Ion mobility (IM) is now a well-established and fast analytical technique. The IM hardware is constantly being improved, especially in terms of the resolving power. The Drift Tube (DTIMS), the Traveling Wave (TWIMS), and the Trapped Ion Mobility Spectrometry (TIMS) coupled to mass spectrometry are used to determine the Collision Cross-Sections (CCS) of ions. In analytical chemistry, the CCS is approached as a descriptor for ion identification and it is also used in physical chemistry for 3D structure elucidation with computational chemistry support. The CCS is a physical descriptor extracted from the reduced mobility (K) measurements obtainable only from the DTIMS. TWIMS and TIMS routinely require a calibration procedure to convert measured physical quantities (drift time for TWIMS and elution voltage for TIMS) into CCS values. This calibration is a critical step to allow interinstrument comparisons. The previous calibrating substances lead to large prediction bands and introduced rather large uncertainties during the CCS determination. In this paper, we introduce a new IM calibrant (CCS and K) using singly charged sodium adducts of poly(ethylene oxide) monomethyl ether (CHO-PEO-H) for positive ionization in both helium and nitrogen as drift gas. These singly charged calibrating ions make it possible to determine the CCS/K of ions having higher charge states. The fitted calibration plots exhibit larger coverage with less data scattering and significantly improved prediction bands and uncertainties. The reasons for the improved CCS/K accuracy, advantages, and limitations of the calibration procedures are also discussed. A generalized IM calibration strategy is suggested.

Kendrick mass defect (KMD) analysis is widely used for helping the detection and identification of chemically related compounds based on exact mass measurements. We report here the use of KMD as a criterion for filtering complex mass spectrometry dataset. The method enables an automated, easy and efficient data processing, enabling the reconstruction of 2D distributions of family of homologous compounds from MSI images. We show that the KMD filtering, based on an in-house software, is suitable and robust for high resolution (full width at half-maximum, FWHM, at m/z 410 of 20 000) and very high-resolution (FWHM, at m/z 410 of 160 000) MSI data. This method has been successfully applied to two different types of samples, bacteria co-cultures and brain tissue section.

Ion mobility spectrometry (IMS) is a gas phase separation technique, which relies on differences in collision cross section (CCS) of ions. Ionic clouds of unresolved conformers overlap if the CCS difference is below the instrumental resolution expressed as CCS/ΔCCS. The experimental arrival time distribution (ATD) peak is then a superimposition of the various contributions weighted by their relative intensities. This paper introduces a strategy for accurate drift time determination using traveling wave ion mobility spectrometry (TWIMS) of poorly resolved or unresolved conformers. This method implements through a calibration procedure the link between the peak full width at half-maximum (fwhm) and the drift time of model compounds for wide range of settings for wave heights and velocities. We modified a Gaussian equation, which achieves the deconvolution of ATD peaks where the fwhm is fixed according to our calibration procedure. The new fitting Gaussian equation only depends on two parameters: The apex of the peak (A) and the mean drift time value (μ). The standard deviation parameter (correlated to fwhm) becomes a function of the drift time. This correlation function between μ and fwhm is obtained using the TWIMS calibration procedure which determines the maximum instrumental ion beam diffusion under limited and controlled space charge effect using ionic compounds which are detected as single conformers in the gas phase. This deconvolution process has been used to highlight the presence of poorly resolved conformers of crown ether complexes and peptides leading to more accurate CCS determinations in better agreement with quantum chemistry predictions.

Over the years, polymer analyses using ion mobility-mass spectrometry (IM-MS) measurements have been performed on different ion mobility spectrometry (IMS) setups. In order to be able to compare literature data taken on different IM(-MS) instruments, ion heating and ion temperature evaluations have already been explored. Nevertheless, extrapolations to other analytes are difficult and thus straightforward same-sample instrument comparisons seem to be the only reliable way to make sure that the different IM(-MS) setups do not greatly change the gas-phase behavior. We used a large range of degrees of polymerization (DP) of poly(ethylene oxide) PEO homopolymers to measure IMS drift times on three different IM-MS setups: a homemade drift tube (DT), a trapped (TIMS), and a traveling wave (T-Wave) IMS setup. The drift time evolutions were followed for increasing polymer DPs (masses) and charge states, and they are found to be comparable and reproducible on the three instruments. ᅟ.

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Mass spectrometry imaging (MSI) is a powerful and convenient method for revealing the spatial chemical composition of different biological samples. Molecular annotation of the detected signals is only possible if a high mass accuracy is maintained over the entire image and the m/z range. However, the change in the number of ions from pixel-to-pixel of the biological samples could lead to small fluctuations in the detected m/z-values, called mass shift. The use of internal calibration is known to offer the best solution to avoid, or at least to reduce, mass shifts. Their “a priori” selection for a global MSI acquisition is prone to false positive detection and therefore to poor recalibration. To fill this gap, this work describes an algorithm that recalibrates each spectrum individually by estimating its mass shift with the help of a list of pixel-specific internal calibrating ions, automatically generated in a data-adaptive manner (). Through a practical example, we applied the methodology to a zebrafish whole-body section acquired at a high mass resolution to demonstrate the impact of mass shift on data analysis and the capability of our algorithm to recalibrate MSI data. In addition, we illustrate the broad applicability of the method by recalibrating 31 different public MSI data sets from METASPACE from various samples and types of MSI and show that our recalibration significantly increases the numbers of METASPACE annotations (gaining from 20 up to 400 additional annotations), particularly the high-confidence annotations with a low false discovery rate.

Ion mobility–mass spectrometry (IM-MS) experiments are mostly used hand in hand with computational chemistry to correlate mobility measurements to the shape of the ions. Recently, we developed an automatable method to fit IM data obtained with synthetic homopolymers (i.e., collision cross sections; CCS) without resorting to computational chemistry. Here, we further develop the experimental IM data interpretation to explore physicochemical properties of a series of nine polymers and their monomer units by monitoring the relationship between the CCS and the degree of polymerization (DP). Several remarkable points of the CCS evolutions as a function of the DP were found: the first observed DP of each charge state (ΔDPfirst DP), the DPs constituting the structural rearrangements (ΔDPrearr), and the DPs at the half-rearrangement (DPhalf‑rearr). Given that these remarkable points do not rely on absolute CCS values, but on their relative evolution, they can be extracted from CCS or raw IM data without accurate IM calibration. Properties such as coordination numbers of the cations, steric hindrance, or side chain flexibility can be compared. This leads to fit parameter predictions based on the nature of the monomer unit. The interpretation of the fit parameters, extracted using solely experimental data, allows a rapid screening of the properties of the polymers.

Disulfide bonds between cysteine residues are commonly involved in the stability of numerous peptides and proteins and are crucial for providing biological activities. In such peptides, the appropriate cysteine connectivity ensures the proper conformation allowing an efficient binding to their molecular targets. Disulfide bond connectivity characterization is still challenging and is a critical issue in the analysis of structured peptides/proteins targeting pharmaceutical or pharmacological utilizations. This study describes the development of new and fast gas-phase and in-solution electrophoretic methods coupled to mass spectrometry to characterize the cysteine connectivity of disulfide bonds. For this purpose, disulfide isomers of three peptides bearing two intramolecular disulfide bonds but different cysteine connectivity have been investigated. Capillary zone electrophoresis and ion mobility both coupled to mass spectrometry were used to perform the separation in both aqueous and gas phases, respectively. The separation efficiency of each technique has been critically evaluated and compared. Finally, theoretical calculations were performed to support and explain the experimental data based on the predicted physicochemical properties of the different peptides.