Association of EXT1 and EXT2, hereditary multiple exostoses gene products, in Golgi apparatus

We prepared the specific antibodies for EXT1 and EXT2, hereditary multiple exostoses (HME) gene products, and characterized their expression, subcellular localization, and protein association among EXT members. Biochemical analyses indicate that EXT1 and EXT2 can associate and form homo/hetero-oligomers in vivo with or without HME-linked mutations, EXT1 (R340C) and EXT2 (D227N), when exogenously expressed in COS-7 cells. An immunocytochemical analysis showed that both EXT1 and EXT2 localized in Golgi apparatus, irrespective of HME mutations. An immunohistochemical analysis on developing bones further showed that both EXT1 and EXT2 were concomitantly expressed in hypertrophic chondrocytes of forelimb bones from 1-day-old neonatal mouse, but down-regulated in maturing chondrocytes of developing cartilage from 21-day-old mouse. Taken together with the recent finding that EXTs encode for the glycosyltransferase required for the synthesis of heparan sulfate [Lind, T., Tufaro, F., McCormick, C., Lindahl, U., and Lindholt, K. (1998) J. Biol. Chem. 273, 26265-26268], our results implied a molecular basis that a HME-linked mutation found in EXT genes could interfere the physiological function(s) of EXT homo/hetero-oligomers as glycosyltransferases in the developing bones of HME patients.     

Human Pancreatic Tumor Organoids Reveal Loss of Stem Cell Niche Factor Dependence during Disease Progression

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A knowledge base for predicting protein localization sites in eukaryotic cells

To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing a knowledge base by organizing various experimental and computational observations as a collection of if-then rules. Here we report an expert system, which utilizes this knowledge base, for predicting localization sites of proteins only from the information on the amino acid sequence and the source origin. We collected data for 401 eukaryotic proteins with known localization sites (subcellular and extracellular) and divided them into training data and testing data. Fourteen localization sites were distinguished for animal cells and 17 for plant cells. When sorting signals were not well characterized experimentally, various sequence features were computationally derived from the training data. It was found that 66% of the training data and 59% of the testing data were correctly predicted by our expert system. This artificial intelligence approach is powerful and flexible enough to be used in genome analyses.     

The coexistence of Ser84 in renin and His13 in angiotensinogen brings a pH profile of two separate peaks to the reaction of human renin and sheep angiotensinogen

The pH dependence and kinetics parameters of renin-angiotensinogen reactions were determined using wild-type and S84G mutant human renins and wild-type and H13Y mutant sheep angiotensinogens. It is explained in this report that (i) renin catalyzes acidic and basic reactions of which the optimum pHs are 5.5 and 7.5-8.2 respectively, both of which produce angiotensin I; (ii) Ser84 specific to human renin accelerates the acidic reaction by 75-110% through elevation of V(max), and shifts the optimum pH of the basic reaction from 7.5 to 8.0-8.2; and (iii) His13 specific to sheep angiotensinogen accelerates the acidic and basic reactions by 25-42% through reduction of K(m). It is concluded from these results that the coexistence of Ser84 in renin and His13 in angiotensinogen brings a pH profile of two separate peaks at pHs 5.5 and 8.2 to the reaction of human renin and sheep angiotensinogen.     

Conversion of AFLP markers to sequence-specific markers for closely related lines in rice by use of the rice genome sequence

DNA polymorphism between two major japonica rice cultivars, Nipponbare and Koshihikari, was identified by AFLP. Eighty-four polymorphic AFLP markers were obtained by analysis with 360 combinations of primer pairs. Nucleotide sequences of 73 markers, 29 from Nipponbare and 44 from Koshihikari, were determined, and 46 AFLP markers could be assigned to rice chromosomes based on sequence homology to the rice genome sequence. Specific primers were designed for amplification of the regions covering the AFLP markers and the flanking sequences. Out of the 46 primer pairs, 44 amplified single DNA fragments, six of which showed different sizes between Nipponbare and Koshihikari, yielding codominant SCAR markers. Eight primer pairs amplified only Nipponbare sequences, providing dominant SCAR markers. DNA fragments amplified by 13 primer pairs showed polymorphism by CAPS, and polymorphism of those amplified by 13 other primer pairs were detected by PCR-RF-SSCP (PRS). Nucleotide sequences of the other four DNA fragments were determined in Koshihikari, but no difference was found between Koshihikari and Nipponbare. In total, 40 sequence-specific markers for the combination of Nipponbare and Koshihikari were produced. All the SNPs identified by AFLP were detectable by CAPS and PRS. The same method was applicable to a combination of Kokoromachi and Tohoku 168, and 23 polymorphic markers were identified using these two rice cultivars. The procedure of conversion of AFLP-markers to the sequence-specific markers used in this study enables efficient sequence-specific marker production for closely related cultivars.     

Metabolite profiles of polyhydroxyalkanoate-producing Ralstonia eutropha H16

This study describes metabolite profiles of Ralstonia eutropha H16 focusing on biosynthesis of polyhydroxyalkanoates (PHAs), bacterial polyesters attracted as biodegradable bio-based plastics. As CoA-thioesters are important intermediates in PHA biosynthesis, four kinds of acyl-CoAs with medium chain length were prepared and used to establish analytical conditions for capillary electrophoresis-electron spray ionization-tandem mass spectrometry (CE–ESI-MS/MS). Metabolites were extracted from R. eutropha cells in growth, PHA production, and stationary phases on fructose and PHA production phase on octanoate, and subjected to stable isotope dilution-based comparative quantification by multiple reaction monitoring using CE–ESI-MS/MS and ¹³C-labeled metabolites prepared by extraction from R. eutropha mutant grown on U-¹³C₆-glucose. This procedure allowed to quantify relative changes of 94 ionic metabolites including CoA-thioesters. Hexose-phosphates except for glucose 1-phosphate were decreased in the PHA production phase than in the growth phase, suggesting reduced flux of sugar degradation after the cell growth. Several intermediates in TCA cycle and gluconeogenesis were increased in the PHA production phase on octanoate. Interestingly, ribulose 1,5-bisphosphate were detected in all the samples examined, raising possibilities of CO₂ fixation by Calvin–Benson–Bassham cycle in this bacterium even under heterotrophic growth conditions. Turnover of acyl moieties through β-oxidation was suggested to be active on fructose, as CoA-thioesters of C₆ and C₈ were detected in the fructose-grown cells. In addition, major metabolic pools in R. eutropha cells were estimated from the signal intensities. The results of the present study provided new insights into global metabolisms in PHA-producing R. eutropha.