Adaptive Pixel Mass Recalibration for Mass Spectrometry Imaging Based on Locally Endogenous Biological Signals.

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 (https://github.com/LaRoccaRaphael/MSI_recalibration). 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.

Dual-polarity SALDI FT-ICR MS imaging and Kendrick mass defect data filtering for lipid analysis.

Lipids are biomolecules of crucial importance involved in critical biological functions. Yet, lipid content determination using mass spectrometry is still challenging due to their rich structural diversity. Preferential ionisation of the different lipid species in the positive or negative polarity is common, especially when using soft ionisation mass spectrometry techniques. Here, we demonstrate the potency of a dual-polarity approach using surface-assisted laser desorption/ionisation coupled to Fourier transform-ion cyclotron resonance (SALDI FT-ICR) mass spectrometry imaging (MSI) combined with Kendrick mass defect data filtering to (i) identify the lipids detected in both polarities from the same tissue section and (ii) show the complementarity of the dual-polarity data, both regarding the lipid coverage and the spatial distributions of the various lipids. For this purpose, we imaged the same mouse brain section in the positive and negative ionisation modes, on alternate pixels, in a SALDI FT-ICR MS imaging approach using gold nanoparticles (AuNPs) as dual-polarity nanosubstrates. Our study demonstrates, for the first time, the feasibility of (i) a dual-polarity SALDI-MSI approach on the same tissue section, (ii) using AuNPs as nanosubstrates combined with a FT-ICR mass analyser and (iii) the Kendrick mass defect data filtering applied to SALDI-MSI data. In particular, we show the complementarity in the lipids detected both in a given ionisation mode and in the two different ionisation modes. Graphical abstract.

Mass shift in mass spectrometry imaging: comprehensive analysis and practical corrective workflow.

MALDI mass spectrometry imaging (MSI) allows the mapping and the tentative identification of compounds based on their m/z value. In typical MSI, a spectrum is taken at incremental 2D coordinates (pixels) across a sample surface. Single pixel mass spectra show the resolving power of the mass analyzer. Mass shift, i.e., variations of the m/z of the same ion(s), may occur from one pixel to another. The superposition of shifted masses from individual pixels peaks apparently degrades the resolution and the mass accuracy in the average spectrum. This leads to low confidence annotations and biased localization in the image. Besides the intrinsic performances of the analyzer, the sample properties (local composition, thickness, matrix deposition) and the calibration method are sources of mass shift. Here, we report a critical analysis and recommendations to mitigate these sources of mass shift. Mass shift 2D distributions were mapped to illustrate its effect and explore systematically its origin. Adapting the sample preparation, carefully selecting the data acquisition settings, and wisely applying post-processing methods (i.e., m/z realignment or individual m/z recalibration pixel by pixel) are key factors to lower the mass shift and to improve image quality and annotations. A recommended workflow, resulting from a comprehensive analysis, was successfully applied to several complex samples acquired on both MALDI ToF and MALDI FT-ICR instruments.

Rapid visualization of lipopeptides and potential bioactive groups of compounds by combining ion mobility and MALDI imaging mass spectrometry.

Mass spectrometry imaging (MSI) has become a powerful method for mapping metabolite distribution in a tissue. Applied to bacterial colonies, MSI has a bright future, both for the discovery of new bioactive compounds and for a better understanding of bacterial antibiotic resistance mechanisms. Coupled with separation techniques such as ion mobility mass spectrometry (IM-MS), the identification of metabolites directly on the image is now possible and does not require additional analysis such as HPLC-MS/MS. In this article, we propose to apply a semi-targeted workflow for rapid IM-MSI data analysis focused on the search for bioactive compounds. First, chemically-related compounds showing a repetitive mass unit (i.e. lipids and lipopeptides) were targeted based on the Kendrick mass defect analysis. The detected groups of potentially bioactive compounds were then confirmed by fitting their measured ion moibilites to their measured m/z values. Using both their m/z and ion mobility values, the selected groups of compounds were identified using the available databases and finally their distribution was observed on the image. Using this workflow on a co-culture of bacteria, we were able to detect and localize bioactive compounds involved in the microbial interaction.

Combination of Capillary Zone Electrophoresis-Mass Spectrometry, Ion Mobility-Mass Spectrometry, and Theoretical Calculations for Cysteine Connectivity Identification in Peptides Bearing Two Intramolecular Disulfide Bonds.

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.

Rapid Visualization of Chemically Related Compounds Using Kendrick Mass Defect As a Filter in Mass Spectrometry Imaging.

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 data set. The method allow automated, easy and efficient data processing, enabling the reconstruction of 2D distributions of families of homologous compounds from MSI images. We show that KMD filtering, based on 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 cocultures, and brain tissue sections.

Effectiveness and Limitations of Computational Chemistry and Mass Spectrometry in the Rational Design of Target-specific Shift Reagents for Ion Mobility Spectrometry.

Ion mobility spectrometry (IMS) is a gas-phase separation technique based on ion mobility differences in an electric field. It is largely used for the detection of specific ions such as small molecule explosives. IMS detection system includes the use of e. g. a Faraday cupor mass spectrometry (MS). The presence of interfering ion signals in standalone IMS may lead to the detection of false positives or negatives due to e. g. lacking resolving power. In this case, selective mobility shifts obtained using shift reagents (SR), i. e. ligands complexing a specific target, can bring help. The effectiveness of an SR strategy relies on the SR-target ion selectivity. The crucial step lies in the SR design. The aim of this paper is to present an efficient interplay of experimental ion mobility mass spectrometry (IMMS) and predictive computational chemistry using various levels of computational efforts for rationally designing target-specific SR. Mass spectrometry is used to evaluate the efficiency of the SR selectivity with identification and semi-quantification of free and complexed ions. Minimal computational efforts allow the design of the SR, predicting the SR-target ion relative stabilities, and predicting the ion mobility shifts. We demonstrate our approach using crown ethers and ß-cyclodextrin to selectively shift interfering perchlorate, amino acids and diaminonaphthalene isomers. We also release the software ParsIMoS for the straightforward use of ion mobility calculator IMoS.

Comprehensive Ion Mobility Calibration: Poly(ethylene oxide) Polymer Calibrants and General Strategies.

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 (K0) 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 K0) using singly charged sodium adducts of poly(ethylene oxide) monomethyl ether (CH3O-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/K0 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/K0 accuracy, advantages, and limitations of the calibration procedures are also discussed. A generalized IM calibration strategy is suggested.

Correction: Supramolecular influence on cis-trans isomerization probed by ion mobility spectrometry.

Correction for 'Supramolecular influence on cis-trans isomerization probed by ion mobility spectrometry' by Izabella Czerwinska et al., Phys. Chem. Chem. Phys., 2016, 18, 32331-32336.

Accurate Drift Time Determination by Traveling Wave Ion Mobility Spectrometry: The Concept of the Diffusion Calibration.

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.

Supramolecular influence on cis-trans isomerization probed by ion mobility spectrometry.

We used tandem ion mobility spectrometry measurements to investigate how the photo-isomerization of a chromophore (a methylpyridinium derivative) is affected by the complexation with a crown ether. A dramatic blue-shift of the photo-isomerization spectrum was observed upon complexation, which could be well reproduced by ab initio calculations. Our results support that the observed changes in the photo-physical properties of the chromophore originate from the charge-solvation of its pyridinium moiety by the host cage.

The use of ion mobility mass spectrometry for isomer composition determination extracted from Se-rich yeast.

The isomer ratio determination of a selenium-containing metabolite produced by Se-rich yeast was performed. Electrospray ionization and ion mobility mass spectrometry (IM-MS) were unsuccessfully used in order to resolve the isomers according to their collisional cross section (CCS) difference. The isomer ratio determination of 2,3-dihydroxypropionylselenocystathionine was performed after multidimensional liquid chromatography preconcentration from a water extract of Se-rich yeast using preparative size exclusion, anion exchange, and capillary reverse phase columns coupled to IM-MS. 4'-nitrobenzo-15-crown-5 ether, a selective shift reagent (SSR), was added after the last chromatographic dimension in order to specifically increase the CCS of one of the isomers by the formation of a stable host-guest system with the crown ether. Both isomers were consequently fully resolved by IM-MS, and the relative ratio of the isomers was determined to be 11-13% and 87-89%. The present data compared favorably with the literature to support the analytical strategy despite the lack of an authentic standard for method validation. In addition, computational chemistry methods were successfully applied to design the SSR and to support the experimental data.

Standardized Workflow for Mass-Spectrometry-Based Single-Cell Proteomics Data Processing and Analysis Using the scp Package.

Mass-spectrometry (MS)-based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells-proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team to another. Moreover, it is difficult to evaluate pipelines as ground truths are missing. Our team has developed the R/Bioconductor package called scp to provide a standardized framework for SCP data analysis. It relies on the widely used QFeatures and SingleCellExperiment data structures. In addition, we used a design containing cell lines mixed in known proportions to generate controlled variability for data analysis benchmarking. In this chapter, we provide a flexible data analysis protocol for SCP data using the scp package together with comprehensive explanations at each step of the processing. Our main steps are quality control on the feature and cell level, aggregation of the raw data into peptides and proteins, normalization, and batch correction. We validate our workflow using our ground truth data set. We illustrate how to use this modular, standardized framework and highlight some crucial steps.

Investigation of Structure-Stabilizing Elements in Proteins by Ion Mobility Mass Spectrometry and Collision-Induced Unfolding.

A recently developed proteolytic reactor, designed for protein structural investigation, was coupled to ion mobility mass spectrometry to monitor collisional cross section (CCS) evolution of model proteins undergoing trypsin-mediated mono enzymatic digestion. As peptides are released during digestion, the CCS of the remaining protein structure may deviate from the classical 2/3 power of the CCS-mass relationship for spherical structures. The classical relationship between CCS and mass (CCS = A × M2/3) for spherical structures, assuming a globular shape in the gas phase, may deviate as stabilizing elements are lost during digestion. In addition, collision-induced unfolding (CIU) experiments on partially digested proteins provided insights into the CCS resilience in the gas phase to ion activation, potentially due to the presence of stabilizing elements. The study initially investigated a model peptide ModBea (3 kDa), assessing the impact of disulfide bridges on CCS resilience in both reduced and oxidized forms. Subsequently, ß-lactoglobulin (2 disulfide bridges), calmodulin (Ca2+ coordination cation), and cytochrome c (heme) were selected to investigate the influence of common structuring elements on CCS resilience. CIU experiments probed the unfolding process, evaluating the effect of losing specific peptides on the energy landscapes of partially digested proteins. Comparisons of the TWCCSN2→He to trend curves describing the CCS/mass relationship revealed that proteins with structure-stabilizing elements consistently exhibit TWCCSN2→He and greater resilience toward CIU compared to proteins lacking these elements. The integration of online digestion, ion mobility, and CIU provides a valuable tool for identifying structuring elements in biopolymers in the gas phase.

Exploiting Differential Signal Filtering (DSF) and Image Structure Filtering (ISF) Methods for Untargeted Mass Spectrometry Imaging of Bacterial Metabolites.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a label-free technique, producing images where pixels contain mass spectra. The technique allows the visualization of the spatial distribution of (bio)molecules from metabolites to proteins, on surfaces such as tissues sections or bacteria culture media. One particularly exciting example of MALDI-MSI use rests on its potential to localize ionized compounds produced during microbial interactions and chemical communication, offering a molecular snapshot of metabolomes at a given time. The huge size and the complexity of generated MSI data make the processing of the data challenging, which requires the use of computational methods. Despite recent advances, currently available commercial software relies mainly on statistical tools to identify patterns, similarities, and differences within data sets. However, grouping m/z values unique to a given data set according to microbiological contexts, such as coculture experiments, still requires tedious manual analysis. Here we propose a nontargeted method exploiting the differential signals between negative controls and tested experimental conditions, i.e., differential signal filtering (DSF), and a scoring of the ion images using image structure filtering (ISF) coupled with a fold change score between the controls and the conditions of interest. These methods were first applied to coculture experiments involving Escherichia coli and Streptomyces coelicolor, revealing specific MS signals during bacterial interaction. Two case studies were also investigated: (i) cellobiose-mediated induction for the pathogenicity of Streptomyces scabiei, the causative agent of common scab on root and tuber crops, and (ii) iron-repressed production of siderophores of S. scabiei. This report proposes guidelines for MALDI-MSI data treatment applied in the case of microbiology contexts, with enhanced ion peak annotation in specific culture conditions. The strengths and weaknesses of the methods are discussed.

Geometric Analysis of Shapes in Ion Mobility-Mass Spectrometry.

Experimental ion mobility-mass spectrometry (IM-MS) results are often correlated to three-dimensional structures based on theoretical chemistry calculations. The bottleneck of this approach is the need for accurate values, both experimentally and theoretically predicted. Here, we continue the development of the trend-based analyses to extract structural information from experimental IM-MS data sets. The experimental collision cross-sections (CCSs) of synthetic systems such as homopolymers and small ionic clusters are investigated in terms of CCS trends as a function of the number of repetitive units (e.g., degree of polymerization (DP) for homopolymers) and for each detected charge state. Then, we computed the projected areas of expanding but perfectly defined geometric objects using an in-house software called MoShade. The shapes were modeled using computer-aided design software where we considered only geometric factors: no atoms, mass, chemical potentials, or interactions were taken into consideration to make the method orthogonal to classical methods for 3D shape assessments using time-consuming computational chemistry. Our modeled shape evolutions favorably compared to experimentally obtained CCS trends, meaning that the apparent volume or envelope of homogeneously distributed mass effectively modeled the ion-drift gas interactions as sampled by IM-MS. The CCSs of convex shapes could be directly related to their surface area. More importantly, this relationship seems to hold even for moderately concave shapes, such as those obtained by geometry-optimized structures of ions from conventional computational chemistry methods. Theoretical sets of expanding beads-on-a-string shapes allowed extracting accurate bead and string dimensions for two homopolymers, without modeling any chemical interactions.

Label-Free Higher Order Structure and Dynamic Investigation Method of Proteins in Solution Using an Enzymatic Reactor Coupled to Electrospray High-Resolution Mass Spectrometry Detection.

For decades, structural analysis of proteins have received considerable attention, from their sequencing to the determination of their 3D structures either in the free state (e.g., no host-guest system, apoproteins) or (non)covalently bound complexes. The elucidation of the 3D structures and the mapping of intra- and intermolecular interactions are valuable sources of information to understand the physicochemical properties of such systems. X-ray crystallography and nuclear magnetic resonance are methods of choice for obtaining structures at the atomic level. Nonetheless, they still present drawbacks which limit their use to highly purified systems in a relatively high amount. On the contrary, mass spectrometry (MS) has become a powerful tool thanks to its selectivity, sensitivity, and the development of structural methods both at the global shape and the residue level. The combination of several MS-based methods is mandatory to fully assign a putative structure in combination with computational chemistry and bioinformatics. In that context, we propose a strategy which complements the existing methods of structural studies (e.g., circular dichroism, hydrogen/deuterium exchange and cross-links experiments, nuclear magnetic resonance). The workflow is based on the collection of structural information on proteins from the apparition rates and the time of appearance of released peptides generated by a protease in controlled experimental conditions with online detection by electrospray high-resolution mass spectrometry. Nondenaturing, partially or fully denatured proteins were digested by the enzymatic reactor, i.e., ß-lactoglobulin, cytochrome c, and ß-casein. The collected data are interpreted with regard to the kinetic schemes with time-dependent rates of the enzymatic digestion established beforehand, considering kinetics parameters in the Michaelis-Menten formalism including kcat (the turnover number), k1 (formation of the enzyme-substrate complex), k-1 (dissociation of the enzyme-substrate complex), koff (local refolding of the protein around the cleavage site), and kon (local unfolding of the protein around the cleavage site). Solvent-accessible surface analysis through digestion kinetics was also investigated. The initial apparition rates of released peptides varied according to the protein state (folded vs denatured) and informs the koff/kon ratio around the cleavage site. On the other hand, the time of appearance of a given peptide is related to its solvent accessibility and to the resilience of the residual protein structure in solution. Temperature-dependent digestion experiments allowed estimation of the type of secondary structures around the cleavage site.

Differential Kendrick's Plots as an Innovative Tool for Lipidomics in Complex Samples: Comparison of Liquid Chromatography and Infusion-Based Methods to Sample Differential Study.

Lipidomics has developed rapidly over the past decade. Nontargeted lipidomics from biological samples remains a challenge due to the high structural diversity, the concentration range of lipids, and the complexity of biological samples. We introduce here the use of differential Kendrick's plots as a rapid visualization tool for a qualitative nontargeted analysis of lipids categories and classes from data generated by either liquid chromatography-mass spectrometry (LC-MS) or direct infusion (nESI-MS). Each lipid class is easily identified by comparison with the theoretical Kendrick plot pattern constructed from exact mass measurements and by using MSKendrickFilter, an in-house Python software. The lipids are identified with the LIPID MAPS database. In addition, in LC-MS, the software based on the Kendrick plots returns the retention time from all the lipids belonging to the same series. Lipid extracts from a yeast (Saccharomyces cerevisiae) are used as a model. An on/off case comparing Kendrick plots from two cell lines (prostate cancer cell lines treated or not with a DGAT2 inhibition) clearly shows the effect of the inhibition. Our study demonstrates the good performance of direct infusion as a fast qualitative screening method as well as for the analysis of chromatograms. A fast screening semiquantitative approach is also possible, while the targeted mode remains the golden standard for precise quantitative analysis.

Cyclic Peptide Protomer Detection in the Gas Phase: Impact on CCS Measurement and Fragmentation Patterns.

With the recent improvements in ion mobility resolution, it is now possible to separate small protomeric tautomers, called protomers. In larger molecules above 1000 Da such as peptides, a few studies suggest that protomers do exist as well and may contribute to their gas-phase conformational heterogeneity. In this work, we observed a CCS distribution that can be explained by the presence of protomers of surfactin, a small lipopeptide with no basic site. Following preliminary density functional theoretical calculations, several protonation sites in the gas phase were energetically favorable in positive ionization mode. Experimentally, at least three near-resolved IM peaks were observed in positive ionization mode, while only one was detected in negative ionization mode. These results were in good agreement with the DFT predictions. CID breakdown curve analysis after IM separation showed different inflection points (CE50) suggesting that different intramolecular interactions were implied in the stabilization of the structures of surfactin. The fragment ratio observed after collision-induced fragmentation was also different, suggesting different ring-opening localizations. All these observations support the presence of protomers on the cyclic peptide moieties of the surfactin. These data strongly suggest that protomeric tautomerism can still be observed on molecules above 1000 Da if the IM resolving power is sufficient. It also supports that the proton localization involves a change in the 3D structure that can affect the experimental CCS and the fragmentation channels of such peptides.

Using Ion Mobility-Mass Spectrometry to Extract Physicochemical Enthalpic and Entropic Contributions from Synthetic Polymers.

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.