Biomedical subjects

N H Kulkarni

Publications and source records attributed to N H Kulkarni.

5 recordsLinked to original sources

PubMed2005

Effects of parathyroid hormone on Wnt signaling pathway in bone.

The Wnt signaling pathway has recently been demonstrated to play an important role in bone cell function. In previous studies using DNA microarray analyses, we observed a change in some of the molecular components of the canonical Wnt pathway namely, frizzled-1 (FZD-1) and axil, in response to continuous parathyroid hormone (PTH) treatment in rats. In the present study, we further explored other components of the Wnt signaling pathway in rat distal metaphyseal bone in vivo, and rat osteoblastic osteosarcoma cells (UMR 106) in culture. Several Wnt pathway components, including low-density lipoprotein-receptor-related protein 5 (LRP5), LRP6, FZD-1, Dickkopf-1 (Dkk-1), and Kremen-1 (KRM-1), were expressed in bone in vivo and in osteoblasts in vitro. Continuous exposure to PTH (1-38) both in vivo and in vitro upregulated the mRNA expression of LRP6 and FZD-1 and decreased LRP5 and Dkk-1. These effects in UMR 106 cells were associated with an increase in beta-catenin as measured by Western blots and resulted in functional activation (three to six-fold) of a downstream Wnt responsive TBE6-luciferase (TCF/LEF-binding element) reporter gene. Activation of the TBE6-luciferase reporter gene by PTH (1-38) in UMR 106 cells was inhibited by the protein kinase A (PKA) inhibitor, H89. Activation was mimicked by PTH (1-31), PTH-related protein (1-34), and forskolin, but both PTH (3-34) and (7-34) had no effect. These findings suggest that the effect of PTH on the canonical Wnt signaling pathway occurs at least in part via the cAMP-PKA pathway through the differential regulation of the receptor complex proteins (FZD-1/LRP5 or LRP6) and the antagonist (Dkk-1). Taken together, these results reveal a possible role for the Wnt signaling pathway in PTH actions in bone.

Animals↗

PubMed2001

Functional genomics of odor-guided behavior in Drosophila melanogaster.

The avoidance response to repellent odorants in Drosophila melanogaster, a response essential for survival, provides an advantageous model for studies on the genetic architecture of olfactory behavior. Transposon tagging in a highly inbred strain of flies in combination with a rapid and simple statistical behavioral assay enables the identification of not only large phenotypic effects, but also small aberrations from wild-type avoidance behavior. The recent completion of the sequence of the Drosophila genome facilitates the molecular characterization of transposon-tagged genes and correlation between gene expression and behavior in smell-impaired (smi) mutant lines. Quantitative genetic analyses of a collection of smi lines in a co-isogenic background revealed an extensive network of epistatic interactions among genes that shape the olfactory avoidance response. Candidate genes for several of these transposon-tagged smi loci implicate genes that mediate odorant recognition, including a novel odorant binding protein; signal propagation, including a voltage-gated sodium channel; and a protein containing multiple leucine rich repeats and PDZ domains likely to be involved in postsynaptic organization in the olfactory pathway. Several novel genes of unknown function have also been implicated, including a novel tyrosine-regulated protein kinase. The discovery and characterization of novel gene products that have major, hitherto unappreciated effects on olfactory behavior will provide new insights in the generation and regulation of odor-guided behavior. The identification and functional characterization of proteins encoded by smi genes that form part of the olfactory subgenome and correlation of polymorphisms in these genes with variation in odor-guided behavior in natural populations will advance our understanding of the genetic architecture of chemosensory behavior.

Animals↗

PubMed2000

Characterization and differential expression of a human gene family of olfactomedin-related proteins.

Olfactomedin-related proteins are secreted glycoproteins with conserved C-terminal motifs. Olfactomedin was originally identified as the major component of the mucus layer that surrounds the chemosensory dendrites of olfactory neurons. Homologues were subsequently found also in other tissues, including the brain and in species ranging from Caenorhabditis elegans to Homo sapiens. Most importantly, the TIGR/myocilin protein, expressed in the eye and associated with the pathogenesis of glaucoma, is an olfactomedin-related protein. The prevalence of olfactomedin-related proteins among species and their identification in different tissues prompted us to investigate whether a gene family exists within a species, specifically Homo sapiens. A GenBank search indeed revealed an entire human gene family of olfactomedin-related proteins with at least five members, designated hOlfA through hOlfD and the TIGR/myocilin protein. hOlfA corresponds to the rat neuronal AMZ protein. Phylogenetic analyses of 18 olfactomedin-related sequences resolved four distinct subfamilies. Among the human proteins, hOlfA and hOlfC, both expressed in brain, are most closely related. Northern blot analyses of 16 human tissues demonstrated highly specific expression patterns: hOlfA is expressed in brain, hOlfB in pancreas and prostate, hOlfC in cerebellum, hOlfD in colon, small intestine and prostate and TIGR/myocilin in heart and skeletal muscle. The link between TIGR/myocilin and ocular hypertension and the expression of several of these proteins in mucus-lined tissues suggest that they play an important role in regulating physical properties of the extracellular environment. Future studies can now assess whether other members of this gene family, like TIGR/myocilin, are also associated with human disease processes.

Amino Acid Sequence↗

PubMedDate not supplied

Data-driven analysis approach for biomarker discovery using molecular-profiling technologies.

High-throughput molecular-profiling technologies provide rapid, efficient and systematic approaches to search for biomarkers. Supervised learning algorithms are naturally suited to analyse a large amount of data generated using these technologies in biomarker discovery efforts. The study demonstrates with two examples a data-driven analysis approach to analysis of large complicated datasets collected in high-throughput technologies in the context of biomarker discovery. The approach consists of two analytic steps: an initial unsupervised analysis to obtain accurate knowledge about sample clustering, followed by a second supervised analysis to identify a small set of putative biomarkers for further experimental characterization. By comparing the most widely applied clustering algorithms using a leukaemia DNA microarray dataset, it was established that principal component analysis-assisted projections of samples from a high-dimensional molecular feature space into a few low dimensional subspaces provides a more effective and accurate way to explore visually and identify data structures that confirm intended experimental effects based on expected group membership. A supervised analysis method, shrunken centroid algorithm, was chosen to take knowledge of sample clustering gained or confirmed by the first step of the analysis to identify a small set of molecules as candidate biomarkers for further experimentation. The approach was applied to two molecular-profiling studies. In the first study, PCA-assisted analysis of DNA microarray data revealed that discrete data structures exist in rat liver gene expression and correlated with blood clinical chemistry and liver pathological damage in response to a chemical toxicant diethylhexylphthalate, a peroxisome-proliferator-activator receptor agonist. Sixteen genes were then identified by shrunken centroid algorithm as the best candidate biomarkers for liver damage. Functional annotations of these genes revealed roles in acute phase response, lipid and fatty acid metabolism and they are functionally relevant to the observed toxicities. In the second study, 26 urine ions identified from a GC/MS spectrum, two of which were glucose fragment ions included as positive controls, showed robust changes with the development of diabetes in Zucker diabetic fatty rats. Further experiments are needed to define their chemical identities and establish functional relevancy to disease development.

Algorithms↗

PubMedDate not supplied

Optimized blood cell profiling method for genomic biomarker discovery using high-density microarray.

High-quality biomarkers for disease progression, drug efficacy and toxicity liability are essential for improving the efficiency of drug discovery and development. The identification of drug-activity biomarkers is often limited by access to and the quantity of target tissue. Peripheral blood has increasingly become an attractive alternative to tissue samples from organs as source for biomarker discovery, especially during early clinical studies. However, given the heterogeneous blood cell population, possible artifacts from ex vivo activations, and technical difficulties associated with overall performance of the assay, it is challenging to profile peripheral blood cells directly for biomarker discovery. In the present study, Applied BioSystems' blood collection system was evaluated for its ability to isolate RNA suitable for use on the Affymetrix microarray platform. Blood was collected in a TEMPUS tube and RNA extracted using an ABI-6100 semi-automated workstation. Using human and rat whole blood samples, it was demonstrated that the RNA isolated using this approach was stable, of high quality and was suitable for Affymetrix microarray applications. The microarray data were statistically analysed and compared with other blood protocols. Minimal haemoglobin interference with RNA labelling efficiency and chip hybridization was found using the TEMPUS tube and extraction method. The RNA quality, stability and ease of handling requirement make the TEMPUS tube protocol an attractive approach for expression profiling of whole blood to support target and biomarker discovery.

Animals↗