Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of -2

As constant at 1.6 ± 0.1 g/L for BP000 and 1.8 ± 0.1 g/L for BP10001.<p><b>Copyright information:</b></p><p>Taken from "Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of "</p><p>http://www.microbialcellfactories.com/content/7/1/9</p><p>Microbial Cell Factories 2008;7():9-9.</p><p>Published online 17 Mar 2008</p><p>PMCID:PMC2315639.</p><p></p

Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of -3

to values of 0.15 U/mg with NADH and 0.18 U/mg with NADPH. In strain BP10001, the specific activities are 0.26 U/mg with NADH and 0.33 U/mg with NADPH.<p><b>Copyright information:</b></p><p>Taken from "Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of "</p><p>http://www.microbialcellfactories.com/content/7/1/9</p><p>Microbial Cell Factories 2008;7():9-9.</p><p>Published online 17 Mar 2008</p><p>PMCID:PMC2315639.</p><p></p

Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of -1

As constant at 1.4 ± 0.1 g/L for BP000 and 1.5 ± 0.1 g/L for BP10001. Error bars show the S.D. of triplicate fermentation experiments.<p><b>Copyright information:</b></p><p>Taken from "Altering the coenzyme preference of xylose reductase to favor utilization of NADH enhances ethanol yield from xylose in a metabolically engineered strain of "</p><p>http://www.microbialcellfactories.com/content/7/1/9</p><p>Microbial Cell Factories 2008;7():9-9.</p><p>Published online 17 Mar 2008</p><p>PMCID:PMC2315639.</p><p></p

Positively Charged Mini-Protein Z_basic2 As a Highly Efficient Silica Binding Module: Opportunities for Enzyme Immobilization on Unmodified Silica Supports

Silica is a highly attractive support material for protein immobilization in a wide range of biotechnological and biomedical-analytical applications. Without suitable derivatization, however, the silica surface is not generally usable for attachment of proteins. We show here that Z_basic2 (a three α-helix bundle mini-protein of 7 kDa size that exposes clustered positive charges from multiple arginine residues on one side) functions as highly efficient silica binding module (SBM), allowing chimeras of target protein with SBM to become very tightly attached to underivatized glass at physiological pH conditions. We used two enzymes, d-amino acid oxidase and sucrose phosphorylase, to demonstrate direct immobilization of Z_basic2 protein from complex biological samples with extremely high selectivity. Immobilized enzymes displayed full biological activity, suggesting that their binding to the glass surface had occurred in a preferred orientation via the SBM. We also show that charge complementarity was the main principle of affinity between SBM and glass surface, and Z_basic2 proteins were bound in a very strong, yet fully reversible manner, presumably through multipoint noncovalent interactions. Z_basic2 proteins were immobilized on porous glass in a loading of 30 mg protein/g support or higher, showing that attachment via the SBM combines excellent binding selectivity with a technically useful binding capacity. Therefore, Z_basic2 and silica constitute a fully orthogonal pair of binding module and insoluble support for oriented protein immobilization, and this opens up new opportunities for the application of silica-based materials in the development of supported heterogeneous biocatalysts

Effects of point directed mutagenesis on descriptors.

a<p>PDB ID.</p>b<p>Net-charge of wildtype (WT) in elementary charge units, e.</p>c<p>Net-charge, difference between mutant and WT.</p>d<p>Dipole moment of wildtype in eÅ.</p>e<p>Dipole moment, difference between mutant and WT.</p

Renewal of the Air–Water Interface as a Critical System Parameter of Protein Stability: Aggregation of the Human Growth Hormone and Its Prevention by Surface-Active Compounds

Soluble proteins are often highly unstable under mixing conditions that involve dynamic contacting between the main liquid phase and a gas phase. The recombinant human growth hormone (rhGH) was recently shown to undergo aggregation into micrometer-sized solid particles composed of non-native (mis- or unfolded) protein, once its solutions were stirred or shaken to generate a continuously renewed air–water interface. To gain deepened understanding and improved quantification of the air–water interface effect on rhGH stability, we analyzed the protein’s aggregation rate (<i>r</i>_agg) at controlled specific air–water surface areas (<i>a</i>_G/L) established by stirring or bubble aeration. We show that in spite of comparable time-averaged values for <i>a</i>_G/L (≈ 100 m²/m³), aeration gave a 40-fold higher <i>r</i>_agg than stirring. The enhanced <i>r</i>_agg under aeration was ascribed to faster macroscopic regeneration of free <i>a</i>_G/L during aeration as compared to stirring. We also show that <i>r</i>_agg was independent of the rhGH concentration in the range 0.67 – 6.7 mg/mL, and that it increased linearly dependent on the available <i>a</i>_G/L. The nonionic surfactant Pluronic F-68, added in 1.6-fold molar excess over rhGH present, resulted in complete suppression of <i>r</i>_agg. Foam formation was not a factor influencing <i>r</i>_agg. Using analysis by circular dichroism spectroscopy and small-angle X-ray scattering, we show that in the presence of Pluronic F-68 under both stirring and aeration, the soluble protein retained its original fold, featuring native-like relative composition of secondary structural elements. We further provide evidence that the efficacy of Pluronic F-68 resulted from direct, probably hydrophobic protein–surfactant interactions that prevented rhGH from becoming attached to the air–water interface. Surface-induced aggregation of rhGH is suggested to involve desorption of non-native protein from the air–water interface as the key limiting step. Proteins or protein aggregates released back into the bulk liquid appear to be essentially insoluble

Leloir Glycosyltransferases as Biocatalysts for Chemical Production

Glycosylation is a chemical transformation that is centrally important in all glycoscience and related technologies. Catalysts offering good control over reactivity and selectivity in synthetic glycosylations are much sought. The enzymes responsible for glycosylations in natural biosynthesis are sugar-nucleotide-dependent (Leloir) glycosyltransferases. Discovery-oriented synthesis and pilot batch production of oligosaccharides and glycosylated natural products have previously relied on Leloir glycosyltransferases. However, despite their perceived synthetic utility, Leloir glycosyltransferases are yet to see widespread application in industrial biocatalysis. Here we show progress and limitations in the development of Leloir glycosyltransferases into robust biocatalytic systems for use in glycosylations for chemical production. Obtaining highly active and stable (whole-cell) catalysts that can promote the desired glycosylation(s) coupled to an in situ sugar nucleotide supply remains a difficult problem. Optimizing glycosyltransferase cascade reactions for high process efficiency is another. Glycosylations of some natural products (e.g., flavonoids, terpenoids) involve acceptor substrate solubility as a special challenge for biocatalytic process design. Strategies to overcome these problems are illustrated from examples of integrated biocatalytic process development with this class of enzymes

Calculated potentials of mean force between pseudo proteins.

<p>A: three PPs with varying net-charge, constant hydrophobicity and dipole moment; B: the two PPs with the largest and smallest hydrophobicities () but identical net-charges and dipole moments; C: six PPs with varying dipole moment, identical net-charge and similar values.</p

Two PPs with different surface topologies.

<p>Left: PP10, right: PP08. Atoms are colored according to the net-charges they carry (blue negative, red positive, white neutral). The PPs are oriented so that the atom with the maximum lssc value, the center of the patch with the highest hydrophobicity, is in the center of each representation.</p

Models for protein solubilities based on molecular descriptors.

<p>Results from three different linear regression models for protein solubilities, combining the protein net-charge (q) with one of the three descriptors dipole-moment (p), normalized SAP-score (nSAP), or largest SAP value (SAPmax), and from the CCSol web-server. Included are the coefficients of the linear regression models (Eq.3), the correlations between experimental and calculated solubility (), and the P-value (probability that the observed correlation is coincidental). Data are given for two protein sets: 18 proteins from EColi-K12 (setA), and 20 mutations of RNAseSA (setB).</p