Biomedical subjects

Kyung-Hoon Kwon

Publications and source records attributed to Kyung-Hoon Kwon.

8 recordsLinked to original sources

PubMed2006

Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis.

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.

Blood Proteins↗

PubMed2006

Analysis of aromatic catabolic pathways in Pseudomonas putida KT 2440 using a combined proteomic approach: 2-DE/MS and cleavable isotope-coded affinity tag analysis.

Proteomic analysis of Pseudomonas putida KT2440 cultured in monocyclic aromatic compounds was performed using 2-DE/MS and cleavable isotope-coded affinity tag (ICAT) to determine whether proteins involved in aromatic compound degradation pathways were altered as predicted by genomic analysis (Jiménez et al., Environ Microbiol. 2002, 4, 824-841). Eighty unique proteins were identified by 2-DE/MS or MS/MS analysis from P. putida KT2440 cultured in the presence of six different organic compounds. Benzoate dioxygenase (BenA, BenD) and catechol 1,2-dioxygenase (CatA) were induced by benzoate. Protocatechuate 3,4-dixoygenase (PcaGH) was induced by p-hydroxybenzoate and vanilline. beta-Ketoadipyl CoA thiolase (PcaF) and 3-oxoadipate enol-lactone hydrolase (PcaD) were induced by benzoate, p-hydroxybenzoate and vanilline, suggesting that benzoate, p-hydroxybenzoate and vanilline were degraded by different dioxygenases and then converged in the same beta-ketoadipate degradation pathway. An additional 110 proteins, including 19 proteins from 2-DE analysis, were identified by cleavable ICAT analysis for benzoate-induced proteomes, which complemented the 2-DE results. Phenylethylamine exposure induced beta-ketoacyl CoA thiolase (PhaD) and ring-opening enzyme (PhaL), both enzymes of the phenylacetate (pha) biodegradation pathway. Phenylalanine induced 4-hydroxyphenyl-pyruvate dioxygenase (Hpd) and homogentisate 1,2-dioxygenase (HmgA), key enzymes in the homogentisate degradation pathway. Alkyl hydroperoxide reductase (AphC) was induced under all aromatic compounds conditions. These results suggest that proteome analysis complements and supports predictive information obtained by genomic sequence analysis.

Affinity Labels↗

PubMed2006

Profiling human brain proteome by multi-dimensional separations coupled with MS.

In our initial attempt to analyze the human brain proteome, we applied multi-dimensional protein separation and identification techniques using a combination of sample fractionation, 1-D SDS-PAGE, and MS analysis. The complexity of human brain proteome requires multiple fractionation strategies to extend the range and total number of proteins identified. According to the method of Klose (Methods Mol. Biol. 1999, 112, 67), proteins of the temporal lobe of human brain were fractionated into (i) cytoplasmic and nucleoplasmic, (ii) membrane and other structural, and (iii) DNA-binding proteins. Each fraction was then separated by SDS-PAGE, and the resulting gel line was cut into approximately 50 bands. After trypsin digestion, the resulting peptides from each band were analyzed by RP-LC/ESI-MS/MS using an LTQ spectrometer. The SEQUEST search program, which searched against the IPI database, was used for peptide sequence identification, and peptide sequences were validated by reversed sequence database search and filtered by the Protein Hit Score. Ultimately, 1533 proteins could be detected from the human brain. We classified the identified proteins according to their distribution on cellular components. Among these proteins, 24% were membrane proteins. Our results show that the multiple separation strategy is effective for high-throughput characterization of proteins from complex proteomic mixtures.

Brain↗

PubMed2005

Proteomic analysis of Korean ginseng (Panax ginseng C.A. Meyer).

Although many reports have been published regarding the pharmacological effects of ginseng, little is known about the biochemical pathways operant in ginsenoside biosynthesis, or the genes involved therein. Proteomics analysis is an approach to elucidate the physiological characteristics and biosynthetic pathways of ginsenosides, main components of ginseng. In this review, we introduced the recent progress in proteomics studies of ginseng (Panax ginseng C.A. Meyer). We briefly reference the genomic analyses of P. ginseng, without which proteomics approaches would have been impossible. Functional genomics studies regarding secondary metabolism in P. ginseng are also introduced here, in order to introduce possible future prospects for further study.

Databases, Genetic↗

PubMed2005

Utility of electrophoretically derived protein mass estimates as additional constraints in proteome analysis of human serum based on MS/MS analysis.

The proteome of a HUPO human serum reference sample was analyzed using multidimensional separation techniques at both the protein and the peptide levels. To eliminate false-positive identifications from the search results, we employed a data filtering method using molecular weight (MW) correlations derived from denaturing 1-DE. First, the six most abundant serum proteins were removed from the sample using immunoaffinity chromatography. 1-DE was then used to fractionate the remaining serum proteins according to the MW. Gel bands were isolated and in-gel digested with trypsin, and the resulting peptides were analyzed by 2-D LC/ESI-MS/MS. A SEQUEST search using the MS/MS results identified 494 proteins. Of these, 202 were excluded formally using protein data filtering as they were single-assignment proteins and their theoretical and electrophoretically-derived MWs did not correlate at high confidence. To evaluate this method, the results were compared with those of 1-D LC/MALDI-TOF/TOF and HUPO Plasma Proteome Project analyses. Our data filtering approach proved valuable in analysis of complex, large-scale proteomes such as human serum.

Amino Acid Sequence↗

PubMed2003

Proteome analysis of the responses of Panax ginseng C. A. Meyer leaves to high light: use of electrospray ionization quadrupole-time of flight mass spectrometry and expressed sequence tag data.

We performed comparative proteomic analyses in order to understand the physiological responses of ginseng (Panax ginseng C. A. Meyer) to high light (HL). As a first step, we analyzed the proteins expressed in ginseng leaves. Proteins extracted from leaves were separated by two-dimensional polyacrylamide gel electrophoresis. Protein spots were identified by tandem mass spectra analysis using electrospray ionization quadrupole-time of flight mass spectrometry (ESI Q-TOF MS). We used a ginseng expressed sequence tag (EST) database as well as a nonredundant protein database from NCBI to identify proteins. Eighty-one proteins were identified using the nr protein database, 51 of which were also verified from the ginseng EST database. An additional 66 proteins were identified only from the ginseng EST database. Proteins that function in energy metabolism, protein stabilization, and protection against oxidative stress were abundant. To understand the light responses of ginseng leaves, we studied time dependent changes in expressed proteins produced by 0-4 h of HL exposure. Six HL-responsive proteins were identified: three proteins were up-regulated (cytosolic small heat-shock protein, cytosolic ascorbate peroxidase, and putative major latex-like protein) and three proteins were down-regulated (Rieske Fe/S protein, putative 3-beta hydroxysteroid dehydrogenase/isomerase-like protein, and oxygen-evolving enhancer-like protein). Our results show that the ginseng EST database combined with ESI Q-TOF MS analysis can be used to identify ginseng proteins and to elucidate the protective mechanism of ginseng against HL induced damage.

Amino Acid Sequence↗

PubMed2003

Proteome analysis of hairy root from Panax ginseng C.A. Meyer using peptide fingerprinting, internal sequencing and expressed sequence tag data.

As an initial step to the comprehensive proteomic analysis of Panax ginseng C. A. Meyer, protein mixtures extracted from the cultured hairy root of Panax ginseng were separated by two-dimensional polyacrylamide gel electrophoresis (2-DE). The protein spots were analyzed and identified by peptide finger printing and internal amino acid sequencing by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and electrospray ionization quadrupole-time of flight mass spectrometry (ESI Q-TOF MS), respectively. More than 300 protein spots were detected on silver stained two-dimensional (2-D) gels using pH 3-10, 4-7, and 4.5-5.5 gradients. Major protein spots (159) were analyzed by peptide fingerprinting or de novo sequencing and the functions of 91 of these proteins were identified. Protein identification was achieved using the expressed sequence tag (EST) database from Panax ginseng and the protein database of plants like Arabidopsis thaliana and Oryza sativa. However, peptide mass fingerprinting by MALDI-TOF MS alone was insufficient for protein identification because of the lack of a genome database for Panax ginseng. Only 17 of the 159 protein spots were verified by peptide mass fingerprinting using MALDI-TOF MS whereas 87 out of 102 protein spots, which included 13 of the 17 proteins identified by MALDI-TOF MS, were identified by internal amino acid sequencing using tandem mass spectrometry analysis by ESI Q-TOF MS. When the internal amino acid sequences were used as identification markers, the identification rate exceeded 85.3%, suggesting that a combination of internal sequencing and EST data analysis was an efficient identification method for proteome analysis of plants having incomplete genome data like ginseng. The 2-D patterns of the main root and leaves of Panax ginseng differed from that of the cultured hairy root, suggesting that some proteins are exclusively expressed by different tissues for specific cellular functions. Proteome analysis will undoubtedly be helpful for understanding the physiology of Panax ginseng.

Databases, Protein↗

PubMed2003

Efficiency improvement of peptide identification for an organism without complete genome sequence, using expressed sequence tag database and tandem mass spectral data.

We compared peptide identification by database (DB) search methods with de novo sequencing results for proteomics study in an organism without genome sequence information. When the former was done by searching the Expressed Sequence Tag (EST) DB of the sample organism or the NCBI nonredundant (nr) protein DB of green plants using either the MASCOT or SEQUEST software program, it was confirmed that the former is as accurate as the latter. Peptides identified from EST DB were twice as many as those from the nr protein DB, in spite of the fact that the EST DB has less data (26 222 EST) than the NCBI nr protein DB (224 238). This study demonstrates that EST DB with tandem mass spectra can be used reliably for high-throughput proteomics studies in an organism without genome information.

Algorithms↗