Study On Several Key Thechniques Of Data Processing In Chromatography-mass Spectrometry

Chromatography-mass spectrometry hyphenated instrument which is a closelyintegrated product of chromatography and mass spectrometry technology is widelyused in environmental monitoring, food safety, life science and many other fields. Itsdevelopment related to computer technology. The data processing technology willdirectly affect the analysis results.There are two main forms in chromatography-mass spectrometry area: Gaschromatography-mass spectrometry (GC-MS) and liquid chromatography-massspectrometry (LC-MS). For GC-MS, this thesis focused on the deconvolutionalgorithm. For LC-MS, it focused on protein analysis, researched the protein peptideretention time prediction model and retention time factors application in theidentification of protein. The main work in this thesis is as follow:1、 Back-folded deconvolution method for GC-MS data analysis. A novelback-folded method for chromatographic peak separation was presented in this thesisbased on the differential algorithm. Based on the back-folded chromatographic peakseparation algorithm and process of deconvolution in matrix form, a newdeconvolution algorithm for GC-MS data was proposed which achieve purificationpure spectrum by matrix operation. The experimental results validated that thisalgorithm can effectively extract pure mass spectra and determine the retention timefor each component in the mixture.2、A novel deconvolution algorithm for GC-MS data based on K-medoidsclustering analysis. When the difference of retention times of two or multiplecompounds is less then one scan, traditional deconvolution processes are unable toextract pure mass spectrum. In view of this situation, the K-medoids clusteringalgorithm was introduced to GC-MS data processing. The data analysis workflowconsists of three sequential steps: peak detection, deconvolution and chromatographicpeak shape correction. The real experimental data was analyzed using the K-medoidsalgorithm and AMDIS system. The results show that K-medoids clustering algorithmcan separated overlapped chromatographic peaks effectively which is out of theability of AMDIS system.3、LC-MS hyphenated instruments is an important form of chromatography-mass spectrometry technology. Proteomics is the main application field of HPLC-MS.In protein identification, retention time of peptides offers the other dimension of information beyond mass-to-charge ratios, could improve protein identificationaccuracy, therefore establishing the prediction model for retention time of proteinpeptides is needed. The establishment of this model is divided into three stages:（1）The primary peptide retention time prediction model using TFA as ionpairing reagent was established based on a small sample data set.（2）Then analyzed the influences of peptide length, amino acid position,neighbor effect, clusters of amino acids, further optimizad the prediction model basedon a larger data set.（3）The alkylation of cysteine is a key element in protein analysis. The retentioncoefficient for cysteine was corrected when it was alkylated by iodoacetamide,iodoacetic acid,4-vinylpyridine, acrylamide and methyl-methanethiosulfonate. Freecysteine was also concerned.4、Through the analysis of retention time coefficient of each amino acid in thethree model, a method for separating the peptides with different charge using differentacidic ion pairing reagent combination in two-dimensional HPLC. The experimentproved that this method could elute peptides with different charge in clusters. Basedon this separation, A novel method for enrichment of protein N terminal and Ctermina peptides was present which could provide a new way for identification ofproteins., experiments using human Jurcat cells and termite Clostridium cells assamples show that the method can effectively enriched N terminal and C terminalpeptides of protein.