Project description:A quadrupole time-of-flight mass spectrometry coupled with a trapped ion mobility mass spectrometer operated in parallel accumulation-serial fragmentation mode has recently emerged as proteome profiling platform capable of providing four dimensional features of elution time, collision cross section, precursor and fragment ion masses of peptides. The PASEF mode has demonstrated its superior performance by providing nearly 100% ion sampling efficiency both in data-dependent acquisition and data-independent acquisition modes without sacrificing sensitivity. In addition, the substantial gain in selectivity has been proven in targeted measurements using PASEF integrated parallel reaction monitoring mode. However, because these are emerging technologies in the field of proteomics, their applicability to clinical samples has been less investigated. Cerebrospinal fluid is in direct contact with brain and has been shown to contain biomarkers related to a variety of neurological diseases although the proteomics data have been mainly generated using orbitrap-based mass spectrometers. Thus, we acquired in-depth proteome profiles of human CSF in DDA mode to generate a spectral library of 3,478 proteins. The benefit of applying the spectral library to PRM experiments was demonstrated by using CSF samples from 15 Alzheimer’s disease patients and 19 controls and utilizing the spectral library to determine elution times and ion mobility values of targeting peptide. Further, we acquired DIA data from the same CSF samples, and analyzed using the spectral library without additional efforts to generate study-specific library, which also resulted in sensitive protein identification compared to a library-free approach. Overall, we established resource of CSF proteome profiles with 4D features and demonstrated the significant gain for designing and analyzing targeted and DIA studies, which is expected to facilitate 4D proteomics of CSF to study various neurological disorders.

Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.

Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.

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Synchro-PASEF allows precursor-specific fragment ion extraction and interference removal in data-independent acquisition

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