Project description:Dataset used for biochemometric analyses on the extract and fractions of Rosmarinus officinalis (Salvia rosmarinus) tested against MRSA.
| MSV000086110 | MassIVE
Project description:Dataset used for 3q29 Project samples (n=46) analyses
Project description:The aqueous extract of yerba mate, a South American tea beverage made from Ilex paraguariensis leaves, has demonstrated bactericidal and inhibitory activity against bacterial pathogens, including methicillin-resistant Staphylococcus aureus (MRSA). The gas chromatography-mass spectrometry (GC-MS) analysis of two unique fractions of yerba mate aqueous extract revealed 8 identifiable small molecules in those fractions with antimicrobial activity. For a more comprehensive analysis, a data analysis pipeline was assembled to prioritize compounds for antimicrobial testing against both MRSA and methicillin-sensitive S. aureus using forty-two unique fractions of the tea extract that were generated in duplicate, assayed for activity, and analyzed with GC-MS. As validation of our automated analysis, we checked our predicted active compounds for activity in literature references and with used authentic standards to test for antimicrobial activity. 3,4-dihydroxybenzaldehyde showed the most antibacterial activity against MRSA at low concentrations in our bioassays. In addition, quinic acid and quercetin were identified using random forests analysis and 5-hydroxy pipecolic acid was identified using linear discriminant analysis. We additionally also generated a ranked list of unidentified compounds that may contribute to the antimicrobial activity of yerba mate against MRSA. Here we utilized GC-MS data to implement an automated analysis that resulted in a ranked list of compounds that likely contribute to the antimicrobial activity of aqueous yerba mate extract against MRSA.
Project description:SYBA uses a fragment-based approach to classify whether a molecule is easy or hard to synthesize, and it can also be used to analyze the contribution of individual fragments to the total synthetic accessibility. The easy-to-synthesize dataset is an extract of the ZINC purchasable compounds, and the hard-to-synthesize dataset is generated using a Nonpher approach (introducing small molecular perturbations to transform molecules into more complex compounds). The fragments are calculated with ECFP8 descriptors, and independence between fragments is assumed.
Model Type: Predictive machine learning model.
Model Relevance: Prediction of synthetic accessibility
Model Encoded by: Miquel Duran-Frigola (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos7pw8
Project description:The associated files are mass spec data from 4 separate mixed-bed ion exchange column separations of Arabidopsis thaliana Col-0 seedling native extract. Two fractionations used extract from seedlings grown in light and two fractionations used extract from etiolated seedlings (grown in the dark). All fractions were processed similarly for LC-MS/MS but one light-grown fractionation was analyzed on a different mass spectrometer than the other three sets of ion exchange fractions.
Project description:Triton X-100 soluble crude extract from BCECs displaying limited blood-brain barrier functions was fractionated into 5 fractions (F0, F25, F50, F75) with increasing concentrations of acetonitrile (0%, 25%, 50%, 75%). This is the merging of triplicate dataset of subfraction # F0.
Project description:Here we identify the genome-wide occupancy of PHF6 in T-ALL cells. Human T-ALL cells were cross-linked with formaldehyde for 20 min. DNA was enriched by chromatin immunoprecipitation (ChIP) and analyzed by Solexa sequencing. A sample of whole cell extract (WCE) was sequenced and used as the background to determine enrichment. ChIP was performed using an antibody against total PHF6 (Bethyl A301-451A). This represents the ChIP-seq portion of this dataset.
Project description:Real-time quantitative PCR analysis of human epithelial cells The activity of Malva sylvestris extract and fractions infected by A. actinomycetemcomitans were investigated using an adapted dual chamber model, oral human epithelial cells were used in the co-culture model. One microgram of RNA was converted in cDNA using RT2 First Strand Kit. 84 genes were analyzed using inflammatory response & Autoimmunity Array RT2 profiler (Qiagen Sabiosciences, Valencia, CA, USA) with buffers supplied by the manufacturer qPCR gene expression profiling. Oral human epithelial cells were infected by A. Actinomycetemcomintans and treated with Malva sylvestris extract and fractions prior to gene expression analysis.
Project description:The intermediate filament protein Nestin serves as a biomarker for stem cells and has been used to identify subsets of cancer stem-like cells. However, the mechanistic contributions of Nestin to cancer pathogenesis are not understood. Here we report that Nestin binds the hedgehog pathway transcription factor Gli3 to mediate the development of medulloblastomas of the hedgehog subtype. In a mouse model system, Nestin levels increased progressively during medulloblastoma formation resulting in enhanced tumor growth. Conversely, loss of Nestin dramatically inhibited proliferation and promoted differentiation. Mechanistic investigations revealed that the tumor-promoting effects of Nestin were mediated by binding to Gli3, a zinc finger transcription factor that negatively regulates hedgehog signaling. Nestin binding to Gli3 blocked Gli3 phosphorylation and its subsequent proteolytic processing, thereby abrogating its ability to negatively regulate the hedgehog pathway. Our findings show how Nestin drives hedgehog pathway-driven cancers and uncover in Gli3 a therapeutic target to treat these malignancies.