<p>Mass spectrometry (MS) is an important tool in analytical chemistry today, particularly in the field of proteomics where identification of proteins is the central activity. The focus in this thesis has been to improve the mass accuracy of MS-analyses in order to improve the possibility for unambiguous identification of proteins.</p><p>In paper I a new peak picking algorithm has been developed for Matrix Assisted Laser Desorption/Ionization - Time of Flight - Mass Spectrometry (MALDI-TOF-MS). The new algorithm is based on the assumption that two sets of ions are formed during the ionisation, and that these two sets have different Gaussian-distributed velocity profiles. The algorithm then deconvolutes the spectral peak into two Gaussian distributions, were the narrower of the two distributions is utilized for peak picking. The two-Gaussian peak picking algorithm proved to be especially useful when dealing with weak, distorted peaks.</p><p>In paper II a novel chip-based target for MALDI analysis is described. The target features pairs of 50x50 μm anchors in close proximity. Each anchor within a pair could be individually addressed with different sample solutions. Each pair could then be irradiated with the MALDI laser, which allowed ionization to take place on separated anchors simultaneously. This made it possible for us to calibrate analytes with calibration standards that where physically separated from the analyte, but ionized simultaneously. The use of new chip-based MALDI target resulted in a 2-fold reduction of relative mass errors. We could also report a significant reduction of ion suppression. The small size of the anchors provided a good platform for efficient utilization of sample. This resulted in a detection limit of ca. 1.5 attomole of angiotensin I at a S/N of 22:1.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:kth-313 |
| Date | January 2005 |
| Creators | Kempka, Martin |
| Publisher | KTH, Chemistry |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Licentiate thesis, comprehensive summary, text |
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