79 research outputs found
Characterization of an extracellular lipase and its chaperone from Ralstonia eutropha H16
Lipase enzymes catalyze the reversible hydrolysis of triacylglycerol to fatty acids and glycerol at the lipid–water interface. The metabolically versatile Ralstonia eutropha strain H16 is capable of utilizing various molecules containing long carbon chains such as plant oil, organic acids, or Tween as its sole carbon source for growth. Global gene expression analysis revealed an upregulation of two putative lipase genes during growth on trioleate. Through analysis of growth and activity using strains with gene deletions and complementations, the extracellular lipase (encoded by the lipA gene, locus tag H16_A1322) and lipase-specific chaperone (encoded by the lipB gene, locus tag H16_A1323) produced by R. eutropha H16 was identified. Increase in gene dosage of lipA not only resulted in an increase of the extracellular lipase activity, but also reduced the lag phase during growth on palm oil. LipA is a non-specific lipase that can completely hydrolyze triacylglycerol into its corresponding free fatty acids and glycerol. Although LipA is active over a temperature range from 10 °C to 70 °C, it exhibited optimal activity at 50 °C. While R. eutropha H16 prefers a growth pH of 6.8, its extracellular lipase LipA is most active between pH 7 and 8. Cofactors are not required for lipase activity; however, EDTA and EGTA inhibited LipA activity by 83 %. Metal ions Mg[superscript 2+], Ca[superscript 2+], and Mn[superscript 2+] were found to stimulate LipA activity and relieve chelator inhibition. Certain detergents are found to improve solubility of the lipid substrate or increase lipase-lipid aggregation, as a result SDS and Triton X-100 were able to increase lipase activity by 20 % to 500 %. R. eutropha extracellular LipA activity can be hyper-increased, making the overexpression strain a potential candidate for commercial lipase production or in fermentations using plant oils as the sole carbon source.Malaysia-MIT Biotechnology Partnership Programm
In Situ Proteolysis to Generate Crystals for Structure Determination: An Update
For every 100 purified proteins that enter crystallization trials, an average of 30 form crystals, and among these only 13–15 crystallize in a form that enables structure determination. In 2007, Dong et al reported that the addition of trace amounts of protease to crystallization trials—in situ proteolysis—significantly increased the number of proteins in a given set that produce diffraction quality crystals. 69 proteins that had previously resisted structure determination were subjected to crystallization with in situ proteolysis and ten crystallized in a form that led to structure determination (14.5% success rate). Here we apply in situ proteolysis to over 270 new soluble proteins that had failed in the past to produce crystals suitable for structure determination. These proteins had produced no crystals, crystals that diffracted poorly, or produced twinned and/or unmanageable diffraction data. The new set includes yeast and prokaryotic proteins, enzymes essential to protozoan parasites, and human proteins such as GTPases, chromatin remodeling proteins, and tyrosine kinases. 34 proteins yielded deposited crystal structures of 2.8 Å resolution or better, for an overall 12.6% success rate, and at least ten more yielded well-diffracting crystals presently in refinement. The success rate among proteins that had previously crystallized was double that of those that had never before yielded crystals. The overall success rate is similar to that observed in the smaller study, and appears to be higher than any other method reported to rescue stalled protein crystallography projects
In Situ Proteolysis to Generate Crystals for Structure Determination: An Update
For every 100 purified proteins that enter crystallization trials, an average of 30 form crystals, and among these only 13–15 crystallize in a form that enables structure determination. In 2007, Dong et al reported that the addition of trace amounts of protease to crystallization trials—in situ proteolysis—significantly increased the number of proteins in a given set that produce diffraction quality crystals. 69 proteins that had previously resisted structure determination were subjected to crystallization with in situ proteolysis and ten crystallized in a form that led to structure determination (14.5% success rate). Here we apply in situ proteolysis to over 270 new soluble proteins that had failed in the past to produce crystals suitable for structure determination. These proteins had produced no crystals, crystals that diffracted poorly, or produced twinned and/or unmanageable diffraction data. The new set includes yeast and prokaryotic proteins, enzymes essential to protozoan parasites, and human proteins such as GTPases, chromatin remodeling proteins, and tyrosine kinases. 34 proteins yielded deposited crystal structures of 2.8 Å resolution or better, for an overall 12.6% success rate, and at least ten more yielded well-diffracting crystals presently in refinement. The success rate among proteins that had previously crystallized was double that of those that had never before yielded crystals. The overall success rate is similar to that observed in the smaller study, and appears to be higher than any other method reported to rescue stalled protein crystallography projects
Enhancement of crystallization with nucleotide ligands identified by dye-ligand affinity chromatography
Ligands interacting with Mycobacterium tuberculosis recombinant proteins were identified through use of the ability of Cibacron Blue F3GA dye to interact with nucleoside/nucleotide binding proteins, and the effects of these ligands on crystallization were examined. Co-crystallization with ligands enhanced crystallization and enabled X-ray diffraction data to be collected to a resolution of at least 2.7 Å for 5 of 10 proteins tested. Additionally, clues about individual proteins’ functions were obtained from their interactions with each of a panel of ligands
To automate or not to automate: this is the question
New protocols and instrumentation significantly boost the outcome of structural biology, which has resulted in significant growth in the number of deposited Protein Data Bank structures. However, even an enormous increase of the productivity of a single step of the structure determination process may not significantly shorten the time between clone and deposition or publication. For example, in a medium size laboratory equipped with the LabDB and HKL-3000 systems, we show that automation of some (and integration of all) steps of the X-ray structure determination pathway is critical for laboratory productivity. Moreover, we show that the lag period after which the impact of a technology change is observed is longer than expected
Small-scale, semi-automated purification of eukaryotic proteins for structure determination
A simple approach that allows cost-effective automated purification of recombinant proteins in levels sufficient for functional characterization or structural studies is described. Studies with four human stem cell proteins, an engineered version of green fluorescent protein, and other proteins are included. The method combines an expression vector (pVP62K) that provides in vivo cleavage of an initial fusion protein, a factorial designed auto-induction medium that improves the performance of small-scale production, and rapid, automated metal affinity purification of His8-tagged proteins. For initial small-scale production screening, single colony transformants were grown overnight in 0.4 ml of auto-induction medium, produced proteins were purified using the Promega Maxwell 16, and purification results were analyzed by Caliper LC90 capillary electrophoresis. The yield of purified [U-15N]-His8-Tcl-1 was 7.5 μg/ml of culture medium, of purified [U-15N]-His8-GFP was 68 μg/ml, and of purified selenomethione-labeled AIA–GFP (His8 removed by treatment with TEV protease) was 172 μg/ml. The yield information obtained from a successful automated purification from 0.4 ml was used to inform the decision to scale-up for a second meso-scale (10–50 ml) cell growth and automated purification. 1H–15N NMR HSQC spectra of His8-Tcl-1 and of His8-GFP prepared from 50 ml cultures showed excellent chemical shift dispersion, consistent with well folded states in solution suitable for structure determination. Moreover, AIA–GFP obtained by proteolytic removal of the His8 tag was subjected to crystallization screening, and yielded crystals under several conditions. Single crystals were subsequently produced and optimized by the hanging drop method. The structure was solved by molecular replacement at a resolution of 1.7 Å. This approach provides an efficient way to carry out several key target screening steps that are essential for successful operation of proteomics pipelines with eukaryotic proteins: examination of total expression, determination of proteolysis of fusion tags, quantification of the yield of purified protein, and suitability for structure determination
Defining the Functional Domain of Programmed Cell Death 10 through Its Interactions with Phosphatidylinositol-3,4,5-Trisphosphate
Cerebral cavernous malformations (CCM) are vascular abnormalities of the central nervous system predisposing blood vessels to leakage, leading to hemorrhagic stroke. Three genes, Krit1 (CCM1), OSM (CCM2), and PDCD10 (CCM3) are involved in CCM development. PDCD10 binds specifically to PtdIns(3,4,5)P3 and OSM. Using threading analysis and multi-template modeling, we constructed a three-dimensional model of PDCD10. PDCD10 appears to be a six-helical-bundle protein formed by two heptad-repeat-hairpin structures (α1–3 and α4–6) sharing the closest 3D homology with the bacterial phosphate transporter, PhoU. We identified a stretch of five lysines forming an amphipathic helix, a potential PtdIns(3,4,5)P3 binding site, in the α5 helix. We generated a recombinant wild-type (WT) and three PDCD10 mutants that have two (Δ2KA), three (Δ3KA), and five (Δ5KA) K to A mutations. Δ2KA and Δ3KA mutants hypothetically lack binding residues to PtdIns(3,4,5)P3 at the beginning and the end of predicted helix, while Δ5KA completely lacks all predicted binding residues. The WT, Δ2KA, and Δ3KA mutants maintain their binding to PtdIns(3,4,5)P3. Only the Δ5KA abolishes binding to PtdIns(3,4,5)P3. Both Δ5KA and WT show similar secondary and tertiary structures; however, Δ5KA does not bind to OSM. When WT and Δ5KA are co-expressed with membrane-bound constitutively-active PI3 kinase (p110-CAAX), the majority of the WT is co-localized with p110-CAAX at the plasma membrane where PtdIns(3,4,5)P3 is presumably abundant. In contrast, the Δ5KA remains in the cytoplasm and is not present in the plasma membrane. Combining computational modeling and biological data, we propose that the CCM protein complex functions in the PI3K signaling pathway through the interaction between PDCD10 and PtdIns(3,4,5)P3
Solution of the structure of aspergillus-niger acid alpha-amylase by combined molecular replacement and multiple isomorphous replacement methods
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