Network generation enhances interpretation of proteomic data from induced apoptosis.

Thirteen proteins (identified with 2-D gels and MALDI-TOF MS) are significantly altered during staurosporine-induced apoptosis in SH-SY5Y cells. To gain further insight into the integrated cellular response to apoptosis, we have investigated whether a network can be generated of direct and indirect interactions between these 13 proteins. A network that contains 12 out of the 13 proteins was generated using Ingenuity Pathway Analysis (IPA) and this network is dominated (89%) by direct protein-protein interactions. This network scored 34 with IPA. Bootstrapping 1000 random lists of 13 proteins suggested that the frequency of this score occurring by chance was 1 in 500. We examined whether subsets of proteins such as HSPs, which were elevated after staurosporine, had a disproportionate impact on the network generated. There was no evidence that any subset of 8 from the 13 proteins contributed disproportionately to the network. Network generation, using IPA, identified common features (such as endoplasmic reticular stress protein interactions) in apoptotic studies from different laboratories. The generation of protein interaction networks clearly enhances the interpretation of proteomic data, but only when interpreted cautiously, particularly in respect of statistical analyses.

The utility of functional interaction and cluster analysis in CNS proteomics.

Proteomic studies offer enormous potential for gaining insight into cellular dynamics and disease processes. An immediate challenge for enhancing the utility of proteomics in translational research lies in methods of handling and interpreting the large datasets generated. Publications rarely extend beyond lists of proteins, putatively altered derived from basic statistics. Here we describe two additional distinct approaches (with particular strengths and limitations) that will enhance the analysis of proteomic datasets. Arithmetic and functional cluster analyses have been performed on proteins found differentially regulated in human glioma. These two approaches highlight (i) subgroups of proteins that may be co-regulated and play a role in glioma pathophysiology, and (ii) functional protein interactions that may improve comprehension of the biological mechanisms involved. A coherent proteomic strategy which involves both arithmetic and functional clustering, (together with careful consideration of conceptual limitations), is imperative for quantitative proteomics to deliver and advance the biological understanding of disease of the CNS. A strategy which combines arithmetic analysis and bioinformatics of protein-protein interactions is both generally applicable and will facilitate the interpretation of proteomic data.

Apoptosis induced by staurosporine alters chaperone and endoplasmic reticulum proteins: Identification by quantitative proteomics.

Apoptosis contributes to cell death after cerebral ischaemia. A quantitative proteomics approach has been employed to define alterations in protein levels in apoptosis induced with staurosporine (STS). Human neuroblastoma derived SH-SY5Y cells were treated with STS (500 nM for 6 h) to induce apoptosis. Quantitative 2-DE was used to determine the changing protein levels with MALDI-TOF MS identification of proteins. Of the 154 proteins analysed, 13 proteins were significantly altered as a result of the apoptotic stimulus; ten of the proteins showed an increase in level with STS and were identified as heat shock cognate 71 (Hsc71), two isoforms of heat shock protein 70 (Hsp70), glucose regulated protein 78 (GRP78), F-actin capping protein, stress-induced phosphoprotein 1, chromatin assembly factor 1 (CAF-1), protein disulphide isomerase A3 (PDI A3) precursor, transitional ER ATPase and actin interacting protein 1 (AIP 1). Three proteins which displayed significant decrease in levels with STS were identified as tubulin, vimentin and glucose regulated protein 94 (GRP94). The functional roles and subcellular locations of these proteins collectively indicate that STS-induced apoptosis provokes induces an unfolded protein response involving molecular chaperones, cochaperones and structural proteins indicative of ER stress.

Differential proteomics analysis of synaptic proteins identifies potential cellular targets and protein mediators of synaptic neuroprotection conferred by the slow Wallerian degeneration (Wlds) gene.

Non-somatic synaptic and axonal compartments of neurons are primary pathological targets in many neurodegenerative conditions, ranging from Alzheimer disease through to motor neuron disease. Axons and synapses are protected from degeneration by the slow Wallerian degeneration (Wld(s)) gene. Significantly the molecular mechanisms through which this spontaneous genetic mutation delays degeneration remain controversial, and the downstream protein targets of Wld(s) resident in non-somatic compartments remain unknown. In this study we used differential proteomics analysis to identify proteins whose expression levels were significantly altered in isolated synaptic preparations from the striatum of Wld(s) mice. Eight of the 16 proteins we identified as having modified expression levels in Wld(s) synapses are known regulators of mitochondrial stability and degeneration (including VDAC1, Aralar1, and mitofilin). Subsequent analyses demonstrated that other key mitochondrial proteins, not identified in our initial screen, are also modified in Wld(s) synapses. Of the non-mitochondrial proteins identified, several have been implicated in neurodegenerative diseases where synapses and axons are primary pathological targets (including DRP-2 and Rab GDP dissociation inhibitor beta). In addition, we show that downstream protein changes can be identified in pathways corresponding to both Ube4b (including UBE1) and Nmnat1 (including VDAC1 and Aralar1) components of the chimeric Wld(s) gene, suggesting that full-length Wld(s) protein is required to elicit maximal changes in synaptic proteins. We conclude that altered mitochondrial responses to degenerative stimuli are likely to play an important role in the neuroprotective Wld(s) phenotype and that targeting proteins identified in the current study may lead to novel therapies for the treatment of neurodegenerative diseases in humans.

Metabolism of trans, trans-muconaldehyde, a cytotoxic metabolite of benzene, in mouse liver by alcohol dehydrogenase Adh1 and aldehyde reductase AKR1A4.

The reductive metabolism of trans, trans-muconaldehyde, a cytotoxic metabolite of benzene, was studied in mouse liver. Using an HPLC-based stopped assay, the primary reduced metabolite was identified as 6-hydroxy-trans, trans-2,4-hexadienal (OH/CHO) and the secondary metabolite as 1,6-dihydroxy-trans, trans-2,4-hexadiene (OH/OH). The main enzymes responsible for the highest levels of reductase activity towards trans, trans-muconaldehyde were purified from mouse liver soluble fraction first by Q-sepharose chromatography followed by either blue or red dye affinity chromatography. In mouse liver, trans, trans-muconaldehyde is predominantly reduced by an NADH-dependent enzyme, which was identified as alcohol dehydrogenase (Adh1). Kinetic constants obtained for trans, trans-muconaldehyde with the native Adh1 enzyme showed a Vmax of 2141+/-500 nmol/min/mg and a Km of 11+/-4 microM. This enzyme was inhibited by pyrazole with a KI of 3.1+/-0.57 microM. Other fractions were found to contain muconaldehyde reductase activity independent of Adh1, and one enzyme was identified as the NADPH-dependent aldehyde reductase AKR1A4. This showed a Vmax of 115 nmol/min/mg and a Km of 15+/-2 microM and was not inhibited by pyrazole.