Project description:We investigated the combined sensitivity of micro-flow liquid chromatography with a ZenoTOF mass spectrometer for high throughput proteomic and phosphoproteomic analysis of rat tissues. Comparing the proteomes acquired using data-independent acquisition (DIA) on the ZenoTOF 7600 with the previous generation TripleTOF 6600, more proteins were quantified using a fifth of the sample load and a third of the instrument time. Zeno SWATH data was evaluated using replicate injections of rat organ digests to compare FragPipe and DIA-NN computational pipelines. FragPipe identified more proteins in 7 of the 8 rat organs, with an extra 12% and 17% observed in heart and muscle tissue respectively. The number of identified peptides per protein were higher with FragPipe and the precision of missing values across replicate injections was more consistent. Single-shot phosphopeptide enrichment from 100 µg rat tissue, without fractionation, was acquired using data-dependent acquisition (DDA) on both instruments. A total of 5,108 phosphosites were quantified with a negligible increase in phosphosites found using the ZenoTOF 7600 relative to the 6600. Using DIA on the ZenoTOF, 8,013 phosphosites were quantified using Spectronaut.
Project description:Generation of a new library of targeted mass spectrometry assays for accurate protein quantification in triple negative breast cancer (TNBC) tissues. Primary tumor tissue lysates from 105 TNBC patients treated at Masaryk Memorial Cancer Institute (MMCI) in Brno, Czech Republic, were used to generate the spectral library. This project covers raw files from data-dependent acquisition (DDA) – parallel accumulation-serial fragmentation (PASEF) measurements of 12 hydrophilic chromatography (HILIC) fractions of aliquot pool from complete set of 105 samples measured on timsTOF Pro; raw files of 16 individual samples measured in data-independent acquisition (DIA) – PASEF mode and used for hybrid library generation and for demonstrative quantitative DIA data extraction; Pulsar archive generated in Spectronaut 16.0 from 12 DDA-PASEF measurements of HILIC fractions and from 16 data-independent acquisition DIA-PASEF measurements of individual samples. The 16 DIA-PASEF runs of individual samples used for library generation were analyzed using newest versions of Spectronaut (version 18.5) and DIA-NN (version 1.8.1) software tools in library-based setting using the newly generated library as well as in library-free setting showing library-based method to outperform the use of predicted libraries in the terms of identification numbers.
Project description:These data cover all of the analyses described in the paper "Specter: linear deconvolution as a new paradigm for targeted analysis of data-independent acquisition mass spectrometry proteomics". Specifically, the data consist of - 20 DIA and DDA files from the HEK293T/synthetic phosphopeptides spike-in experiments - 10 DDA files, one for each of ten fractions of an E. coli lysate digest - 14 DIA files for the experiments involving mixtures of synthetic peptides - 11 DDA files for the isolated runs of these synthetic peptides - 84 DIA files for measurements of the phosphoproteome of perturbed PC3 cells - 10 DDA files for spectral library construction for the phosphoproteomics data - 3 DIA and 3 DDA files for analysis of an unfractionated E. coli lysate digest. See the spreadsheet "Specter Datasets Catalog.xlsx" for further descriptions and file metadata.
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.
Project description:Data Independent Acquisition (DIA) is increasingly preferred over Data Dependent Acquisition (DDA) due to its higher throughput and fewer missing values. Whereas DDA often utilizes stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mTRAQ and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios. Spike-in SILAC methods utilize an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA with spike-in SILAC (DIA-SiS), leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed and rigorously validated DIA-SiS through a mixed-species benchmark to assess its performance in proteome coverage and quantification. We demonstrate that DIA-SiS significantly improves proteome coverage and quantification compared to label-free approaches and reduces the incidence of incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded (FFPE) tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate and comprehensive proteome profiling.
Project description:The study investigated presentation of HLA A2 restricted H3.3K27M neopeptide using immunopeptidomics followed by DDA and/or targeted multiple monitoring reaction (MRM).
Project description:Breast cancer is the most prevalent cancer in women worldwide. Triple-negative breast cancer (TNBC) is characterized by the lack of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. It is the most aggressive subtype of breast cancer and accounts for 12-20% of all breast cancer cases. TNBC is associated with younger age of onset, greater metastatic potential, higher incidence of relapse, and lower overall survival rates. Based on molecular phenotype, TNBC has been classified into six subtypes (BL1, BL2, M, MES, LAR, and IM). TNBC treatment is challenging due to its heterogeneity, highly invasive nature, and relatively poor therapeutics response. Chemotherapy and radiotherapy are conventional strategies for the treatment of TNBC. Recent research in TNBC and mechanistic understanding of disease pathogenesis using cutting-edge technologies has led to the unfolding of new lines of therapies that have been incorporated into clinical practice. Poly (ADP-ribose) polymerase and immune checkpoint inhibitors have made their way to the current TNBC treatment paradigm. This review focuses on the classification, features, and treatment progress in TNBC. Histological subtypes connected to recurrence, molecular classification of TNBC, targeted therapy for early and advanced TNBC, and advances in non-coding RNA in therapy are the key highlights in this review.
Project description:A mass spectrometry (MS) method is described here that can reproducibly identify hundreds of peptides across multiple experiments. The method uses intelligent data acquisition to precisely target peptides while simultaneously identifying thousands of other, nontargeted peptides in a single nano-LC-MS/MS experiment. We introduce an online peptide elution order alignment algorithm that targets peptides based on their relative elution order, eliminating the need for retention-time-based scheduling. We have applied this method to target 500 mouse peptides across six technical replicate nano-LC-MS/MS experiments and were able to identify 440 of these in all six, compared with only 256 peptides using data-dependent acquisition (DDA). A total of 3757 other peptides were also identified within the same experiment, illustrating that this hybrid method does not eliminate the novel discovery advantages of DDA. The method was also tested on a set of mice in biological quadruplicate and increased the number of identified target peptides in all four mice by over 80% (826 vs 459) compared with the standard DDA method. We envision real-time data analysis as a powerful tool to improve the quality and reproducibility of proteomic data sets.