Characterization of Ferroplasma acidiphilum growing in pure and mixed culture with Leptospirillum ferriphilum.

Biomining is defined as biotechnology for metal recovery from minerals, and is promoted by the concerted effort of a consortium of acidophile prokaryotes, comprised of members of the Bacteria and Archaea domains. Ferroplasma acidiphilum and Leptospirillum ferriphilum are the dominant species in extremely acid environments and have great use in bioleaching applications; however, the role of each species in this consortia is still a subject of research. The hypothesis of this work is that F. acidiphilum uses the organic matter secreted by L. ferriphilum for growth, maintaining low levels of organic compounds in the culture medium, preventing their toxic effects on L. ferriphilum. To test this hypothesis, a characterization of Ferroplasma acidiphilum strain BRL-115 was made with the objective of determining its optimal growth conditions. Subsequently, under the optimal conditions, L. ferriphilum and F. acidiphilum were tested growing in each other's supernatant, in order to define if there was exchange of metabolites between the species. With these results, a mixed culture in batch cyclic operation was performed to obtain main specific growth rates, which were used to evaluate a mixed metabolic model previously developed by our group. It was observed that F. acidiphilum, strain BRL-115 is a chemomixotrophic organism, and its growth is maximized with yeast extract at a concentration of 0.04% wt/vol. From the experiments of L. ferriphilum growing on F. acidiphilum supernatant and vice versa, it was observed that in both cases cell growth is favorably affected by the presence of the filtered medium of the other microorganism, proving a synergistic interaction between these species. Specific growth rates were obtained in cyclic batch operation of the mixed culture and were used as input data for a Flux Balance Analysis of the mixed metabolic model, obtaining a reasonable behavior of the metabolic fluxes and the system as a whole, therefore consolidating the model previously developed. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1390-1396, 2016.

Genome-scale reconstruction of Salinispora tropica CNB-440 metabolism to study strain-specific adaptation.

The first manually curated genome-scale metabolic model for Salinispora tropica strain CNB-440 was constructed. The reconstruction enables characterization of the metabolic capabilities for understanding and modeling the cellular physiology of this actinobacterium. The iCC908 model was based on physiological and biochemical information of primary and specialised metabolism pathways. The reconstructed stoichiometric matrix consists of 1169 biochemical conversions, 204 transport reactions and 1317 metabolites. A total of 908 structural open reading frames (ORFs) were included in the reconstructed network. The number of gene functions included in the reconstructed network corresponds to 20% of all characterized ORFs in the S. tropica genome. The genome-scale metabolic model was used to study strain-specific capabilities in defined minimal media. iCC908 was used to analyze growth capabilities in 41 different minimal growth-supporting environments. These nutrient sources were evaluated experimentally to assess the accuracy of in silico growth simulations. The model predicted no auxotrophies for essential amino acids, which was corroborated experimentally. The strain is able to use 21 different carbon sources, 8 nitrogen sources and 4 sulfur sources from the nutrient sources tested. Experimental observation suggests that the cells may be able to store sulfur. False predictions provided opportunities to gain new insights into the physiology of this species, and to gap fill the missing knowledge. The incorporation of modifications led to increased accuracy in predicting the outcome of growth/no growth experiments from 76 to 93%. iCC908 can thus be used to define the metabolic capabilities of S. tropica and guide and enhance the production of specialised metabolites.

A 50-gene signature is a novel scoring system for tumor-infiltrating immune cells with strong correlation with clinical outcome of stage I/II non-small cell lung cancer.

PURPOSE: To identify a novel system for scoring intratumoral immune response that can improve prognosis and therapy decisions in early stage non-small cell lung cancer (NSCLC). METHODS/PATIENTS: Eighty-four completely resected stage I/II NSCLC without adjuvant therapy were classified by expression profiling using whole genome microarrays. An external cohort of 162 tumors was used to validate the results. Immune cells present in tumor microenvironment were evaluated semiquantitatively by CD20, CD79, CD3, CD8, CD4 and CD57 immunostaining. Univariate and multivariate analyses of variables associated with recurrence-free survival were performed. RESULTS: Initial molecular classification identified three clusters, one with significantly better RFS. A reduced two-subgroup classification and a 50-gene predictor were built and validated in an external dataset: high and low risk of recurrence patients (HR = 3.44; p = 0.001). Analysis of the predictor´s genes showed that the vast majority were related to a B/plasma cell immune response overexpressed in the low-risk subgroup. The predictor includes genes coding for unique B lineage-specific genes, functional elements or other genes that, although non-restricted to this lineage, have strong influence on B-cell homeostasis. Immunostains confirmed increased B-cells in the low-risk subgroup. Gene signature (p < 0.0001) and CD20 (p < 0.05) were predictors for RFS, while CD79 and K-RAS mutations showed a tendency. CONCLUSIONS: Favorable prognosis in completely resected NSCLC is determined by a B-cell-mediated immune response. It can be differently scored by a 50-gene expression profile or by CD20 immunostaining. That prognosis information not reflected by traditional classifications may become a new tool for determining individualized adjuvant therapies.

Stoichiometric model and flux balance analysis for a mixed culture of Leptospirillum ferriphilum and Ferroplasma acidiphilum.

The oxidation process of sulfide minerals in natural environments is achieved by microbial communities from the Archaea and Bacteria domains. A metabolic reconstruction of two dominant species, Leptospirillum ferriphilum and Ferroplasma acidiphilum, which are always found together as a mixed culture in this natural environments, was made. The metabolic model, composed of 152 internal reactions and 29 transport reactions, describes the main interactions between these species, assuming that both use ferrous iron as energy source, and F. acidiphilum takes advantage of the organic compounds secreted by L. ferriphilum for chemomixotrophic growth. A first metabolic model for a mixed culture used in bacterial leaching is proposed in this article, which pretends to represent the characteristics of the mixed culture in a simplified manner. It was evaluated with experimental data through flux balance analysis (FBA) using as objective function the maximization of biomass. The growth yields on ferrous iron obtained for each microorganism are consistent with experimental data, and the flux distribution obtained allows understanding of the metabolic capabilities of both microorganisms growing together in a bioleaching process. The model was used to simulate the growth of F. acidiphilum on different substrates, to determine in silico which compounds maximize cell growth, and which are essential. Knockout simulations were carried out for L. ferriphilum and F. acidiphilum metabolic models, predicting key enzymes of central metabolism. The results of this analysis are consistent with experimental data from literature, showing a robust behavior of the metabolic model.

Analyzing redox balance in a synthetic yeast platform to improve utilization of brown macroalgae as feedstock.

Macroalgae have high potential to be an efficient, and sustainable feedstock for the production of biofuels and other more valuable chemicals. Attempts have been made to enable the co-fermentation of alginate and mannitol by Saccharomyces cerevisiae to unlock the full potential of this marine biomass. However, the efficient use of the sugars derived from macroalgae depends on the equilibrium of cofactors derived from the alginate and mannitol catabolic pathways. There are a number of strong metabolic limitations that have to be tackled before this bioconversion can be carried out efficiently by engineered yeast cells. An analysis of the redox balance during ethanol fermentation from alginate and mannitol by Saccharomyces cerevisiae using metabolic engineering tools was carried out. To represent the strain designed for conversion of macroalgae carbohydrates to ethanol, a context-specific model was derived from the available yeast genome-scale metabolic reconstructions. Flux balance analysis and dynamic simulations were used to determine the flux distributions. The model indicates that ethanol production is determined by the activity of 4-deoxy-l-erythro-5-hexoseulose uronate (DEHU) reductase (DehR) and its preferences for NADH or NADPH which influences strongly the flow of cellular resources. Different scenarios were explored to determine the equilibrium between NAD(H) and NADP(H) that will lead to increased ethanol yields on mannitol and DEHU under anaerobic conditions. When rates of mannitol dehydrogenase and DehRNADH tend to be close to a ratio in the range 1-1.6, high growth rates and ethanol yields were predicted. The analysis shows a number of metabolic limitations that are not easily identified through experimental procedures such as quantifying the impact of the cofactor preference by DEHU reductase in the system, the low flux into the alginate catabolic pathway, and a detailed analysis of the redox balance. These results show that production of ethanol and other chemicals can be optimized if a redox balance is achieved. A possible methodology to achieve this balance is presented. This paper shows how metabolic engineering tools are essential to comprehend and overcome this limitation.

Correlation between response to neoadjuvant chemotherapy and survival in locally advanced breast cancer patients.

BACKGROUND: Measurement of residual disease following neoadjuvant chemotherapy that accurately predicts long-term survival in locally advanced breast cancer (LABC) is an essential requirement for clinical trials development. Several methods to assess tumor response have been described. However, the agreement between methods and correlation with survival in independent cohorts has not been reported. PATIENTS AND METHODS: We report survival and tumor response according to the measurement of residual breast cancer burden (RCB), the Miller and Payne classification and the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, in 151 LABC patients. Kappa Cohen's coefficient (К) was used to test the agreement between methods. We assessed the correlation between the treatment outcome and overall survival (OS) and relapse-free survival (RFS) by calculating Harrell's C-statistic (c). RESULTS: The agreement between Miller and Payne classification and RCB classes was very high (К = 0.82). In contrast, we found a moderate-to-fair agreement between the Miller and Payne classification and RECIST criteria (К = 0.52) and RCB classes and RECIST criteria (К = 0.38). The adjusted C-statistic to predict OS for RCB index (0.77) and RCB classes (0.75) was superior to that of RECIST criteria (0.69) (P = 0.007 and P = 0.035, respectively). Also, RCB index (c = 0.71), RCB classes (c = 0.71) and Miller and Payne classification (c = 0.67) predicted better RFS than RECIST criteria (c = 0.61) (P = 0.005, P = 0.006 and P = 0.028, respectively). CONCLUSIONS: The pathological assessment of tumor response might provide stronger prognostic information in LABC patients.

Cloning, expression and decoding of the cold adaptation of a new widely represented thermolabile subtilisin-like protease.

AIMS: Cloning, expression and characterization of a new cold-adapted protease with potential biotechnological application, isolated from Antarctic bacteria. METHOD AND RESULTS: A subtilisin-like gene was isolated from several Antarctic bacterial genus using CODPEHOP-designed primers and a genome walking method. This gene encodes a precursor protein, which undergoes an autocatalytic cleavage resulting in a 34.6 kDa active cold-adapted protease with a maximum activity at 25-35°C and optimum pH of 8.0-9.0. It showed a higher catalytic efficiency at lower temperatures compared to its mesophilic counterpart. Heat-induced inactivation resulted in a very low melting point. Local packing analysis using the homology model indicated Ala284 as an important cold-adaptation determinant, which was corroborated by the site-directed mutagenesis. CONCLUSIONS: A new thermolabile subtilisin-like protease has been successfully cloned and analysed, and an important hot spot in the evolution of the cold adaptation and substrate specificity of this enzyme was identified and tested. SIGNIFICANCE AND IMPACT OF THE STUDY: This work reports a new cold-adapted protease with a vast representation amongst Antarctic genus, suggesting therefore its evolutionary success in this cold environment. Likewise, important sites for genetic potentiation have been identified, which are extrapolated to other enzymes of the same kind.

A randomized phase II trial of platinum salts in basal-like breast cancer patients in the neoadjuvant setting. Results from the GEICAM/2006-03, multicenter study.

Chemotherapy remains as the only systemic treatment option available for basal-like breast cancer (BC) patients. Preclinical models and several phase II studies suggested that platinum salts are active drugs in this BC subtype though there is no randomized study supporting this hypothesis. This study investigates if the addition of carboplatin to a combination of an alkylating agent together with anthracyclines and taxanes is able to increase the efficacy in the neoadjuvant treatment context. Patients with operable breast cancer and immunophenotypically defined basal-like disease (ER-/PR-/HER2- and cytokeratin 5/6+ or EGFR+) were recruited. Patients were randomized to receive EC (epirubicin 90 mg/m(2) plus cyclophosphamide 600 mg/m(2) for 4 cycles) followed either by D (docetaxel 100 mg/m(2) × 4 cycles; EC-D) or DCb (docetaxel 75 mg/m(2) plus carboplatin AUC 6 × 4 cycles; EC-DCb). The primary end point was pathological complete response (pCR) in the breast following the Miller and Payne criteria. Ninety-four patients were randomized (46 EC-D, 48 EC-DCb). pCR rate in the breast was seen in 16 patients (35 %) with EC-D and 14 patients (30 %) with EC-DCb (P value = 0.61). pCR in the breast and axilla was seen in 30 % of patients in both arms. The overall clinical response rate was 70 % (95 % CI 56-83) in the EC-D arm and 77 % (95 % CI 65-87) in the EC-DCb arm. Grade 3/4 toxicity was similar in both arms. The addition of carboplatin to conventional chemotherapy with EC-D in basal-like breast cancer patients did not improve the efficacy probably because they had already received an alkylating agent. These findings should be taken into consideration when developing new agents for this disease.

Chemotherapy (CT) and hormonotherapy (HT) as neoadjuvant treatment in luminal breast cancer patients: results from the GEICAM/2006-03, a multicenter, randomized, phase-II study.

BACKGROUND: Luminal breast cancer is a highly endocrine responsive disease. However, the therapeutic benefit of chemotherapy (CT) in this population is not fully characterized. This study investigates the value of CT and hormone therapy (HT) in luminal breast cancer patients in the neoadjuvant setting. PATIENTS AND METHODS: Patients with operable breast cancer and immunophenotypically defined luminal disease (ER+/PR+/HER2-/cytokeratin 8/18+) were recruited. Patients were randomized to CT (epirubicin 90 mg/m(2) plus cyclophosphamide 600 mg/m(2) 4 cycles followed by docetaxel 100 mg/m(2 )4 cycles [EC-T]) or HT (exemestane 25 mg daily 24 weeks [combined with goserelin in premenopausal patients]). The primary end point was the clinical response measured by magnetic resonance imaging. RESULTS: Ninety-five patients were randomized (47 CT, 48 HT). The clinical response rate was 66% for CT and 48% for HT (P = 0.075). We performed an unplanned analysis based on Ki67 levels (cut-off of 10%). Similar clinical response was seen between arms in patients with low Ki67 (CT: 63%, HT: 58%; P = 0.74); patients with high Ki67 had a better response with CT (67 versus 42%; P = 0.075). Grade 3/4 toxicity was more frequent with CT. CONCLUSIONS: Luminal immunophenotype is not enough to identify patients who do not benefit from neoadjuvant CT. Luminal patients with low proliferation index could potentially avoid CT.

Continuous modeling of metabolic networks with gene regulation in yeast and in vivo determination of rate parameters.

A continuous model of a metabolic network including gene regulation to simulate metabolic fluxes during batch cultivation of yeast Saccharomyces cerevisiae was developed. The metabolic network includes reactions of glycolysis, gluconeogenesis, glycerol and ethanol synthesis and consumption, the tricarboxylic acid cycle, and protein synthesis. Carbon sources considered were glucose and then ethanol synthesized during growth on glucose. The metabolic network has 39 fluxes, which represent the action of 50 enzymes and 64 genes and it is coupled with a gene regulation network which defines enzyme synthesis (activities) and incorporates regulation by glucose (enzyme induction and repression), modeled using ordinary differential equations. The model includes enzyme kinetics, equations that follow both mass-action law and transport as well as inducible, repressible, and constitutive enzymes of metabolism. The model was able to simulate a fermentation of S. cerevisiae during the exponential growth phase on glucose and the exponential growth phase on ethanol using only one set of kinetic parameters. All fluxes in the continuous model followed the behavior shown by the metabolic flux analysis (MFA) obtained from experimental results. The differences obtained between the fluxes given by the model and the fluxes determined by the MFA do not exceed 25% in 75% of the cases during exponential growth on glucose, and 20% in 90% of the cases during exponential growth on ethanol. Furthermore, the adjustment of the fermentation profiles of biomass, glucose, and ethanol were 95%, 95%, and 79%, respectively. With these results the simulation was considered successful. A comparison between the simulation of the continuous model and the experimental data of the diauxic yeast fermentation for glucose, biomass, and ethanol, shows an extremely good match using the parameters found. The small discrepancies between the fluxes obtained through MFA and those predicted by the differential equations, as well as the good match between the profiles of glucose, biomass, and ethanol, and our simulation, show that this simple model, that does not rely on complex kinetic expressions, is able to capture the global behavior of the experimental data. Also, the determination of parameters using a straightforward minimization technique using data at only two points in time was sufficient to produce a relatively accurate model. Thus, even with a small amount of experimental data (rates and not concentrations) it was possible to estimate the parameters minimizing a simple objective function. The method proposed allows the obtention of reasonable parameters and concentrations in a system with a much larger number of unknowns than equations. Hence a contribution of this study is to present a convenient way to find in vivo rate parameters to model metabolic and genetic networks under different conditions.

Genomic predictors of response to doxorubicin versus docetaxel in primary breast cancer.

UNLABELLED: Taxanes and anthracyclines improve the outcome of early breast cancer, although the benefit is limited to a small proportion of patients and are toxic. We prospectively looked for predictors of response to these drugs. EXPERIMENTAL DESIGN: Four cycles of doxorubicin (75 mg/m²) or docetaxel (100 mg/m²) were compared as presurgical chemotherapy for breast cancer. Biomarkers were determined by immunohistochemistry and fluorescent in situ hybridization using prechemotherapy core biopsies. Tumors were also classified into one of the molecular intrinsic subtypes using an immunohistochemical panel of five biomarkers and genomic profiles. Single genes and intrinsic subtypes were correlated with response to doxorubicin versus docetaxel. Among the 204 evaluable patients, significant predictors of sensitivity in multivariate analysis were low topo2a expression and ER-negative status for doxorubicin and small tumor size and ER-negative status for docetaxel. Predictors of resistance in multivariate analysis were triple-negative status (ER/PgR/HER2 negative by IHC/FISH) for doxorubicin, and high TNM stage for docetaxel. Triple-negative tumors were associated with topo2a overexpression more than the other subtypes. In 94 patients with gene expression profiles, docetaxel was superior to doxorubicin in the basal-like subtype (good pathological response rate - PCR + class I of 56 vs. 0%; P = 0.034); no significant differences were observed in the other subtypes when comparing these two drugs. Low topo2a expression and ER-negative status were predictors of response to doxorubicin, while small tumor size and ER-negative status predicted response to docetaxel. Docetaxel was superior to doxorubicin in triple-negative/basal-like tumors, while no significant differences were seen in the remaining intrinsic subtypes.

Extension of the selection of protein chromatography and the rate model to affinity chromatography.

The rational selection of optimal protein purification sequences, as well as mathematical models that simulate and allow optimization of chromatographic protein purification processes have been developed for purification procedures such as ion-exchange, hydrophobic interaction and gel filtration chromatography. This paper investigates the extension of such analysis to affinity chromatography both in the selection of chromatographic processes and in the use of the rate model for mathematical modelling and simulation. Two affinity systems were used: Blue Sepharose and Protein A. The extension of the theory developed previously for ion-exchange and HIC chromatography to affinity separations is analyzed in this paper. For the selection of operations two algorithms are used. In the first, the value of η, which corresponds to the efficiency (resolution) of the actual chromatography and, Σ, which determines the amount of a particular contaminant eliminated after each separation step, which determines the purity, have to be determined. It was found that the value of both these parameters is not generic for affinity separations but will depend on the type of affinity system used and will have to be determined on a case by case basis. With Blue Sepharose a salt gradient was used and with Protein A, a pH gradient. Parameters were determined with individual proteins and simulations of the protein mixtures were done. This approach allows investigation of chromatographic protein purification in a holistic manner that includes ion-exchange, HIC, gel filtration and affinity separations for the first time.

C4D immunostaining in surveillance endomyocardial biopsies from well-functioning heart allografts.

OBJECTIVE: The meaning of biopsy C4d detection in heart allografts without dysfunction or morphologic changes suggesting antibody-mediated rejection (AMR) is not clear. The aim of this study was to search for an association between C4d detection in allograft biopsies of well-functioning hearts without changes suggestive of AMR, and clinical outcomes. METHODS: Endomyocardial protocol biopsies from 44 heart transplant patients with well-functioning grafts and without changes suggesting AMR were performed at 1 month and 1 year after transplantation and analyze the presence of C4d deposition using immunohistochemistry. Two-year follow-up was based on clinical parameters and echocardiographic information. Heart graft function was categorized as good vs. poor. The presence of C4d, using diverse schemes to graduate the extension of the deposition, was correlated with clinical graft outcomes. RESULTS: C4d deposition was observed in the capillary walls of 33 biopsies (37.5%; n = 25 patients; 56.8%). No biopsy had diffuse (>50%) immunostaining. Six patients presented with multifocal capillary C4d immunostaining in at least 1 biopsy. Capillary positivity for C4d (if focal or multifocal) showed no statistical association with cellular rejection or graft function. Perimyocytic C4d detection was neither associated with rejection nor graft outcome. CONCLUSION: Our work failed to demonstrate an association between C4d detection in protocol biopsies of heart grafts and clinical outcomes. The clinical utility of C4d staining in solid organ transplantation may vary by organ. Our results suggest that C4d did not have clinical utility in surveillance biopsies of well-functioning heart grafts without morphological changes suggesting AMR.

Stoichiometric model and metabolic flux analysis for Leptospirillum ferrooxidans.

A metabolic model for Leptospirillum ferrooxidans was developed based on the genomic information of an analogous iron oxidizing bacteria and on the pathways of ferrous iron oxidation, nitrogen and CO(2) assimilation based on experimental evidence for L. ferrooxidans found in the literature. From this metabolic reconstruction, a stoichiometric model was built, which includes 86 reactions describing the main catabolic and anabolic aspects of its metabolism. The model obtained has 2 degrees of freedom, so two external fluxes were estimated to achieve a determined and observable system. By using the external oxygen consumption rate and the generation flux biomass as input data, a metabolic flux map with a distribution of internal fluxes was obtained. The results obtained were verified with experimental data from the literature, achieving a very good prediction of the metabolic behavior of this bacterium at steady state.

Celecoxib in a 12-year-old boy with familial adenomatous polyposis.

Familial Adenomatous Polyposis (FAP) is an autosomal dominant disorder characterized by colonic polyps in early adult life. Children with this disease are at risk for colonic cancer, so prophylactic colectomy is the standard treatment to prevent this complication. Chemoprevention experience with NSAIDs in children is exceptional. This case report describes our experience with Celecoxib, a COX-2 inhibitor, in a 12-year-old boy.

Viral vectors for the treatment of alcoholism: use of metabolic flux analysis for cell cultivation and vector production.

The HEK293 cell line has been used for the production of adenovirus vectors to be used in the potential treatment of alcoholism using a gene therapy strategy. Culture optimization and scale-up has been achieved by first adapting the cells to serum-free media and secondly by growing them in suspension. Adenovirus production after infection was increased, resulting in higher specific glucose consumption and lactate accumulation rates compared to the growth phase. We applied media design tools and Metabolic Flux Analysis (MFA) to compare the metabolic states of cells during growth and adenovirus production and to optimize culture media according to the metabolic demand of the cells in terms of glucose and glutamine concentrations. This allowed obtaining a higher maximum cell concentration and increased adenovirus production by minimizing the production of metabolites that can have an inhibitory effect on cell growth. We have proposed a stoichiometric equation for adenovirus synthesis. MFA results allowed determination of how these changes in composition affected the way cells distribute their nutrient resources during cell growth and virus production. Virus purification was successfully achieved using chromatography and Aqueous Two-Phase Systems (ATPS).

Mathematical modeling of elution curves for a protein mixture in ion exchange chromatography applied to high protein concentration.

Protein elution curves in ion exchange chromatography (IEC) were simulated with a rate model. Three pure proteins and their mixture were used (alpha-lactalbumin, BSA, and conalbumin) under different operational conditions. The anionic matrix Q-Sepharose FF was used packed in a 1 mL column. A high protein concentration (37.5 mg/mL of total protein injected into the column) was used in order to extend the utility of the model. Mass transfer parameters were calculated using empiric correlations, where the axial dispersion was negligible (Pe > 300) and the mass transfer was controlled by the intraparticle diffusion (Bi > 10). The model assumes a modulator-eluite relationship were the equilibrium constant of the Langmuir isotherm was a function of salt concentration. Adsorption kinetic parameters were estimated from experimental data. The parameters for pure proteins were determined, and elution curves for changes in flow rate, ionic strength gradient, concentration, and sample size were predicted by the model. Then the kinetic parameters of the mixture were determined under the same operational conditions and some of the parameters had to be modified to take into account effects such as protein-protein interactions, competition, and displacement. Experimental elution curves obtained for changes in operational conditions such as flow rate and ionic strength gradient were simulated by the rate model for the protein mixture with a relative error in retention time of visible peaks <5%. IEC operational conditions and the peak fraction collection can be selected using a cost function of the production process which considers yield, purity, concentration, and process time that are obtained from simulations. Operational conditions that gave the minimum cost were selected. Simulations allows to diminish experimental time and cost.

Global gene expression in recombinant and non-recombinant yeast Saccharomyces cerevisiae in three different metabolic states.

Global gene expression of two strains of Saccharomyces cerevisiae, one recombinant (P+), accumulating large amounts of an intracellular protein Superoxide Dismutase (SOD) and one non-recombinant (P-) which does not contain the recombinant plasmid, were compared in batch culture during diauxic growth when cells were growing exponentially on glucose, when they were growing exponentially on ethanol, and in the early stationary phase when glycerol was being utilized. When comparing the gene expression for P- (and P+) during growth on ethanol to that on glucose (Eth/Gluc), overexpression is related to an increase in consumption of glycerol, activation of the TCA cycle, degradation of glycogen and metabolism of ethanol. Furthermore, 97.6% of genes (80 genes) involved in the central metabolic pathway are overexpressed. This is similar to that observed by DeRisi et al. [DeRisi, J.L., Iyer, V.R. & Brown, P.O. 1997. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278:680-686.] but very different from was observed for Metabolic Flux Analysis (MFA), where the specific growth rate is lowered to ca. 40%, the fluxes in the TCA cycle are reduced to ca. 40% (to 30% in P+), glycolysis is reduced to virtually 0 and protein synthesis to ca. 50% (to 40% in P+). Clearly it is not possible to correlate in a simple or direct way, quantitative mRNA expression levels with cell function which is shown by the Metabolic Flux Analysis (MFA). When comparing the two strains in the 3 growth stages, 4 genes were found to be under or overexpressed in all cases. The products of all of these genes are expressed at the plasma membrane or cell wall of the yeast. While comparing the strains (P+/P-) when growing on glucose, ethanol and in the early stationary phase, many of the genes of the central metabolic pathways are underexpressed in P+, which is similar to the behaviour of the metabolic fluxes of both strains (MFA). Comparing the gene expression for P- (and to some extent P+) during the early stationary phase to growth on ethanol (Stat/Eth), underexpression is generalized. This shows that the switch in metabolism between ethanol and early stationary phases has an almost instantaneous effect on gene expression but a much more retarded effect on metabolic fluxes and that the "early stationary" phase represents a "late ethanol" phase from the metabolic analysis point of view since ethanol is still present and being consumed although at a much slower rate.

A stoichiometric model of Acidithiobacillus ferrooxidans ATCC 23270 for metabolic flux analysis.

A stoichiometric model of Acidithiobacillus ferrooxidans based on the sequenced genome from strain ATCC 23270 is derived and parameterized using genome/pathway databases. The model describes the main aspects of catabolism and anabolism. By the construction and utilization of the mathematical determination of the network, metabolic flux analysis is performed for such a bacterium for the first time and results are successfully verified by comparison to literature values. This first metabolic model of A. ferrooxidans is able to simulate the main aspects of metabolism and will be useful for further investigation and improvement of bioleaching procedures.

Protein purification using chromatography: selection of type, modelling and optimization of operating conditions.

To achieve a high level of purity in the purification of recombinant proteins for therapeutic or analytical application, it is necessary to use several chromatographic steps. There is a range of techniques available including anion and cation exchange, which can be carried out at different pHs, hydrophobic interaction chromatography, gel filtration and affinity chromatography. In the case of a complex mixture of partially unknown proteins or a clarified cell extract, there are many different routes one can take in order to choose the minimum and most efficient number of purification steps to achieve a desired level of purity (e.g. 98%, 99.5% or 99.9%). This review shows how an initial 'proteomic' characterization of the complex mixture of target protein and protein contaminants can be used to select the most efficient chromatographic separation steps in order to achieve a specific level of purity with a minimum number of steps. The chosen methodology was implemented in a computer- based Expert System. Two algorithms were developed, the first algorithm was used to select the most efficient purification method to separate a protein from its contaminants based on the physicochemical properties of the protein product and the protein contaminants and the second algorithm was used to predict the number and concentration of contaminants after each separation as well as protein product purity. The application of the Expert System approach was experimentally tested and validated with a mixture of four proteins and the experimental validation was also carried out with a supernatant of Bacillus subtilis producing a recombinant beta-1,3-glucanase. Once the type of chromatography is chosen, optimization of the operating conditions is essential. Chromatographic elution curves for a three-protein mixture (alpha-lactoalbumin, ovalbumin and beta-lactoglobulin), carried out under different flow rates and ionic strength conditions, were simulated using two different mathematical models. These models were the Plate Model and the more fundamentally based Rate Model. Simulated elution curves were compared with experimental data not used for parameter identification. Deviation between experimental data and the simulated curves using the Plate Model was less than 0.0189 (absorbance units); a slightly higher deviation [0.0252 (absorbance units)] was obtained when the Rate Model was used. In order to optimize operating conditions, a cost function was built that included the effect of the different production stages, namely fermentation, purification and concentration. This cost function was also successfully used for the determination of the fraction of product to be collected (peak cutting) in chromatography. It can be used for protein products with different characteristics and qualities, such as purity and yield, by choosing the appropriate parameters.