Automation of data collection for matrix-assisted laser desorption/ionization mass spectrometry using a correlative analysis algorithm.
Automation of data collection in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry using a correlative analysis algorithm is demonstrated. This algorithm was employed to compensate for mass spectral jittering in MALDI data collection (e.g., peak shifts along the m/z axis, signal intensity deviations, etc.). Several important parameters for performing correlative analysis, such as the minimum correlation coefficient to be used and number of mass spectra to acquire prior to correlation, have been investigated and optimized. In addition, the correlation algorithm improved mass resolution of low- and high-molecular-weight compounds by as much as a factor of 4. Signal reproducibility in MALDI quantitative analysis also is improved when correlation is employed for data collection. This data collection algorithm can be used in conjunction with other instrumental optimization programs to allow for fully automated MALDI analysis, which is required for the routine applications carried out in many analytical laboratories.
Nicola
A J
AJ
Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA.
Gusev
A I
AI
Proctor
A
A
Hercules
D M
DM
D000465:Algorithms; D000803:Angiotensin I / Q000032:analysis; D000804:Angiotensin II / Q000032:analysis; D001330:Electronic Data Processing / Q000379:methods*; D004744:Enkephalin, Methionine / Q000032:analysis; D007328:Insulin / Q000032:analysis; D008970:Molecular Weight; D010446:Peptide Fragments / Q000032:analysis; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
D007328:Insulin; D010446:Peptide Fragments; D000804:Angiotensin II; D004744:Enkephalin, Methionine; D000803:Angiotensin I