Serotonin Receptor Gene Expression And Insulin Function In Streptozotocin Induced Diabetic Rats

Recent studies have established a fimctional correlation of serotonergic and adrenergic function in the brain regions with insulin secretion in diabetic rats (Vahabzadeh et al., 1995). Administration of 5-HT”. agonist 8-OH-DPAT to conscious rats caused an increase in blood glucose level. This increase in blood glucose is due to inhibition of insulin secretion by increased circulating EPI (Chaouloff et al., 1990a; Chaouloff et al., 1990d; Chaoulo1T& Jeanrenaud, 1987). The increase in EPI is brought about by increased sympathetic stimulation. This increase can lead to increased sympatho-medullary stimulation thereby inhibiting insulin release (Bauhelal & Mir, 1993, Bauhelal & Mir, 1990a; Chaouloffet al., 1990d). Also, studies have shown that Gi protein in the liver has been decreased in diabetes which will increase gluconeogenesis and glycogenolysis thereby causing hyperglycaemia (Pennington, 1987). Serotonergic control is suggested to exert different effects on insulin secretion according to the activation of different receptor subclasses (Pontiroli et al., 1975). In addition to this mechanism, the secretion of insulin is dependent on the turnover ratio of endogenous 5-hydroxy tryptophan (5-HTP) to 5-HT in the pancreatic islets (Jance er al., 1980). The reports so far stated does not explain the complete mechanism and the subclass of 5-HT receptors whose expression regulate insulin secretion in a diabetic state. Also, there is no report of a direct regulation of insulin secretion by 5-HT from the pancreatic islets even though there are reports stating that the pancreatic islets is a rich source of 5-HT (Bird et al., 1980). Therefore, in the present study the mechanism by which 5-HT and its receptors regulate insulin secretion from pancreatic [3-cells was investigated. Our results led to the following hypotheses by which 5-HT and its receptors regulate the insulin secretion.

ADRENERGIC RECEPTOR GENE EXPRESSION DURING PANCREATIC REGENERATION AND INSULIN SECRETION IN RATS –

In the present study, the changes in the brain EPI (Epinephrine), adrenergic receptors and the receptor gene expression were investigated during pancreatic regeneration and insulin secretion. The changes in the pancreatic islet EPI and adrenergic receptors were also studied in the pancreatectomised rats. The regulatory function of EPI in association with Epidermal growth factor (EGF) and glucose were investigated in rat islet cultures. In vitro studies were carried out using antagonists for adrenergic receptor subtypes to see their involvement in the islet DNA synthesis. The mechanism by which the peripheral EPI regulate insulin secretion was also investigated by studying the nuclear binding proteins in the pancreatic islets during pancreatic regeneration and diabetes. The study reveals that EPI can regulate the pancreatic islet cell proliferation by controlling the insulin synthesis and secretion. The brain adrenergic receptor gene expression and functional correlation regulate the pancreatic adrenergic receptors. The functional balance of α and β-adrenergic receptors controls the insulin secretion and pancreatic β-cell proliferation, which will have immense clinical significance in the treatment of Diabetes mellitus.

Alterations in the muscarinic M I and M3 receptor gene expression in the brain stem during pancreatic regeneration and insulin secretion in weanling rats

Muscarinic M1 and M3 receptor changes in the brain stem during pancreatic regeneration were investigated. Brain stem acetylcholine esterase activity decreased at the time of regeneration . Sympathetic activity also decreased as indicated by the norepinephrine (NE) and epinephrine (EPI) content of adrenals and also in the plasma. Muscarinic Ml and M3 receptors showed reciprocal changes in the brain stem during regeneration. Muscairnic M1 receptor number decreased at time of regeneration without any change in the affinity. High affinity M3 receptors showed an increase in the number. The affinity did not show any change . The number of low affinity receptors decreased with decreased Kd at 72 hours after partial pancreatectomy. The Kd reversed to control value with a reversal of the number of receptors to near control value . Gene expression studies also showed a similar change in the mRNA level of Ml and M3 receptors . These alterations in the muscarinic receptors regulate sympathetic activity and maintain glucose level during pancreatic regeneration. Central muscarinic M1 and M3 receptor subtypes functional balance is suggested to regulate sympathetic and parasympathetic activity, which in turn control the islet cell proliferation and glucose homeostasis.

5-HT1A and -HT2c Receptor Gene Expression: Their Functional Role in Pancreatic Regeneration and Insulin Secretion in Rats

Department of Biotechnology, Cochin University of Science and Technology

Serotonin- 5-HT2A and Glutamate Receptors Gene Expression in Streptozotocin induced diabetic rats:Effects of pyridoxine and Aegle marmelose leaf extract

Department of Biotechnology, Cochin University of Science and Technology

Muscarinic M1 and M3 Receptors,IP3 and cGMP Functional Regulation in Streptozotocin Induced Diabetic Rats: Insulin and Somatotropin Induced Rejuvenation as a Function of Age

The present study describes that acetylcholine through muscarinic Ml and M3 receptors play an important role in the brain function during diabetes as a function of age. Cholinergic activity as indicated by acetylcholine esterase, a marker for cholinergic function, decreased in the brain regions - the cerebral cortex, brainstem and corpus striatum of old rats compared to young rats. in diabetic condition, it was increased in both young and old rats in cerebral cortex, and corpus striatum while in brainstem it was decreased. The functional changes in the muscarinic receptors were studied in the brain regions and it showed that muscarinic M I receptors of old rats were down regulated in cerebral cortex while in corpus striatum and brainstem it was up regulated. Muscarinic M3 receptors of old rats showed no significant change in cerebral cortex while in corpus striatum and brainstem muscarinic receptors were down regulated. During diabetes, muscarinic M I receptors were down regulated in cerebral cortex and brainstem of young rats while in corpus striatum they were up regulated. In old rats, M I receptors were up regulated in cerebral cortex, corpus striatum and in brainstem they were down regulated. Muscarinic M3 receptors were up regulated in cerebral cortex and brainstem of young rats while in corpus striatum they were down regulated. In old rats, muscarinic M l receptors were up regulated in cerebral cortex, corpus striatum and brainstem. In insulin treated diabetic rats the activity of the receptors were reversed to near control. Pancreatic muscarinic M3 receptor activity increased in the pancreas of both young and old rats during diabetes. In vitro studies using carbachol and antagonists for muscarinic Ml and M3 receptor subtypes confirmed the specific receptor mediated neurotransmitter changes during diabetes. Calcium imaging studies revealed muscarinic M I mediated Ca2 + release from the pancreatic islet cells of young and old rats. Electrophysiological studies using EEG recording in young and old rats showed a brain activity difference during diabetes. Long term low dose STH and INS treated rat brain tissues were used for gene expression of muscarinic Ml, M3, glutamate NMDARl, mGlu-5,alpha2A, beta2, GABAAa1 and GABAB, DAD2 and 5-HT 2C receptors to observe the neurotransmitter receptor functional interrelationship for integrating memory, cognition and rejuvenating brain functions in young and old. Studies on neurotransmitter receptor interaction pathways and gene expression regulation by second messengers like IP3 and cGMP in turn will lead to the development of therapeutic agents to manage diabetes and brain activity.From this study it is suggested that functional improvement of muscarinic Ml, M3, glutamate NMDAR1, mGlu-5, alpha2A, beta2, GABAAa1 and GABAB, DAD2 and 5-HT 2C receptors mediated through IP3 and cGMP will lead to therapeutic applications in the management of diabetes. Also, our results from long term low dose STH and INS treatment showed rejuvenation of the brain function which has clinical significance in maintaining healthy period of life as a function of age.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

GABAA and GABAI Receptor Subunits Gene Expression and their Functional Role in Pilocarpine Induced Temporal Lobe Epilepsy

The research work which was carried out to characterization of wastes from natural rubber and rubber wood processing industries and their utilization for biomethanation. Environmental contamination is an inevitable consequence of human activity. The liquid and solid wastes from natural rubber based industries were: characterized and their use for the production of biogas investigated with a view to conserve conventional energy, and to mitigate environmental degradation.Rubber tree (flevea brasiliensis Muell. Arg.), is the most important commercial source of natural rubber and in india. Recently, pollution from the rubber processing factories has become very serious due to the introduction of modern methods and centralized group processing practices.The possibility of the use of spent slurry as organic manure is discussed.l0 percent level of PSD, the activity of cellulolytic, acid producing,proteolytic, lipolytic and methanogenic bacteria were more in the middle stage of methanogenesis.the liquid wastes from rubber processing used as diluents in combination with PSD, SPE promoted more biogas production with high methane content in the gas.The factors that favour methane production like TS, VS, cellulose and hemicellulose degradation were favoured in this treatment which led to higher methane biogenesis.The results further highlight ways and means to use agricultural wastes as alternative sources of energy.

Primary hemocyte culture of Penaeus monodon as an in vitro model for white spot syndrome virus titration, viral and immune related gene expression and cytotoxicity assays

Immortal cell lines have not yet been reported from Penaeus monodon, which delimits the prospects of investigating the associated viral pathogens especially white spot syndrome virus (WSSV). In this context, a method of developing primary hemocyte culture from this crustacean has been standardized by employing modified double strength Leibovitz-15 (L-15) growth medium supplemented with 2% glucose, MEM vitamins (1 ), tryptose phosphate broth (2.95 g l 1), 20% FBS, N-phenylthiourea (0.2 mM), 0.06 lgml 1 chloramphenicol, 100 lgml 1 streptomycin and 100 IU ml 1 penicillin and hemolymph drawn from shrimp grown under a bio-secured recirculating aquaculture system (RAS). In this medium the hemocytes remained viable up to 8 days. 5-Bromo-20-deoxyuridine (BrdU) labeling assay revealed its incorporation in 22 ± 7% of cells at 24 h. Susceptibility of the cells to WSSV was confirmed by immunofluoresence assay using a monoclonal antibody against 28 kDa envelope protein of WSSV. A convenient method for determining virus titer as MTT50/ml was standardized employing the primary hemocyte culture. Expression of viral genes and cellular immune genes were also investigated. The cell culture could be demonstrated for determining toxicity of a management chemical (benzalkonium chloride) by determining its IC50. The primary hemocyte culture could serve as a model for WSSV titration and viral and cellular immune related gene expression and also for investigations on cytotoxicity of aquaculture drugs and chemicals

Lymphoid organ cell culture system from Penaeus monodon (Fabricius) as a platform for white spot syndrome virus and shrimp immune-related gene expression

Shrimp cell lines are yet to be reported and this restricts the prospects of investigating the associated viral pathogens, especially white spot syndrome virus (WSSV). In this context, development of primary cell cultures from lymphoid organs was standardized. Poly-l-lysine-coated culture vessels enhanced growth of lymphoid cells, while the application of vertebrate growth factors did not, except insulin-like growth factor-1 (IGF-1). Susceptibility of the lymphoid cells to WSSV was confirmed by immunofluoresence assay using monoclonal antibody against the 28 kDa envelope protein of WSSV. Expression of viral and immunerelated genes in WSSV-infected lymphoid cultures could be demonstrated by RT-PCR. This emphasizes the utility of lymphoid primary cell culture as a platform for research in virus–cell interaction, virus morphogenesis, up and downregulation of shrimp immune-related genes, and also for the discovery of novel drugs to combat WSSV in shrimp culture

Biclustering Gene Expression Data using MSR Difference Threshold

Biclustering is simultaneous clustering of both rows and columns of a data matrix. A measure called Mean Squared Residue (MSR) is used to simultaneously evaluate the coherence of rows and columns within a submatrix. In this paper a novel algorithm is developed for biclustering gene expression data using the newly introduced concept of MSR difference threshold. In the first step high quality bicluster seeds are generated using K-Means clustering algorithm. Then more genes and conditions (node) are added to the bicluster. Before adding a node the MSR X of the bicluster is calculated. After adding the node again the MSR Y is calculated. The added node is deleted if Y minus X is greater than MSR difference threshold or if Y is greater than MSR threshold which depends on the dataset. The MSR difference threshold is different for gene list and condition list and it depends on the dataset also. Proper values should be identified through experimentation in order to obtain biclusters of high quality. The results obtained on bench mark dataset clearly indicate that this algorithm is better than many of the existing biclustering algorithms