators and reviewers through fine-grained annotation of all three roles at the reaction and pathway level. These data are visible in the web interface and provided through the various data download formats. To enhance visibility and credit attribution for the work of authors, curators and reviewers, and to provide additional opportunities for Reactome community engagement, we have implemented key changes to Reactome: contributor names are now fully searchable in the web interface, and contributors can ‘claim’ their contributions to their ORCID profile with a few clicks. In addition, we are reaching out to domain experts to request their help in reviewing and editing Reactome pathways through a new ‘Contribution’ section, highlighting pathways which are awaiting community review.Database URL: https://reactome.org

The STAT3/Slug Axis Enhances Radiation-Induced Tumor Invasion and Cancer Stem-like Properties in Radioresistant Glioblastoma.

Glioblastoma multiforme (GBM) requires radiotherapy (RT) as a part of definitive management strategy. RT is highly effective, destroying cancer cells that may exist around the surgical tumor bed. However, GBM still has a poor prognosis and a high local recurrence rate after RT. Accumulating research indicates that GBM contains cancer stem-like cells (CSCs), which are radioresistant and result in therapeutic failure. Additionally, GBM cells can aggressively invade normal brain tissue, inducing therapeutic failure. Using clinical observations, we evaluated the effect of radiation on tumor control. We also explored the biomolecular pathways that connect radioresistance and CSC- and epithelial-mesenchymal transition (EMT)-associated phenotypes in patient-derived GBM cells. Transwell and microarray assay demonstrated that radioresistant GBM cells (GBM-R2I2) exhibit increased invasion and self-renewal abilities compared with parental GBM cells. Finally, to identify potential mechanisms underlying these observations, we used a PCR array to search for molecular markers of cell motility. Signal transducer and activator of transcription 3 (STAT3) directly bound to the Slug promoter in a chromatin immunoprecipitation assay. Reduced STAT3 decreased Slug expression and suppressed cell invasion in GBM-R2I2 cells while increasing Slug reversed these effects. In addition, STAT3 knockdown significantly inhibited CSC properties, synergistically increased the radiotherapeutic effect, and effectively increased the survival rate in vivo. We deciphered a new pathway of GBM radioresistance, invasion, and recurrence via the STAT3/Slug axis that could be a new target of GBM therapy.

Differential growth and shape formation in plant organs

Morphogenesis is a phenomenon by which a wide variety of functional organs are formed in biological systems. In plants, morphogenesis is primarily driven by differential growth of tissues. Much effort has been devoted to identifying the role of genetic and biomolecular pathways in regulating cell division and cell expansion and in influencing shape formation in plant organs. However, general principles dictating how differential growth controls the formation of complex 3D shapes in plant leaves and flower petals remain largely unknown. Through quantitative measurements on live plant organs and detailed finite-element simulations, we show how the morphology of a growing leaf is determined by both the maximum value and the spatial distribution of growth strain. With this understanding, we develop a broad scientific framework for a morphological phase diagram that is capable of rationalizing four configurations commonly found in plant organs: twisting, helical twisting, saddle bending, and edge waving. We demonstrate the robustness of these findings and analyses by recourse to synthetic reproduction of all four configurations using controlled polymerization of a hydrogel. Our study points to potential approaches to innovative geometrical design and actuation in such applications as building architecture, soft robotics and flexible electronics.

Albumin nano-encapsulation of caffeic acid phenethyl ester and piceatannol potentiated its ability to modulate HIF and NF-kB pathways and improves therapeutic outcome in experimental colitis

Hypoxia inducible factor and nuclear factor-kappa beta pathways have been proposed as therapeutic targets for several inflammatory diseases. Caffeic acid phenethyl ester (CAPE) and piceatannol (PIC) are natural anti-inflammatory compounds; however, poor bioavailability and limited understanding of biomolecular mechanistic limits its clinical use. The aims of this study are to enhance bioavailability and investigate their impact on nuclear p65 and HIF-1α for the first time in experimental colitis.Dextran sulphate sodium was used to induce colitis in mice and effect of either free CAPE/PIC or CAPE/PIC loaded albumin nanoparticles treatment was observed on disease development and levels of cellular p65 and HIF-1α.Our results indicate that albumin nano-encapsulation of CAPE/PIC not only enhances its anti-inflammatory potential but also potentiates its ability to effectively modulate inflammation related biomolecular pathways. Hence, combining nanotechnology with natural compounds could result in development of new therapeutic options for IBD.

Keratosis Pilaris and its Subtypes: Associations, New Molecular and Pharmacologic Etiologies, and Therapeutic Options.

Keratosis pilaris is a common skin disorder comprising less common variants and rare subtypes, including keratosis pilaris rubra, erythromelanosis follicularis faciei et colli, and the spectrum of keratosis pilaris atrophicans. Data, and critical analysis of existing data, are lacking, so the etiologies, pathogeneses, disease associations, and treatments of these clinical entities are poorly understood. The present article aims to fill this knowledge gap by reviewing literature in the PubMed, EMBASE, and CINAHL databases and providing a comprehensive, analytical summary of the clinical characteristics and pathophysiology of keratosis pilaris and its subtypes through the lens of disease associations, genetics, and pharmacologic etiologies. Histopathologic, genomic, and epidemiologic evidence points to keratosis pilaris as a primary disorder of the pilosebaceous unit as a result of inherited mutations or acquired disruptions in various biomolecular pathways. Recent data highlight aberrant Ras signaling as an important contributor to the pathophysiology of keratosis pilaris and its subtypes. We also evaluate data on treatments for keratosis pilaris and its subtypes, including topical, systemic, and energy-based therapies. The effectiveness of various types of lasers in treating keratosis pilaris and its subtypes deserves wider recognition.

Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling

Non-synonymous mutations linked to the complex diseases often have a global impact on a biological system, affecting large biomolecular networks and pathways. However, the magnitude of the mutation-driven effects on the macromolecular network is yet to be fully explored. In this work, we present a systematic multi-level characterization of human mutations associated with genetic disorders by determining their individual and combined interaction-rewiring, “edgetic,” effects on the human interactome. Our in silico analysis highlights the intrinsic differences and important similarities between the pathogenic single-nucleotide variants (SNVs) and frameshift mutations. We show that pathogenic SNVs are more likely to cause gene pleiotropy than pathogenic frameshift mutations and are enriched on the protein interaction interfaces. Functional profiling of SNVs indicates widespread disruption of the protein–protein interactions and synergistic effects of SNVs. The coverage of our approach is several times greater than the recently published experimental study and has the minimal overlap with it, while the distributions of determined edgotypes between the two sets of profiled mutations are remarkably similar. Case studies reveal the central role of interaction-disrupting mutations in type 2 diabetes mellitus and suggest the importance of studying mutations that abnormally strengthen the protein interactions in cancer. With the advancement of next-generation sequencing technology that drives precision medicine, there is an increasing demand in understanding the changes in molecular mechanisms caused by the patient-specific genetic variation. The current and future in silico edgotyping tools present a cheap and fast solution to deal with the rapidly growing data sets of discovered mutations.

Probiotic DSF counteracts chemotherapy induced neuropathic pain.

Problem statement: Chemotherapy-induced peripheral neuropathy (CIPN) is a widespread and potentially disabling side effect of various anticancer drugs. In spite of the intensive research focused on obtaining therapies capable to treat or prevent CIPN, the medical demand remains very high. Microtubule-stabilizing agents, among which taxanes, are effective chemotherapeutic agents for the therapy of several oncologic diseases. The inflammatory process activated by chemotherapeutic agents has been interpreted as a potential trigger of the nociceptive process in CIPN. The chemotherapy-driven release of proinflammatory and chemokines has been recognized as one of the principal mechanisms controlling the establishment of CIPN. Several reports have indicated that probiotics are capable to regulate the balance of anti-inflammatory and pro-inflammatory cytokines. Accordingly, it has been suggested that some probiotic formulations, may have an effective role in the management of inflammatory pain symptoms. Experimental approaches used: we tested the hypothesis that paclitaxel-induced neuropathic pain can be counteracted by the probiotic DSF by using an in vitro model of sensitive neuron, the F11 cells. On this model, the biomolecular pathways involved in chemotherapy induced peripheral neuropathy depending on inflammatory cytokines were investigated by Real-time PCR, Western blotting and confocal microscopy. General conclusions: the results obtained, i.e. the increase of acetylated tubulin, the increase of the active forms of proteins involved in the establishment of neuropathic pain, point towards the use of this probiotic formulation as a possible adjuvant agent for counteracting CINP symptoms.

Computational Methods for Estimating Molecular System from Membrane Potential Recordings in Nerve Growth Cone

Biological cells express intracellular biomolecular information to the extracellular environment as various physical responses. We show a novel computational approach to estimate intracellular biomolecular pathways from growth cone electrophysiological responses. Previously, it was shown that cGMP signaling regulates membrane potential (MP) shifts that control the growth cone turning direction during neuronal development. We present here an integrated deterministic mathematical model and Bayesian reversed-engineering framework that enables estimation of the molecular signaling pathway from electrical recordings and considers both the system uncertainty and cell-to-cell variability. Our computational method selects the most plausible molecular pathway from multiple candidates while satisfying model simplicity and considering all possible parameter ranges. The model quantitatively reproduces MP shifts depending on cGMP levels and MP variability potential in different experimental conditions. Lastly, our model predicts that chloride channel inhibition by cGMP-dependent protein kinase (PKG) is essential in the core system for regulation of the MP shifts.

Organellar transcriptome sequencing reveals mitochondrial localization of nuclear encoded transcripts

Mitochondria are organelles involved in a variety of biological functions in the cell, apart from their principal role in generation of ATP, the cellular currency of energy. The mitochondria, in spite of being compact organelles, are capable of performing complex biological functions largely because of the ability to exchange proteins, RNA, chemical metabolites and other biomolecules between cellular compartments. A close network of biomolecular interactions are known to modulate the crosstalk between the mitochondria and the nuclear genome. Apart from the small repertoire of genes encoded by the mitochondrial genome, it is now known that the functionality of the organelle is highly reliant on a number of proteins encoded by the nuclear genome, which localize to the mitochondria. With exceptions to a few anecdotal examples, the transcripts that have the potential to localize to the mitochondria have been poorly studied. We used a deep sequencing approach to identify transcripts encoded by the nuclear genome which localize to the mitoplast in a zebrafish model. We prioritized 292 candidate transcripts of nuclear origin that are potentially localized to the mitochondrial matrix. We experimentally demonstrated that the transcript encoding the nuclear encoded ribosomal protein 11 (Rpl11) localizes to the mitochondria. This study represents a comprehensive analysis of the mitochondrial localization of nuclear encoded transcripts. Our analysis has provided insights into a new layer of biomolecular pathways modulating mitochondrial-nuclear cross-talk. This provides a starting point towards understanding the role of nuclear encoded transcripts that localize to mitochondria and their influence on mitochondrial function.

Metabolomics profiling reveals differential adaptation of major energy metabolism pathways associated with autophagy upon oxygen and glucose reduction

The ability of cells to rearrange their metabolism plays an important role in compensating the energy shortage and may provide cell survival. Our study focuses on identifing the important adaptational changes under the conditions of oxygen and glucose reduction. Employing mass spectrometry-based metabolomics in combination with biochemistry and microscopy techniques we identified metabolites, proteins and biomolecular pathways alterations in primary human IMR90 fibroblasts upon energy deficits. Multivariate statistical analyses revealed significant treatment-specific metabolite level and ratio alterations as well as major energy metabolism pathways like ‘glycolysis’, ‘pentose phosphate pathway’, ‘mitochondrial electron transport chain’ and ‘protein biosynthesis (amino acids)’ indicating an activation of catabolism and reduction of anabolism as important mechanisms of adaptation towards a bioenergetic demand. A treatment-specific induction of the autophagic and mitophagic degradation activity upon oxygen reduction, glucose reduction as well as oxygen-glucose reduction further supports our results. Therefore, we suggest that the observed alterations represent an adaptive response in order to compensate for the cells’ bioenergetics needs that ultimately provide cell survival.

Reactome graph database: Efficient access to complex pathway data.

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

Reactome diagram viewer: data structures and strategies to boost performance.

MotivationReactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community.ResultsThe pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partitioning data structure minimizes CPU workload, enabling the introduction of new features that further enhance user experience. Through the use of highly optimized data structures and algorithms, Reactome has boosted the performance and usability of the new pathway diagram viewer, providing a robust, scalable and easy-to-integrate solution to pathway visualization. As graph-based visualization of complex data is a frequent challenge in bioinformatics, many of the individual strategies presented here are applicable to a wide range of web-based bioinformatics resources.Availability and implementationReactome is available online at: https://reactome.org. The diagram viewer is part of the Reactome pathway browser (https://reactome.org/PathwayBrowser/) and also available as a stand-alone widget at: https://reactome.org/dev/diagram/. The source code is freely available at: https://github.com/reactome-pwp/diagram.Supplementary information Supplementary data are available at Bioinformatics online.

Metabolite fingerprinting reveals new serum metabolites and associated pathways in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is associated with an increased risk for adverse physical health outcomes. However, the underlying bio-molecular processes and associated pathways remain poorly elucidated. Using time-of-flight mass spectrometry (TOF-MS), the untargeted and holistic investigation of the metabolome – the total of hydrophilic and amphiphilic metabolites - holds the potential to provide novel insights into PTSD pathophysiology. To address metabolome changes associated with PTSD, serum from 20 individuals with a PTSD diagnosis and 18 healthy controls was analyzed with TOF-MS. Symptom severity of PTSD was assessed using the Clinician-administered PTSD scale (CAPS). Univariate and multivariate approaches, namely Partial Least Square Discriminant Analysis, were applied for statistical analyses. The group comparison revealed 13 metabolites significantly altered in PTSD, including four glycerophospholipids and one metabolite involved in endocannabinoid signaling. Out of the 13, eleven metabolites showed a correlation between the serum level and the CAPS score. In the multivariate approach, a metabolite profile of 19 biomolecules predicted PTSD with an accuracy of 85%. Here, we initially illustrate the potential of metabolite fingerprinting to identify novel pathophysiological underpinnings of PTSD. It further provides the possibility to highlight associated pathways, such as lipid-derived and endocannabinoid signaling. More research will help to gain not only a deeper understanding of the molecular mechanisms and associated pathways in PTSD, but also of the biological processes stimulated by (psycho) therapeutical treatment.

The Two-State Prehensile Tail of the Antibacterial Toxin Colicin N

Intrinsically disordered regions within proteins are critical elements in many biomolecular interactions and signaling pathways. Antibacterial toxins of the colicin family, which could provide new antibiotic functions against resistant bacteria, contain disordered N-terminal translocation domains (T-domains) that are essential for receptor binding and the penetration of the Escherichia coli outer membrane. Here we investigate the conformational behavior of the T-domain of colicin N (ColN-T) to understand why such domains are widespread in toxins that target Gram-negative bacteria. Like some other intrinsically disordered proteins in the solution state of the protein, ColN-T shows dual recognition, initially interacting with other domains of the same colicin N molecule and later, during cell killing, binding to two different receptors, OmpF and TolA, in the target bacterium. ColN-T is invisible in the high-resolution x-ray model and yet accounts for 90 of the toxin’s 387 amino acid residues. To reveal its solution structure that underlies such a dynamic and complex system, we carried out mutagenic, biochemical, hydrodynamic and structural studies using analytical ultracentrifugation, NMR, and small-angle x-ray scattering on full-length ColN and its fragments. The structure was accurately modeled from small-angle x-ray scattering data by treating ColN as a flexible system, namely by the ensemble optimization method, which enables a distribution of conformations to be included in the final model. The results reveal, to our knowledge, for the first time the dynamic structure of a colicin T-domain. ColN-T is in dynamic equilibrium between a compact form, showing specific self-recognition and resistance to proteolysis, and an extended form, which most likely allows for effective receptor binding.

Reactome enhanced pathway visualization.

MotivationReactome is a free, open-source, open-data, curated and peer-reviewed knowledge base of biomolecular pathways. Pathways are arranged in a hierarchical structure that largely corresponds to the GO biological process hierarchy, allowing the user to navigate from high level concepts like immune system to detailed pathway diagrams showing biomolecular events like membrane transport or phosphorylation. Here, we present new developments in the Reactome visualization system that facilitate navigation through the pathway hierarchy and enable efficient reuse of Reactome visualizations for users’ own research presentations and publications.ResultsFor the higher levels of the hierarchy, Reactome now provides scalable, interactive textbook-style diagrams in SVG format, which are also freely downloadable and editable. Repeated diagram elements like ‘mitochondrion’ or ‘receptor’ are available as a library of graphic elements. Detailed lower-level diagrams are now downloadable in editable PPTX format as sets of interconnected objects.Availability and implementation http://reactome.org

Mechanism of Off-Target Interactions and Toxicity of Tamoxifen and Its Metabolites.

Tamoxifen is an estrogen modulator that acts to competitively inhibit the binding of endogenous estrogens. It is widely used for treatment of breast cancer; however, analogous with many antineoplastic agents, tamoxifen is associated with numerous adverse effects, most prominently nausea. We have identified several off-target receptors of tamoxifen and 22 of its metabolites that include histamine H1 and H3, and muscarinic M1, M4, and M5 subtypes, and dopamine D2 receptor. We have shown how they are associated with tamoxifen and its metabolites' toxicity through a comprehensive computational analysis of their interaction modes, which were also compared to that of the related endogenous substrates of each receptor. The results were further evaluated using available in vivo and in vitro data. The presented work provides foundational knowledge toward the determination of the precise mechanism of nausea induction, and in particular, interactions of tamoxifen and its metabolites with the receptors involved in that biomolecular pathway. This study can assist in predicting the potential undesired effects of the chemicals with common pharmacophores or similar fragments to that of tamoxifen and its metabolites and serve drug discovery research in developing more effective and tolerable tamoxifen analogues or chemotherapeutic agents.

Chemotherapy for Hepatocellular Carcinoma: Current Evidence and Future Perspectives.

Hepatocarcinogenesis is a multistep process, heralded by abnormalities in cell differentiation and proliferation and sustained by an aberrant neoangiogenesis. Understanding the underlying molecular pathogenesis leading to hepatocellular carcinoma is a prerequisite to develop new drugs that will hamper or block the steps of these pathways. As hepatocellular carcinoma has higher arterial vascularization than normal liver, this could be a good target for novel molecular therapies. Introduction of the antiangiogenic drug sorafenib into clinical practice since 2008 has led to new perspectives in the management of this tumor. The importance of this drug lies not only in the modest gain of patients’ survival, but in having opened a roadmap towards the development of new molecules and targets. Unfortunately, after the introduction of sorafenib, during the last years, a wide number of clinical trials on antiangiogenic therapies failed in achieving significant results. However, many of these trials are still ongoing and promise to improve overall survival and progression-free survival. A recent clinical trial has proven regorafenib effective in patients showing tumor progression under sorafenib, thus opening new interesting therapeutic perspectives. Many other expectations have been borne from the discovery of the immune checkpoint blockade, already known in other solid malignancies. Furthermore, a potential role in hepatocellular carcinoma therapy may derive from the use of branched-chain amino acids and of nutritional support. This review analyses the biomolecular pathways of hepatocellular carcinoma and the ongoing studies, the actual evidence and the future perspectives concerning drug therapy in this open field.

Energy-based analysis of biomolecular pathways.

Decomposition of biomolecular reaction networks into pathways is a powerful approach to the analysis of metabolic and signalling networks. Current approaches based on analysis of the stoichiometric matrix reveal information about steady-state mass flows (reaction rates) through the network. In this work, we show how pathway analysis of biomolecular networks can be extended using an energy-based approach to provide information about energy flows through the network. This energy-based approach is developed using the engineering-inspired bond graph methodology to represent biomolecular reaction networks. The approach is introduced using glycolysis as an exemplar; and is then applied to analyse the efficiency of free energy transduction in a biomolecular cycle model of a transporter protein [sodium-glucose transport protein 1 (SGLT1)]. The overall aim of our work is to present a framework for modelling and analysis of biomolecular reactions and processes which considers energy flows and losses as well as mass transport.