Marta Tortajada

Microbial β-glucosidases from cow rumen metagenome enhance the saccharification of lignocellulose in combination with commercial cellulase cocktail

BackgroundA complete saccharification of plant polymers is the critical step in the efficient production of bio-alcohols. Beta-glucosidases acting in the degradation of intermediate gluco-oligosaccharides produced by cellulases limit the yield of the final product.ResultsIn the present work, we have identified and then successfully cloned, expressed, purified and characterised 4 highly active beta-glucosidases from fibre-adherent microbial community from the cow rumen. The enzymes were most active at temperatures 45–55°C and pH 4.0-7.0 and exhibited high affinity and activity towards synthetic substrates such as p-nitrophenyl-beta-D-glucopyranoside (p NPbetaG) and p NP-beta-cellobiose, as well as to natural cello-oligosaccharides ranging from cellobiose to cellopentaose. The apparent capability of the most active beta-glucosidase, herein named LAB25g2, was tested for its ability to improve, at low dosage (31.25 units g-1 dry biomass, using p NPbetaG as substrate), the hydrolysis of pre-treated corn stover (dry matter content of 20%; 350 g glucan kg-1 dry biomass) in combination with a beta-glucosidase-deficient commercial Trichoderma reseei cellulase cocktail (5 units g-1 dry biomass in the basis of p NPbetaG). LAB25g2 increased the final hydrolysis yield by a factor of 20% (44.5 ± 1.7% vs. 34.5 ± 1.5% in control conditions) after 96–120 h as compared to control reactions in its absence or in the presence of other commercial beta-glucosidase preparations. The high stability (half-life higher than 5 days at 50°C and pH 5.2) and 2–38000 fold higher (as compared with reported beta-glucosidases) activity towards cello-oligosaccharides may account for its performance in supplementation assays.ConclusionsThe results suggest that beta-glucosidases from yet uncultured bacteria from animal digestomes may be of a potential interest for biotechnological processes related to the effective bio-ethanol production in combination with low dosage of commercial cellulases.

Hierarchical bimodal porous silicas and organosilicas for enzyme immobilization

This work shows the ability of a hierarchical porous silica-based network with pore systems at two different length scales for enzyme immobilization. Two different enzymes have been selected, lysozyme, a relatively small globular enzyme, and α-L-arabinofuranosidase, a large enzyme of interest in the winemaking industry. The lysozyme immobilization on several silica supports (bimodal porous silicas denoted UVM-7 materials and conventional silica xerogels) has been studied and the loading amounts can be correlated to the open nature and accessibility of the internal surface area. Bimodal UVM-7 silicas present a very quick adsorption rate and high enzyme loading. α-L-Arabinofuranosidase has been immobilized on nanoparticulated bimodal organosilicas with UVM-7 architecture. In this case we compare the results of electrostatic and covalent immobilization. The covalent immobilization allow us to shift the optimum enzymatic working conditions towards lower pH values and higher temperatures than the free enzyme, together with an increased resistance to high glucose and ethanol concentrations.

Validation of a constraint-based model of Pichia pastoris metabolism under data scarcity.

BackgroundConstraint-based models enable structured cellular representations in which intracellular kinetics are circumvented. These models, combined with experimental data, are useful analytical tools to estimate the state exhibited (the phenotype) by the cells at given pseudo-steady conditions.ResultsIn this contribution, a simplified constraint-based stoichiometric model of the metabolism of the yeast Pichia pastoris, a workhorse for heterologous protein expression, is validated against several experimental available datasets. Firstly, maximum theoretical growth yields are calculated and compared to the experimental ones. Secondly, possibility theory is applied to quantify the consistency between model and measurements. Finally, the biomass growth rate is excluded from the datasets and its prediction used to exemplify the capability of the model to calculate non-measured fluxes.ConclusionsThis contribution shows how a small-sized network can be assessed following a rational, quantitative procedure even when measurements are scarce and imprecise. This approach is particularly useful in lacking data scenarios.

Interconnected mesopores and high accessibility in UVM-7-like silicas

Nanoparticulated bimodal mesoporous silicas (NBS) have proved to constitute adequate supports in a variety of applications requiring enhanced accessibility to the active sites. Mass-transfer kinetics seems to be highly favoured in UVM-7-derived NBS materials. To understand the mass-diffusion phenomena throughout UVM-7-like supports requires well-grounded knowledge about their pore architecture. 3-D reconstructions of the UVM-7 mesostructure carried out by electron tomography reveal the existence of a true hierarchic connectivity involving both inter- and intra-nanoparticle pores. This connectivity makes self-supported nanoparticulated mesoporous bimodal carbon replicas of the supports feasible to obtaining by nanocasting. Both the temperature-induced mobility of gold nanodomains and the fast and efficient enzyme adsorption in UVM-7-like silicas are examples of non-constrained diffusion processes happening inside such an open network.

Genome sequence of the methanotrophic poly-?-hydroxybutyrate producer Methylocystis parvus OBBP

Methylocystis parvus OBBP is an obligate methylotroph considered the type species of the genus Methylocystis. Two pmoCAB particulate methane monooxygenase operons and one additional singleton pmoC paralog were identified in the sequence. No evidence of genes encoding soluble methane monooxygenase was found. Comparison of M. parvus OBBP and Methylocystis sp. strain Rockwell (ATCC 49242) suggests that both species should be taxonomically classified in different genera.

Genome sequence of the butanol hyperproducer Clostridium saccharoperbutylacetonicum N1-4

ABSTRACT Clostridium saccharoperbutylacetonicum is one of the most important acetone-butanol-ethanol (ABE)-generating industrial microorganisms and one of the few bacteria containing choline in its cell wall. Here, we report the draft genome sequence of C. saccharoperbutylacetonicum strain N1-4 (6.6 Mbp; G+C content, 29.4%) and the findings obtained from the annotation of the genome.

Validation of an FBA model for Pichia pastoris in chemostat cultures

BackgroundConstraint-based metabolic models and flux balance analysis (FBA) have been extensively used in the last years to investigate the behavior of cells and also as basis for different industrial applications. In this context, this work provides a validation of a small-sized FBA model of the yeast Pichia pastoris. Our main objective is testing how accurate is the hypothesis of maximum growth to predict the behavior of P. pastoris in a range of experimental environments.ResultsA constraint-based model of P. pastoris was previously validated using metabolic flux analysis (MFA). In this paper we have verified the model ability to predict the cells behavior in different conditions without introducing measurements, experimental parameters, or any additional constraint, just by assuming that cells will make the best use of the available resources to maximize its growth. In particular, we have tested FBA model ability to: (a) predict growth yields over single substrates (glucose, glycerol, and methanol); (b) predict growth rate, substrate uptakes, respiration rates, and by-product formation in scenarios where different substrates are available (glucose, glycerol, methanol, or mixes of methanol and glycerol); (c) predict the different behaviors of P. pastoris cultures in aerobic and hypoxic conditions for each single substrate. In every case, experimental data from literature are used as validation.ConclusionsWe conclude that our predictions based on growth maximisation are reasonably accurate, but still far from perfect. The deviations are significant in scenarios where P. pastoris grows on methanol, suggesting that the hypothesis of maximum growth could be not dominating in these situations. However, predictions are much better when glycerol or glucose are used as substrates. In these scenarios, even if our FBA model is small and imposes a strong assumption regarding how cells will regulate their metabolic fluxes, it provides reasonably good predictions in terms of growth, substrate preference, product formation, and respiration rates.

Study on the effects of several operational variables on the enzymatic batch saccharification of orange solid waste

In this work, batch enzyme-aided extraction and enzymatic saccharification of blade-milled orange waste was studied. The operation variables for this process were thoroughly analysed. It was determined that batch runs with initial pH values of 5.0 and 5.2 controlled during the first hour, 50°C and 300-500r.p.m. agitation resulted in the best yields, with a limited total and partial first-order enzyme deactivation (for cellulases and polygalacturonidase, respectively). Orange peel waste (OPW) at 6.7% w/w dry solid, 0.22 filter paper units (FPU)/g DS and proportional activities of other enzymes led to over 40g/L free monosaccharides and global yields to glucose over 80%. When using 10.1% w/w DS in these conditions, glucose yield was 63%, with total monosaccharide concentration on top of 50g/L. Similar concentrations were obtained by additional partial drying of OPW to 60% humidity at DS/L ratios near 7.5% (glucose yield >80%).

Dynamic Metabolic Flux Analysis for Online Estimation of Recombinant Protein Productivity in Pichia pastoris Cultures

Abstract One approach to model living cells is based on successively imposing the (known) constraints–such as enzyme capacities, mass balances or thermodynamic laws– that limit their behaviour. This process results in a constraint-based model that encloses all the functional states that cells might exhibit. By combining the model with experimental measurements, it is possible to determine the particular cellular state at given conditions, an exercise that is generally referred to as Metabolic Flux Analysis (MFA). In this work we use a previously validated model (Tortajada et al. , 2010) and an MFA-wise method (Llaneras et al. , 2009) for on-line monitoring of industrial cultures of the yeast Pichia pastoris. Given a set of standard measurements –substrates, gases and biomass growth–, Possibilistic dynamic MFA provides estimates for unmeasured, time-varying extracellular metabolites and intracellular fluxes, while accounting for the imprecision and uncertainty common in industrial settings. The production of the recombinant protein of interest can be estimated by means of a relationship among ATP consumption rate and specific growth rate, which is integrated into the model. To test the viability of the approach some preliminary experimental results are shown, using data from a set of batch cultivations performed in microbioreactors. The procedure is of great industrial interest because it can provide not only a way to monitor the metabolic state of P. pastoris cultures during a running process, but also a direct online estimation of the protein production rate.

Possibilistic validation of a constraint-based model under data Scirccity: application to Pichia pastoris cultures

Abstract Constraint-based modelling allows building structured models of cells without accounting for intracellular kinetics. These models can be combined with experimental data to estimate the (pseudo-steady) state or phenotype exhibited by cells at given conditions, standing out as a useful analytical tool. In this work, a simplified, constraint-based model of Pichia pastoris , a widely recognized platform for recombinant protein expression, is derived from its metabolic network. Then, the model is validated against experimental data provided by different research groups: possibility theory is used to analyse the consistency between model and measurements. Afterwards, the biomass growth rate is estimated to illustrate the ability of the model to predict non-measured fluxes. The approach followed in this contribution is particularly useful in scenarios lacking data; it makes it possible to link the extracellular behaviour of Pichia pastoris during cultivation with its internal state, being a promising tool for optimization and monitoring industrial processes.