Collision-Induced Unfolding Reveals Disease-Associated Stability Shifts in Mitochondrial Transfer Ribonucleic Acids

Abstract

Ribonucleic acids (RNAs) remain challenging targets for structural biology, creating barriers to understanding their vast functions in cellular biology and fully realizing their applications in biotechnology. The inherent dynamism of RNAs creates numerous obstacles in capturing their biologically relevant higher-order structures (HOSs), and as a result, many RNA functions remain unknown. In this study, we describe the development of native ion mobility−mass spectrometry and collision-induced unfolding (CIU) for the structural characterization of a variety of RNAs. We evaluate the ability of these techniques to preserve native structural features in the gas phase across a wide range of functional RNAs. Finally, we apply these tools to study the elusive mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes-associated A3243G mutation. Our data demonstrate that our experimentally determined conditions preserve some solution-state memory of RNAs via the correlated complexity of CIU fingerprints and RNA HOS, the observation of predicted stability shifts in the control RNA samples, and the retention of predicted magnesium binding events in gas-phase RNA ions. Significant differences in collision cross section and stability are observed as a function of the A3243G mutation across a subset of the mitochondrial tRNA maturation pathway. We conclude by discussing the potential application of CIU for the development of RNA-based biotherapeutics and, more broadly, transcriptomic characterization.

CIUSuite 3: Next-Generation CCS Calibration and Automated Data Analysis Tools for Gas-Phase Protein Unfolding Data

“…For instance, some charge states of α-synuclein have been observed to exhibit parallel CIU features across multiple collision voltages, complicating robust stability comparisons . In addition, CIU of nucleic acids, especially RNAs, typically undergo slight compaction transitions prior to unfolding during CIU, necessitating nonstandard approaches for the evaluation of CIU50 values . CIUSuite 2 feature detection only registers CIU features only when they become the most intense signal in at least one voltage slice, resulting in many lower intensity features being unanalyzed.…”

“…For example, intermediate features are skipped for both IgG1 and BSA CIU 2 data (Figure A), while lower energy features are skipped for the tRNA CIU analyzed as these features populate intermediate IM drift times. In a prior report, we demonstrated the utility of skipping intermediate features in RNA CIU data to record reliable CIU50 values . Overall, across all samples tested, feature skipping properly identifies the CIU features with the shortest and longest drift times and omits all other CIU features from the final feature list.…”

“…Furthermore, we constructed a built-in CCS calibration algorithm for both TWIM-MS and DTIM-MS data to enable faster conversion of experimental drift time data to CCS. In addition, it can be beneficial to compare CIU50 values between nonadjacent features . To support such CIU50 workflows, we have produced a feature skipping function for CIUSuite 3 that allows users to record CIU50 values between nonadjacent CIU features.…”

Ion Mobility-Mass Spectrometry and Collision-Induced Unfolding Rapidly Characterize the Structural Polydispersity and Stability of an Fc-Fusion Protein

“…When comparing the CIU fingerprints for two of the linker variants detected, we observe a transitional CIU feature (Figure A) that is irreproducible across different fingerprints recorded for linker variants. As such, we have implemented a feature skipping approach to enable the robust and reproducible assessment of CIU 50 values available in the remainder of the CIU data sets acquired . By implementing this procedure, we detect shifts in CIU 50 -1 values across linker variants, where an increase in linker length produces a stabilization in IL-10 dimers.…”