ABSTRACT: Dataset contains mixture of 41 standards mixed at equimolar concentration of 10uM and then subsequently diluted down to 100 pM. Each sample ran in triplicate.
Project description:Dataset contains mixture of 41 standards mixed at equimolar concentration of 10uM in Fecal background and then subsequently diluted down to 100 pM. Each sample ran in triplicate.
Project description:A standard proteolytic digest of a human protein mixture, prepared at 1.5-fold to 3-fold protein concentration changes, and diluted into a constant background of yeast proteins. Similar to other datasets used for ground truth in quantitative studies, with the exception of being more granular, and much larger in terms of replicates, to enable more rigorous and accurate testing of quantitative algorithms.
Project description:Iron titration was performed (for replicates) into mixture of commercial standards (DFE, DFB, enterobactin, rhodotorulic acid, and ferrichrome), into cheese culture (JB 182), and E coli Nissle culture. Then iron concentration was kept constant (at 5 different concentrations) while the concentration of standard mixture was increased. This will be another way to determine Kd of each compound.
Project description:RNA-Seq on libraries made from External RNA Controls Consortium (ERCC) external RNA controls, and a mixture of mRNA from Drosophila melanogaster S2 cell and ERCC mRNAs. We evaluated performance of RNA-Seq on known synthetic PolyA+ mRNAs from the External RNA Controls Consortium (ERCC) alone and in mixtures with PolyA+ mRNA from Drosophila S2 cells. ERCC mRNAs were obtained under Phase V testing from the National Institutes of Standards and Technology (NIST). The ERCC pool contained 96 species of mRNA of various lengths and GC content covering a 2^20 concentration range. Libraries were constructed using 100ng S2 mRNA with 5ng, 2.5ng, or 1ng ERCC mRNAs, and using 50ng ERCC mRNA without S2 cell mRNA. Our data shows an outstanding linear fit between RNA-Seq read density and known input amounts.
Project description:Micro algae's are used as alternative protein source in human and animal diets. Besides micro algae contain substantial amounts of proteins they also contain a high concentration of, often unique, biological and chemical substances with potential to induce beneficial and health promoting effects in humans and animals. This study was set up to evaluate the potential of these substances to improve (intestinal) health. The effect of extracts prepared from 3 monocultures of micro algae's (Chlorella vulgaris [C], Haematococcus pluvialis [H], and Spirulina platensis [S]) and a mixed culture of micro algae's (AM; a mixture of Scenedesmus sp. and Chlorella sp. ) was studied in the presence and absence of the enterotoxigenic bacterium Escherichia coli k99 strain (ETEC, [E]) as an in vitro challenge. The E.coli-k99 strain with adhesion factor F41 (41/32) was isolated from a mastitis-infected udder. Gene expression was measured in cultured intestinal porcine epithelium cells (IPECJ2 cell line) after 2 and 6 hours incubation with C, H, and S extracts, and after 6 hours with the AM extract, using “whole genome” porcine microarrays. Gene expression profiles were analysed using functional bioinformatics programs to provide insight in the biological processes induced by micro algae extracts.
Project description:Time and concentration dependent transcriptome signatures in the ZFE of a mixture consisting of diruon, diclofenac and naproxen. Mixture composition: diuron 11%; diclofenac 2.6%; naproxen 86.4% Keywords: Expression profiling by array
Project description:Gender dependent gene expression in the kidney of 36 day old rats using the Affymetrix GeneChip rat expression set 230 array RAE230A. mixed model ANOVA using log2 transformed signal intensity of PM. Keywords: repeat
Project description:Open tenotomy of the Achilles tendon of 6 rats was performed. The animals were divided into two groups according to exposure of PM2.5 (particulate matter less than 2.5 µm): control group (Non-PM group) or PM exposure group (PM group). After 6 weeks of PM exposure, the tendon DNA was extracted and anlyzed. Genome-wide DNA methylation profiles were determinen. DNA amplicons were prepared using Differential Methylation Hybridization (DMH) method, subsequently hybridized on to the Customized Agilent Rat CpG island Microarray. The goal was to unravel the DNA methylation patterns in different subgropus of tendon tissue according to partciulate matter exposure.
Project description:Exposure to ambient particulate matter (PM) is associated with adverse health effects. Yet, due to the complexity of its chemical composition, the molecular effects of PM exposure and the mechanism of PM-mediated toxicity remain largely unknown. Here, we show that water-soluble inorganics such as nitrate and sulfate ions, rather than PM themselves, are responsible for perturbing gene expression in the lungs by rapidly penetrating the lung surfactant barrier to the alveolar region. Furthermore, from high-throughput sequencing of lung adenocarcinoma cells, we find that exposure to nitrate and sulfate ions activates the cholesterol biosynthetic metabolism and induces the expression of genes related to tumorigenesis and inflammatory response, particularly interferon-gamma. Transcriptome analysis of mouse lungs exposed to nitrate/sulfate aerosols further supports our findings. Notably, we find that exposure to nitrate/sulfate mixture leads to a unique gene expression pattern that is not observed when nitrate or sulfate is treated alone. Our work suggests the water-soluble ions as a potential source of PM-mediated toxicity and provides a roadmap to unveil the working mechanism of health hazards of PM exposure.
Project description:We report the development of an RNA sequencing method – AQRNA-seq – that minimizes biases and enables absolute quantification of all small RNA species in a sample mixture. Validation of AQRNA-seq library preparation and data mining algorithms using a 963-member microRNA reference library, RNA oligonucleotide standards of varying lengths, and northern blots demonstrated a direct, linear correlation between sequencing read count and RNA abundance.