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.
Project description:Untargeted-metabolomics LC-MS/MS analysis of commercial natural products pool, analyzed with different DDA settings with the objective to find the best one.
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:In this experiment, 3 replicate phosphopeptide enrichments using titanium dioxide spin tips (GL Science) of the filamentous fungus Magnaporthe oryzae were measured on a) Orbitrap Exploris 480 in DDA and b) timsTOF Pro 2 in DIA for comparison of model/acquisition type differences.
Project description:<p>We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent identification algorithm requiring matches by both MS and MS/MS data, MetaboKit provides identification results with significantly greater specificity than the competing software packages without loss in sensitivity. The proposed MS/MS-based screening of ISFs also reduces the chance of unverifiable identification of ISFs considerably. MetaboKit's quantification module produced peak area values highly correlated with known concentrations in a DIA analysis of the metabolite standards at both MS1 and MS2 levels. Moreover, the analysis of Cdk1Liv-/- mouse livers showed that MetaboKit can identify a wide range of lipid species and their ISFs, and quantitatively reconstitute the well-characterized fatty liver phenotype in these mice. In DIA data, the MS1-level and MS2-level peak area data produced similar fold change estimates in the differential abundance analysis, and the MS2-level peak area data allowed for quantitative comparisons in compounds whose precursor ion chromatogram was too noisy for peak integration.</p><p><br></p><p><strong>Standard mixture assay</strong> is reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS1311' rel='noopener noreferrer' target='_blank'><strong>MTBLS1311</strong></a>.</p><p><strong>Mouse liver assays</strong> are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS1266' rel='noopener noreferrer' target='_blank'><strong>MTBLS1266</strong></a>.</p>