Highly conserved cysteines of mouse core 2 beta1,6-N-acetylglucosaminyltransferase I form a network of disulfide bonds and include a thiol that affects enzyme activity

Core 2 beta1,6-N-acetylglucosaminyltransferase I (C2GnT-I) plays a pivotal role in the biosynthesis of mucin-type O-glycans that serve as ligands in cell adhesion. To elucidate the three-dimensional structure of the enzyme for use in computer-aided design of therapeutically relevant enzyme inhibitors, we investigated the participation of cysteine residues in disulfide linkages in a purified murine recombinant enzyme. The pattern of free and disulfide-bonded Cys residues was determined by liquid chromatography/electrospray ionization tandem mass spectrometry in the absence and presence of dithiothreitol. Of nine highly conserved Cys residues, under both conditions, one (Cys217) is a free thiol, and eight are engaged in disulfide bonds, with pairs formed between Cys59-Cys413, Cys100-Cys172, Cys151-Cys199, and Cys372-Cys381. The only non-conserved residue within the beta1,6-N-acetylglucosaminyltransferase family, Cys235, is also a free thiol in the presence of dithiothreitol; however, in the absence of reductant, Cys235 forms an intermolecular disulfide linkage. Biochemical studies performed with thiolreactive agents demonstrated that at least one free cysteine affects enzyme activity and is proximal to the UDP-GlcNAc binding site. A Cys217 --> Ser mutant enzyme was insensitive to thiol reactants and displayed kinetic properties virtually identical to those of the wild-type enzyme, thereby showing that Cys217, although not required for activity per se, represents the only thiol that causes enzyme inactivation when modified. Based on the pattern of free and disulfide-linked Cys residues, and a method of fold recognition/threading and homology modeling, we have computed a three-dimensional model for this enzyme that was refined using the T4 bacteriophage beta-glucosyltransferase fold.     

Probing the ligand preferences of the three types of bacterial pantothenate kinase

Pantothenate kinase (PanK) catalyzes the transformation of pantothenate to 4′-phosphopantothenate, the first committed step in coenzyme A biosynthesis. While numerous pantothenate antimetabolites and PanK inhibitors have been reported for bacterial type I and type II PanKs, only a few weak inhibitors are known for bacterial type III PanK enzymes. Here, a series of pantothenate analogues were synthesized using convenient synthetic methodology. The compounds were exploited as small organic probes to compare the ligand preferences of the three different types of bacterial PanK. Overall, several new inhibitors and substrates were identified for each type of PanK.     

Specific Activity of Brain Palmitoyl-CoA Pool Provides Rates of Incorporation of Palmitate in Brain Phospholipids in Awake Rats

Abstract: In vivo rates of palmitate incorporation into brain phospholipids were measured in awake rats following programmed intravenous infusion of unesterified [9,10-³H]palmitate to maintain constant plasma specific activity. Animals were killed after 2–10 min of infusion by microwave irradiation and analyzed for tracer distribution in brain phospholipid and phospholipid precursor, i.e., brain unesterified palmitate and palmitoyl-CoA, pools. [9,10-³H]Palmitate incorporation into brain phospholipids was linear with time and rapid, with >50% of brain tracer in choline-containing glycerophospholipids at 2 min of infusion. However, tracer specific activity in brain phospholipid precursor pools was low and averaged only 1.6–1.8% of plasma unesterified palmitate specific activity. Correction for brain palmitoyl-CoA specific activity increased the calculated rate of palmitate incorporation into brain phospholipids (0.52 nmol/s/g) by ∼60-fold. The results suggest that palmitate incorporation and turnover in brain phospholipids are far more rapid than generally assumed and that this rapid turnover dilutes tracer specific activity in brain palmitoyl-CoA pool owing to release and recycling of unlabeled fatty acid from phospholipid breakdown.     

Distinct residues of human p53 implicated in binding to DNA, simian virus 40 large T antigen, 53BP1, and 53BP2.

We identified a minimal domain of human p53 required for the transactivation of a p53 response element in Saccharomyces cerevisiae. This domain contains the central region of p53 sufficient for specific DNA binding, which colocalizes with the region responsible for binding simian virus 40 large T antigen, 53BP1, and 53BP2. Thirty amino acid positions, including natural mutational hot spots (R175, R213, R248, R249, and R273), in the minimal DNA-binding domain were mutated by alanine substitution. Alanine substitutions at positions R213, R248, R249, D281, R282, R283, E286, and N288 affected transactivation but allowed binding to at least one of the three interacting proteins; these amino acids may be involved in amino acid-base pair contacts. Surprisingly, alanine substitution at the mutational hot spot R175 did not affect DNA binding, transactivation, or T-antigen binding, although it nearly eliminated binding to 53BP1 and 53BP2. Mutation of H168 significantly affected only T-antigen binding, and mutation of E285 affected only 53BP1 binding. Thus, we implicate specific residues of p53 in different DNA and protein interactions.     

A pharmacogenomic method for individualized prediction of drug sensitivity

Identifying the best drug for each cancer patient requires an efficient individualized strategy. We present MATCH (M erging genomic and pharmacologic A nalyses for T herapy CH oice), an approach using public genomic resources and drug testing of fresh tumor samples to link drugs to patients. Valproic acid (VPA) is highlighted as a proof‐of‐principle. In order to predict specific tumor types with high probability of drug sensitivity, we create drug response signatures using publically available gene expression data and assess sensitivity in a data set of >40 cancer types. Next, we evaluate drug sensitivity in matched tumor and normal tissue and exclude cancer types that are no more sensitive than normal tissue. From these analyses, breast tumors are predicted to be sensitive to VPA. A meta‐analysis across breast cancer data sets shows that aggressive subtypes are most likely to be sensitive to VPA, but all subtypes have sensitive tumors. MATCH predictions correlate significantly with growth inhibition in cancer cell lines and three‐dimensional cultures of fresh tumor samples. MATCH accurately predicts reduction in tumor growth rate following VPA treatment in patient tumor xenografts. MATCH uses genomic analysis with in vitro testing of patient tumors to select optimal drug regimens before clinical trial initiation.     

Production of cellulolytic enzymes from theXylaria andHypoxylon species of xylariaceae

Eighteen strains of xylariaceous fungi have been screened for higher activities of cellulolytic enzymes,Trichoderma reesei QM 9414 was also examined for comparison. Strains ofXylaria anisopleura andX. regalis had higher endocellulase (CMCase) and exocellulase (Avicelase) activities after 2 weeks' incubation.Hypoxylon stygium produced the highest activity of -glucosidase 3 days after inoculation. The optimum pH for these cellulolytic enzymes was approx. 5.0 and the optimum temperatures ranged from 37 to 50°C. A mixed culture process usingT. reesei QM 9414 andH. stygium was developed to obtain enhanced synthesis of cellulase. -Glucosidase activities in the mixed culture increased within 48h whenH. stygium was introduced after 24h.