Mspire-Simulator: LC-MS Shotgun Proteomic Simulator for Creating Realistic Gold Standard Data

Abstract

The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets.

In-silico Optimisation of Mass Spectrometry Fragmentation Strategies in Metabolomics

“…Our results show how ViMMS can be used to explore parameter combinations for a particular fragmentation strategies in-silico for existing data, virtually re-run existing data under an alternative strategy and benchmark existing fragmentation strategies (like DsDA) with minimal modifications under the proposed framework. This is a capability not available from other simulators [14,16,15,4,3,9]. On top of fragmentation data, ViMMS can also be used to benchmark and perform comparative evaluation of different LC-MS data processing algorithm, such as peak picking and retention time alignment [17] in a more controlled manner.…”

“…Unlike other simulators, e.g. [14,16,15,4,3], chemical objects can also be associated with fragment spectra that could themselves be extracted from spectral databases or generated using in-silico fragment prediction methods (Section 2.2.5). In-silico scan simulation in ViMMS (yellow box in Figure 1) proceeds as follows.…”

“…An appealing alternative way to evaluate fragmentation strategies is through the use of a simulator, which can replicate the underlying LC-MS/MS processes and allow researchers to prototype and compare strategies before validation on the actual MS instrument. Although some mass spectrometry simulators exist they are typically focused on proteomics and do not include simulation of the MS2 acquisition strategy within a chromatographic run [14,16,15,4,3,9]. Additionally existing simulators do not allow for real-time control of scan events (such as programmatically determining which m/z ranges to scan at a particular retention time), a crucial function for developing novel fragmentation strategies that can be controlled through libraries available with modern mass spectrometers, e.g.…”

In Silico Optimization of Mass Spectrometry Fragmentation Strategies in Metabolomics

“…An appealing alternative way to evaluate fragmentation strategies is using a simulator, which can replicate the underlying LC-MS/MS processes and allow researchers to prototype and compare strategies before validation on the actual MS instrument. Although some mass spectrometry simulators exist they are typically focused on proteomics and do not include simulation of the MS2 acquisition strategy within a chromatographic run [5,6,7,8,9,10]. Additionally, existing simulators do not allow for real-time control of scan events (such as programmatically determining which m / z ranges to scan at a particular retention time), a crucial function for developing novel fragmentation strategies that can be controlled through libraries available with modern mass spectrometers, e.g., using the Instrument Application Programming Interface (API) available for Thermo Tribrid instruments [11] that has begun to generate interest within the mass spectrometry community (e.g., [12]).…”

A plain method of prediction of visibility of peptides in mass spectrometry with electrospray ionization

“…Проблема отбора таких пептидов чрезвычайно актуальна, ведь формирование потока ионов из заряженной капли в электроспрее -сложный процесс, обусловленный многими факторами. Данная проблема достаточно подробно исследовалась в конце 80-х начале 90-х годов прошлого века [1,2] и в ряде работ анализировалась возможность отбора хорошо детектируемых пептидов [3][4][5][6][7]. В частности, Fusaro с соавторами [7] предсказывали пептиды с высоким уровнем ответа на основании анализа более 30 дескрипторов, описывающих свойства пептидов методом "случайного леса".…”