Project description:Examined soil microbiome microcosms to determine the effect of changing pH on the production of lignocellulolytic enzymes. Soil from a Prosser, Washington field site was incubated in mesh bags on top of a soil interfacing glass bead matrix with MOPS minimal media amended with or without carboxymethyl cellulose at three different pH levels. After incubation, 2 mL of media solution was collected, centrifuged, and filtered to remove cells prior to preparing supernatant for metabolomics. GC-MS raw data files are processed using the Metabolite Detector (MD) software. Retention indices (RI) of detected metabolites are calculated based on the analysis of the FAMEs mixture, followed by their chromatographic alignment across all analyses after deconvolution. Compound detection is done on MD with a minimum peak threshold of 10.0 and deconvolution width of 8.0. Settings for compound matching and identification are delta RI of 20.0, a required S/N of 5.0, and the scoring method combines the RI and mass spectra. Metabolites are identified by matching experimental spectra to a PNNL augmented version of Agilent GC-MS metabolomics Library, containing spectra and validated RI for over 1200 metabolites. All metabolite identifications and quantification ions are manually confirmed to reduce deconvolution errors during automated data-processing and to eliminate false identifications. The NIST20 and Wiley11 GC-MS libraries are also used to cross-validate the spectral matching scores obtained using the PNNL augmented library. The unknown peaks are additionally matched with the NIST20 and Wiley11 GC-MS libraries and reported as tentative identifications only if the MS score is high. Additionally, the MS-DIAL website provides various types of public GC-MS databases, so they were converted to MSL database format, and unknown peaks can be searched with them using ChemStation.
Project description:For metabolic profiling of mouse CD4+ T cells, stable isotope labeling (SIL) experiments were performed with in vitro-activated T cells using gas chromatography (GC) coupled to mass spectrometry (MS).
Project description:Observational, Multicenter, Post-market, Minimal risk, Prospective data collection of PillCam SB3 videos (including PillCam reports) and raw data files and optional collection of Eneteroscopy reports
Project description:A 2 x 2 factorial design was used to elucidate the genome-wide transcriptional responses of old and young cells to the medium pH control. ?HO strain (BY4742 background) was cultivated batch-wise in SDC media and in fully controlled fermenters. pH was maintained at 4.5 via automatic NaOH addition for pH controlled case while this control was turned off for the unbuffered experiments. Samples of the young and old cells, collected at the 3rd and 7th day of the experiment respectively, were transferred to stimulating media containing fresh SDC medium prior to sample collection for transcriptional profiling.
Project description:We sought to determine how a cystic fibrosis isolate of Stenotrophomonas maltophilia responds to relevant pH gradients (pH 5, 7, and 9) by growing the bacterium in phosphate buffered media and conducting RNAseq experiments. Our data suggests acidic conditions are stressful for strain FLR19, as it responded by increasing expression of stress-response and antibiotic-resistance genes.
Project description:We aim to compare the genomic discrepancies across de novo Ph+ ALL, Ph+ MPAL and Ph+ AML, three diseases characterized by the occurrence of BCR-ABL1 transcripts but showing varied immunophenotypes. The data we are now submitting is the genomic copy number variants of these three groups. The following is the abstract with associated manuscript. The chromosome abnormality of Philadelphia (Ph) is typically seen in de novo acute lymphoblastic leukemia (ALL). It has also been identified in mixed phenotype acute leukemia (MPAL) and acute myeloid leukemia (AML) in the revisions to World Health Organization classification of myeloid neoplasms and actue leukemia. The discrepancies between these patients and potential mechanisms underlying differentiation fate of the leukemia cells remain poorly defined. We evaluated the clinical, genomic and transcriptomic features of Ph+ ALL, Ph+ MPAL and Ph+ AML by taking advantage of high-density genomic analysis, including next-generation sequencing array comparative genomic hybridization and gene expression profiling for transcriptomic analysis. Our results showed that the three cohorts demonstrated diversified clinical features. Ph+ ALL had the best response to induction therapy, with a complete remission (CR) rate of 93.5 and molecular response of 43.5%. Ph+ MPAL had a 90.0% CR rate but only 5.9% of molecular response. The CR rate of Ph+ AML was only 68.8%. Ph+ ALL was characterized by loss and mutations of B-cell development gene IKZF1 and PAX5, and frequent histone H3K36 trimethyltransferase SETD2 mutations. SETD2 mutations were detected in 11.3% of Ph+ ALL patients and predicted higher relapse rate. Ph+ MPAL and Ph+ AML featured high frequency of RUNX1 mutations. Further studies showed RUNX1-R177X mutation inhibited 32D cell differentiation induced by G-Csf, and cooperated with BCR-ABL1 to lead to myeloid differentiation arrest of human cord blood CD34+ cells. It is therefore presumed that these additional mutations work in synergy with BCR-ABL1 fusion gene to facilitate the development of Ph-positive acute leukemia in different immunophenotypic classifications.
Project description:To identify the proteins that interact with SENP8 in GC-1 cells, immunocoprecipitation (IP) experiments were performed. The samples from these experiments were analyzed using LC-MS/MS and subject to Label-free quantification.