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Biomedical subjects

Majid Ghassemian

Publications and source records attributed to Majid Ghassemian.

5 recordsLinked to original sources

Sex-specific disruptions in PKCγ signaling in a mouse model of spinocerebellar ataxia type 14.

Spinocerebellar ataxia type 14 (SCA14) is an autosomal dominant neurodegenerative disease caused by mutations in the gene encoding protein kinase C γ (PKCγ), a Ca2+- and diacylglycerol-dependent Ser/Thr kinase dominantly expressed in cerebellar Purkinje cells. These mutations impair autoinhibitory constraints to increase the basal activity of the kinase, resulting in deficits in the cerebellum that are not observed upon simple deletion of the gene, and severe ataxia. To better understand the impact of aberrant PKCγ signaling in disease pathology, we developed a knockin murine model of the SCA14 mutation ΔF48 in PKCγ. This fully penetrant mutation is severe in humans and is mechanistically informative, as it has high basal activity but is unresponsive to agonist stimulation. Genetic, behavioral, and molecular testing revealed that ΔF48 PKCγ mice have ataxia-related phenotypes and an altered cerebellar phosphoproteome driven primarily by enhanced Ca2+/calmodulin-dependent kinase 2 signaling, effects that were more severe in male mice. Analysis of existing human data revealed that SCA14 has a significantly earlier age of onset for males compared with females. Data from this clinically relevant mutation suggested that enhanced basal activity of PKCγ is sufficient to cause ataxia and that treatment strategies to modulate aberrant PKCγ may be particularly beneficial in males.

Animals↗

Integrative analysis of transcript and metabolite profiling data sets to evaluate the regulation of biochemical pathways during photomorphogenesis.

One of the key developmental processes during photomorphogenesis is the differentiation of prolamellar bodies of proplastids into thylakoid membranes containing the photosynthetic pigment-protein complexes of chloroplasts. To study the regulatory events controlling pigment-protein complex assembly, including the biosynthesis of metabolic precursors and pigment end products, etiolated Arabidopsis thaliana seedlings were irradiated with continuous red light (Rc), which led to rapid greening, or continuous far-red light (FRc), which did not result in visible greening, and subjected to analysis by oligonucleotide microarrays and targeted metabolite profiling. An analysis using BioPathAt, a bioinformatic tool that allows the visualization of post-genomic data sets directly on biochemical pathway maps, indicated that in Rc-treated seedlings mRNA expression and metabolite patterns were tightly correlated (e.g., Calvin cycle, biosynthesis of chlorophylls, carotenoids, isoprenoid quinones, thylakoid lipids, sterols, and amino acids). K-means clustering revealed that gene expression patterns across various biochemical pathways were very similar in Rc- and FRc-treated seedlings (despite the visible phenotypic differences), whereas a principal component analysis of metabolite pools allowed a clear distinction between both treatments (in accordance with the visible phenotype). Our results illustrate the general importance of integrative approaches to correlate post-genomic data sets with phenotypic outcomes.

Arabidopsis↗

Comprehensive post-genomic data analysis approaches integrating biochemical pathway maps.

Post-genomic era research is focusing on studies to attribute functions to genes and their encoded proteins, and to describe the regulatory networks controlling metabolic, protein synthesis and signal transduction pathways. To facilitate the analysis of experiments using post-genomic technologies, new concepts for linking the vast amount of raw data to a biological context have to be developed. Visual representations of pathways help biologists to understand the complex relationships between components of metabolic networks, and provide an invaluable resource for the integration of transcriptomics, proteomics and metabolomics data sets. Besides providing an overview of currently available bioinformatic tools for plant scientists, we introduce BioPathAt, a newly developed visual interface that allows the knowledge-based analysis of genome-scale data by integrating biochemical pathway maps (BioPathAtMAPS module) with a manually scrutinized gene-function database (BioPathAtDB) for the model plant Arabidopsis thaliana. In addition, we discuss approaches for generating a biochemical pathway knowledge database for A. thaliana that includes, in addition to accurate annotation, condensed experimental information regarding in vitro and in vivo gene/protein function.

Computational Biology↗

Genome organization in Arabidopsis thaliana: a survey for genes involved in isoprenoid and chlorophyll metabolism.

The isoprenoid biosynthetic pathway provides intermediates for the synthesis of a multitude of natural products which serve numerous biochemical functions in plants: sterols (isoprenoids with a C30 backbone) are essential components of membranes; carotenoids (C40) and chlorophylls (which contain a C20 isoprenoid side-chain) act as photosynthetic pigments; plastoquinone, phylloquinone and ubiquinone (all of which contain long isoprenoid side-chains) participate in electron transport chains; gibberellins (C20), brassinosteroids (C30) and abscisic acid (C15) are phytohormones derived from isoprenoid intermediates; prenylation of proteins (with C15 or C20 isoprenoid moieties) may mediate subcellular targeting and regulation of activity; and several monoterpenes (C10), sesquiterpenes (C15) and diterpenes (C20) have been demonstrated to be involved in plant defense. Here we present a comprehensive analysis of genes coding for enzymes involved in the metabolism of isoprenoid-derived compounds in Arabidopsis thaliana. By combining homology and sequence motif searches with knowledge regarding the phylogenetic distribution of pathways of isoprenoid metabolism across species, candidate genes for these pathways in A. thaliana were obtained. A detailed analysis of the vicinity of chromosome loci for genes of isoprenoid metabolism in A. thaliana provided evidence for the clustering of genes involved in common pathways. Multiple sequence alignments were used to estimate the number of genes in gene families and sequence relationship trees were utilized to classify their individual members. The integration of all these datasets allows the generation of a knowledge-based metabolic map of isoprenoid metabolic pathways in A. thaliana and provides a substantial improvement of the currently available gene annotation.

Abscisic Acid↗

Fur regulates the expression of iron-stress genes in the cyanobacterium Synechococcus sp. strain PCC 7942.

A homologue of the 'ferric uptake regulation' gene (fur) was isolated from the cyanobacterium Synechococcus sp. strain PCC 7942 by an Escherichia coli-based 'in vivo repression assay'. The assay uses a reporter-gene construct containing the promoter region of the iron-regulated cyanobacterial gene isiA, fused to the coding region for chloramphenicol acetyltransferase. The isolated gene codes for a protein that has 41% sequence similarity (36% identity) to Fur from E. coli and contains the putative iron-binding motif found in the Fur proteins of purple bacteria. No significant similarity was found to the DxtR repressor that regulates the expression of toxin and siderophore production in Gram-positive bacteria. Insertional mutagenesis of the cloned cyanobacterial fur gene led to the creation of heteroallelic mutants that showed iron-deficiency symptoms in iron-replete medium, including the constitutive production of flavodoxin and of hydroxamate siderophores. Failure to eliminate wild-type copies of the fur gene from the polyploid genome of Synechococcus 7942 implies that in this cyanobacterium Fur may have essential functions in addition to the regulation of genes involved in iron scavenging or photosynthetic electron transport.

Amino Acid Sequence↗