Dataset Information

The demo dataset of ApuQuant for testing

ABSTRACT: The demo dataset of ApuQuant for testing consists of DIA data acquired by Orbitrap Astral mass spectrometer. This submission includes two demo datasets together with the corresponding DIA-NN identification results. Demo Data I contains raw files from low-input samples with four technical replicates, as well as the corresponding DIA-NN identification results. Demo Data II contains raw files from dead cell samples with three technical replicates and large-sized cell samples with three technical replicates, together with the corresponding DIA-NN identification results. These datasets are provided as representative test data for evaluating the performance of ApuQuant on challenging DIA proteomics samples, including low-input samples and biologically distinct cell populations. The raw mass spectrometry files and search results can be used for demonstration, benchmarking, and reproducibility assessment of the ApuQuant workflow.

ORGANISM(S): Homo Sapiens

SUBMITTER: Chao Liu

PROVIDER: PXD075426 | iProX | Mon Mar 09 00:00:00 GMT 2026

REPOSITORIES: iProX

ACCESS DATA

Similar Datasets

Project description:This dataset contains label-free DIA proteomics of liver tissue from postnatal day 10 (P10) Taiwanese SMA mice (genotype: Smn−/−; SMN2tg/0), heterozygous carriers (HET, Smn+/−; SMN2tg/0), and wild-type controls (WT, Smn+/+; SMN2 0/0). SMA and HET samples were littermates generated from the same FVB/N × C57BL/6 mixed-background colony, whereas WT controls were age-matched animals on a C57BL/6 background. Whole-liver lysates were processed by in-solution protein digestion and analyzed using data-independent acquisition (DIA) LC–MS/MS on a Thermo Orbitrap Exploris 480 mass spectrometer equipped with a FAIMS Pro differential ion mobility device. A Vanquish Neo nano-HPLC system (Thermo Scientific) was coupled to the mass spectrometer for chromatographic separation. Peptide and protein identification and quantification were performed with DIA-NN v1.8.1using a predicted spectral library generated from the Mus musculus UniProt canonical FASTA file (accession UP000000589, downloaded 2024-01-04). The DIA-NN output was filtered at 1% precursor- and protein-level FDR (global q-value ≤ 0.01), with additional quality filters applied in R (≥ 4 fragment ions per precursor, library q-value ≤ 0.01, unique peptides only). Final LFQ intensities were calculated using the DIA-NN R package, and downstream statistical analysis was performed in Perseus v1.6.15. All RAW files generated during data acquisition are included in this dataset. One SMA biological replicate was identified as an outlier by principal component analysis and excluded from downstream statistical comparisons in the accompanying manuscripts: this corresponds to SMN biological replicate 5 (Raw file: E3_CoIID_656_3632_LI_165). Its RAW file and corresponding DIA-NN output tables are provided here for completeness, transparency, and reproducibility. The dataset contains the original RAW files, DIA-NN search output tables (.tsv), the predicted spectral library used for identification, and the Mus musculus UniProt FASTA database employed for database searching. Experimental factors encoded in the metadata include genotype (WT, HET, SMA) and tissue (liver).

Project description:This submission includes MS data for the paper titled "Suppression of pain transmission and behavior by inhibition of peripheral diacylglycerol metabolism", submitted to Cell Chemical Biology.Summary:Diacylglycerol lipase (DAGL) produce 2-arachidonoylglycerol (2-AG) and other proinflammatory lipids. Inactivation of DAGLs reduces the production of 2-AG, arachidonic acid (AA) and eicosanoids and elicits antinociceptive and anti-(neuro)inflammatory effects in rodents. However, inhibitors that enter the brain can cause significant central nervous system (CNS) side effects. Using activity-based protein profiling (ABPP), we report the discovery of A1480LS, a potent, in vivo active, small molecule dual inhibitor of DAGLα/β that is functionally biased to the periphery. We demonstrate that A1480LS reduces pain in animal models of both inflammatory and neuropathic pain. Moreover, A1480LS accomplishes this by reducing 2-AG and other lipids in peripheral tissues, all without causing adverse CNS effects of seizures. Overall, we show that inhibiting DAG metabolism in the periphery elicits antinociceptive effects that can be functionally dissected from adverse central effects and provide preclinical validation for a non-narcotic strategy to treat pain.Raw files for the selectivity experiment profiling of A1480LS in THP1 cells are listed below. Search and quantification results bearing the same file stem are also provided, as well as the fasta database that was used: uniprot_HumanComplete_121105_cdhit98_plus_Reverse_wContaminants150305.fasta.- RAH-NB1-208_A_03.rawRaw files for the in vivo time course experiment in rat kidneys are listed below. A Skyline export bearing the same name is also provided, as well as the fasta database that was used: uniprot_6organism_constructs_contaminants_20190213_forPRMJOB.fasta.- NN-NB2-213_A1.raw: 0h, Vehicle- NN-NB2-213_A2.raw: 0h, Vehicle- NN-NB2-213_A3.raw: 0h, Vehicle- NN-NB2-213_A4.raw: 0h, Vehicle- NN-NB2-213_B1.raw: 1h, A1480LS- NN-NB2-213_B2.raw: 1h, A1480LS- NN-NB2-213_B3.raw: 1h, A1480LS- NN-NB2-213_B4.raw: 1h, A1480LS- NN-NB2-213_B5.raw: 4h, A1480LS- NN-NB2-213_B6.raw: 4h, A1480LS- NN-NB2-213_B7.raw: 4h, A1480LS- NN-NB2-213_B8.raw: 4h, A1480LS- NN-NB2-213_B9.raw: 8h, A1480LS- NN-NB2-213_B10.raw: 8h, A1480LS- NN-NB2-213_B11.raw: 8h, A1480LS- NN-NB2-213_B12.raw: 12h, A1480LS- NN-NB2-213_C1.raw: 12h, A1480LS- NN-NB2-213_C2.raw: 12h, A1480LS- NN-NB2-213_C3.raw: 12h, A1480LS- NN-NB2-213_C4.raw: 24h, A1480LS- NN-NB2-213_C5.raw: 24h, A1480LS- NN-NB2-213_C6.raw: 24h, A1480LS- NN-NB2-213_C7.raw: 24h, A1480LS- NN-NB2-213_C8.raw: 32h, A1480LS- NN-NB2-213_C9.raw: 32h, A1480LS- NN-NB2-213_C10.raw: 32h, A1480LS- NN-NB2-213_C11.raw: 32h, A1480LS

Dataset Information

The demo dataset of ApuQuant for testing

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets