The reversible phosphorylation of proteins mediates a wide range of biological processes that range from signal transduction cascades to regulation of protein abundance. However, little is known about the mechanisms and evolution of phosphorylation networks. Despite the extraordinary advances in genome sequencing of many yeast species, evolutionary studies on the phosphoproteome of yeast species have been limited to the experimental analysis of phosphorylation in one species and theoretical analysis of the conservation of phospho-acceptor residues with other species. To properly study the evolutionary conservation phosphorylation in yeast, we are utilizing mass spectrometry to study and compare the phosphoproteome of 21 species of yeast, including representative species from each clade of the yeast phylogenetic tree. Most of these species have not been studied before by proteomics. This high-throughput phosphoproteomic study on the yeast species will contribute to the construction of phosphoproteome datasets, which can be exploited for comparative analysis of phosphorylation between the species. One of main aims is to identify phosphorylation sites that show a high degree of conservation across the 21 species of yeast. These highly conserved phosphorylation sites likely regulate the same functions across the different species, and these functions can be further studied and correlated to our understanding of the mechanistics of phosphorylation in key biological processes, as well as the diseases that occur when the signaling pathways that involve these sites are defective. The second aim of this project is to study the correlation between the conservation of the phosphoproteome with the conservation of the genome and transcriptome, which will expand our understanding of the evolution of phenotypic diversity. Finally, the large-scale dataset of the proteomes and phosphoproteomes holds a great potential for other types of computational analysis, and also serves as a foundational reference for future experiments.

Protein phosphorylation is a common regulatory mechanism carried out by the cell, as adding a phosphate group to a particular protein can switch its activity on or off.  Signaling pathways employ this control method to instigate series of phosphorylation events that elicit a particular cell response.  Our research involves extracting and characterizing the phosphoproteome, or the cell’s entire set of expressed phosphorylated proteins, in both yeast and mammalian cell models.  To generate lists of phosphoproteins present in these cell models, we use mass spectrometry, an analytic technique that produces characteristic spectra for individual phosphopeptides that are then matched to a library of known protein spectra through the use of computer algorithms.  In our preliminary results, we have generated large-scale data sets identifying thousands of phosphorylated proteins present in each species and cell type.  The goal of the first project, the yeast study, is to determine the degree of evolutionary conservation in phosphorylation events across 19 yeast species to learn about the basic principles of phosphoregulation.  The conservation of phosphorylation can also give insight into phosphorylation events in other species evolutionarily related to yeast, such as humans.  The second project, the mammalian cell study, examines the phosphoproteome of different breast cancer cell types in order to identify common phosphorylated proteins, from which we can deduce a molecular signature for breast cancer.  This signature can be used in future studies to design a universal protein inhibitor drug as an alternative anti-cancer therapy.  Additionally, by identifying the phosphoproteins exclusive to each cell type, we can uniquely characterize specific types of breast cancer.  Knowledge of the proteins active in one type of breast cancer may facilitate development of inhibitor drugs as a form of personalized medicine.

Breast cancer tumors are classified within different subtypes based on the expression of three types of cell surface receptor proteins.  These proteins connect the extracellular environment with cellular activities via signaling pathways.  To elicit cell responses, signaling pathways employ protein phosphorylation as a regulatory mechanism, as adding a phosphate group to a particular protein can switch its activity on or off.  However, normal signaling can go awry if mutations in signaling proteins lead the cell to believe its components are always phosphorylated and active.  Consequently, the entire signaling pathway functions abnormally, which can lead to uncontrolled cell growth characteristic of cancer.  Given its potential role as a molecular mechanism of disease, our research focuses on obtaining a global view of the phosphoproteome, or the cell’s entire set of expressed, phosphorylated proteins, of 10 breast cancer cell lines.  To generate lists of phosphoproteins present in these cell lines, we are concurrently extracting and analyzing cell line phosphopeptide samples via mass spectrometry, an analytic technique that produces characteristic spectra for individual phosphopeptides that are then matched to a library of known protein spectra through the use of computer algorithms.  In our preliminary results, we have generated large-scale data sets identifying thousands of phosphorylated proteins present in two cell lines and generated side-by-side comparisons of the proteins expressed in each line.   By identifying common phosphorylated proteins across all of the cell lines, our goal is to deduce a molecular signature for breast cancer.  This signature can be used in future studies to design a universal protein inhibitor drug as an alternative anti-cancer therapy.   By identifying the phosphoproteins exclusive to each cell type, we can uniquely characterize specific proteins active in one type of breast cancer which may facilitate development of inhibitor drugs as a form of personalized medicine.

Income inequality and level of education affects countries across the world. Within the last few years, Thailand’s income inequality seems to have worsened, as is seen from many political conflicts created from the significant gap between the rich and poor.  From the World Bank Poverty Analysis, there has been a dramatic decline of poverty in Thailand since early 1960’s.   However, the decline in poverty was not uniform across regions of the country; poverty is more concentrated in the rural areas.   Therefore, the increase in inequality was also not uniform across the country; the wider income differentials between households in different locations accounted for the increase in overall income inequality.  This means educational attainment plays an important role for labor to make a transition from the old sector to the new sector, and thus is one of the determined factors for income inequality.  In this paper, I will examine the impact of education and skills owned by individual on wage and income distribution of Thailand.  First, I will explain about the previous research on the relationship between education, skills, and wage. Then, I will explain about the data set and the methodology that will be used. Lastly, I will present and explain the result using Mincer's wage regression analysis and give the conclusion.