Optimization and cost estimation of novel wheat biorefining for continuous production of fermentation feedstock

A wheat-based continuous process for the production of a nutrient-complete feedstock for bioethanol production by yeast fermentation has been cost-optimized. This process could substitute for the current wheat dry milling process employed in industry for bioethanol production. Each major wheat component (bran, gluten, starch) is extracted and processed for different end-uses. The separate stages, liquefaction and saccharification, used currently in industry for starch hydrolysis have been integrated into a simplified continuous process by exploiting the complex enzymatic consortium produced by on-site fungal bioconversions. A process producing 120 m3 h-1 nutrient-complete feedstock for bioethanol production containing 250 g L-1 glucose and 0.85 g L-1 free amino nitrogen would result in a production cost of $0.126/kg glucose.     

A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait

A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some “baseline” family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a set of combinations of parameters of a given prior distribution, the effects of the prior dissipated when the number of replicate samples per genotype was increased. Thus, the Dirichlet process model seems to be useful for gauging the number of QTLs affecting the trait: if the number of clusters inferred is small, probably just a few QTLs code for the trait. If the number of clusters inferred is large, this may imply that standard parametric models based on the baseline distribution may suffice. However, priors may be influential, especially if sample size is not large and if only a few genotypic configurations have replicate phenotypes in the sample.     

Process simulation for recombinant protein production: cost estimation and sensitivity analysis for heparinase I expressed in Escherichia coli

Heparinase I from flavobacterium heparinum has several potential clinical applications; the resulting high demands on protein purity and quantity can be met by recombinant expression in Escherichia coli. Based on laboratory scale experiments with insoluble heparinase I expression followed by renaturation, a process for production of 3 kg/year of heparinase I was designed. We present a comparative analysis of the production costs of soluble and insoluble heparinase I expression, as well as a generalized approach to sensitivity analysis, based on perturbation around a base case design scenario. This may assist focusing further development on process steps for which improvements both are feasible and result in significant cost saving. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 53: 575-582, 1997.     

A compartmentalised model for the estimation of the cost of coccidiosis to the world's chicken production industry

A compartmentalised model is presented for the estimation of the monetary losses suffered by the world's poultry industry resulting from coccidiosis of chickens and costs of its control. The model is designed so that the major elements of loss may be separately quantified for any chicken-producing entity, e.g., a farm, a poultry company, a country, etc. Examples are presented and the sources, reliability and geographical relevance of the data used for each parameter are provided. Loss elements for specific geographical areas should be recalculated at appropriate intervals to take into account local and international fluctuations in costs of chicks feed, labour, financial inflation and world currency exchange rates. Equations are given for relationships among numbers of chickens, liveweights, weights of carcasses, feed consumptions, feed conversion ratio (FCR), prices of feeds, prices of anticoccidial therapeutic and prophylactic drugs, values of chickens, chicken rearing costs; and effects of coccidiosis on mortality, weight gain and FCR. Using these equations, it is theoretically possible for an international team of representatives, each using reliable local data, to calculate simultaneously each relevant loss element for their respective countries. Addition of these elements could give, for the first time, an accurate global estimate of the losses due to chicken coccidiosis. The total cost of coccidiosis in chickens in the United Kingdom in 1995 is estimated to have been at least GB pound silver 38 588 795, of which 98.1% involved broilers (80.6% due to effects on mortality, weight gain and feed conversion, and 17.5% due to the cost of chemoprophylaxis and therapy). The costs of poor performance due to coccidiosis and its chemical control totalled 4.54% of the gross revenue from UK sales of live broilers. This model includes a new method for comparing the profitabilities of different treatments in commercial trials. providing actual costs rather than the arbitrary numerical scores of other methods. Although originally designed for the study of coccidiosis, the model is equally applicable to any disease. It should be of value to agricultural economists, the animal feed and poultry industries, animal health companies, and to research scientists (particularly for preparing grant applications).     

Species selection in a reactor-settler system

The competition between flocculating and nonflocculating microorganisms was investigated in a continuous reactor-settler system (e.g. activated sludge). Co existence states were found to be possible, over a certain domain of operating conditions, even with simple monotonic kinetics and simple competition. Multiple solutions exist when coexistence states are unstable. Coexistence solutions are stable when the flocculating bacteria grow faster at feed conditions as in the activated sludge problem. The analysis applies to one or several mixed or plug flow reactors. Other effects, such as enrichment of the recycle stream by the flocculating microorganism or substrate adsorption and storage, may change the structure of solution.     

A mannose selection system for production of fertile transgenic maize plants from protoplasts

 Maize (Zea mays L.) callus cultures cannot use mannose as a sole carbohydrate source, but can utilize fructose for that purpose. Phosphomannose isomerase (PMI) can convert mannose to fructose. Transgenic maize plants were obtained by selecting polyethylene glycol (PEG)-mediated transformed protoplasts on mannose (20 g/l) containing medium. Transgenic calluses and plants carrying the PMI structural gene, manA, were able to convert mannose to fructose. The PEG-mediated protoplast transformation frequency was 0.06%. Stable transformation was confirmed by PCR, PMI activity, germination tests, and by histochemical staining with 5-bromo-4-chloro-3-indolyl-β-D-glucuronide (X-Gluc). Stable integration of the transgenes into the maize genome was demonstrated in T₁ and T₂ plants. Results indicate that the mannose selection system can be used for maize PEG-mediated protoplast transformation. Received: 12 July 1999 / Revision received: 11 October 1999 / Accepted: 11 October 1999     

Performance-based selection of likelihood models for phylogeny estimation

Phylogenetic estimation has largely come to rely on explicitly model-based methods. This approach requires that a model be chosen and that that choice be justified. To date, justification has largely been accomplished through use of likelihood-ratio tests (LRTs) to assess the relative fit of a nested series of reversible models. While this approach certainly represents an important advance over arbitrary model selection, the best fit of a series of models may not always provide the most reliable phylogenetic estimates for finite real data sets, where all available models are surely incorrect. Here, we develop a novel approach to model selection, which is based on the Bayesian information criterion, but incorporates relative branch-length error as a performance measure in a decision theory (DT) framework. This DT method includes a penalty for overfitting, is applicable prior to running extensive analyses, and simultaneously compares all models being considered and thus does not rely on a series of pairwise comparisons of models to traverse model space. We evaluate this method by examining four real data sets and by using those data sets to define simulation conditions. In the real data sets, the DT method selects the same or simpler models than conventional LRTs. In order to lend generality to the simulations, codon-based models (with parameters estimated from the real data sets) were used to generate simulated data sets, which are therefore more complex than any of the models we evaluate. On average, the DT method selects models that are simpler than those chosen by conventional LRTs. Nevertheless, these simpler models provide estimates of branch lengths that are more accurate both in terms of relative error and absolute error than those derived using the more complex (yet still wrong) models chosen by conventional LRTs. This method is available in a program called DT-ModSel.     

Yeast selection for fuel ethanol production in Brazil

Brazil is one of the largest ethanol biofuel producers and exporters in the world and its production has increased steadily during the last three decades. The increasing efficiency of Brazilian ethanol plants has been evident due to the many technological contributions. As far as yeast is concerned, few publications are available regarding the industrial fermentation processes in Brazil. The present paper reports on a yeast selection program performed during the last 12 years aimed at selecting Saccharomyces cerevisiae strains suitable for fermentation of sugar cane substrates (cane juice and molasses) with cell recycle, as it is conducted in Brazilian bioethanol plants. As a result, some evidence is presented showing the positive impact of selected yeast strains in increasing ethanol yield and reducing production costs, due to their higher fermentation performance (high ethanol yield, reduced glycerol and foam formation, maintenance of high viability during recycling and very high implantation capability into industrial fermenters). Results also suggest that the great yeast biodiversity found in distillery environments could be an important source of strains. This is because during yeast cell recycling, selective pressure (an adaptive evolution) is imposed on cells, leading to strains with higher tolerance to the stressful conditions of the industrial fermentation.     

Variable selection and parameter estimation of viral amplification in vero cell cultures dedicated to the production of a dengue vaccine

In this study, a dynamic model of a Vero cell culture-based dengue vaccine production process is developed. The approach consists in describing the process dynamics as functions of the whole living (uninfected and infected) biomass whereas previous works are based on population balance approaches. Based on the assumption that infected biomass evolves faster than other variable, the model can be simplified using a slow-fast approximation. The structural identifiability of the model is analysed using differential algebra as implemented in the software DAISY. The model parameters are inferred from experimental datasets collected from an actual vaccine production process and the model predictive capability is confirmed both in direct and cross-validation. The model prediction shows the impact of the metabolism on virus yield and confirms observations reported in previous studies. Multi-modality and sensitivity analysis complement the parameter estimation, and allow to obtain confidence intervals on both parameters and state estimates. Finally, the model is used to compute the maximum infectious virus yield that can be obtained for different combinations of multiplicity of infection (MOI) and time of infection (TOI). © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2687, 2019     

Bias in error estimation when using cross-validation for model selection

Background  

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data.     

AGMIAL: implementing an annotation strategy for prokaryote genomes as a distributed system

We have implemented a genome annotation system for prokaryotes called AGMIAL. Our approach embodies a number of key principles. First, expert manual annotators are seen as a critical component of the overall system; user interfaces were cyclically refined to satisfy their needs. Second, the overall process should be orchestrated in terms of a global annotation strategy; this facilitates coordination between a team of annotators and automatic data analysis. Third, the annotation strategy should allow progressive and incremental annotation from a time when only a few draft contigs are available, to when a final finished assembly is produced. The overall architecture employed is modular and extensible, being based on the W3 standard Web services framework. Specialized modules interact with two independent core modules that are used to annotate, respectively, genomic and protein sequences. AGMIAL is currently being used by several INRA laboratories to analyze genomes of bacteria relevant to the food-processing industry, and is distributed under an open source license.     

Sexual selection reveals a cost of pathogen resistance undetected in life-history assays

Mechanisms of resistance to pathogens and parasites are thought to be costly and thus to lead to evolutionary trade-offs between resistance and life-history traits expressed in the absence of the infective agents. On the other hand, sexually selected traits are often proposed to indicate “good genes” for resistance, which implies a positive genetic correlation between resistance and success in sexual selection. Here I show that experimental evolution of improved resistance to the intestinal pathogen Pseudomonas entomophila in Drosophila melanogaster was associated with a reduction in male sexual success. Males from four resistant populations achieved lower paternity than males from four susceptible control populations in competition with males from a competitor strain, indicating an evolutionary cost of resistance in terms of mating success and/or sperm competition. In contrast, no costs were found in larval viability, larval competitive ability and population productivity assayed under nutritional limitation; together with earlier studies this suggests that the costs of P. entomophila resistance for nonsexual fitness components are negligible. Thus, rather than indicating heritable pathogen resistance, sexually selected traits expressed in the absence of pathogens may be sensitive to costs of resistance, even if no such costs are detected in other fitness traits.     

Frequency-dependent selection in a wild plant-pathogen system

This study investigated the occurrence of the rust fungus Puccinia chondrillina in clonal populations of its host plant, Chondrilla juncea. In 16 populations spread across eastern Turkey, 48 different multilocus isozyme phenotypes were identified in the host. Of these clones, 88% were restricted to single localities, while the remaining 12% were found in 2–11 populations. For 13 of the 16 plant populations the commonest host clone was always infected. Indeed, at ten sites this clone was the only one found to carry disease. In the remaining three populations the rusted plants were all of the second commonest isozyme type. The possibility of such a tight association of rust incidence with host clone frequency simultaneously across a wide geographic area is very low (P0.023), supporting the contention that the pathogen P. chondrillina may be imposing negative frequency-dependent selection on these C. juncea populations.     

Growing duckweed in swine wastewater for nutrient recovery and biomass production

Spirodela oligorrhiza, a promising duckweed identified in previous studies, was examined under different cropping conditions for nutrient recovery from swine wastewater and biomass production. To prevent algae bloom during the start-up of a duckweed system, inoculating 60% of the water surface with duckweed fronds was required. In the growing season, the duckweed system was capable of removing 83.7% and 89.4% of total nitrogen (TN) and total phosphorus (TP) respectively from 6% swine lagoon water in eight weeks at a harvest frequency of twice a week. The total biomass harvested was 5.30 times that of the starting amount. In winter, nutrients could still be substantially removed in spite of the limited duckweed growth, which was probably attributed to the improved protein accumulation of duckweed plants and the nutrient uptake by the attached biofilm (algae and bacteria) on duckweed and walls of the system.