The production of hybrid Ty:IFN virus-like particles in yeast.

The yeast retrotransposon Ty encodes proteins that assemble into virus-like particles (Ty-VLPs) which can be readily purified. We have recently shown that expression of the pl protein encoded by the TYA gene of Ty is sufficient for particle formation. In this paper we show that when a heterologous coding sequence, human interferon-alpha 2 (IFN), is fused in frame to the TYA gene, the resulting p1-IFN fusion protein is still assembled into VLPs. These Ty:IFN-VLPs can be easily purified to near homogeneity and furthermore, they induce an antibody response to interferon when they are injected into rabbits. Therefore, these data show that hybrid Ty-VLPs can be used as a convenient system for the efficient purification of fusion proteins in yeast.     

Hybrid process models for process optimisation,monitoring and control

Hybrid models aim to describe different components of a process in different ways. This makes sense when the corresponding knowledge to be represented is different as well. In this way, the most efficient representations can be chosen and, thus, the model performance can be increased significantly. From the various possible variants of hybrid model, three are selected which were applied for important biotechnical processes, two of them from existing production processes. The examples show that hybrid models are powerful tools for process optimisation, monitoring and control.     

The release of virus-like particles from recombinant Saccharomyces cerevisiae: effect of freezing and thawing on homogenization and bead milling

Recombinant cells of Saccharomyces cerevisiae, expressing virus-like particles (Ty-VLPs), can be readily disrupted in a high pressure homogenizer and show identical disruption kinetics to the untransformed host strain. When the cells are freeze/thawed before disruption, they become about four times more resistant to homogenization. This effect increases with the number of freeze/thaw cycles, but is independent of the time the cells remain frozen. The freeze/thaw effect is observed with cells harvested during both the logarithmic and stationary phase of growth, and occurs with the untransformed host strain as well as the transformed one. Freeze/thawed cells are twice as resistant to disruption in the bead mill as fresh cells. (c) 1994 John Wiley & Sons, Inc.     

Ty virus-like particles, DNA vaccines and Modified Vaccinia Virus Ankara; comparisons and combinations

Three types of vaccine, all expressing the same antigen from Plasmodium berghei, or a CD8+ T cell epitope from that antigen, were compared for their ability to induce CD8+ T cell responses in mice. Higher levels of lysis and numbers of IFN-gamma secreting T cells were primed with Ty virus-like particles and Modified Vaccinia Virus Ankara (MVA) than with DNA vaccines, but none of the vaccines were able to protect immunised mice from infectious challenge even after repeated doses. However, when the immune response was primed with one type of vaccine (Ty-VLPs or DNA) and boosted with another (MVA) complete protection against infection was achieved. Protection correlated with very high levels of IFN-gamma secreting T cells and lysis. This method of vaccination uses delivery systems and routes that can be used in humans and could provide a generally applicable regime for the induction of high levels of CD8+ T cells.     

Improving the integrated hybrid LCA in the upstream scope 3 emissions inventory analysis

Purpose

The protocols of carbon footprints generally define three scopes for different greenhouse gas (GHG) emissions levels. The most important carbon footprint emissions source comes from upstream indirect emissions of scope 3 for products that do not consume energy during their use phase. Upstream scope 3 GHG inventory can usually be analyzed through input–output or hybrid LCA analysis. The economic input–output life cycle analysis (EIO-LCA) and the hybrid LCA model have been widely used for this purpose. However, a cutoff error exists in the hybrid model, and the lack of a truncation criterion between process and IO inventory may lead to a high level of uncertainty in the hybrid model. This study attempts to improve the problem of cutoff uncertainty in hybrid LCA and proposes a method to minimize the cutoff uncertainty.

Methods

The way to improve the cutoff uncertainty could follow two steps. First, through the IO inventory analysis of EIO-LCA, we can define the emissions by various tiers of product components. The IO inventory indicator can provide a definitive criterion for the process inventory of the hybrid model. Second, we connect the process- and IO-LCI according to the IO inventory result. The advantage of the process inventory is that it provides detailed manufacturing information on the target while the IO encompasses a complete system boundary. For improvements, the process inventory can catch the most important process of the GHG emissions, and the IO inventory could compensate for the remainder of the incomplete system inventory.

Results and discussion

In this case study, the printed circuit board production process is used to evaluate the efficiency of the improved method. The threshold M was set to 70 in this case study, and the IO inventory provides the remaining 30 %. For the integrated hybrid model, the tier 3 process inventory takes only 64 % while the incorporation of the proposed method can include 92 % of the total emissions, which shows the cutoff uncertainty can be reduced through the improvement.

Conclusions

This study provides a clear guideline for process and IO cutoff criteria, which can help the truncation uncertainty. When higher precision is required, process LCI will need to play an important role, and thus, a higher M value should be set. In this situation, the emissions from IO-LCI would be smaller than the emissions from the process LCI. The appropriate solution would attain a comfortable balance between data accuracy and time and labor consumption.     

Interspecific hybridization in natural populations ofCyrtandra (Gesneriaceae) on the Hawaiian Islands: Evidence from RAPD markers

Interspecific hybridization among Hawaiian species ofCyrtandra (Gesneriaceae) was investigated using randomly amplified polymorphic DNA (RAPD) markers. Thirty-three different primers were used to investigate interspecific hybridization for 17 different putative hybrids based on morphological intermediacy and sympatry with putative parental species. RAPD data provided evidence for the hybrid origin of all putative hybrid taxa examined in this analysis. However, the patterns in the hybrid taxa were not found to be completely additive of the patterns found in the parental species. Markers missing in the hybrid taxa can be attributed to polymorphism in the populations of the parental species and the dominant nature of inheritance for RAPD markers. Unique markers found within hybrid taxa require further explanation but do not necessarily indicate that the taxa are not of hybrid origin. The implications suggest that these interspecific hybridization events had, and continue to have, an effect on the adaptive radiation and conservation biology ofCyrtandra.     

Rapid recovery of photosynthetic cell suspension cultures following heterotrophic bleaching

Summary Seven suspension-cultured lines of five different species (Amaranthus powellii Datura innoxia, Glycine max, Gossypium hirsutum, andNicotiana tabacum × Nicotiana glutinosa fusion hybrid), which had been grown under photomixotrophic conditions, were placed under heterotrophic conditions (darkness and media with 3% sucrose or starch) where the chlorophyll levels declined to near zero. After three transfers over a 70-d period, the cells were placed back into photomixotrophic or photoautotrophic conditions where regreening occurred rapidly and continued growth was observed. This rapid adaptation to photosynthetic conditions contrasts with the original initiation process for these cultures, which required many months and an apparent selection since many of the original cells died. Thus, these seven photosynthetic cell suspension cultures appear to be different from the original cultures due possible to genetic or adaptive changes.     

A hybrid mechanistic-empirical model for in silico mammalian cell bioprocess simulation

In cell culture processes cell growth and metabolism drive changes in the chemical environment of the culture. These environmental changes elicit reactor control actions, cell growth response, and are sensed by cell signaling pathways that influence metabolism. The interplay of these forces shapes the culture dynamics through different stages of cell cultivation and the outcome greatly affects process productivity, product quality, and robustness. Developing a systems model that describes the interactions of those major players in the cell culture system can lead to better process understanding and enhance process robustness. Here we report the construction of a hybrid mechanistic-empirical bioprocess model which integrates a mechanistic metabolic model with subcomponent models for cell growth, signaling regulation, and the bioreactor environment for in silico exploration of process scenarios. Model parameters were optimized by fitting to a dataset of cell culture manufacturing process which exhibits variability in metabolism and productivity. The model fitting process was broken into multiple steps to mitigate the substantial numerical challenges related to the first-principles model components. The optimized model captured the dynamics of metabolism and the variability of the process runs with different kinetic profiles and productivity. The variability of the process was attributed in part to the metabolic state of cell inoculum. The model was then used to identify potential mitigation strategies to reduce process variability by altering the initial process conditions as well as to explore the effect of changing CO₂ removal capacity in different bioreactor scales on process performance. By incorporating a mechanistic model of cell metabolism and appropriately fitting it to a large dataset, the hybrid model can describe the different metabolic phases in culture and the variability in manufacturing runs. This approach of employing a hybrid model has the potential to greatly facilitate process development and reactor scaling.     

Hybrid Framework for Managing Uncertainty in Life Cycle Inventories

Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input–output (I‐O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom‐up process model can be estimated via a top‐down approach such as the economic I‐O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long‐term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method.     

Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses.     

Agrobacterium tumefaciens-mediated transformation and regeneration of herbicide resistant onion (Allium cepa) plants

Transgenic onion plants (Allium cepa) tolerant to herbicides containing active ingredients glyphosate and phosphinothricin were recovered from immature embryos of open pollinated and hybrid parent onion lines at a maximum transformation frequency of 0.9%. Transformants of different onion cultivars, grown on different selective agents and confirmed by Southern analysis, thrived with no apparent ill effects when sprayed with the respective herbicides at double the recommended field dosage for weed eradication. This study demonstrates that the transformation process described previously can be used with different selective agents and is cultivar independent.     

P-M system of hybrid dysgenesis inDrosophila melanogaster: thermic modifications of the cytotype can be detected for several generations

Summary In the P-M system of hybrid dysgenesis inDrosophila melanogaster, the cytotype corresponds to an extrachromosomal state which controls the mobility of the P transposable elements. Previous experiments have shown that thermic treatments during development and ageing may dramatically influence the cytotype transformation process in certain types of hybrid females. We show here that these temperature-induced modifications can be detected in subsequent generations. The consequences for the cytotypic characterisation of strains are discussed.     

Association of protein amount polymorphism (PAP) among maize lines with performances of their hybrids

Summary It has been suggested that molecular foundations of phenotypic diversity reside in the variability of genome expression. This variability can be appraised through the polymorphism of individual protein amounts (PAP: protein amount polymorphism). Eight maize inbred lines and ten of their single-cross hybrids were analyzed by two-dimensional polyacrylamide gel electrophoresis in order to examine the potential of PAP for predicting hybrid vigor. The 28 possible pairs of lines were characterized for: (i) the number, H of expected heterozygous structural loci in their hybrid, in the sample of loci revealed by 2D-PAGE; (ii) four distance indices based on PAP; (iii) the hybrid values for five agromorphological characters measured in four different year/locations. For the subset of ten hybrids analyzed by 2D-PAGE, the number of cases of nonadditive inheritance (NA) was also counted. Whereas H appeared to be related neither to the PAP indices, nor to NA, nor to hybrid performances, PAP indices were correlated to NA, and both were positively associated to hybrid performances. The possibility that PAP is responsible for quantitative trait variation is discussed. This could result in the definition of biological predictors of heterosis.     

Recent advances in membrane bio-technologies for sludge reduction and treatment

This paper is designed to critically review the recent developments of membrane bio-technologies for sludge reduction and treatment by covering process fundamentals, performances (sludge reduction efficiency, membrane fouling, pollutant removal, etc.) and key operational parameters. The future perspectives of the hybrid membrane processes for sludge reduction and treatment are also discussed. For sludge reduction using membrane bioreactors (MBRs), literature review shows that biological maintenance metabolism, predation on bacteria, and uncoupling metabolism through using oxic-settling-anaerobic (OSA) process are promising ways that can be employed in full-scale applications. Development of control methods for worm proliferation is in great need of, and a good sludge reduction and MBR performance can be expected if worm growth is properly controlled. For lysis-cryptic sludge reduction method, improvement of oxidant dispersion and increase of the interaction with sludge cells can enhance the lysis efficiency. Green uncoupler development might be another research direction for uncoupling metabolism in MBRs. Aerobic hybrid membrane system can perform well for sludge thickening and digestion in small- and medium-sized wastewater treatment plants (WWTPs), and pilot-scale/full-scale applications have been reported. Anaerobic membrane digestion (AMD) process is a very competitive technology for sludge stabilization and digestion. Use of biogas recirculation for fouling control can be a powerful way to decrease the energy requirements for AMD process. Future research efforts should be dedicated to membrane preparation for high biomass applications, process optimization, and pilot-scale/full-scale tracking research in order to push forward the real and wide applications of the hybrid membrane systems for sludge minimization and treatment.     

The application of yeast hybrid systems in protein interaction analysis

Yeast hybrid systems have been widely used due to their convenience and low cost. Based on these systems, many methods have been developed to analyze protein–protein, protein–DNA and protein–RNA interactions. In this paper, we are reviewing these different yeast hybrid systems. According to the number of hybrid proteins, yeast hybrid systems can be divided into three categories, yeast one-hybrid, yeast two-hybrid and yeast three-hybrid systems. Alternatively, yeast hybrid systems can be categorized according to the subcellular localization of the protein interaction process in the cell into nuclear protein–protein interactions, cytosol protein–protein interactions and membrane protein–protein interactions. Throughout the review, we focus on the progress and limitations of each yeast hybrid system over the recent years.