Specific inhibition of the chymotrypsin-like activity of the proteasome induces a bipolar morphology in neuroblastoma cells

AbstractBackground: Lactacystin inhibits cell proliferation and induces a distinctive, predominantly bipolar (two-neurite-bearing) morphology in Neuro 2A murine neuroblastoma cells. It binds with high specificity to the multicatalytic 20S proteasome and inhibits at least three of its peptidase activities (chymotrypsin-like, trypsin-like and peptidylglutamyl-peptide hydrolyzing), each at a different rate, without inhibiting other known proteases. The chymotrypsin-like and trypsin-like activities of the proteasome are inhibited most rapidly, and irreversibly. In an effort to determine which of the peptidase activities needs to be inhibited for neurite outgrowth to occur, we treated Neuro 2A cells with peptide aldehydes that selectively inhibit different proteasome activities.Results: Treatment with peptide aldehydes ending in a hydrophobic residue, all of which inhibit the chymotrypsin-like activity, results in a bipolar morphology in Neuro 2A cells, whereas treatment with a peptide aidehyde inhibitor of the trypsin-like activity does not lead to a detectable change in morphology. One of the inhibitors that induces neurite outgrowth has been previously shown to inhibit the chymotrypsin-like activity of the proteasome without inhibiting the other apparently distinct peptidase activities that cleave after neutral residues, the so-called ‘branched chain amino acid preferring’ (BrAAP) and ‘small neutral amino acid preferring’ (SNAAP) activities, or the peptidylglutamyl-peptide hydrolyzing (PGPH) activity.Conclusions: The chymotrypsin-like activity appears to antagonize bipolar-type neurite outgrowth in Neuro 2A cells, while the trypsin-like, PGPH, BrAAP and SNAAP appear not to do so. Selective inhibition of a single peptidase activity, as opposed to general inhibition of the proteasome, appears sufficient to induce a specific cellular process. Selective inhibition might be useful in managing diseases where only one activity is involved without completely inhibiting the proteasome. It is also possible that endogenous regulators of the proteasome could affect cellular processes and that certain peptidase activities of the proteasome may have roles in specifying a given cell fate

Multilevel regulation of growth rate in yeast revealed using systems biology

The effect of changing growth rates on the transcriptome, proteome and metabolome has been systematically studied. Measurements made under varying nutrient conditions, corresponding to biochemical pathways that correlate primarily with growth rate, reveal a central role for mitochondrial metabolism and the TOR (target of rapamycin) signaling pathway

Systems Biology Graphical Notation: Process Description language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps

Systems Biology Graphical Notation: Process Description language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps

Apoptosis-inducing natural products found in utero during murine pregnancy

AbstractBackground: Hormones, lipids, vitamins and other biologically active small molecules can be removed from animal tissues by extraction with organic solvents. These compounds can have dramatic effects on cultured cells and the characterization of such compounds can lead to the discovery of new functions for known molecules, or even to the discovery of previously unknown compounds.Results: Organic-soluble compounds in 17.5-day-old mouse embryos were removed with tert-butylmethylether and found to induce apoptosis in T-antigen-transformed Jurkat T cells. These embryonic extracts were fractionated and their apoptosis-inducing components were identified as a mixture of polyunsaturated fatty acids, including arachidonic, docosatetraenoic and docosahexaenoic acids. Docosatetraenoic acid was the most potent apoptosis inducer with an effective dose (ED50) of 30 μM.Conclusions: A family of polyunsaturated fatty acids is shown to be abundant in utero during pregnancy. Members of this family are able to induce cleavage of poly(ADP)ribose polymerase, and ultimately to induce apoptosis, in T-antigen-transformed Jurkat T cells. Free radical scavengers, including phenol and benzyl alcohol, block the apoptosis-inducing properties of these polyunsaturated fatty acids; this is consistent with a lipid peroxidation mechanism involving formation of hydroperoxy fatty acids

Skeletally Diverse Small Molecules Using a Build/Couple/Pair Strategy

Intermolecular couplings of simple building blocks using catalytic, stereoselective cross-Mannich reactions followed by intramolecular functional group-pairing reactions of easily accessed variants of the Mannich products are explored as a route to skeletally diverse small molecules. The synthetic pathway yields products having 12 different skeletons using only three steps and has the potential to enable substantial stereochemical diversification in the future