Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics

Abstract

Compound identification and annotation in (untargeted) metabolomics experiments based on accurate mass require the highest possible accuracy of the mass determination. Experimental LC/TOF-MS platforms equipped with a time-to-digital converter (TDC) give the best mass estimate for those mass signals with an intensity similar to that of the lock-mass used for internal calibration. However, they systematically underestimate the mass obtained at higher signal intensity and overestimate it at low signal intensities compared to that of the lock-mass. To compensate for these effects, specific tools are required for correction and automation of accurate mass calculations from LC/MS signals. Here, we present a computational procedure for the derivation of an intensity-dependent mass correction function. The chromatographic mass signals for a set of known compounds present in a large number of samples were reconstructed over consecutive scans for each sample. It was found that the mass error is a linear function of the logarithm of the signal intensity adjusted to the associated lock-mass intensity. When applied to all mass data points, the correction function reduced the mass error for the majority of the tested compounds to B1 ppm over a wide range of signal intensities. The mass correction function has been implemented in a Python 2.4 script, which accepts raw data in NetCDF format as input, corrects the detected masses and returns the corrected NetCDF files for subsequent (automated) processing, such as mass signal alignment and database searching.

Structure Annotation and Quantification of Wheat Seed Oxidized Lipids by High-Resolution LC-MS/MS

“…Noteworthy, the average error was approximately zero around m/z 622.0289, the m/z of the compound used for lock-mass calibration. The m/z deviations depend on m/z value (Mihaleva et al, 2008;Lommen et al, 2011). We followed the plausible argument of the authors to assume that we must have correctly annotated a certain number of lipid sum formulae because they are known to exist in our sample.…”

Accurate mass measurement: Terminology and treatment of data

“…Note: this term is also referred to as "mean mass measurement accuracy," "average mass measurement accuracy," "mass accuracy," "average error" [20], and "average mass error" [21]. The first two terms would appear mathematically appropriate to use, and mass accuracy is a common abbreviated term.…”

“…If the experimental data can reasonably be represented by a normal distribution then the standard deviation can be quoted and its meaning is well understood. However, the term "average mass error" [21] is commonly used for mass measurements. As the term "average mass error" is confused with mass measurement accuracy, it is best to state explicitly if absolute values of errors are used to create an average.…”

“…As the term "average mass error" is confused with mass measurement accuracy, it is best to state explicitly if absolute values of errors are used to create an average. The literature cites the following terms for the same quantity: "average mass error (absolute values)" [21], "average absolute error" [22], "average absolute mass error", "absolute exact-mass errors" [23] and "average absolute mass measurement accuracy" [24]. The term average absolute mass measurement accuracy (AAMMA) is widely used, see below.…”

Differential metabolomics software for capillary electrophoresis-mass spectrometry data analysis

“…However, while it can considerably facilitate compound identification, the differential detection of features using high-resolution data often requires undesirable or unrealistic computational power and time, and introduces additional steps and hurdles. These include, for example, the need for m/z correction across datasets that arise from incomplete m/z correction by the MS instrument mass lock feature (Hack and Benner 2002;Soga et al 2006;Wu and McAllister 2003), an intensity-dependent m/z shift due to the signal processing capacity of MS detector (Mihaleva et al 2008), or peak distortion in the m/z dimension (Kempka et al 2004). For these reasons, we elected to use m/z binning as a reasonable trade-off.…”