Parts-Per-Billion Mass Measurement Accuracy Achieved through the Combination of Multiple Linear Regression and Automatic Gain Control in a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

Abstract

Fourier transform ion cyclotron resonance mass spectrometry has the ability to achieve unprecedented mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ICR cell for a particular measurement. Even through the use of automatic gain control (AGC), the total ion population is not constant between spectra. Multiple linear regression calibration in conjunction with AGC is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. This ability allows for the extension of dynamic range of the instrument while allowing mean MMA values to remain less than 1 ppm. In addition, multiple linear regression calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion level.

Advanced Mass Calibration and Visualization for FT-ICR Mass Spectrometry Imaging

“…7.13.0.564 (64 bit), Mathworks, Natick, MA USA) using the "proportion" method described by Wenger (Supplemental Material equation S2) [38]. The multiple linear regression method described by Muddiman et al was used to correct for total ion abundance and relative ion abundance fluctuations (Supplemental Material equation S3) [29,31,32]. This method adds two terms to a modified "Francl" calibration equation, which were calculated by multiple linear regression (Microsoft Excel) from 12 spectra that covered the range of total ion abundance observed throughout the MS imaging experiment.…”

“…(For more information on ion population-dependent space charge-induced frequency shifts in FT-ICR MS, see the following and references therein [20][21][22][23][24][25][26].) Thus, calibration equations that account for ion number fluctuations should improve mass accuracy for FT-MS imaging experiments [23,[25][26][27][28][29][30][31][32][33]. However, it should be noted that such calibration equations do not take into account other interactions in the ICR cell, which can affect the measured frequency, such as image charge when ions approach the detection electrodes, instability of electric trapping fields or instability of the magnetic field.…”

Improved mass accuracy for higher mass peptides by using SWIFT excitation for MALDI-FTICR mass spectrometry

“…Fourier-transform ion cyclotron resonance (FTICR) mass spectrometry, developed by Comisarow and Marshall [7,8], currently provides the best mass resolution and mass accuracy (Ͻ1 ppm) of all types of mass analyzers [9 -11] and has proven to be useful for protein identification by database searching [2,12]. Mass measurement accuracy (MMA) at the sub part-per-million (ppm) level using internal calibration [13,14] and several ppm using external calibration have been demonstrated [15,16], and these have led to much greater identification specificity, as described in recent reviews [17,18].For FTICR/MS, space-charge is the principal cause of mass measurement error [15,19,20]. The best MMA is obtained by using internal calibration, as this eliminates global space-charge effects [16].…”

“…Such issues can be avoided with external calibration, but space-charge shifts of cyclotron frequencies can lead to systematic errors in mass measurement. The most accurate external calibration procedures rely on a calibration equation that accounts for ion intensities [15,16,24], or for matching the ion abundance between the analyte and calibrant spectra, e.g., by automatic gain control (AGC) [14,25]. However, AGC is not applicable to MALDI-FTICR measurements due to the large shot-to-shot variation in ion intensity that is characteristic of MALDI.…”

“…Conventionally, internal calibration is achieved by mixing a calibrant with the analyte. Internal calibration can be achieved without adding calibrant directly into the analyte by using a dual-spray source [14,21] in ESI experiments or by using the internal calibration on adjacent samples (InCAS) calibration method [22,23] in MALDI experiments. However, internal calibration requires having both calibrant and analyte ions present at the same time in the analyzer cell, which congests the mass spectrum and can lead to overlapping peaks.…”