Monkeypox Knowledge Graph: A comprehensive representation embedding chemical entities and associated biology of Monkeypox
Ontology highlight
ABSTRACT:
SUBMITTER: 
Reagon Karki
PROVIDER: MODEL2208040001 | BioModels | 2022-10-17
REPOSITORIES: BioModels
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Project description:The BY-COVID Knowledge Graph integrates biological and chemical data from BY-COVID project partner sites. These data are further enriched with information such as biological processes, assays, drug candidates, drug indications, mechanism of action and side effects to form a dynamic and comprehensive network. This is achieved by using the UniProt, ChEMBL and OpenTargets API. The KG is compliant with FAIR annotations allowing seamless transformation and integration to/with other formats and infrastructures. Please check the github for more details: https://github.com/Fraunhofer-ITMP/BY-COVID-KG.
2022-10-17 | MODEL2209020001 | BioModels
Project description:This Agilent QTOF data consists of urine and liver of mice fed AFFF, as well as PFAS chemical standards treated with mouse enzymes for biotransformation. Data acquired by Sheng Liu and David A. Dukes.
It goes alongside the manuscript:
"Expanding PFAS Identification with Transformation Product Libraries: Non-Targeted Analysis Reveals Biotransformation Products in Mice" published in Environmental Science & Technology
An interactive dataset after FluoroMatch annotation for the urine data can be found here:
https://innovativeomics.com/datasets/non-targeted-pfas-dataset-from-urine-of-afff-fed-mice/
Software with the biotransformation libraries can also be found at:
https://innovativeomics.com
Per- and polyfluoroalkyl substances (PFAS) are widely used persistent synthetic chemicals that have been linked to adverse health effects. While the behavior of PFAS has been evaluated in the environment, our understanding of reaction products in mammalian systems is limited. This study identified biological PFAS transformation products and generated mass spectral libraries to facilitate automated search and identification. The biological transformation products of 27 PFAS, spanning 5 chemical subclasses (alcohols, sulfonamides, carboxylic acids, ethers, and esters), were evaluated following enzymatic reaction with mouse liver S9 fractions. Four major pathways were identified by liquid chromatography-high resolution mass spectrometry: glucuronidation; sulfation; dealkylation and oxidation. Class-based fragmentation rules and associated PFAS transformation product libraries were generated and integrated into an automated non-targeted PFAS data analysis software (FluoroMatch). Fragmentation was additionally predicted for the potential transformation products of more than 2,500 PFAS in the EPA CompTox Chemicals Dashboard PFASSTRUCTv4. Generated mass spectral libraries were validated by applying FluoroMatch to a dataset of urine from aqueous film-forming foam (AFFF)-dosed mice. Toxicity predictions showed identified PFAS transformation products as potential developmental and mutagenic toxicants. This research enables more comprehensive PFAS characterization in biological systems which will improve assessment of exposures and evaluation of the associated health impacts.
| MSV000095980 | MassIVE
Project description:Diffuse midline glioma (DMG) is a uniformly fatal pediatric, adolescent, and young adult cancer diagnosed in the midline structures of the brain. PI3K/Akt signaling is an overarching contributor to the poor outcomes of DMG patients due to their dependance on insulin and recurring mutations and amplifications in PI3K/Akt genes. Paxalisib (GDC-0084) is a potent PI3K/Akt inhibitor developed to penetrate the brain’s protective blood-brain barrier (BBB). We performed paxalisib regimen optimization by assessment of blood glucose levels, analysis in vivo pharmacokinetics/pharmacodynamics properties, and employed DMG patient derived xenograft (PDX) mouse models to determine preclinical efficacy. To identify novel combination strategies, we conducted high-resolution quantitative phosphoproteomics of DMG cells treated with paxalisib. Elevated blood glucose levels promoting hyperglycemia was seen in mice using paxalisib 10 mg/kg/day (~mouse equivalent human maximum tolerated dose- NCT03696355). Whereas 5 mg/kg/day, or 5mg/kg/b.i.d. (twice daily) non-significantly increased blood glucose levels compared to controls. Pharmacokinetic analysis of mouse tissues showed 5 mg/kg/b.i.d. increased paxalisib acumination in the brainstem, suppressing PI3K/Akt signaling to significantly extend the survival of DMG PDX models compared to all other regimens; a survival benefit amplified when combined with the anti-glycemic therapy metformin. Phosphoproteomic profiling identified increased Protein kinase C (PKC) signaling following paxalisib treatment. The combination of paxalisib and enzastaurin (PKC inhibitor) synergistically extended the survival of PDX models. Our optimized dosing regimen increased the preclinical benefits of paxalisib, with the combination of paxalisib with metformin, or paxalisib with enzastaurin, heralding rationally designed combination strategies for the treatment of DMG
2024-02-20 | PXD036114 | Pride
Project description:The primary goal of toxicology and safety testing is to identify agents that have the potential to cause adverse effects in humans. Unfortunately, many of these tests have not changed significantly in the past 30 years and most are inefficient, costly, and rely heavily on the use of animals. The rodent cancer bioassay is one of these safety tests and was originally established as a screen to identify potential carcinogens that would be further analyzed in human epidemiological studies. Today, the rodent cancer bioassay has evolved into the primary means to determine the carcinogenic potential of a chemical and generate quantitative information on dose-response behavior in chemical risk assessments. Due to the resource-intensive nature of these studies, each bioassay costs $2 to $4 million and takes over three years to complete. Over the past 30 years, only 1,468 chemicals have been tested in a rodent cancer bioassay. By comparison, approximately 9,000 chemicals are used by industry in quantities greater than 10,000 lbs and nearly 90,000 chemicals have been inventoried by the U.S. Environmental Protection Agency as part of the Toxic Substances Control Act. Given the disparity between the number of chemicals tested in a rodent cancer bioassay and the number of chemicals used by industry, a more efficient and economical system of identifying chemical carcinogens needs to be developed. Experiment Overall Design: Five-week old female B6C3F1 mice were exposed for 13 weeks in the following dose groups: 1) 1,5-Naphthalenediamine, CAS No. 2243-62-1, feed, 2000 ppm, positive lung carcinogen; 2) 2,3-Benzofuran, CAS No. 271-89-6, gavage, 240 mg/kg, positive lung carcinogen; 3) 2,2-Bis(bromomethyl)-1,3-propanediol, CAS No. 3296-90-0, feed, 1250 ppm, positive lung carcinogen; 4) N-Methylolacrylamide, CAS No. 924-42-5, gavage (water), 50 mg/kg, positive lung carcinogen; 5) 1,2-Dibromoethane, CAS No. 106-93-4, gavage (corn oil), 62 mg/kg, positive lung carcinogen; 6) Coumarin, CAS No. 91-64-5, gavage (corn oil), 200 mg/kg, positive lung carcinogen; 7) Benzene, CAS No. 71-43-2, gavage (corn oil), 100 mg/kg, positive lung carcinogen; 8) N-(1-naphthyl)ethylenediamine dihydrochloride, CAS No. 1465-25-4, feed, 2000 ppm, negative lung carcinogen; 9) Pentachloronitrobenzene, CAS No. 82-68-8, feed, 8187 ppm, negative lung carcinogen; 10) 4-Nitroanthranilic acid, CAS No. 619-17-0, feed, 10000 ppm, negative lung carcinogen; 11) 2-Chloromethylpyridine hydrochloride, CAS No. 6959-47-3, gavage (water), 250 mg/kg, negative lung carcinogen; 12) Diazinon, CAS No. 333-41-5, feed, 200 ppm, negative lung carcinogen; 13) Malathion, CAS No. 121-75-5, feed, 16000 ppm, negative lung carcinogen; 14) Corn oil control, gavage; 15) Water control, gavage; 16) Rodent diet control, feed. Feed animals were exposed 7 days/week and gavage animals were exposed 5 days/week (5 ml/kg). After 13 weeks, animals were euthanized and lungs were collected. The right lobe was used for microarray analysis. Microarray analysis was performed on the lungs of three to four mice per treatment group.
2008-06-14 | E-GEOD-6116 | biostudies-arrayexpress
Project description:Chemical graph generators are software packages to generate computer representations of chemical structures adhering to certain boundary conditions. Their development is a research topic of cheminformatics. Chemical graph generators are used in areas such as virtual library generation in drug design, in molecular design with specified properties, called inverse QSAR/QSPR, as well as in organic synthesis design, retrosynthesis or in systems for computer-assisted structure elucidation (CASE). CASE systems again have regained interest for the structure elucidation of unknowns in computational metabolomics, a current area of computational biology.
| S-EPMC7785115 | biostudies-literature
Project description:Background: Information on the carcinogenic potential of chemicals is only availably for High Production Volume products. There is however, a pressing need for alternative methods allowing for the chronic toxicity of substances, including carcinogenicity, to be detected earlier and more reliably. Here we applied advanced genomics to a cellular transformation assay to identify gene signatures useful for the prediction of risk for carcinogenicity. Methods: Genome wide gene expression analysis and qRT-PCR were applied to untransformed and transformed Balb/c 3T3 cells that exposed to 2, 4-diaminotoluene (DAT), benzo(a)pyrene (BaP), 2-Acetylaminoflourene (AAF) and 3-methycholanthrene (MCA) for 24h and 120h, at different concentrations, respectively. Furthermore, various bioinformatics tools were used to identify gene signatures predicting for the carcinogenic risk. Results: Bioinformatics analysis revealed distinct datasets for the individual chemicals tested while the number of significantly regulated genes increased with ascending treatment concentration of the cell cultures. Filtering of the data revealed a common gene signature that comprised of 13 genes whose regulation in cancer tissue has already been established. Strikingly, this gene signature was already identified prior to cell transformation therefore confirming the predictive power of this gene signature in identifying carcinogenic risks of chemicals. Comparison of fold changes determined by microarray analysis and qRT-PCR were in good agreement. Conclusion: Our data describes selective and commonly regulated carcinogenic pathways observed in an easy to use in vitro carcinogenicity assay. Here we defined a set of genes which can serve as a simply assay to predict the risk for carcinogenicity by use of an alternative in vitro testing strategy.
2010-10-02 | GSE22180 | GEO
Project description:Analysis of wild type genome expression profile altered by albino chemicals. Results uncovered a several groups of genes that were significant responsive to these chemicals which may contribute to the albino phenotype.
2012-03-28 | GSE36887 | GEO
Project description:Background: Information on the carcinogenic potential of chemicals is only availably for High Production Volume products. There is however, a pressing need for alternative methods allowing for the chronic toxicity of substances, including carcinogenicity, to be detected earlier and more reliably. Here we applied advanced genomics to a cellular transformation assay to identify gene signatures useful for the prediction of risk for carcinogenicity. Methods: Genome wide gene expression analysis and qRT-PCR were applied to untransformed and transformed Balb/c 3T3 cells that exposed to 2, 4-diaminotoluene (DAT), benzo(a)pyrene (BaP), 2-Acetylaminoflourene (AAF) and 3-methycholanthrene (MCA) for 24h and 120h, at different concentrations, respectively. Furthermore, various bioinformatics tools were used to identify gene signatures predicting for the carcinogenic risk. Results: Bioinformatics analysis revealed distinct datasets for the individual chemicals tested while the number of significantly regulated genes increased with ascending treatment concentration of the cell cultures. Filtering of the data revealed a common gene signature that comprised of 13 genes whose regulation in cancer tissue has already been established. Strikingly, this gene signature was already identified prior to cell transformation therefore confirming the predictive power of this gene signature in identifying carcinogenic risks of chemicals. Comparison of fold changes determined by microarray analysis and qRT-PCR were in good agreement. Conclusion: Our data describes selective and commonly regulated carcinogenic pathways observed in an easy to use in vitro carcinogenicity assay. Here we defined a set of genes which can serve as a simply assay to predict the risk for carcinogenicity by use of an alternative in vitro testing strategy. Balb/c 3T3 cells were seeded at 200 cells in each 60 x 15 mm culture dish with 4 ml M10F, using six culture dishes for every treatment. When cells reached a confluence of 60-65%, the culture medium was removed and replaced with fresh medium containing all tested chemicals at a specific concentration and two time points (24 and 120h). First we treated the cells both 24h and 120h with concentrations reported in the literature (0.5µM BaP, 50µM DAT, 25µM AAF and 2µM MCA). In a second approach IC20 concentrations were investigated for each chemical at both time points. The concentrations determined for IC20 ranged from 1.5 µM BaP to 700 µM DAT for 24h of treatment, and from 0.1 µM BaP or MCA to 10µM AAF for 120h of treatment. Balb/c 3T3 cells treated with 0.75% DMSO alone were kept as controls. Each experiment was run in triplicate.
2010-10-02 | E-GEOD-22180 | biostudies-arrayexpress
Project description:Analysis of wild type genome expression profile altered by albino chemicals. Results uncovered a several groups of genes that were significant responsive to these chemicals which may contribute to the albino phenotype. WT (Col-0) sown on 0.5x MS agar medium and stratified in the dark at 4 °C for 3 days and then germinated in the light condition (16 h light/8 h dark) for 5 days at 22 °C, and then transfer to the 0.5x MS solution one day for adapt the treatment condition. In the DAG 6 (day after germination), final concentration 50 μM chemicals (7606596 and 5929745) were supplemented into the medium for chemical treatment. Approximately 2,000 seedlings were used to collect tissues before the chemicals treatment as the time zero samples. Seedlings were collected after the chemical treatment for 3 hours and 12 hours. Total RNA extracted from the collected samples was applied in each microarray experiment with Arabidopsis ATH1 GeneChip (Affymetrix). Qiagen RNAeasy mini kit (Qiagen) was used for RNA preparation. cDNA labeling, array hybridization, and scanning followed by standard Affymetrix expression array protocol. Two independent sets of microarray analyses were performed in this assay.
2012-03-27 | E-GEOD-36887 | biostudies-arrayexpress
Project description:Diffuse midline glioma (DMG) is a uniformly fatal pediatric, adolescent, and young adult cancer diagnosed in the midline structures of the brain. PI3K/Akt signaling is an overarching contributor to the poor outcomes of DMG patients due to their dependance on insulin and recurring mutations and amplifications in PI3K/Akt genes. Paxalisib (GDC-0084) is a potent PI3K/Akt inhibitor developed to penetrate the brain’s protective blood-brain barrier (BBB). We performed paxalisib regimen optimization by assessment of blood glucose levels, analysis in vivo pharmacokinetics/pharmacodynamics properties, and employed DMG patient derived xenograft (PDX) mouse models to determine preclinical efficacy. To identify novel combination strategies, we conducted high-resolution quantitative phosphoproteomics of DMG cells treated with paxalisib. Elevated blood glucose levels promoting hyperglycemia was seen in mice using paxalisib 10 mg/kg/day (~mouse equivalent human maximum tolerated dose- NCT03696355). Whereas 5 mg/kg/day, or 5mg/kg/b.i.d. (twice daily) non-significantly increased blood glucose levels compared to controls. Pharmacokinetic analysis of mouse tissues showed 5 mg/kg/b.i.d. increased paxalisib acumination in the brainstem, suppressing PI3K/Akt signaling to significantly extend the survival of DMG PDX models compared to all other regimens; a survival benefit amplified when combined with the anti-glycemic therapy metformin. Phosphoproteomic profiling identified increased Protein kinase C (PKC) signaling following paxalisib treatment. The combination of paxalisib and enzastaurin (PKC inhibitor) synergistically extended the survival of PDX models. Our optimized dosing regimen increased the preclinical benefits of paxalisib, with the combination of paxalisib with metformin, or paxalisib with enzastaurin, heralding rationally designed combination strategies for the treatment of DMG.
2024-02-20 | GSE211565 | GEO