Project description:The SZ-4 cell was originally identified in a Sezary disease patient and expresses FOXP3. There are different subclones of SZ4 cell which have different expression of FOXP3. Here, we used FOXP3 positive and negative SZ4 cell lines to do miRNA microarray.
Project description:The data set contains MS/MS data on teeth extracts for Ancient DNA teeth samples ran in both positive and Negative ionization modes
Project description:To define the senescence-associated secretory phenotype (SASP) of beta-cells, we used conditioned media (CM) generated from bleomycin-treated MIN6 cells and from senescent (beta-Gal-positive) primary beta-cells. In order to culture senescent beta-cells, we isolated islet, FACS-sorted them into beta-Gal-positive and negative populations, excluding immune cells through negative selection of CD45-positive and CD11beta-positive cells. For both the MIN6 and primary beta-cell models, we cultured cells in serum-free media to generate CM for proteomic analysis using the aptamer-based SomaScan platform.
Project description:The Gene Ontology (GO) is the most widely used ontology for creating biomedical annotations. GO annotations are statements associating a biological entity with a GO term. These statements comprise a large dataset of biological knowledge that is used widely in biomedical research. GO Annotations are available as "gene association files" from the GO website in a tab-delimited file format (GO Annotation File Format) composed of rows of 15 tab-delimited fields. This simple format lacks the knowledge representation (KR) capabilities to represent unambiguously semantic relationships between each field. This paper demonstrates that this KR shortcoming leads users to interpret the files in ways that can be erroneous. We propose a complementary format to represent GO annotation files as knowledge bases using the W3C recommended Web Ontology Language (OWL).
Project description:Punarnava [Boerhaavia diffusa L.] is a medicinal plant and constituent of several Indian traditional medicines. According to Ayurveda, this plant is a rich source of nutrients. Traditionally, it is used to provide relief against various gastrointestinal disorders, treat wounds, reduce joint pains, and as an anti-stress agent. Despite its pharmacological importance, detailed characterization of the metabolite composition of this plant has not been reported to date. Therefore, we have taken up metabolomic profiling of Punarnava choorna, as part of a larger project of metabolomic profiling of ayurvedic drugs. We carried out a global metabolomic analysis using a high-resolution mass spectrometry to investigate metabolite composition of Punarnava choorna. In total 1747 and 4031 features were identified at MS1 using XCMS in the positive and negative modes, respectively. Using MS2Compound, we identified 1229 and 709 features in the positive and negative modes, respectively. We also identified 362 and 191 metabolites at MS2 level in the positive and negative modes, respectively using the MS2Compound tool. The data were searched against the PlantCyc, KEGG, PhenolExplorer and HMDB databases. A large number of nutritionally important metabolites including amino acids, sugars and vitamins were identified in Purnarnava choorna. Further, the identified metabolites were mapped to their potential protein interactors using BindingDB tool. Highest number of interactions was observed for plant serotonins. The data provides molecular evidence to accelerate the discovery of mode of action of Purnarnava choorna.
Project description:In the present study we carried out global and targeted metabolomics of differentiated IMR32 cells to study the neuroprotective mechanism of Yashtimadhu (Glycyrrhiza glabra L.) in rotenone induced cellular model of parkinsons disease. Our mass spectrometry data highlighted 2403 and 2934 aligned metabolites from the positive and negative modes respectively. Among the aligned metabolites, 756 metabolites from positive and 731 metabolites from negative polarity, were mapped to a known metabolite, and the others remained unassigned. A total of 1,102 non-redundant metabolites from the positive and negative modes were assigned.
Project description:Mitogen-activated protein kinase 4 (MPK4) was first identified as a negative regulator of systemic acquired resistance (SAR). It is also an important kinase that gets involved in other plant biological processes in plants, including cytokinesis, reproduction and photosynthesis. Arabidopsis thaliana mpk4 mutant is a dwarf and sterile. Previous ‘omics’ studies including genomics, transcriptomics and proteomics have revealed new functions of MPK4 in different biological processes. However, due to challenges in metabolomics, no study has focused on metabolomic profiles of the mpk4 mutant and what metabolites and metabolic pathways are potentially regulated by MPK4 are not known. Metabolites are crucial components of plants, which plays an and they play important roles in plant signaling, defense, and growth and development. Here we used targeted and untargeted metabolomics to profile metabolites in wild type (WT) and the mpk4 mutant where we found that in addition to jasmonic acid (JA) and salicylic acid (SA) pathways, MPK4 got involved in polyamine synthesis and photosynthesis. In addition, we also conducted label-free proteomics of the two genotypes. Integration of metabolomics and proteomics data allowed insight into the metabolomic networks that are potentially regulated by MPK4.
Project description:Dataset of the Ocotea diospyrifolia (Meisn.) Mez leaf extract analyzed in negative and positive ionization modes, with 2 blanks samples.