The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.
Recently developed methods of ambient ionization allow the collection of mass spectrometric datasets for biological and medical applications at an unprecedented pace. One of the areas that could employ such analysis is neurosurgery. The fast in situ identification of dissected tissues could assist the neurosurgery procedure. In this paper tumor tissues of astrocytoma and glioblastoma are compared. The vast majority of the data representation methods are hard to use, as the number of features is high and the amount of samples is limited. Furthermore, the ratio of features and samples number restricts the use of many machine learning methods. The number of features could be reduced through feature selection algorithms or dimensionality reduction methods. Different algorithms of dimensionality reduction are considered along with the traditional noise thresholding for the mass spectra. From our analysis, the Isomap algorithm appears to be the most effective dimensionality reduction algorithm for negative mode, whereas the positive mode could be processed with a simple noise reduction by a threshold. Also, negative and positive mode correspond to different sample properties: negative mode is responsible for the inner variability and the details of the sample, whereas positive mode describes measurement in general.
The gas-phase adsorption of N2 on protonated serine (Ser, C3H7NO3), threonine (Thr, C4H9NO3), glycine (Gly, C2H5NO2), and 2-aminoethanol (C2H7NO) was investigated using a tandem mass spectrometer equipped with an electrospray ionization source and a cold ion trap. N2 molecules were adsorbed on the free X–H (X=O and N) groups of protonated molecules. Gas-phase N2 adsorption-mass spectrometry detected the presence of free X–H groups in the molecular structures, and was applied to the structural elucidation of small molecules. When the 93 structures with an elemental composition of C3H7NO3 were filtered using the gas-phase N2 adsorption-mass spectrometry results for Ser, the number of possible molecular structures was reduced to 8 via the quantification of the X–H groups. Restricting and minimizing the number of possible candidates were effective steps in the structural elucidation process. Gas-phase N2 adsorption-mass spectrometry combined with mass spectrometry-based techniques has the potential for being useful for elucidating the molecular structures of a variety of molecules.