MOLECULAR MECHANISMS UNDERLYING THE TRANSCRIPTIONAL REGULATION OF T HELPER 17 AND REGULATORY T CELLS

CD4+ T helper (Th) lymphocytes are vital for integrating immune responses by orchestrating the function of other immune cell types. Naïve Th cells can differentiate into different effector subsets that are characterized by their cytokine profile and immune regulatory functions. These subsets include Th1, Th2, Th17, natural and inducible regulatory T cells (nTreg and iTreg respectively), among others. We focused our investigation on two Th lineages, Th17 and regulatory T cells, with opposing functions in the immune system. These subsets have been suggested to be reciprocally regulated since they both require TGF-b for their development. We investigated the role of the Treg-associated master transcription factor Foxp3, and found that Foxp3 inhibits Th17 cell generation by preventing the transcriptional activity of the two main Th17-specific transcription factors, nuclear orphan receptors RORa and RORgt. At the molecular level, we identified two different functional domains in Foxp3 required for such inhibition: the LQALL sequence in exon 2 and the TIP60/HDAC7 binding domain. These domains could be crucial to either prevent the association of the nuclear receptors to coactivators or to recruit histone deacetylases to RORa- or RORgt-target genes. Since TGF-b is a common cytokine required for the commitment towards both Th lineages, we determined the role of the TGF-b-dependent signaling pathway in the generation of each subset. By using mice with deficiencies in signaling molecules downstream of TGF-b, we found that while Smad2, Smad3 and Smad4 are required for the generation of iTreg cells, only Smad2 is indispensable for the induction of IL-17-producing cells, suggesting that TGF-b induces these T helper lineages through differential signaling pathways. Thus, our findings describe novel transcriptional regulatory mechanisms that control the generation of two T helper lineages with opposing functions. These findings could provide novel therapeutic targets to treat diseases where the balance of these T cells is dysregulated, such as in autoimmunity, chronic infectious diseases and cancer.

GLUCAGON GENE EXPRESSION: ANALYSIS OF PREPROGLUCAGON

Glucagon is a 29 amino acid polypeptide hormone produced in the (alpha) cells of the pancreatic islets. The purpose of this research was to understand better the role of glucagon in the regulation of metabolic processes. As with other polypeptide hormones, the synthesis of glucagon is thought to involve a larger precursor, which is then enzymatically cleaved to the functional form. The specific research objectives were to obtain cloned copies of the messenger RNA (mRNA) for pancreatic glucagon, to determine their primary sequences, and from this coding information to deduce the amino acid sequence of the initial glucagon precursor. From this suggested preproglucagon sequence and prior information on possible proglucagon intermediate processing products, the overall objective of this research is to propose a possible pathway for the biosynthesis of pancreatic glucagon.^ Synthetic oligodeoxynucleotide probes of 14-nucleotides (14-mer) and 17-nucleotides (a 17-mer) complementary to codons specifying a unique sequence of mature glucagon were synthesized. The ('32)P-labeled-14-mer was hybridized with size-fractionated fetal bovine pancreatic poly(A('+))RNA bound to nitrocellulose. RNA fractions of (TURN)14S were found to hybridize specifically, resulting in an (TURN)10-fold enrichment for these sequences. These poly(A('+))RNAs were translated in a cell-free system and the products analyzed by gel electrophoresis. The translation products were found to be enriched for a protein of the putative size of mammalian preproglucagon ((TURN)21 kd). These enriched RNA fractions were used to construct a complementary DNA (cDNA) library is plasmid pBR322.^ Screening of duplicate colony filters with the ('32)P-labeled-17-mer and a ('32)P-labeled-17-mer-primed cDNA probe indicated 25 possible glucagon clones from 3100 colonies screened. Restriction mapping of 6 of these clones suggested that they represented a single mRNA species. Primary sequence analysis of one clone containing a 1200 base pair DNA insert revealed that it contained essentially a full-length copy of glucagon cDNA.^ Analaysis of the cDNA suggested that it encoded an initial translation product of 180 amino acids with an M(,r) = 21 kd. The first initiation codon (ATG, methionine) followed by the longest open reading frame of 540 nucleotides was preceded by a 5'-untranslated region of 90 nucleotides, and was followed by a longer 3'-untranslated region of 471 nucleotides, resulting in a total of 1101 nucleotides. . . . (Author's abstract exceeds stipulated maximum length. Discontinued here with permission of author.) UMI ^

CHARACTERIZATION OF HIGH MOBILITY GROUP AND HISTONE H1 PROTEIN LEVELS AND SYNTHESIS DURING SPERMATOGENESIS IN THE RAT

In order to propose a role for internucleosomal high mobility group proteins (HMGs), and HI histone variants study of their levels and synthesis in a system of development and differentiation--rat spermatogenesis--was undertaken. HMG1, 2, 14, and 17 were isolated from rat testes and found to be very similar to calf thymus HMGs. Testis levels of HMGs, relative to DNA, were equivalent to other rat tissues for HMG1 (13 ug/mg DNA), HMG14 (2 ug/mg DNA), and HMG17 (5 ug/mg DNA). HMG2 levels were different among rat tissues, with three groups observed: (1) nonproliferating tissues (1-5 ug/mg DNA); (2) proliferating tissues (8-13 ug/mg DNA); and (3) the testis (32 ug/mg DNA). Other species (toad, opposum, mouse, dog, and monkey) showed the same testis-specific increase of HMG2. Populations of purified testis cell types were separated by centrifugal elutriation and density gradient centrifugation from adult and immature rat testes. Pachytene spermatocytes and early spermatids (56 and 47 ug/mg DNA, respectively) caused the testis-specific increase of HMG2 levels. Cell types preceding pachytenes (types A and B spermatogonia, mixtures of spermatogonia and early primary spermatocytes, and early pachytenes contained HMG2 levels similar to proliferating tissues (12 ug/mg DNA). Late spermatids did not contain HMGs. Somatic Sertoli and Leydig cells (2 ug/mg DNA) exhibited HMG2 levels similar to nonproliferating tissues. HMGs synthesized in spermatogonia and spermatocytes had similar specific activities, but early spermatids did not synthesize HMGs. Germ cells also contained an HMG2 species (on acid-urea gels) not found in somatic tissues. Other investigators have shown that HMGs may be associated with transcriptional or replicative processes. Thus, it is proposed that HMG2 plays a role in modulatable gene expression, while HMG1 is associated with housekeeping functions.^ HI histone variants were also studied throughout spermatogenesis. The minor somatic variant, HIa, is the predominant variant in spermatogonia and early primary spermatocytes. In early pachytenes, the testis-specific variant, HIt, is first synthesized and appears, largely replacing somatic variants HIbcd and e by late pachytene stage. Early spermatids contain the same HI composition as pachytenes, but do not synthesize HI histones. HI('0) is present in low amounts in all germ cells. These results suggest that expression of HI variants is developmentally controlled.^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

The identification and regulation of a novel interaction occurring between $\beta$-catenin and the actin -bundling protein fascin

Catenins were first characterized as linking the cytoplasmic domains of cadherin cell-cell adhesion molecules to the cortical actin cytoskeleton. In addition to their essential role in modulating cadherin adhesion, catenins have more recently been indicated to participate in cell and developmental signaling pathways. $\beta$-catenin, for example, associates directly with receptor tyrosine kinases and transcription factors such as LEF-1/TCF, and tranduces developmental signals within the Wnt pathway. $\beta$-catenin also appear to a role in regulating cell proliferation via its interaction with the tumor supressor protein APC. I have employed the yeast two-hybrid method to reveal that fascin, a bundler of actin filaments, binds to $\beta$-catenin's central Armadillo-repeat domain. The $\beta$-catenin-fascin interaction exists in cell lines as well as in animal brain tissues as revealed by immunoprecipitation analysis, and substantiated in vitro with purified proteins. Fascin additionally binds to plakoglobin, which contains a more divergent Armadillo-repeat domain. Fascin and E-cadherin utilize a similar binding-site within $\beta$-catenin, such that they form mutually exclusive complexes with $\beta$-catenin. Fascin and $\beta$-catenin co-localize at cell-cell borders and dynamic cell leading edges of epithelial and endothelial cells. Total immunoprecipitable b-catein has several isoforms, only the hyperphosphorylated isoform 1 associated with fascin. An increased $\beta$-catenin-fascin interaction was observed in HGF stimulated cells, and in Xenopus embryos injected with src kinase RNAs. The increased $\beta$-catenin association with fascin is correlated with increased levels of $\beta$-catenin phosphorylation. $\beta$-catenin, but not fascin, can be readily phosphorylated on tyrosine in vivo following src injection of embryos, or in vitro following v-src addition to purified protein components. These observations suggest a role of $\beta$-catenin phosphorylation in regulating its interaction with fascin, and src kinase may be an important regulator of the $\beta$-catenin-fascin association in vivo. The $\beta$-catenin-fascin interaction represents a novel catenin complex, that may conceivably regulate actin cytoskeletal structures, cell adhesion, and cellular motility, perhaps in a coordinate manner with its functions in cadherin and APC complexes. ^