Autopiquer - a robust and reliable peak detection algorithm for mass spectrometry

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks

Conformational Space and Stability of ETD Charge Reduction Products of Ubiquitin

Owing to its versatility, electron transfer dissociation (ETD) has become one of the most commonly utilized fragmentation techniques in both native and non-native top-down mass spectrometry. However, several competing reactions—primarily different forms of charge reduction—occur under ETD conditions, as evidenced by the distorted isotope patterns usually observed. In this work, we analyze these isotope patterns to compare the stability of nondissociative electron transfer (ETnoD) products, specifically noncovalent c/z fragment complexes, across a range of ubiquitin conformational states. Using ion mobility, we find that more extended states are more prone to fragment release. We obtain evidence that for a given charge state, populations of ubiquitin ions formed either directly by electrospray ionization or through collapse of more extended states upon charge reduction, span a similar range of collision cross-sections. Products of gas-phase collapse are, however, less stabilized towards unfolding than the native conformation, indicating that the ions retain a memory of previous conformational states. Furthermore, this collapse of charge-reduced ions is promoted if the ions are ‘preheated’ using collisional activation, with possible implications for the kinetics of gas-phase compaction

Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches

Desorption electrospray ionisation-mass spectrometry imaging (DESI-MSI) is a powerful imaging technique for the analysis of complex surfaces. However, the often highly complex nature of biological samples is particularly challenging for MSI approaches, as options to appropriately address mass spectral complexity are limited. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers superior mass accuracy and mass resolving power, but its moderate throughput inhibits broader application. Here we demonstrate the dramatic gains in mass resolution and/or throughput of DESI-MSI on an FT-ICR MS by developing and implementing a sophisticated data acquisition and data processing pipeline. The presented pipeline integrates, for the first time, parallel ion accumulation and detection, post-processing absorption mode Fourier transform and pixel-by-pixel internal re-calibration. To achieve that, first, we developed and coupled an external high-performance data acquisition system to an FT-ICR MS instrument to record the time-domain signals (transients) in parallel with the instrument’s built-in electronics. The recorded transients were then processed by the in-house developed computationally-efficient data processing and data analysis software. Importantly, the described pipeline is shown to be applicable even to extremely large, up to 1 TB, imaging datasets. Overall, this approach provides improved analytical figures of merits such as: (i) enhanced mass resolution at no cost in experimental time; and (ii) up to 4-fold higher throughput while maintaining a constant mass resolution. Using this approach, we not only demonstrate the record 1 million mass resolution for lipid imaging from brain tissue, but explicitly demonstrate such mass resolution is required to resolve the complexity of the lipidome