RESUMEN
Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key interactions or processes. Hence, we have developed SignaLink3 (http://signalink.org/), a value-added knowledge-base that provides manually curated data on signaling pathways and integrated data from several types of databases (interaction, regulation, localisation, disease, etc.) for humans, and three major animal model organisms. SignaLink3 contains over 400 000 newly added human protein-protein interactions resulting in a total of 700 000 interactions for Homo sapiens, making it one of the largest integrated signaling network resources. Next to H. sapiens, SignaLink3 is the only current signaling network resource to provide regulatory information for the model species Caenorhabditis elegans and Danio rerio, and the largest resource for Drosophila melanogaster. Compared to previous versions, we have integrated gene expression data as well as subcellular localization of the interactors, therefore uniquely allowing tissue-, or compartment-specific pathway interaction analysis to create more accurate models. Data is freely available for download in widely used formats, including CSV, PSI-MI TAB or SQL.
Asunto(s)
Bases de Datos Genéticas , Redes Reguladoras de Genes/genética , Mapas de Interacción de Proteínas/genética , Transducción de Señal/genética , Animales , Caenorhabditis elegans/genética , Drosophila melanogaster/genética , Humanos , Pez Cebra/genéticaRESUMEN
Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.
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COVID-19/metabolismo , Colitis Ulcerosa/metabolismo , Biología Computacional/métodos , Proteínas/metabolismo , Transducción de Señal , Animales , Comunicación Celular , Colitis Ulcerosa/patología , Bases de Datos Factuales , Enzimas/metabolismo , Humanos , Ratones , Procesamiento Proteico-Postraduccional , Proteínas/genética , Ratas , Análisis de la Célula Individual , Programas Informáticos , Flujo de TrabajoRESUMEN
The SARS-CoV-2 pandemic of 2020 has mobilised scientists around the globe to research all aspects of the coronavirus virus and its infection. For fruitful and rapid investigation of viral pathomechanisms, a collaborative and interdisciplinary approach is required. Therefore, we have developed ViralLink: a systems biology workflow which reconstructs and analyses networks representing the effect of viruses on intracellular signalling. These networks trace the flow of signal from intracellular viral proteins through their human binding proteins and downstream signalling pathways, ending with transcription factors regulating genes differentially expressed upon viral exposure. In this way, the workflow provides a mechanistic insight from previously identified knowledge of virally infected cells. By default, the workflow is set up to analyse the intracellular effects of SARS-CoV-2, requiring only transcriptomics counts data as input from the user: thus, encouraging and enabling rapid multidisciplinary research. However, the wide-ranging applicability and modularity of the workflow facilitates customisation of viral context, a priori interactions and analysis methods. Through a case study of SARS-CoV-2 infected bronchial/tracheal epithelial cells, we evidence the functionality of the workflow and its ability to identify key pathways and proteins in the cellular response to infection. The application of ViralLink to different viral infections in a context specific manner using different available transcriptomics datasets will uncover key mechanisms in viral pathogenesis.
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COVID-19/metabolismo , Biología Computacional/métodos , Regulación Viral de la Expresión Génica , SARS-CoV-2/patogenicidad , Transducción de Señal , Algoritmos , Bronquios/virología , Análisis por Conglomerados , Perfilación de la Expresión Génica , Interacciones Huésped-Patógeno , Humanos , Investigación Interdisciplinaria , Pulmón/virología , Modelos Estadísticos , Biología de Sistemas , Transcriptoma , Flujo de TrabajoRESUMEN
Triple negative breast cancer (TNBC) is currently associated with a lack of treatment options. Arsenic derivatives have shown antitumoral activity both in vitro and in vivo; however, their mode of action is not completely understood. In this work we evaluate the response to arsenate of the double positive MCF-7 breast cancer cell line as well as of two different TNBC cell lines, Hs578T and MDA-MB-231. Multimodal experiments were conducted to this end, using functional assays and microarrays. Arsenate was found to induce cytoskeletal alteration, autophagy and apoptosis in TNBC cells, and moderate effects in MCF-7 cells. Gene expression analysis showed that the TNBC cell lines' response to arsenate was more prominent in the G2M checkpoint, autophagy and apoptosis compared to the Human Mammary Epithelial Cells (HMEC) and MCF-7 cell lines. We confirmed the downregulation of anti-apoptotic genes (MCL1, BCL2, TGFß1 and CCND1) by qRT-PCR, and on the protein level, for TGFß2, by ELISA. Insight into the mode of action of arsenate in TNBC cell lines it is provided, and we concluded that TNBC and non-TNBC cell lines reacted differently to arsenate treatment in this particular experimental setup. We suggest the future research of arsenate as a treatment strategy against TNBC.
Asunto(s)
Neoplasias de la Mama Triple Negativas , Apoptosis , Arseniatos , Línea Celular Tumoral , Proliferación Celular , Humanos , Células MCF-7 , Neoplasias de la Mama Triple Negativas/genética , Neoplasias de la Mama Triple Negativas/metabolismoRESUMEN
Current in vitro models for hepatotoxicity commonly suffer from low detection rates due to incomplete coverage of bioactivity space. Additionally, in vivo exposure measures such as Cmax are used for hepatotoxicity screening and are unavailable early on. Here we propose a novel rule-based framework to extract interpretable and biologically meaningful multiconditional associations to prioritize in vitro end points for hepatotoxicity and understand the associated physicochemical conditions. The data used in this study were derived for 673 compounds from 361 ToxCast bioactivity measurements and 29 calculated physicochemical properties against two lowest effective levels (LEL) of rodent hepatotoxicity from ToxRefDB, namely 15 mg/kg/day and 500 mg/kg/day. To achieve 80% coverage of toxic compounds, 35 rules with accuracies ranging from 96% to 73% using 39 unique ToxCast assays are needed at a threshold level of 500 mg/kg/day, whereas to describe the same coverage at a threshold of 15 mg/kg/day, 20 rules with accuracies of between 98% and 81% were needed, comprising 24 unique assays. Despite the 33-fold difference in dose levels, we found relative consistency in the key mechanistic groups in rule clusters, namely (i) activities against Cytochrome P, (ii) immunological responses, and (iii) nuclear receptor activities. Less specific effects, such as oxidative stress and cell cycle arrest, were used more by rules to describe toxicity at the level of 500 mg/kg/day. Although the endocrine disruption through nuclear receptor activity formulated an essential cluster of rules, this bioactivity was not covered in four commercial assay setups for hepatotoxicity. Using an external set of 29 drugs with drug-induced liver injury (DILI) labels, we found that promiscuity over important assays discriminates between compounds with different levels of liver injury. In vitro-in vivo associations were also improved by incorporating physicochemical properties especially for the potent, 15 mg/kg/day toxicity level as well for assays describing nuclear receptor activity and phenotypic changes. The most frequently used physicochemical properties, predictive for hepatotoxicity in combination with assay activities, are linked to bioavailability, which were the number of rotatable bonds (less than 7) at a of level of 15 mg/kg/day and the number of rings (of less than 3) at level of 500 mg/kg/day. In summary, hepatotoxicity cannot very well be captured by single assay end points, but better by a combination of bioactivities in relevant assays, with the likelihood of hepatotoxicity increasing with assay promiscuity. Together, these findings can be used to prioritize assay combinations that are appropriate to assess potential hepatotoxicity.
Asunto(s)
Enfermedad Hepática Inducida por Sustancias y Drogas , Evaluación Preclínica de Medicamentos/métodos , Animales , Bioensayo , Ensayos Analíticos de Alto Rendimiento , Humanos , Hígado , Pruebas de ToxicidadRESUMEN
Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of plasticity at late stages of tumor development. The fluctuating intensity of stress factors, like hypoxia, inflammation and the either cooperative or hostile interactions of tumor inter-cellular networks, all increase the adaptation potential of cancer cells. This may lead to the bypass of cellular senescence, and to the development of cancer stem cells. We propose that the central tenet of cancer stem cell definition lies exactly in the indefinability of cancer stem cells. Actual properties of cancer stem cells depend on the individual "stress-history" of the given tumor. Cancer stem cells are characterized by an extremely large evolvability (i.e. a capacity to generate heritable phenotypic variation), which corresponds well with the defining hallmarks of cancer stem cells: the possession of the capacity to self-renew and to repeatedly re-build the heterogeneous lineages of cancer cells that comprise a tumor in new environments. Cancer stem cells represent a cell population, which is adapted to adapt. We argue that the high evolvability of cancer stem cells is helped by their repeated transitions between plastic (proliferative, symmetrically dividing) and rigid (quiescent, asymmetrically dividing, often more invasive) phenotypes having plastic and rigid networks. Thus, cancer stem cells reverse and replay cancer development multiple times. We describe network models potentially explaining cancer stem cell-like behavior. Finally, we propose novel strategies including combination therapies and multi-target drugs to overcome the Nietzschean dilemma of cancer stem cell targeting: "what does not kill me makes me stronger".
Asunto(s)
Hipoxia de la Célula/fisiología , Transformación Celular Neoplásica/patología , Senescencia Celular/fisiología , Inflamación/patología , Células Madre Neoplásicas/patología , HumanosRESUMEN
There is a widening recognition that cancer cells are products of complex developmental processes. Carcinogenesis and metastasis formation are increasingly described as systems-level, network phenomena. Here we propose that malignant transformation is a two-phase process, where an initial increase of system plasticity is followed by a decrease of plasticity at late stages of carcinogenesis as a model of cellular learning. We describe the hallmarks of increased system plasticity of early, tumor initiating cells, such as increased noise, entropy, conformational and phenotypic plasticity, physical deformability, cell heterogeneity and network rearrangements. Finally, we argue that the large structural changes of molecular networks during cancer development necessitate a rather different targeting strategy in early and late phase of carcinogenesis. Plastic networks of early phase cancer development need a central hit, while rigid networks of late stage primary tumors or established metastases should be attacked by the network influence strategy, such as by edgetic, multi-target, or allo-network drugs. Cancer stem cells need special diagnosis and targeting, since their dormant and rapidly proliferating forms may have more rigid, or more plastic networks, respectively. The extremely high ability of cancer stem cells to change the rigidity/plasticity of their networks may be their key hallmark. The application of early stage-optimized anti-cancer drugs to late-stage patients may be a reason of many failures in anti-cancer therapies. Our hypotheses presented here underlie the need for patient-specific multi-target therapies applying the correct ratio of central hits and network influences - in an optimized sequence.
Asunto(s)
Transformación Celular Neoplásica/metabolismo , Neoplasias/metabolismo , Células Madre Neoplásicas/metabolismo , Transducción de Señal , Antineoplásicos/uso terapéutico , Transformación Celular Neoplásica/efectos de los fármacos , Transformación Celular Neoplásica/patología , Humanos , Redes y Vías Metabólicas/efectos de los fármacos , Modelos Biológicos , Neoplasias/tratamiento farmacológico , Neoplasias/patología , Células Madre Neoplásicas/efectos de los fármacos , Células Madre Neoplásicas/patologíaRESUMEN
Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last eight years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, expansion, termination, etc.); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user's needs. The resource is available in various file formats (e.g. CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org.Abbreviations: ARN: Autophagy Regulatory Network; ATG: autophagy related; BCR: B cell receptor pathway; BECN1: beclin 1; GABARAP: GABA type A receptor-associated protein; IIP: innate immune pathway; LIR: LC3-interacting region; lncRNA: long non-coding RNA; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; miRNA: microRNA; NHR: nuclear hormone receptor; PTM: post-translational modification; RTK: receptor tyrosine kinase; TCR: T cell receptor; TLR: toll like receptor.
Asunto(s)
Autofagia , MicroARNs , Autofagia/fisiología , Proteómica , Beclina-1 , Mitofagia , Transducción de Señal/genéticaRESUMEN
Patients with inflammatory bowel disease (IBD) are known to have perturbations in microRNA (miRNA) levels as well as altered miRNA regulation. Although experimental methods have provided initial insights into the functional consequences that may arise due to these changes, researchers are increasingly utilising novel bioinformatics approaches to further dissect the role of miRNAs in IBD. The recent exponential increase in transcriptomics datasets provides an excellent opportunity to further explore the role of miRNAs in IBD pathogenesis. To effectively understand miRNA-target gene interactions from gene expression data, multiple database resources are required, which have become available in recent years. In this technical note, we provide a step-by-step protocol for utilising these state-of-the-art resources, as well as systems biology approaches to understand the role of miRNAs in complex disease pathogenesis. We demonstrate through a case study example how to combine the resulting miRNA-target gene networks with transcriptomics data to find potential disease-specific miRNA regulators and miRNA-target genes in Crohn's disease. This approach could help to identify miRNAs that may have important disease-modifying effects in IBD and other complex disorders, and facilitate the discovery of novel therapeutic targets.
Asunto(s)
Enfermedad de Crohn , Enfermedades Inflamatorias del Intestino , MicroARNs , Enfermedad de Crohn/genética , Redes Reguladoras de Genes , Humanos , Enfermedades Inflamatorias del Intestino/genética , MicroARNs/metabolismo , Transcriptoma/genéticaRESUMEN
Inflammatory bowel disease (IBD) is a chronic immune-mediated inflammatory disorder of the gastrointestinal tract that arises due to complex interactions between host genetic risk factors, environmental factors, and a dysbiotic gut microbiota. Although metagenomic approaches have attempted to characterise the dysbiosis occurring in IBD, the precise mechanistic pathways interlinking the gut microbiota and the intestinal mucosa are still yet to be unravelled. To deconvolute these complex interactions, a more reductionist approach involving microbial metabolites has been suggested. Bile acids have emerged as a key class of microbiota-associated metabolites that are perturbed in IBD patients. In recent years, metabolomics studies have revealed a consistent defect in bile acid metabolism with an increase in primary bile acids and a reduction in secondary bile acids in IBD patients. This review explores the evolving evidence that specific bile acid metabolites interact with intestinal epithelial and immune cells to contribute to the inflammatory milieu seen in IBD. Furthermore, we summarise evidence linking bile acids with intracellular pathways that are known to be relevant in IBD including autophagy, apoptosis, and the inflammasome pathway. Finally, we discuss how novel experimental and bioinformatics approaches could further advance our understanding of the role of bile acids and inform novel therapeutic strategies in IBD.
Asunto(s)
Ácidos y Sales Biliares/fisiología , Microbioma Gastrointestinal/fisiología , Enfermedades Inflamatorias del Intestino/etiología , Animales , Ácidos y Sales Biliares/metabolismo , Disbiosis/patología , Humanos , Mucosa Intestinal/patologíaRESUMEN
The gastrointestinal (GI) tract harbours a complex microbial community, which contributes to its homeostasis. A disrupted microbiome can cause GI-related diseases, including inflammatory bowel disease (IBD), therefore identifying host-microbe interactions is crucial for better understanding gut health. Bacterial extracellular vesicles (BEVs), released into the gut lumen, can cross the mucus layer and access underlying immune cells. To study BEV-host interactions, we examined the influence of BEVs generated by the gut commensal bacterium, Bacteroides thetaiotaomicron, on host immune cells. Single-cell RNA sequencing data and host-microbe protein-protein interaction networks were used to predict the effect of BEVs on dendritic cells, macrophages and monocytes focusing on the Toll-like receptor (TLR) pathway. We identified biological processes affected in each immune cell type and cell-type specific processes including myeloid cell differentiation. TLR pathway analysis highlighted that BEV targets differ among cells and between the same cells in healthy versus disease (ulcerative colitis) conditions. The in silico findings were validated in BEV-monocyte co-cultures demonstrating the requirement for TLR4 and Toll-interleukin-1 receptor domain-containing adaptor protein (TIRAP) in BEV-elicited NF-kB activation. This study demonstrates that both cell-type and health status influence BEV-host communication. The results and the pipeline could facilitate BEV-based therapies for the treatment of IBD.
Asunto(s)
Bacteroides thetaiotaomicron/metabolismo , Vesículas Extracelulares/metabolismo , Microbioma Gastrointestinal/inmunología , Enfermedades Inflamatorias del Intestino/inmunología , Células Dendríticas/inmunología , Células Dendríticas/metabolismo , Interacciones Microbiota-Huesped , Humanos , Enfermedades Inflamatorias del Intestino/microbiología , Macrófagos/inmunología , Macrófagos/metabolismo , Glicoproteínas de Membrana/antagonistas & inhibidores , Monocitos/inmunología , Monocitos/metabolismo , Mapas de Interacción de Proteínas , Receptores de Interleucina-1/antagonistas & inhibidores , Transducción de Señal , Receptor Toll-Like 4/antagonistas & inhibidores , Receptores Toll-Like/metabolismoRESUMEN
Increasing evidence points towards the key role of the epithelium in the systemic and over-activated immune response to viral infection, including SARS-CoV-2 infection. Yet, how viral infection alters epithelial-immune cell interactions regulating inflammatory responses, is not well known. Available experimental approaches are insufficient to properly analyse this complex system, and computational predictions and targeted data integration are needed as an alternative approach. In this work, we propose an integrated computational biology framework that models how infection alters intracellular signalling of epithelial cells and how this change impacts the systemic immune response through modified interactions between epithelial cells and local immune cell populations. As a proof-of-concept, we focused on the role of intestinal and upper-airway epithelial infection. To characterise the modified epithelial-immune interactome, we integrated intra- and intercellular networks with single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids as well as from infected airway ciliated epithelial cells. This integrated methodology has proven useful to point out specific epithelial-immune interactions driving inflammation during disease response, and propose relevant molecular targets to guide focused experimental analysis.
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COVID-19 , Virosis , Células Epiteliales , Humanos , SARS-CoV-2 , Transducción de SeñalRESUMEN
We describe a precision medicine workflow, the integrated single nucleotide polymorphism network platform (iSNP), designed to determine the mechanisms by which SNPs affect cellular regulatory networks, and how SNP co-occurrences contribute to disease pathogenesis in ulcerative colitis (UC). Using SNP profiles of 378 UC patients we map the regulatory effects of the SNPs to a human signalling network containing protein-protein, miRNA-mRNA and transcription factor binding interactions. With unsupervised clustering algorithms we group these patient-specific networks into four distinct clusters driven by PRKCB, HLA, SNAI1/CEBPB/PTPN1 and VEGFA/XPO5/POLH hubs. The pathway analysis identifies calcium homeostasis, wound healing and cell motility as key processes in UC pathogenesis. Using transcriptomic data from an independent patient cohort, with three complementary validation approaches focusing on the SNP-affected genes, the patient specific modules and affected functions, we confirm the regulatory impact of non-coding SNPs. iSNP identified regulatory effects for disease-associated non-coding SNPs, and by predicting the patient-specific pathogenic processes, we propose a systems-level way to stratify patients.
Asunto(s)
Colitis Ulcerosa , MicroARNs , Algoritmos , Colitis Ulcerosa/genética , Genómica , Humanos , Carioferinas/genética , Polimorfismo de Nucleótido SimpleRESUMEN
Inflammatory bowel disease (IBD) is a chronic immune-mediated condition arising due to complex interactions between multiple genetic and environmental factors. Despite recent advances, the pathogenesis of the condition is not fully understood and patients still experience suboptimal clinical outcomes. Over the past few years, investigators are increasingly capturing multi-omics data from patient cohorts to better characterise the disease. However, reaching clinically translatable endpoints from these complex multi-omics datasets is an arduous task. Network biology, a branch of systems biology that utilises mathematical graph theory to represent, integrate and analyse biological data through networks, will be key to addressing this challenge. In this narrative review, we provide an overview of various types of network biology approaches that have been utilised in IBD including protein-protein interaction networks, metabolic networks, gene regulatory networks and gene co-expression networks. We also include examples of multi-layered networks that have combined various network types to gain deeper insights into IBD pathogenesis. Finally, we discuss the need to incorporate other data sources including metabolomic, histopathological, and high-quality clinical meta-data. Together with more robust network data integration and analysis frameworks, such efforts have the potential to realise the key goal of precision medicine in IBD.
RESUMEN
Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine-cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from the literature and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated the literature information on cell-cytokine interactions from two systems of immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink, we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify cell types and cytokine interactions following SARS-CoV-2 infection, highlighting important cytokine interactions that might contribute to severe illness in a subgroup of patients. Such findings have the potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository.
Asunto(s)
COVID-19/inmunología , Citocinas/metabolismo , Inmunidad , Enfermedades Inflamatorias del Intestino/inmunología , Comunicación Celular , Colitis Ulcerosa/inmunología , Colitis Ulcerosa/patología , Bases de Datos Genéticas , Humanos , Enfermedades Inflamatorias del Intestino/patología , Transducción de SeñalRESUMEN
Hyper-induction of pro-inflammatory cytokines, also known as a cytokine storm or cytokine release syndrome (CRS), is one of the key aspects of the currently ongoing SARS-CoV-2 pandemic. This process occurs when a large number of innate and adaptive immune cells activate and start producing pro-inflammatory cytokines, establishing an exacerbated feedback loop of inflammation. It is one of the factors contributing to the mortality observed with coronavirus 2019 (COVID-19) for a subgroup of patients. CRS is not unique to the SARS-CoV-2 infection; it was prevalent in most of the major human coronavirus and influenza A subtype outbreaks of the past two decades (H5N1, SARS-CoV, MERS-CoV, and H7N9). With a comprehensive literature search, we collected changing the cytokine levels from patients upon infection with the viral pathogens mentioned above. We analyzed published patient data to highlight the conserved and unique cytokine responses caused by these viruses. Our curation indicates that the cytokine response induced by SARS-CoV-2 is different compared to other CRS-causing respiratory viruses, as SARS-CoV-2 does not always induce specific cytokines like other coronaviruses or influenza do, such as IL-2, IL-10, IL-4, or IL-5. Comparing the collated cytokine responses caused by the analyzed viruses highlights a SARS-CoV-2-specific dysregulation of the type-I interferon (IFN) response and its downstream cytokine signatures. The map of responses gathered in this study could help specialists identify interventions that alleviate CRS in different diseases and evaluate whether they could be used in the COVID-19 cases.
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COVID-19/inmunología , Síndrome de Liberación de Citoquinas/inmunología , Virus de la Influenza A/inmunología , Gripe Humana/inmunología , Coronavirus del Síndrome Respiratorio de Oriente Medio/inmunología , SARS-CoV-2/inmunología , Síndrome Respiratorio Agudo Grave/inmunología , Coronavirus Relacionado al Síndrome Respiratorio Agudo Severo/inmunología , Índice de Severidad de la Enfermedad , COVID-19/sangre , COVID-19/patología , COVID-19/virología , Síndrome de Liberación de Citoquinas/sangre , Síndrome de Liberación de Citoquinas/virología , Citocinas/sangre , Humanos , Inflamación/inmunología , Gripe Humana/sangre , Gripe Humana/virología , Síndrome Respiratorio Agudo Grave/sangre , Síndrome Respiratorio Agudo Grave/virologíaRESUMEN
Dichapetalum madagascariense Poir (Dichapetalaceae) is traditionally used to treat bacterial infections, jaundice, urethritis and viral hepatitis in Africa. Its root contains a broad spectrum of biologically active dichapetalins. To evaluate the plant's effect on human MCF-7 cells and its' antibacterial and antiparasitic potentials, we isolated and identified the known dichapetalins A and M from the roots. Both dichapetalins were tested on six bacterial strains (Shigella flexneri, Bacillus cereus, Salmonella paratyphi B, Listeria monocytogenes, Escherichia coli, Staphylococcus aureus) and two parasite strains; Trypanosoma brucei brucei, and Leishmania donovani using the Alamar Blue assay system. Dichapetalins A and M were more potent against B. cereus with IC50 values of 11.15 and 3.15 µg/ml, respectively, compared to the positive control ampicillin (IC50 = 19.50 µg/ml). Dichapetalins A (IC50 = 74.22 µg/ml) and M (IC50 = 72.34 µg/ml) were less active against T. b. brucei, compared to the standard Suramin (IC50 = 4.96 µg/ml). Dichapetalin M showed moderate activity against L. donovani (Amphotericin B: IC50 = 0.21 µg/ml) with an IC50 of 16.80 µg/ml. In human MCF-7 cells expressing the NR1I2 receptor, the activity of dichapetalin M was higher (IC50 = 4.71 µM and 3.95 µM) for 48 and 72 h of treatment, respectively compared to Curcumin with IC50 of 17.49 µM and 12.53 µM for 48 and 72 h of treatment, respectively. Results from in vitro expression studies with qPCR confirmed an antagonistic effect of dichapetalin M on PXR (NR1I2) signaling; supporting the PXR signaling pathway as a possible mode of action of dichapetalin M as predicted by in silico results. These findings confirm previous studies that D. madagascariense can be a source of potential lead compounds for development of novel antibiotic, antiparasitic and anticancer medicines, and provide further insights into the mechanism of action of the dichapetalins.
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Antibacterianos , Extractos Vegetales/farmacología , África , Antibacterianos/farmacología , Simulación por Computador , Humanos , Pruebas de Sensibilidad Microbiana , Staphylococcus aureusRESUMEN
Investigating the interactions among various drugs is an indispensable issue in the field of computational biology. Scientific literature represents a rich source for the retrieval of knowledge about the interactions between drugs. Predicting drug-drug interaction (DDI) types will help biologists to evade hazardous drug interactions and support them in discovering potential alternatives that increase therapeutic efficacy and reduce toxicity. In this paper, we propose a general-purpose method called ADDI (standing for Alternative Drug-Drug Interaction) that applies deep learning on PubMed abstracts to predict interaction types among drugs. As an application, ADDI recommends alternatives for drug-drug interactions (DDIs) which have Negative Health Effects Types (NHETs). ADDI clearly outperforms state-of-the-art methods, on average by 13%, with respect to accuracy by using only the textual content of the online PubMed papers. Additionally, manual evaluation of ADDI indicates high precision in recommending alternatives for DDIs with NHETs.
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Biología Computacional , Preparaciones Farmacéuticas , Interacciones Farmacológicas , PubMedRESUMEN
Discovering important proteins in Protein-Protein Interaction (PPI) networks has attracted a lot of attention in recent years. Most of the previous work applies different network centrality measures such as Closeness, Betweenness, PageRank and many others to discover the most influential proteins in PPI networks. Although entropy is a well-known graph-based method in computer science, according to our knowledge, it is not used in the biology domain for this purpose. In this paper, first, we annotate the human PPI network with available annotation data. Second, we introduce a new concept called annotation-context that describes each protein according to annotation data of its neighbors. Third, we apply an entropy measure to discover proteins with varied annotation-context. Empirical results indicate that our proposed method succeeded in (1) differentiating essential and non-essential proteins in PPI networks with annotation data; (2) outperforming centrality measures in the task of discovering essential nodes; (3) predicting new annotated proteins based on existing annotation data.
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Mapas de Interacción de Proteínas , Proteínas , Algoritmos , Entropía , Humanos , Mapeo de Interacción de Proteínas , Proteínas/metabolismoRESUMEN
Pathway analysis is an informative method for comparing and contrasting drug-induced gene expression in cellular systems. Here, we define the effects of the marine natural product fucoxanthin, separately and in combination with the prototypic phosphatidylinositol 3-kinase (PI3K) inhibitor LY-294002, on gene expression in a well-established human glioblastoma cell system, U87MG. Under conditions which inhibit cell proliferation, LY-294002 and fucoxanthin modulate many pathways in common, including the retinoblastoma, DNA damage, DNA replication and cell cycle pathways. In sharp contrast, we see profound differences in the expression of genes characteristic of pathways such as apoptosis and lipid metabolism, contributing to the development of a differentiated and distinctive drug-induced gene expression signature for each compound. Furthermore, in combination, fucoxanthin synergizes with LY-294002 in inhibiting the growth of U87MG cells, suggesting complementarity in their molecular modes of action and pointing to further treatment combinations. The synergy we observe between the dietary nutraceutical fucoxanthin and the synthetic chemical LY-294002 in producing growth arrest in glioblastoma, illustrates the potential of nutri-pharmaceutical combinations in targeting this challenging disease.