Proteomic survey of Oxytricha trifallax macronuclei and micronuclei
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ABSTRACT: TMT-labeled samples of Oxytricha trifallax MIC and MAC samples. Channels 2-4 are MIC and 5-7 are MAC, with a mix of all samples as channel 1.
Project description:Gastric ECL cells and parietal (PC) cells in normal conditions and gastric ECL cells after 24 hrs fasting were purified using a combination of counter-flow elutriation, nycodenz gradient and FACS based on acridine orange labeling of histamine containing vesicles (ECL cells) or autofluorescense (PC cells) to homogeneity. cRNA probes from this purified cell suspensions and from mixed gastric homogenates were hybridized to whole rat genome expression oligonucleotide microarrays. We imported each channel separately (normalized intensity of Cy3 labeled samples = gProcessedSignal and of Cy5 labeled samples = rProcessedSignal) from the original Agilent Feature Extraction data files (submitted as raw data) after slide scanning from all slides into a Genespring 7.3 microarray database warehouse. Genespring’s built in statistical module was used to compare all channels to each other. The normalization used was against specific samples (the 5 channels of Gastric mucosal scrapings). Genespring identifies genes differentially expressed in the ECL cell samples and the parietal samples and also calculates the significance of difference (p-value). Keywords: rat whole genome expression microarray analysis (transcriptome)
Project description:Part I - SI-NET tumors High Resolution Isoelectric Focusing (HiRIEF) LC-MS and relative quantification by iTRAQ 8-plex was used to analyze 14 small intestinal neuroendocrine tumors (SI-NETs). The data was obtained from two separate TMT10plex sets and linked by a single internal pooled standard. The internal pooled standard was made by combining equal aliquots of the tryptic peptide mixtures from each of the 14 tissue samples. iTRAQ set1 was composed of 7 SI-NET samples, all from different individuals, and internal pooled standard labelled as follows: Channel 113 (sample Screen-1 with liver metastasis), Channel 114 (sample Screen-8 with liver metastasis), Channel 115 (sample Screen-3 with liver metastasis), Channel 116 (sample Screen-2 with liver metastasis), Channel 117 (sample Screen-5 no liver metastasis), Channel 118 (sample Screen-4 no liver metastasis), Channel 119 (sample Screen-10 no liver metastasis), Channel 121 (internal pooled standard). iTRAQ set2 was composed of 7 SI-NET samples, all from different individuals, and internal pooled standard labelled as follows: Channel 113 (sample Screen-7 with liver metastasis), Channel 114 (sample Screen-11 with liver metastasis), Channel 115 (sample Screen-13 with liver metastasis), Channel 116 (sample Screen-6 no liver metastasis), Channel 117 (sample Screen-12 no liver metastasis), Channel 118 (sample Screen-9 no liver metastasis), Channel 119 (sample Screen-14 no liver metastasis), Channel 121 (internal pooled standard). Part II - time course profiling in cell lines High Resolution Isoelectric Focusing (HiRIEF) LC-MS and relative quantification by TMT 10-plex was used to analyze cellular response to the neddylation inhibitor pevonedistat (MLN4924) at different timepoints in two SI-NET (small intestinal neuroendocrine tumors) cell lines. The data was obtained from two separate TMT 10-plex experiments. TMT set1 includes a time course experiment upon pevonedistat treatment of CNDT2 cells with harvests at 2h, 6h, 12h and 24h after treatment as well as of untreated control cells. Isobaric tag labelling of peptide samples with TMT10plex was used as follows. Biological duplicate controls (TMT channels 126, 127N), duplicate 2h (127C, 128N), duplicate 6h (128C, 129N), duplicate 12h (129C, 130N) and duplicate 24h (130C, 131) samples were employed. TMT set2 includes a time course experiment upon pevonedistat treatment of HC45 cells with harvests at 2h, 6h, 12h and 24h after treatment as well as of untreated control cells. Isobaric tag labelling of peptide samples with TMT10plex was used as follows. Biological duplicate controls (TMT channels 126, 127N), duplicate 2h (127C, 128N), duplicate 6h (128C, 129N), duplicate 12h (129C, 130N) and duplicate 24h (130C, 131) samples were employed.
Project description:This project contains raw LC-MS/MS data and processed pGlyco3 output files from a TMT6-labeled serum N-glycoproteomic study of human gastric cancer samples. TMT channels 126, 127 and 128 correspond to the non-metastasis group, while TMT channels 129, 130 and 131 correspond to the metastasis group. Glycopeptide identification and quantification were performed using pGlyco3.
Project description:Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively.
Project description:To evaluate the effects of GLSO on protein expression levels in immunocompromised mics, 2-3 biological replicates of the thymus sample were pooled and labeled one unit of TMT reagent, resulting in the creation of a 9-channel (3 biological pooled replicates in each group) TMT-base proteome.
Project description:5 rats were offered food containing 40mM Li/Kg dry weight for 4 weeks, and 5 control rats obtained standard food. The RNA from the inner medulla of the Li-treated rats was labeled red (channel 1), and from the control rats labeled green (channel 2). The samples from Li-treated rats 1+2 and control rats 1+2 were hybridized to array Li-NDI 1. The samples from Li-treated rats 3+4 and control rats 3+4 were hybridized to array Li-NDI 2. The samples from Li-treated rat 5 and control rat 5 were hybridized to array Li-NDI 3. Keywords: parallel sample
Project description:Microarray Expression profiles from 58 samples comprising of 3 normals and 55 gastric cancers is used for molecular subclassification of Gastric Cancers. Data Generation and Processing: The ratiometric data here is given by Ch1(Cy3)/Ch2(Cy5) where Ch2 is Universal Reference RNA from Stratagene. Two different chips were used (13K and 18k); The ratio metric is given by (Biological sample / Universal Reference). The Biological Samples are labeled with Cy3 (Green) and the Universal Reference RNA is always labeled with Cy5 (Red). Two types of spots were excluded a) Spots for which Foreground intensity was lower from background by lesser than 10 fluoresence units. b) Spots that couldnt be identified reliably by the scanner (Arrayworx) software within the "region of interest" masked by the user. The 2 channels for each array are equalized by multiplying the reference channel Ch2(Cy5) by a constant which is derived by (Total Cy3 / Total Cy5). Subsequently, all expression ratios from each array is normalized to have median expression value = 1. Keywords: other
Project description:Using RNA sequencing of FACS sorted retro-labeled sensory neurons innervating tongue tissue, we determined changes in transcriptomic profiles in males and female mice under naïve as well as tongue-tumor bearing conditions Our data revealed the following interesting findings: 1) Naïve female neurons innervating the tongue exclusively expressed immune cell markers such as Csf1R, C1qa and others, that weren’t expressed in males. 2) Male neurons were more tightly regulated than female neurons upon tumor growth; 3) While very few differentially expressed genes (DEGs) overlapped between males and females post-tumor growth, several biological processes (BPs) were similar between two sexes. However, additional distinct processes were sex-specific; 4) Post-tumor growth, male DEGs contained an equal mix of transcription factors, ligands, growth factors, receptors and channels, whereas female DEGs predominantly contained channels/receptors, enzymes, cytokines and chemokines.