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57 results for “Quantitative proteomics”
A proteome-wide quantitative platform for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs
<p><strong>EM Quantitation:</strong></p> <p>Raw data gathered from EM images taken to determine nanodisc population size distribution.</p> <p> </p> <p><strong>NNB TGN46 analysis:</strong></p> <p>Data analysis of the Native Nanobleach experiments of TGN46 in native nanodiscs to determine population distribution of oligomeric organizations.</p> <p> </p> <p><strong>Polymer conditions:</strong></p> <p>Physiochemical characteristic and extraction conditions for all polymers in the library both commercially available and in-house.</p> <p> </p> <p><strong>Protein groups polymer screen original file:</strong></p> <p>Original output of MaxQuant data processing of polymer screen data.</p> <p> </p> <p><strong>Organelle matching:</strong></p> <p>Code used for mathcing proteins identified in the proteomics output to organelle or residence for all organellar annotations.</p> <p> </p> <p><strong>Polymer code:</strong></p> <p>Code used to process and normalize the MaxQuant output and calulate extraction efficiency across all detected proteins.</p> <p> </p> <p><strong>MAP Library Details:</strong></p> <p>Graphic and table explaining chemical details of all polymer used in the screen, both commerically available and in-house synthesized.</p> <p> </p> <p><strong>NNB TGN46:</strong></p> <p>Raw scope files for the TIRF microscopy single molecule step photobleaching experiment with TGN46.</p> <p> </p> <p><strong>Organellar Breakdown Database:</strong></p> <p>Proteins detected in the polymer screen through proteomics experiments stratified into organelle of residence.</p> <p> </p> <p><strong>Human Proteome FASTA:</strong></p> <p>The FASTA file used for proteome searching in processing the proteomics data to build the screening database.</p> <p> </p> <p><strong>Hand Curated Organellar Proteomes:</strong></p> <p>Organellar proteomes used for organellar sorting and identification of proteins detected in the screen.</p> <p> </p> <p><strong>Polymer SEC Superdex75:</strong></p> <p>Size exculsion chromatography traces for chloroSMA series of polymers. Was used to characterize length and population polydispersity.</p> <p> </p> <p><strong>Negative Stain Raw:</strong></p> <p>RAW TEM scope images of purified synaptophysin-vamp2 containing nanodiscs. Populatoin size distribution was determined.</p> <p> </p> <p><strong>FSEC Polymer CS80:</strong></p> <p>Fluoresence size exclusion chromatogram for purified synaptophysin-vamp2 containing nanodiscs to ensure population homogeneity and purity.</p> <p><strong>NMR Raw data:</strong></p> <p>NMR raw files for characterizing the in-house synthesized Chloro-SMA series and AASTY series.</p> <p> </p>
Data for manuscript, "An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples"
<p>Clinical BALF samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, MS based proteomic analysis of BALF is impeded by the dynamic range of protein abundance, and potential for interfering contaminants. We have developed a workflow that eliminates these challenges. By combining high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, our workflow is compatible with both qualitative and quantitative MS-based proteomic analysis. The workflow includes collection of endogenous peptides for peptidomic analysis of BALF, if desired, as well as amenability to offline semi-preparative or microscale fractionation of peptide mixtures prior to LC-MS/MS analysis, for increased depth of analysis. We show the effectiveness of this workflow on BALF samples from COPD patients. Overall, our workflow should allow MS-based proteomics to be applied to a wide variety of studies focused on BALF clinical samples. </p> <p>Note: Due to the nature of some of the files, file <em>wendt005_ostr0103_18260_20210831_BALF_FAIMS_MS2_TMT16.msf, wendt005_ostr0103_18976_20230202_quantReport.msf, cmsptc_higgi022_18988_20230203_18976DW_EnF_hcdlT_1R.raw, cmsptc_higgi022_18988_20230203_18976DW_EnF_hcdlT_2R.raw, cmsptc_higgi022_18988_20230203_18976DW_EnF_hcdlT_3R.raw and cmsptc_higgi022_18988_20230203_18976DW_Eclipse_noFAIMS_quantReport.msf</em> were zipped into compressed folders before uploading.</p>
Data from: Quantitative proteomics reveals rapid divergence in the postmating response of female reproductive tracts among sibling species
<p><span><span><span><span><span><span><span><span><span><span><span>Fertility depends, in part, on interactions between male and female reproductive proteins inside the female reproductive tract (FRT) that mediate postmating changes in female behavior, morphology, and physiology. Coevolution between interacting proteins within species may drive reproductive incompatibilities between species, yet the mechanisms underlying postmating-prezygotic isolating barriers remain poorly resolved. Here, we used quantitative proteomics in sibling <i>Drosophila</i> species to investigate the molecular composition of the FRT environment and its role in mediating species-specific postmating responses. We found that (1) FRT proteomes in <i>D. simulans</i> and<i> D. mauritiana</i> virgin females express unique combinations of secreted proteins and are enriched for distinct functional categories, (2) mating induces substantial changes to the FRT proteome in <i>D. mauritiana</i> but not in <i>D. simulans</i>, and (3) the <i>D. simulans </i>FRT proteome exhibits limited postmating changes irrespective of whether females mate with conspecific or heterospecific males, suggesting an active female role in mediating reproductive interactions. Comparisons with similar data in the closely related outgroup species <i>D. melanogaster </i>suggest that divergence is concentrated on the <i>D. simulans </i>lineage. Our study suggests that divergence in the FRT extracellular environment and postmating response contribute to previously described patterns of postmating-prezygotic isolation and the maintenance of species boundaries.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Proteomic fingerprinting enables quantitative biodiversity assessments of species and ontogenetic stages in Calanus congeners (Copepoda, Crustacea) from the Arctic Ocean
<p><span>Species identification is pivotal in biodiversity assessments, and proteomic fingerprinting by MALDI-TOF mass spectrometry has already been shown to reliably identify calanoid copepods to species level. However, MALDI-TOF data may contain more information beyond mere species identification. In this study, we investigated different ontogenetic stages (copepodids C1-C6 females) of three co-occurring <em>Calanus</em> species from the Arctic Fram Strait, which cannot be identified to species level based on morphological characters alone. Differentiation of the three species based on mass spectrometry data was without any error. In addition, a clear stage-specific signal was detected in all species, supported by clustering approaches as well as machine learning using Random Forest. More complex mass spectra in later ontogenetic stages as well as relative intensities of certain mass peaks were found as the main drivers of stage distinction in these species. Through a dilution series, we were able to show that this did not result from the higher amount of biomass that was used in tissue processing of the larger stages. Finally, the data were tested in a simulation for application in a real biodiversity assessment by using Random Forest for stage classification of specimens absent from the training data. This resulted in a successful stage-identification rate of almost 90%, making proteomic fingerprinting a promising tool to investigate polewards shifts of Atlantic <em>Calanus</em> species and, in general, to assess stage compositions in biodiversity assessments of Calanoida, which can be notoriously difficult using conventional identification methods.</span></p>
Proteomics LC-MS/MS test dataset for protein quantitation via stable isotope labelling
<p>The provided mzML file can be used as a test dataset for protein identification and quantitation software. It was generated from human embryonic kidney (HEK) cells that were either unlabelled or labelled with heavy SILAC (K6R6, unimod accession 188, PSI-MS Name: "Label:13C(6)"). Apart from different labelling, the HEK cells were kept in exactly the same conditions and harvested simultaneously. Light and heavy labelled proteins from HEK cell lysate were mixed in a certain ratio, digested with Trypsin and measured on a ThermoFisher QExactive mass spectrometer. A more detailed description on the generation of the dataset will soon be accessible at PRIDE.</p> <p>The provided mzML file has been converted from Thermo RAW and slightly modified via msConvert (ProteoWizard). To reduce the filesize and to speed up analysis, it has further been filtered to contain only the data measured between 2,000 sec and 3,000 sec of the original LC-MS/MS run.</p>
The analysis of composition and abundance of the raft proteome of microglia using a tandem mass tag (TMT)-based quantitative proteomic analysis.
<p>To determine the proteins in the membrane raft, we used the TMT-labeling and nano-liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis by Creative Proteomics (NY, USA; https://www.creative-proteomics.com/). Rat primary microglia were treated with IL-6 (25 ng/ml) for 15 min. Membrane rafts were obtained by flotation assay. Samples were prepared from three independent experiments. Proteins in equal volumes of raft fractions were digested with trypsin, desalted, and labeled with a TMT reagent (Thermo Fisher Science). The TMT-labeled peptides were fractionated and analyzed by nano-LC-MS/MS. The resulting MS/MS data were analyzed and searched against the rat protein database using Proteome Discoverer 2.1.</p>
KidDO project update - quantitative proteomic and metabolomic analysis of five mouse models with chronic kidney disease
<p>Chronic kidney disease (CKD) is one of the most deadly diseases faced by patients and is a major global health and socioeconomic burden.CKD increases cardiovascular morbidity and premature mortality and decreases quality of life. Hypertension (HTN) and type 2 diabetes mellitus (T2DM), which are reaching epidemic levels, are major risk factors for CKD. CKD diagnosis and progression is based on estimated GFR (eGFR) and urinary albumin excretion. However, eGFR only has a predictive value in advanced disease and there is risk of progressive CKD in non-albuminuric individuals. Thus, there is an urgent need for new approaches for early detection of the most “at risk” individuals and identification of CKD signatures to aid in designing novel drugs and preventive measures that could ameliorate progression of CKD.</p> <p>Our overarching goal is to identify metabolites that predict kidney cell phenotypes during CKD and how crosstalk of these metabolites with the proteome drive CKD progression. We will integrate metabolomics and proteomic information from animal models of CKD with human CKD patient biopsies to identify common signatures in the tubulointerstitium that correlate with human pathophysiology.</p> <p>Here we provide quantitative proteomic and metabolomic datasets, as well as plasma and urine electrolyte measurements on five CKD mouse models.</p>
Data from: Proteomic fingerprinting enables quantitative biodiversity assessments of species and ontogenetic stages in Calanus congeners (Copepoda, Crustacea) from the Arctic Ocean
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RNA-seq and label-free quantitative proteomics data from: KDM4A serves as an α-tubulin demethylase regulating microtubule polymerization and cell mitosis
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Data from: Quantitative proteomics reveals rapid divergence in the postmating response of female reproductive tracts among sibling species
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Data from: Quantitative proteomics reveals key roles for post-transcriptional gene regulation in the molecular pathology of FSHD
DUX4 is a transcription factor whose misexpression in skeletal muscle causes facioscapulohumeral muscular dystrophy (FSHD). While DUX4's transcriptional activity has been extensively characterized, the DUX4-induced proteome remains undescribed. Here, we report concurrent measurement of RNA and protein levels in DUX4-expressing cells via RNA-seq and quantitative mass spectrometry. DUX4 transcriptional targets were robustly translated, confirming the likely clinical relevance of proposed FSHD biomarkers. However, a multitude of mRNAs and proteins exhibited discordant expression changes upon DUX4 expression. Our dataset revealed unexpected proteomic, but not transcriptomic, dysregulation of diverse molecular pathways, including Golgi apparatus fragmentation, as well as extensive post-transcriptional buffering of stress response genes. Key components of RNA degradation machineries, including UPF1, UPF3B, and XRN1, exhibited suppressed protein, but not mRNA, levels, explaining the build-up of aberrant RNAs that characterizes DUX4-expressing cells. Our results provide a resource for the FSHD community and illustrate the importance of post-transcriptional processes to DUX4-induced pathology.
Data from: Evidence for local adaptation to extreme heat across populations of a widespread tree from quantitative proteomics
1. Heat waves are increasing in frequency and intensity globally with negative consequences for biological function. Assessing the effect of extreme heat on species requires an understanding of their adaptive capacity for mitigating physiological damage. Where long-term exposure to hot conditions in natural populations provides sufficient selection pressure, populations should exhibit signals of adaptive thermotolerance to temperature extremes. 2. Using quantitative proteomics, we tested this idea in the widespread and commercially-important tree species Eucalyptus grandis (Flooded Gum). Seedlings from six natural populations of E. grandis spanning a 2000 km gradient were exposed to a four-day extreme heat treatment (42-24°C day-night cycle) in experimental growth chambers. Populations differed in their long-term exposure to extreme heat conditions, defined both as the number of days annually ≥15°C above mean annual temperature (MAT), and average number of days annually with temperature maxima ≥ 35°C between 1960-1990. 3. Long-term exposure to extreme heat conditions in the field predicted the protein-level response of E. grandis to experimental heat waves. Relationships between long-term extreme heat exposure and protein increases were positive and linear for all combinations of extreme heat (days ≥15°C above MAT, mean days with temperature maxima ≥35°C annually) and expression (all differentially expressed proteins, isolated heat shock proteins, proteins involved in molecular stress responses). 4. Although extreme climate events are typically rare (e.g. 1 day 15° ≥ MAT per 5 years in some populations in our study), E. grandis populations sampled from across a 2000km range exhibit a clear capacity to increase expression of proteins involved in heat stress in response to simulated heat wave exposure. Presumably they respond similarly under natural heat wave conditions. 5. We show that a long-lived species with a broad environmental niche exhibits adaptive variation in protein response to temperature extremes at the population level. This implies that restoration, translocation and silvicultural programs should consider the molecular response of source populations to climatic extremes to maximise success under future climates. 6. Tree populations with low exposure to extreme heat conditions may be limited in their ability to respond to heat wave events, potentially limiting their adaptive capacity to withstand novel climate conditions.
Quantitative proteomics reveals Populus cathayana males are more responsive to solar UV-B radiation than females
<p>This data set provides the detailed information of total identified proteins in P. cathayana males and females under UV-B radiation in our experiment. To investigate the changes in the protein profiles in response to solar UV-B radiation, proteins were extracted from the poplar leaves and analyzed using an iTRAQ-based shotgun proteomics strategy. Using the Mascot search engine, a total of 6091 peptides from the trypsin-digested proteins were identified; of these, 5210 peptides were unique. A total of 2405 proteins were identified.</p>
Data for SWATH-based Quantitative Proteomic Analysis of Morus alba L. Leaf under Ultraviolet-B radiation and Dark Treatment
<p><em>Morus alba (M. alba) </em>have been used in traditional Chinese medicine. Since, previous studies indicated that the accumulation of several secondary metabolites was significantly induced by UV-B radiation with dark treatment. To investigate the response of <em>Morus alba</em> leaf to UV-B radiation and UV-B radiation followed by dark incubation (UVD), SWATH-based quantitative proteomic analysis was performed on <em>Morus alba</em> leaf of control, UV-B radiation and UV-B radiation then dark incubation. A total of 716 proteins were identified and quantified.</p>
Quantitative Proteome-wide O-Glycoproteomics Analysis with FragPipe
<p>Processed search results and parameter files supporting the analyses presented in the publication "Quantitative Proteome-wide O-Glycoproteomics Analysis with FragPipe".</p>
Quantitative Analysis of Global Proteome in Bone Samples From Patients With Osteoporotic and Nonosteoporotic Fracture
ClinicalTrials.gov study NCT03428672. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Data from: Evidence for local adaptation to extreme heat across populations of a widespread tree from quantitative proteomics
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Data from: Quantitative proteomics reveals key roles for post-transcriptional gene regulation in the molecular pathology of FSHD
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Data from: Identification of glucose kinase dependent and independent pathways for carbon control of primary metabolism, development and antibiotic production in Streptomyces coelicolor by quantitative proteomics
Members of the soil-dwelling prokaryotic genus Streptomyces are indispensable for the recycling of complex polysaccharides, and produce a wide range of natural products. Nutrient availability is a major determinant for the switch to development and antibiotic production in streptomycetes. Carbon catabolite repression (CCR), a main signaling pathway underlying this phenomenon, was so far considered fully dependent on the glycolytic enzyme glucose kinase (Glk). Here we provide evidence of a novel Glk-independent pathway in Streptomyces coelicolor, using advanced proteomics that allowed the comparison of the expression of some 2,000 proteins, including virtually all enzymes for central metabolism. While CCR and inducer exclusion of enzymes for primary and secondary metabolism and precursor supply for natural products is mostly mediated via Glk, enzymes for the urea cycle, as well as for biosynthesis of the γ-butyrolactone Scb1 and the responsive cryptic polyketide Cpk are subject to Glk-independent CCR. Deletion of glkA led to strong downregulation of biosynthetic proteins for prodigionin and calcium-dependent antibiotic (CDA) in mannitol-grown cultures. Repression of bldB, bldN, and its target bldM explains the poor development of S. coelicolor on solid-grown cultures containing glucose. A new model for carbon catabolite repression in streptomycetes is presented.
Data from: iTRAQ-based quantitative proteomic analysis on S100 calcium binding protein A2 in metastasis of laryngeal cancer
Laryngeal cancer is the most frequent neoplasm in the head and neck region, with the vast majority of tumors originating from squamous cells. The survival rate of patients with laryngeal cancer has not improved substantially over the past 25 years. To acquire further knowledge regarding the molecules responsible for laryngeal cancer oncogenesis and, in turn, to improve target therapy,iTRAQ and mass spectrometry analysis were utilized to detect differences in protein expression from 15 paired laryngeal cancer and adjacent non-cancerous tissue samples. Using mass spectrometry analysis, the expression levels of 100 proteins in laryngeal cancer samples were distinct from the non-tumor, non-cancerous samples. Further validation of the differentially expressed proteins S100A2, KRT16, FGB and HSPB1 were carried out using quantitative real-time RT-PCR, immunoblot and immunohistochemistry. Functional analysis of one of the highly expressed proteins, S100 calcium binding protein A2 (S100A2), was performed using RNA interference. As a consequence, attenuated S100A2 expression enhanced the ability of HEp-2 cell lines to migrate and invade in vitro. Our investigation complements the current understanding of laryngeal cancer progression. Furthermore, this study supports the concept that enhanced expression of S100A2 may be a promising strategy in developing novel cancer therapeutic drugs.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.