High-resolution Fourier transform ion cyclotron resonance mass spectrometry with increased throughput for
Konstantin O Nagornov1, Mikhail V Gorshkov, Anton N Kozhinov
1Biomolecular Mass Spectrometry Laboratory, Ecole Polytechnique Fédérale de Lausanne , 1015 Lausanne, Switzerland.
Abstract:
A multielectrode ion cyclotron resonance (ICR) cell, herein referred to as the "4X cell", for signal detection at the quadruple frequency multiple was implemented and characterized on a commercial 10 T Fourier transform ICR mass spectrometer (FT-ICR MS). Notably, with the 4X cell operating at a 10 T magnetic field we achieved a 4-fold increase in MS acquisition rate per unit of resolving power for signal detection periods typically employed in FTMS, viz., shorter than 6 s. Effectively, the obtained resolution performance represents the limit of the standard measurement principle with dipolar signal detection and FT signal processing at an equivalent magnetic field of 40 T. In other words, the achieved resolving powers are 4 times higher than those provided by 10 T FT-ICR MS with a standard ICR cell. For example, resolving powers of 170,000 and 70,000 were obtained in magnitude-mode Fourier spectra of 768 and 192 ms apodized transient signals acquired for a singly charged fluorinated phosphazine (m/z 1422) and a 19-fold charged myoglobin (MW 16.9 kDa), respectively. In peptide analysis, the baseline-resolved isotopic fine structures were obtained with as short as 768 ms transients. In intact protein analysis, the average resolving power of 340,000 across the baseline-resolved (13)C isotopic pattern of multiply charged ions of bovine serum albumin was obtained with 1.5 s transients. The dynamic range and the mass measurement accuracy of the 4X cell were found to be comparable to the ones obtained for the standard ICR cell on the same mass spectrometer. Overall, the reported results validate the advantages of signal detection at frequency multiples for increased throughput in FT-ICR MS, essential for numerous applications with time constraints, including proteomics.
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