Screening of lipases for regioselective hydrolysis of peracetylated β-monosaccharides

The monodeacetylation of peracetylated-β-d-galactose (1) and peracetylated N-acetyl-β-d-glucosamine (2) by different lipases is here described. Lipases from different sources in an immobilized form were evaluated to find those that offer the higher activity and regioselectivity in the reactions. In the hydrolysis of 1, the lipase from Aspergillus niger was the most active one, although it hydrolyzed the anomeric position. Using the lipase from Candida rugosa, 30% yield of the corresponding 6-OH isomer was achieved. On the other hand, in the hydrolysis of 2, the lipase from A. niger was the most active and regioselective catalyst, producing more than 75% of the 6-OH derivative product.     

Are niche‐based species distribution models transferable in space?

Aim To assess the geographical transferability of niche‐based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice‐versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3–0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter‐specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land‐use history, or to species‐specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche‐based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche‐based models for assessing the fate of species in future environments.     

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown.     

Purification, immobilization and stabilization of a highly enantioselective alcohol dehydrogenase from Thermus thermophilus HB27 cloned in E. coli

This paper shows the purification and immobilization of a very interesting thermophilic alcohol dehydrogenase from Thermus thermophilus HB27 cloned in Escherichia coli. The purification was based on a first thermal treatment of the crude extract, that leaves the target enzyme in the supernatant, followed by the adsorption of most contaminant proteins in a IMAC column (the target protein did not adsorb on these columns due to the poorness of His residues). Final purification factor was around a 9-fold factor (no other protein bands were detected in SDS-PAGE gels) with an overall yield around 80%. Covalent immobilization of the enzyme on very different supports only permitted to improve the enzyme stability by a 5–10-fold factor, very similarly to the results obtained by the adsorption of the enzyme on polyethyleneimine coated supports. This enzyme adsorbed by ionic exchange maintained the activity unaltered during immobilization which was a very rapid process, and was more stable than the covalent preparations in the presence of organic solvents, and the enzyme was quite strongly adsorbed on the support. Therefore, it was proposed as a good option to prepare industrial biocatalysts of the enzyme. This preparation was utilized in the asymmetric reduction of acetophenone to produce (S)-(−)-1-phenylethanol, with an enantiomeric excess of more than 99%.     

MigClim: Predicting plant distribution and dispersal in a changing climate

Aim Many studies have forecasted the possible impact of climate change on plant distributions using models based on ecological niche theory, but most of them have ignored dispersal‐limitations, assuming dispersal to be either unlimited or null. Depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under‐ or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of ‘potentially suitable’ and ‘potentially colonizable’ habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed Mig Clim, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. Mig Clim implements various parameters, such as dispersal distance, increase in reproductive potential over time, landscape fragmentation or long‐distance dispersal. Location Western Swiss Alps. Methods Using our Mig Clim model, several simulations were run for two virtual species by varying dispersal distance and other parameters. Each simulation covered the 100‐year period 2001–2100 and three different IPCC‐based temperature warming scenarios were considered. Results of dispersal‐limited projections were compared with unlimited and no‐dispersal projections. Results Our simulations indicate that: (1) using realistic parameter values, the future potential distributions generated using Mig Clim can differ significantly (up to more than 95% difference in colonized surface) from those that ignore dispersal; (2) this divergence increases under more extreme climate warming scenarios and over longer time periods; and (3) the uncertainty associated with the warming scenario can be as large as the one related to dispersal parameters. Main conclusions Accounting for dispersal, even roughly, can importantly reduce uncertainty in projections of species distribution under climate change scenarios.     

Reproducibility of species lists,visual cover estimates and frequency methods for recording high‐mountain vegetation

Question: When multiple observers record the same spatial units of alpine vegetation, how much variation is there in the records and what are the consequences of this variation for monitoring schemes to detect changes? Location: One test summit in Switzerland (Alps) and one test summit in Scotland (Cairngorm Mountains). Method: Eight observers used the GLORIA protocols for species composition and visual cover estimates in percentages on large summit sections (>100 m²) and species composition and frequency in nested quadrats (1 m²). Results: The multiple records from the same spatial unit for species composition and species cover showed considerable variation in the two countries. Estimates of pseudo‐turnover of composition and coefficients of variation of cover estimates for vascular plant species in 1 m × 1‐m quadrats showed less variation than in previously published reports, whereas our results in larger sections were broadly in line with previous reports. In Scotland, estimates for bryophytes and lichens were more variable than for vascular plants. Conclusions: Statistical power calculations indicated that unless large numbers of plots were used, changes in cover or frequency were only likely to be detected for abundant species (exceeding 10% cover) or if relative changes were large (50% or more). Lower variation could be reached with the point method and with larger numbers of small plots. However, as summits often strongly differ from each other, supplementary summits cannot be considered as a way of increasing statistical power without introducing a supplementary component of variance into the analysis and hence into the power calculations.     

Chemical modification of protein surfaces to improve their reversible enzyme immobilization on ionic exchangers

The enzyme penicillin G acylase (PGA) is not adsorbed at pH 7 on DEAE- or PEI-coated supports, neither is it adsorbed on carboxymethyl (CM)- or dextran sulfate (DS)-coated supports. The surface of the enzyme was chemically modified under controlled conditions: chemical amination of the protein surface of carboxylic groups (using soluble carbodiimide and ethylendiamine) and chemical succinylation (using succinic anhydride) of amino groups. The full chemical modification produced some negative effects on enzyme stability and activity, although partial modification (mainly succinylation) presented negligible effects on both enzyme features. The chemical amination of the protein surface permitted the immobilization of the enzyme on CM- and DS-coated support, while the chemical succinylation permitted the enzyme immobilization on DEAE- and PEI-coated supports. Immobilization was very strong on these supports, mainly in the polymeric ones, and dependent on the degree of modification, although the enzymes still can be desorbed after inactivation by incubation under drastic conditions. Moreover, the immobilization on ionic polymeric beds allowed a significant increase in enzyme stability against the inactivation and inhibitory effects of organic solvents, very likely by the promotion of a certain partition of the organic solvent out of the enzyme environment. These results suggest that the enrichment of the surface of proteins with ionic groups may be a good strategy to take advantage of the immobilization of industrial enzymes via ionic exchange on ionic polymeric beds.     

Use of physicochemical tools to determine the choice of optimal enzyme: stabilization of D-amino acid oxidase

An evaluation of the stability of several forms (including soluble and two immobilized preparations) of d-amino acid oxidases from Trigonopsis variabilis (TvDAAO) and Rhodotorula gracilis (RgDAAO) is presented here. Initially, both soluble enzymes become inactivated via subunit dissociation, and the most thermostable enzyme seemed to be TvDAAO, which was 3-4 times more stable than RgDAAO at a protein concentration of 30 microg/mL. Immobilization on poorly activated supports was unable to stabilize the enzyme, while highly activated supports improved the enzyme stability. Better results were obtained when using highly activated glyoxyl agarose supports than when glutaraldehyde was used. Thus, multisubunit immobilization on highly activated glyoxyl agarose dramatically improved the stability of RgDAAO (by ca. 15,000-fold) while only marginally improving the stability of TvDAAO (by 15-20-fold), at a protein concentration of 6.7 microg/mL. Therefore, the optimal immobilized RgDAAO was much more stable than the optimal immobilized TvDAAO at this enzyme concentration. The lower stabilization effect on TvDAAO was associated with the inactivation of this enzyme by FAD dissociation that was not prevented by immobilization. Finally, nonstabilized RgDAAO was marginally more stable in the presence of H(2)O(2) than TvDAAO, but after stabilization by multisubunit immobilization, its stability became 10 times higher than that of TvDAAO. Therefore, the most stable DAAO preparation and the optimal choice for an industrial application seems to be RgDAAO immobilized on glyoxyl agarose.     

One-step purification,covalent immobilization,and additional stabilization of a thermophilic poly-His-tagged beta-galactosidase from Thermus sp. strain T2 by using novel heterofunctional chelate-epoxy Sepabeads

Using the poly-His-tagged-beta-galactosidase from Thermus sp. strain T2 overexpressed in Escherichia coli (MC1116) as a model enzyme, we have developed a strategy to purify and immobilize proteins in a single step, combining the excellent properties of epoxy groups for enzyme immobilization with the good performance of immobilized metal-chelate affinity chromatography for protein purification. The aforementioned enzyme could not be immobilized onto standard epoxy supports with good yields, and after purification and storage, it exhibited a strong trend to yield very large aggregates as shown by ultracentrifugation experiments. That preparation could not be immobilized in any support, very likely because the pores of the solid became clogged by the large aggregates. These novel epoxy-metal chelate heterofunctional supports contain a low concentration of Co(2+) chelated in IDA groups and a high density of epoxy groups. This enabled the selective adsorption of poly-His-tagged enzymes, and as this adsorption step is necessary for the covalent immobilization procedure, the selective covalent immobilization of the target enzyme could take place. This strategy allowed similar maximum loadings of the target enzyme using either pure or crude preparations of the enzyme. The enzyme derivative presented a very high activity at 70 degrees C (over 1000 IU in the hydrolysis of lactose) and very high stability and stabilization when compared to its soluble counterpart (activity remained unaltered after several days of incubation at 50 degrees C). In fact, this preparation was much more stable than when the same enzyme was immobilized onto standard epoxy Sepabeads.     

Enzymatic synthesis of amoxicillin: avoiding limitations of the mechanistic approach for reaction kinetics

A recurrent doubt that occurs to the enzyme‐kinetics modeler is, When should I stop adding parameters to my mechanistic model in order to fit a non‐conventional behavior? This problem becomes more and more involving when the complexity of the reaction network increases. This work intends to show how the use of artificial neural networks may circumvent the need of including an overwhelming number of parameters in the rate equations obtained through the classical, mechanistic approach. We focus on the synthesis of amoxicillin by the reaction of p‐OH‐phenylglycine methyl ester and 6‐aminopenicillanic acid, catalyzed by penicillin G acylase immobilized on glyoxyl‐agarose, at 25°C and pH 6.5. The reaction was carried on a batch reactor. Three kinetic models of this system were compared: a mechanistic, a semi‐empiric, and a hybrid–neural network (NN). A semi‐empiric, simplified model with a reasonable number of parameters was initially built‐up. It was able to portray many typical process conditions. However, it either underestimated or overestimated the rate of synthesis of amoxicillin when substrates' concentrations were low. A more complex, full‐scale mechanistic model that could span all operational conditions was intractable for all practical purposes. Finally, a hybrid model, that coupled artificial neural networks (NN) to mass‐balance equations was established, that succeeded in representing all situations of interest. Particularly, the NN could predict with accuracy reaction rates for conditions where the semi‐empiric model failed, namely, at low substrate concentrations, a situation that would occur, for instance, at the end of a fed‐batch industrial process. © 2002 Wiley Periodicals, Inc. Biotechnol Bioeng 80: 622–631, 2002.