Evaluation of nanospray capillary LC-MS performance for metabolomic analysis in complex biological matrices

LC-MS metabolomic analysis in complex biological matrices may be complicated by degeneracy when using large-bore columns. Degeneracy is the detection of multiple mass spectral peaks from the same analyte due to adduction of salts to the metabolite, dimerization, or loss of neutrals. This introduces interferences to the MS spectra, diminishes quantification, and increases the rate of false identifications. Analysis using 2.1 mm inner diameter (i.d.) columns typically leads to degenerate peaks whereas nanospray using capillary columns (25, 50, and 75 mu m i.d.) reduces degeneracy. Optimization of chromatographic parameters of capillary LC for amino acid standards showed the lowest HETP at 1.25 mm/sec across all capillary i.d. columns. Results suggest mass-sensitive detection below the optimum velocity. At faster velocities, concentration-dependent detection occurred across all capillaries. The 2.1 mm i.d. analytical scale column showed the greatest level of degeneracy, particularly in the low signal intensity range. 25 mu m i.d. columns showed higher levels of metabolite annotation for the same signal intensity range. It also provided the lowest level of degeneracy, making it best suited for untargeted analysis. The 25 mu m i.d. column achieved a peak capacity (n(c)) of 144 in a 30-minute gradient method with nc decreasing as the column i.d. increased. 75 mu m i.d. capillary columns showed the highest signal intensity, which is beneficial for targeted analysis. These effects of chromatographic performance, resolution, and degeneracy profile of capillary and analytical scale columns were compared for metabolomic analyses in complex serum and cell lysate matrices. (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

LC-MS metabolomic analysis in complex biological matrices can be affected by degeneracy when using large-bore columns, but degeneracy can be reduced by using capillary columns, resulting in improved analysis outcomes.