A Data-Dependent Acquisition Ladder for Ultrasensitive (Neuro)Proteomics
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive
ORGANISM(S): Mus Musculus (mouse)
TISSUE(S): Cell Culture
SUBMITTER: 
Peter Nemes
LAB HEAD: Peter Nemes
PROVIDER: PXD027428 | Pride | 2022-02-18
REPOSITORIES: Pride
Similar Datasets
Project description:We have enabled ultrasensitive proteomics of limited protein digests by developing a tapered-tip nanoelectrospray ionization (nanoESI) interface for microanalytical capillary electrophoresis (CE) high resolution mass spectrometry (HRMS). CE-nanoESI-HRMS allowed us to detect 260 zmol angiotensin II (lower limit of detection) and identify 1 pg of bovine serum albumin and cytochrome c. A 1 ng protein digest from the mouse posterior cortex yielded 217 nonredundant protein groups, including many gene products that are used as classical neuronal markers.
2022-02-18 | PXD005222 | Pride
Project description:We provide a protocol to enable the mass spectrometry-based characterization of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The experimental workflow leverages reproducible cell-fate maps and established technologies from developmental biology to identify, fluorescently label, track, and analyze cells and their progenies from this important biological model of vertebrate development. Proteins are identified and quantified via bottom-up proteomics. Microanalytical capillary electrophoresis or nanoflow liquid chromatography (nanoLC) are used to separate peptides, and electrospray ionization (ESI) high-resolution mass spectrometry (HRMS) are employed for detection.
2022-02-23 | PXD030059 | Pride
Project description:This project employed ultrasensitive proteomics in the discovery setting utilizing microanalytical capillary electrophoresis electrospray ionization (CE-ESI) and trapped ion mobility high-resolution mass spectrometry (TimsTOF HRMS) to quantify proteomic changes during development in the suprachiasmatic nucleus (SCN), before and after the onset of photoreceptor-dependent visual function. Results from this work highlight the maturation of oligodendrocyte myelination as well as extracellular matrix proteins with implications for critical-period plasticity. This work marks the first integration of ultrasensitive proteomics by CE-ESI TimsTOF HRMS with super-resolution STORM microscopy provide, expanding analytical resources to help better understand the brain and vision.
2023-10-25 | PXD038245 | Pride
Project description:In this work, we integrate capillary electrophoresis electrospray ionization mass spectrometry, bottom-up proteomics, and single-cell microanalysis to enable the label-free quantification (LFQ) of proteins in single embryonic cells (D11 blastomeres) in the 16-cell frog (Xenopus laevis) embryo. Based on the LFQ data, we find translational differences between the blastomeres even within the same cell type.
2016-06-23 | PXD004174 | Pride
Project description:In this project, we enabled mass spectrometry based proteomics characterization of single neurons in sections of the mouse brain. We accessed cells in a whole-cell patch clamp configuration and aspirated a portion of the neuronal soma into the patch clamp probe. The collected aspirate was expelled into a microvial, where proteins were extracted and processed for shot-gun analysis. The resulting trace amounts of protein digests were analyzed on a custom-built microanalytical capillary electrophoresis platform that was connected to an electrospray ionization high-resolution mass spectrometer. This “patch proteomics” technology identified ~150 proteins from triplicate measurement of single dopaminergic neurons in the mouse substantia nigra.
2022-02-18 | PXD028040 | Pride
Project description:16 dietary protein preparations were digested according to a standardized invitro digestion (InfoGest) protocol, simulating gastrointestinal digestion. Resulting oligopeptide mixtures were subsequently analyzed by UPLC-MS using DDA shot-gun detection. Peak intensity data from MS1 spectra were obtained using Progenesis QI. MS1 peak data were matched and filtered based on overlap with the reference digest of Whey protein using a custom made script in R. MSMS fragmentation spectra were converted to .mgf format and de novo interpreted using SearchGUI 3.3.17 and RapidNOVOR algorithm. Raw data, peak intensity tables and de novo interpretaion data are provided.
2021-09-09 | PXD021577 | Pride
Project description:Background: In the last decade, much attention has been drawn to probiotic bacteria in the context of inflammatory bowel disease (IBD), since the potential of certain strains to attenuate inflammation was demonstrated in several animal experiments and clinical studies. Data in humans elucidating the molecular mechanism of probiotic action are still scarce. To this end, we used an organ culture system of human colon mucosa and investigated the gene expression profiles after treatment with different probiotic bacteria in phorbol 12-myristate 13-acetate (PMA)/ionomycin (IO)) stimulated samples using whole genome microarrays. Moreover, we analyzed changes occurring in the intestinal explants cultured for 8 hours when compared to fresh, directly frozen mucosa, in order to infer the suitability of the system to study an inflammatory stimulus and likely antiinflammatory responses. Results: Culturing intestinal colon fragments during 8 hours elicited differential gene expression in 283 genes, 229 upregulated and 54 downregulated. Upregulated genes were predominantly related to apoptosis, whereas downregulated genes encoded mitochondrial proteins. No specific enrichment of genes related to inflammation or immune response could be detected, confirming the suitability of the system to further study the inmunomodulatory/anti-inflammatory properties of Lactobacillus casei BL23 (BL23), L.plantarum 299v (LP299v) and L.plantarum 299v (A-) (LP299v (A-)), a mutant strain with reduced adhesive properties to enterocytes. Intestinal explants were stimulated with PMA/IO for 3 hours and subsequently incubated with probiotic bacteria for 4 h. ANOVA analysis (p ? 0,01) revealed 205 differentially expressed genes between Control, PMA/IO (Inflamed), and the 3 bacterial treatments. Most importantly, a number of PMA/IO induced genes related to immune response and immune system process such as IL-2, IFN-?, IL17A and pro-inflammatory cytokines CXCL9 and CXCL11 were downregulated by BL23, LP299v and LP299v (A-). The behaviour of the three Lactobacillus strains was quite similar, although their presence induced differential expression of a small number of genes in a strain dependent manner. Conclusion: The human colon organ culture was found to be a suitable model for the study of inflammatory/anti-inflammatory stimuli, and therefore it constitutes a valuable tool to determine the inmunomodulatory effect of probiotic bacteria. The global transcriptional profile evoked by strains BL23, LP299v and LP299v (A-) in artificially inflamed tissue indicated a clear homeostasis restoring effect, including a decrease of the signals produced by activated T cells. Macroscopically healthy colonic intestinal tissue was obtained at surgery from 3 patients. Intestinal explants were treated with PMA and ionomycin for 3 h to induce pro-inflammatory conditions. Then, culture medium was changed and replaced with either medium or medium containing either Lactobacillus casei BL23, Lactobacillus plantarum 299v, or a nonadherent mutant of L. plantarum 299v (A-) and incubated for further 4 hours. In parallel, control intestinal explants were cultured without any treatment of PMA/ionomycin or probiotic bacteria and compared to directly frozen tissue in order to evaluate changes in gene expression which are due solely to the culture conditions.
2012-06-19 | E-GEOD-23630 | biostudies-arrayexpress
Project description:Class-switching to IgG2a/c in mice is a hallmark response to intracellular pathogens. T cells can promote class-switching and the predominant pathway for induction of IgG2a/c antibody responses has been suggested to be via stimulation from Th1 cells. We previously formulated CAF®01 (cationic liposomes containing dimethyldioctadecylammonium bromide (DDA) and Trehalose-6,6-dibehenate (TDB)) with the lipidated TLR7/8 agonist 3M-052 (DDA/TDB/3M-052), which promoted robust Th1 immunity in newborn mice. When testing this adjuvant in adult mice using the recombinant Chlamydia trachomatis (C.t.) vaccine antigen CTH522, it similarly enhanced IgG2a/c responses compared to DDA/TDB, but surprisingly reduced the magnitude of the IFN-g+ Th1 response in a TLR7 agonist dose-dependent manner. Single cell RNA-sequencing revealed that DDA/TDB/3M-052 liposomes initiated early transcription of class-switch regulating genes directly in pre-germinal center B cells. Mixed bone marrow chimeras further demonstrated that this adjuvant did not require Th1 cells for IgG2a/c switching, but rather facilitated TLR7-dependent T-bet programming directly in B cells. This study underlines that adjuvant-directed IgG2a/c class-switching in vivo can occur in the absence of T cell help, via direct activation of TLR7 on B cells and positions DDA/TDB/3M-052 as a powerful adjuvant capable of eliciting type I-like immunity in B cells without strong induction of Th1 responses.
2023-11-17 | GSE245073 | GEO
Project description:Full-scan, data-dependent acquisition (DDA), and data-independent acquisition (DIA) are the three common data acquisition modes in high resolution mass spectrometry-based untargeted metabolomics. It is an important yet underrated research topic on which acquisition mode is more suitable for a given untargeted metabolomics application. In this work, we compared the three data acquisition techniques using a standard mixture of 134 endogenous metabolites and a human urine sample. Both hydrophilic interaction and reversed-phase liquid chromatographic separation along with positive and negative ionization modes were tested. Both the standard mixture and urine samples generated consistent results. Full-scan mode is able to capture the largest number of metabolic features, followed by DIA and DDA (53.7% and 64.8% respective features fewer on average in urine than full-scan). Comparing the MS2 spectra in DIA and DDA, spectra quality is higher in DDA with average dot product score 83.1% higher than DIA in Urine(H), and the number of MS2 spectra (spectra quantity) is larger in DIA (on average 97.8% more than DDA in urine). Moreover, a comparison of relative standard deviation distribution between modes shows consistency in the quantitative precision, with the exception of DDA showing a minor disadvantage (on average 19.8% and 26.8% fewer features in urine with RSD < 5% than full-scan and DIA). In terms of data preprocessing convenience, full-scan and DDA data can be processed by well-established software. In contrast, several bioinformatic issues remain to be addressed in processing DIA data and the development of more effective computational programs is highly demanded.
2020-05-21 | MTBLS1572 | MetaboLights
Project description:<p>Despite the growing popularity of liquid chromatography-mass spectrometry (LC-MS)-based metabolomics, no study has yet to systematically compare the performance of different data acquisition modes in the discovery of significantly altered metabolic features, which is an important task of untargeted metabolomics for identifying clinical biomarkers and elucidating disease mechanism in comparative samples. In this work, we performed a comprehensive comparison of three most commonly used data acquisition modes, including full-scan, data-dependent acquisition (DDA), and data-independent acquisition (DIA), using a metabolomics study of human plasma samples from leukemia patients before and after one-month chemotherapy. After optimization of data processing parameters, we extracted and compared statistically significant metabolic features from the results of each data acquisition mode. We found that most significant features can be consistently found in all three data acquisition modes with similar statistical performance as evaluated by Pearson correlation and receiver operating characteristic (ROC) analysis. Upon comparison, DDA mode consistently generated fewer uniquely found significant features than full-scan and DIA modes. We then manually inspected over 2000 uniquely discovered significant features in each data acquisition mode and showed that these features can be generally categorized into four major types. Many significant features were missed in DDA mode, primarily due to its low capability of detecting or extracting these features from raw LC-MS data. We thus proposed a bioinformatic solution to rescue these missing significant features from the raw DDA data with good reproducibility and accuracy. Overall, our work asserts that data acquisition modes can influence metabolomics results, suggesting room for improvement of data acquisition modes for untargeted metabolomics.</p>
2020-10-02 | MTBLS1842 | MetaboLights