Master of Science / Department of Entomology / Srinivas Kambhampati / Termites (Isoptera) are separated into morphologically and behaviorally specialized castes of sterile workers and soldiers, and the reproductive alates. Previous research on eusocial insects has indicated that caste differentiation has a genetic basis. Although much has been studied about the genetic basis of caste differentiation and behavior in the honey bee, Apis mellifera, termites remain comparatively understudied. Therefore, my objective was to compare the gene expression patterns of different castes of the termite Reticulitermes flavipes based on EST analyses and a microarray. Soldier, worker, and alate caste and two larval life stage cDNA libraries were constructed, and ~15,000 randomly chosen clones were sequenced to compile an EST database. Putative gene functions were assigned based on a BLASTX Swissprot search. Categorical expression patterns for each library were compared using the in silico methods of BLAST2GO and r-statistics. I chose 2,240 unique-ESTs based on their putative function and sequence quality, which I used to fabricate a Combimatrix microarray. I used the microarray to compare expression levels between workers and soldiers from Kansas and Florida populations. Seventy to ninety percent of the sequences from the ESTs of each caste and life stages had no significant similarity to those in existing databases. All libraries contained sequences with putative reproductive functions, which was unexpected in the non-reproductive soldier and worker castes. Sequences of interest that showed a putative bias among castes include a viral protein in soldiers and a possible chemosensory protein in alates, which may be involved in termite reproductive functionality or communication. The microarray showed increased expression in the soldier caste of a sequence that matched tropomyosin and an increased expression level of a sequence that matched a PDZ-domain containing protein in some worker samples. This study leads to several candidate genes of potential caste specific function, which can be further tested using functional analysis and between the different castes and life stages of R. flavipes. These genes include the sequences similar to pebIII and RGS-GAIP. I have also expanded upon the available sequences for this termite and utilized the r-statistic in silico method for the first time to putatively compare gene expression in the different castes of a eusocial insect. The in silico analysis allowed us to identify several genes which may show biased expression patterns in the different cDNA libraries and which may reveal caste-specific expression controlling important functions after further analysis. These candidates include: an alate-biased gene, which had a predicted function of neurotransmitter secretion and cholesterol absorption as well as a late larval-biased gene which was predicted to be involved in protein biosynthesis and ligase activity.

The most widely used classification system describing enzyme-catalysed reactions is the Enzyme Commission (EC) number. Understanding enzyme function is important for both fundamental scientific and pharmaceutical reasons. The EC classification is essentially unrelated to the reaction mechanism. In this work we address two important questions related to enzyme function diversity. First, to investigate the relationship between the reaction mechanisms as described in the MACiE (Mechanism, Annotation, and Classification in Enzymes) database and the main top-level class of the EC classification. Second, how well these enzymes biocatalysis are adapted in nature. In this thesis, we have retrieved 335 enzyme reactions from the MACiE database. We consider two ways of encoding the reaction mechanism in descriptors, and three approaches that encode only the overall chemical reaction. To proceed through my work, we first develop a basic model to cluster the enzymatic reactions. Global study of enzyme reaction mechanism may provide important insights for better understanding of the diversity of chemical reactions of enzymes. Clustering analysis in such research is very common practice. Clustering algorithms suffer from various issues, such as requiring determination of the input parameters and stopping criteria, and very often a need to specify the number of clusters in advance. Using several well known metrics, we tried to optimize the clustering outputs for each of the algorithms, with equivocal results that suggested the existence of between two and over a hundred clusters. This motivated us to design and implement our algorithm, PFClust (Parameter-Free Clustering), where no prior information is required to determine the number of cluster. The analysis highlights the structure of the enzyme overall and mechanistic reaction. This suggests that mechanistic similarity can influence approaches for function prediction and automatic annotation of newly discovered protein and gene sequences. We then develop and evaluate the method for enzyme function prediction using machine learning methods. Our results suggest that pairs of similar enzyme reactions tend to proceed by different mechanisms. The machine learning method needs only chemoinformatics descriptors as an input and is applicable for regression analysis. The last phase of this work is to test the evolution of chemical mechanisms mapped onto ancestral enzymes. This domain occurrence and abundance in modern proteins has showed that the / architecture is probably the oldest fold design. These observations have important implications for the origins of biochemistry and for exploring structure-function relationships. Over half of the known mechanisms are introduced before architectural diversification over the evolutionary time. The other halves of the mechanisms are invented gradually over the evolutionary timeline just after organismal diversification. Moreover, many common mechanisms includes fundamental building blocks of enzyme chemistry were found to be associated with the ancestral fold.

To PTEN δρα ως ογκοκατασταλτικό γονίδιο, μέσω της δράσης του προϊόντος πρωτεΐνης της φωσφατάσης. Η φωσφατάση εμπλέκεται στη ρύθμιση του κυτταρικού κύκλου εμποδίζοντας τα κύτταρα να αναπτυχθούν και έχοντας σαν αποτέλεσμα την υπερβολικά γρήγορη διαίρεση. Το γονίδιο αυτό έχει ταυτοποιηθεί ως ογκοκατασταλτικό και σε αρκετές περιπτώσεις καρκίνων έχουν εντοπιστεί μεταλλάξεις του. Στην παρούσα διπλωματική εργασία, θα μελετηθεί η δράση του PTEN στο αδενοκαρκίνωμα του παχέως εντέρου και θα εξεταστεί η δυνατότητα χρήσης των επιπέδων έκφρασής του σαν βιοδείκτη για το συγκεκριμένο είδος καρκίνου. Σκοπός της παρούσας διπλωματικής είναι με χρήση κλινικών δεδομένων και της έντασης της έκφρασης της πρωτεΐνης του γονιδίου PTEN, να μελετηθεί με στατιστικές μεθόδους η δυνατότητα πρόβλεψης της βαθμοποίησης και της σταδιοποίησης του αδενοκαρκινώματος του παχέος εντέρου. Για τον σκοπό αυτό χρησιμοποιήθηκαν πραγματικά κλινικά δεδομένα 60 ασθενών που προήλθαν από το κυτταρολογικό εργαστήριο του Νοσηλευτικού Ιδρύματος Μετοχικού Ταμείου Στρατού 417 (Ν.Ι.Μ.Τ.Σ.). Τα δεδομένα αυτά αναλύθηκαν με εφαρμογή της περιγραφικής στατιστικής, της λογιστικής παλινδρόμησης και της πολυμεταβλητής παλινδρόμησης με χρήση του στατιστικού πακέτου R. Παρόλα αυτά κανένα από τα εξαγόμενα στατιστικά μοντέλα δεν βρέθηκε να μπορεί να συσχετίσει την ποσότητα έκφρασης του PTEN γονιδίου με τη βαθμοποίηση και τη σταδιοποίηση του αδενοκαρκινώματος του παχέος εντέρου. Για αυτό τον λόγο καταλήγουμε ότι με χρήση των συγκεκριμένων βιολογικών δεδομένων δεν μπορούμε να επαληθεύσουμε ότι το PTEN γονίδιο είναι βιοδείκτης του αδενοκαρκινώματος του παχέος εντέρου. Μελλοντικά αυτό πρέπει να διερευνηθεί περαιτέρω είτε με τη χρήση επιπλέον κλινικών δεδομένων καθώς το υπάρχον σύνολο δεδομένων περιέχει λίγα δείγματα ασθενών σε σχέση με τις ελεύθερες μεταβλητές του προβλήματος (small sample size problem), είτε με μεθόδους που αυξάνουν τεχνητά τα δείγματα του συνόλου δεδομένων. / PTEN tumor suppressor gene acts as through the action of the protein product of phosphatase. The phosphatase is involved in regulating the cell cycle by preventing cells to grow and the resulting too rapid division. This gene has been identified as tumor suppressor in several cancers identified mutations. In this paper, we studied the effect of PTEN in adenocarcinoma of the colon and consider the possibility of using the levels of expression as biomarker for this type of cancer. The purpose of this thesis is to use clinical data and the intensity of the protein expression of the gene PTEN and be studied using statistical methods for predict the grade and stage of adenocarcinoma of the colon. For this purpose we used real clinical data of 60 patients who came from the cytology laboratory of the hospital in the Army Pension Fund 417 (N.I.M.T.S.). The data were analyzed using the descriptive statistics, regression and multivariate regression using the statistical package R. However none of the extracted statistical models were found to be correlated to the amount of expression of PTEN gene with grade and stage of adenocarcinoma of the colon. For this reason, we conclude that the use of these biological data can not verify that the PTEN gene is a biomarker of adenocarcinoma of the colon. Future should be investigated further or using additional clinical data as the existing data set contains few patient samples relative to the free variables of the problem (small sample size problem), or by methods that increase artificially the samples in the data set.