Native LESA TWIMS-MSI: Spatial, Conformational, and Mass Analysis of Proteins and Protein Complexes

Abstract

We have previously demonstrated native liquid extraction surface analysis (LESA) mass spectrometry imaging of small intact proteins in thin tissue sections. We also showed calculation of collision cross sections for specific proteins extracted from discrete locations in tissue by LESA traveling wave ion mobility spectrometry (TWIMS). Here, we demonstrate an integrated native LESA TWIMS mass spectrometry imaging (MSI) workflow, in which ion mobility separation is central to the imaging experiment and which provides spatial, conformational, and mass information on endogenous proteins in a single experiment. The approach was applied to MSI of a thin tissue section of mouse kidney. The results show that the benefits of integration of TWIMS include improved specificity of the ion images and the capacity to calculate collision cross sections for any protein or protein complex detected in any pixel (without a priori knowledge of the presence of the protein).

Figure 1

(a) Kidney section with pixel grid overlaid. (b) Ion image for m/z 2894.7 (11⁺), corresponding to hemoglobin heterodimer. (c) The raw mass spectrum (i.e., without arrival time filtering) obtained from pixel 48. Peaks corresponding to a hemoglobin heterotetramer and heterodimer are observed. (d) The raw mass spectrum obtained from pixel 42 reveals low ion abundance.

Figure 2

Ion images for Hb α^H 7+ monomer (a–c), αβ^2H 11+ dimer (d–f), and (αβ^2H)₂¹⁵⁺ tetramer (g–i) produced without arrival time (t_A) filtering (a,d,g), with a broad selection rule that predominantly removed singly charged signals (b,e,h), and with a specific t_A selected for each ion of interest (c,f,i). Color bars indicate normalized signal intensity after baseline subtraction.

Figure 3

Comparison of ion images for m/z 1241.65 ± 1 where (a) includes signals at all arrival times (t_A), whereas (d) is restricted to signals with t_A between 5.4 and 8.2 ms. The raw spectrum for pixel 34 (b) shows low intensity peaks for β-thymosin 4 are lost within the baseline signals, but t_A filtering increases the S/N ratio (e). With baseline subtraction during image processing, real ion signals within the baseline may be lost entirely (c). The increased S/N provided by specific t_A filtering in (e) improved detection of β-thymosin signals in pixel 34 (f). Color bars in (a) and (d) indicate normalized intensity after baseline subtraction.

Figure 4

(a) Mass spectrum for pixel 48 after background subtraction (MassLynx function, polynomial order 15, 10% below curve) with labels indicating the peaks for heme-coordinated ions; hemoglobin tetramer (αβ^2H)₂, heterodimer (αβ^2H), and monomer (α^H). Arrival time distributions are shown for (b) [(αβ^2H)₂]¹⁵⁺, (c) [(αβ^2H)]¹⁰⁺, and (d) [α^H]⁷⁺. Errors indicate one standard deviation above and below the mean value of three measurements at TW heights of 24 (red), 25 (blue), and 26 V (black).