Simultaneous expression of recombinant proteins in the insect cell-baculovirus system: production of virus-like particles

The insect cell-baculovirus system (IC-BEVS) is widely used for the production of recombinant viral proteins for vaccine applications. It is especially suitable for the production of virus-like particles, which often require the simultaneous production of several recombinant proteins. Here, the available tools and process requirements for the simultaneous production of several recombinant proteins using the IC-BEVS are discussed. The production of double-layered rotavirus like particles is used as a specific example for the simultaneous production of two recombinant proteins. Methods to quantify VLP in small samples are described. The multiplicity and time of infection are presented as tools to manipulate protein concentration, and the effect on protein concentration ratios on the assembly efficiency of double-layered rotavirus like particles is discussed. It was found that not only the ratio between the recombinant proteins is determinant of VLP assembly efficiency, but also that assembly efficiency is related to the characteristics of the assembled proteins. This is the first time that kinetics of VLP production are followed during cultures, and that the assembly efficiency is quantitatively determined.     

A case study in the design of flexible assembly systems

The design of production systems is generally based on economic considerations, which are related to certain technical criteria, such as capacity, availability, and reliability. To realize a cost-effective design, these technical and economic criteria should be considered in their mutual coherence during the conceptual design process. This paper focuses on a productivity model, which is related to this subject. This model allows an opinion to be formed about the technical and economic performance of conceptual robotic assembly cells, during the process of design. First, the system design process is discussed in brief, after which the productivity variables are presented. An illustration of the model is used to assess the technical and economic behavior of alternative system structures for the assembly of a power plug assortment.     

Species assembly in model ecosystems, II: Results of the assembly process

In the companion paper of this set (Capitán and Cuesta, 2010) we have developed a full analytical treatment of the model of species assembly introduced in Capitán et al. (2009). This model is based on the construction of an assembly graph containing all viable configurations of the community, and the definition of a Markov chain whose transitions are the transformations of communities by new species invasions. In the present paper we provide an exhaustive numerical analysis of the model, describing the average time to the recurrent state, the statistics of avalanches, and the dependence of the results on the amount of available resource. Our results are based on the fact that the Markov chain provides an asymptotic probability distribution for the recurrent states, which can be used to obtain averages of observables as well as the time variation of these magnitudes during succession, in an exact manner. Since the absorption times into the recurrent set are found to be comparable to the size of the system, the end state is quickly reached (in units of the invasion time). Thus, the final ecosystem can be regarded as a fluctuating complex system where species are continually replaced by newcomers without ever leaving the set of recurrent patterns. The assembly graph is dominated by pathways in which most invasions are accepted, triggering small extinction avalanches. Through the assembly process, communities become less resilient (e.g., have a higher return time to equilibrium) but become more robust in terms of resistance against new invasions.     

Cost optimization of activated sludge systems

Activated sludge is a widely used aerobic biological waste-water treatment process. A rational approach to least cost design of an integrated system is described which includes the following processes: activated sludge reactor, final settling tanks, gravity thickening, and aerobic sludge digestion. Both capital and operation and maintenance costs are considered. Biological reactor design is based on microbial kinetic concepts and continuous culture of microorganisms theory. Biological solids retention time (θ_c) is utilized as the primary independent design variable to which system performance is related, e.g., effluent quality, ammonia oxidation, and excess sludge production. Liquid-biomass separation is based on the batch flux technique, a rational approach to design of gravity separators (final settling tanks). Trade-offs among reactor volume, clarifier size, recycle pumping capacity, thickener capacity, digester volume, air requirements, and sludge production are discussed. The optimum design is taken as the combination of these parameters within the acceptable design domain, determined by effluent quality criteria, that results in minimum cost. While the method described is general, design of a given treatment system depends on availability, from lab or pilot studies, of system specific numerical values for biological growth coefficients and biomass setting characteristics. A design example illustrates the approach.     

Early commitment of yeast pre-mRNA to the spliceosome pathway.

Pre-mRNA splicing in vitro is preceded by complex formation (spliceosome assembly). U2 small nuclear RNA (snRNA) is found in the earliest form of the spliceosome detected by native gel electrophoresis, both in Saccharomyces cerevisiae and in metazoan extracts. To examine the requirements for the formation of this early complex (band III) in yeast extracts, we cleaved the U2 snRNA by oligonucleotide-directed RNase H digestion. U2 snRNA depletion by this means inhibits both splicing and band III formation. Using this depleted extract, we were able to design a chase experiment which shows that a pre-mRNA substrate is committed to the spliceosome assembly pathway in the absence of functional U2 snRNP. Interactions occurring during the commitment step are highly resistant to the addition of an excess of unlabeled substrate and require little or no ATP. Sequence requirements for this commitment step have been analyzed by competition experiments with deletion mutants: both the 5' splice site consensus sequence and the branch point TACTAAC box sequence are necessary. These experiments strongly suggest that the initial assembly process requires a trans-acting factor(s) (RNA and/or proteins) that recognizes and stably binds to the two consensus sequences of the pre-mRNA prior to U2 snRNP binding.     

Assembly Root Cause Analysis: A Way to Reduce Dimensional Variation in Assembled Products

The objective of root cause analysis (RCA) is to make the trouble shooting dimensional error efforts in an assembly plant more efficient and successful by pinpointing the underlying reasons for variation. The result of eliminating or limiting these sources of variation is a real and long term process improvement. Complex products are manufactured in multileveled hierarchical assembly processes using positioning fixtures. A general approach for diagnosing fixture related errors using routine measurement on products, rather than from special measurements on fixtures, is presented. The assembly variation is effectively tracked down into variation in the fixture tooling elements, referred to as locators. In this way, the process engineers can focus on adjusting the locators affected by most variation. However, depending on the assembly process configuration, inspection strategy, and the type of locator error, it can be impossible to completely sort out the variation caused by an individual locator. The reason for this is that faults in different locators can cause identical dimensional deviation in the inspection station. Conditions guaranteeing diagnosability are derived by considering multiple uncoupled locator faults, in contrast to previous research focusing on single or multiple coupled locator faults. Furthermore, even if an assembly is not diagnosable, it is still possible to gain information for diagnosis by using a novel approach to find an interval for each locator containing the true underlying locator variation. In this way, some locators can be excluded from further analysis, some can be picked out for adjustment, and others remain as potential reason for assembly variation. Another way around the problem of diagnosability is to make a higher level diagnosis by calculating the amount of variation originating from different assembly stations. Also, a design for diagnosis approach is discussed, where assembly and inspection concepts allowing for root cause analysis are the objective.     

RNA‐guided Cas9 as an in vivo desired‐target mutator in maize

The RNA‐guided Cas9 system is a versatile tool for genome editing. Here, we established a RNA‐guided endonuclease (RGEN) system as an in vivo desired‐target mutator (DTM) in maize to reduce the linkage drag during breeding procedure, using the LIGULELESS1 (LG1) locus as a proof‐of‐concept. Our system showed 51.5%–91.2% mutation frequency in T0 transgenic plants. We then crossed the T1 plants stably expressing DTM with six diverse recipient maize lines and found that 11.79%–28.71% of the plants tested were mutants induced by the DTM effect. Analysis of successive F2 plants indicated that the mutations induced by the DTM effect were largely heritable. Moreover, DTM‐generated hybrids had significantly smaller leaf angles that were reduced more than 50% when compared with that of the wild type. Planting experiments showed that DTM‐generated maize plants can be grown with significantly higher density and hence greater yield potential. Our work demonstrate that stably expressed RGEN could be implemented as an in vivoDTM to rapidly generate and spread desired mutations in maize through hybridization and subsequent backcrossing, and hence bypassing the linkage drag effect in convention introgression methodology. This proof‐of‐concept experiment can be a potentially much more efficient breeding strategy in crops employing the RNA‐guided Cas9 genome editing.     

Equipment ontology for modular reconfigurable assembly systems

Evolvable and Reconfigurable Assembly Systems (RAS) enable enterprises to rapidly respond to changes in today’s increasingly volatile and dynamic global markets. One of the key success factors for the effective use of RAS is methods and tools that can rapidly configure and reconfigure assembly systems driven by changing requirements. The focus of this paper is the development of a suitable equipment model to support the effective design of reconfigurable assembly systems. The work has been motivated by the need to provide solutions for increasing product customisation and volume changes over the product life-cycle that directly impact on the final product assembly. The paper proposes a comprehensive equipment ontology to enable effective decision-making during the design and evaluation of new RAS configurations. The proposed ontology is based on the function-behaviour-structure paradigm, and is formalised to facilitate its application in distributed web-enabled decision-making environments. The equipment configuration and reconfiguration approach and prototype decision-making environment are illustrated using system design examples.     

A Column-Generation Approach for the Assembly System Design Problem with Tool Changes

This assembly system design problem (ASDP) is to prescribe the minimum-cost assignment of machines, tooling, and tasks to stations, observing task precedence relationships and cycle time requirements. The ASDP with tool changes (ASDPTCs) also prescribes the optimal sequence of operations at each station, including tool changes, which are important, for example, in robotic assembly. A unique solution approach decomposes the model into a master problem, which is a minimum-cost network-flow problem that can be solved as a linear program, and subproblems, which are constrained, shortest-path problems that generate station configurations. Subproblems are solved on state-operation networks, which extend earlier formulations to incorporate tooling considerations. This paper presents a specialized algorithm to solve the subproblems. Computational tests benchmark the approach on several classes of problems, and the results are promising. In particular, tests demonstrate the importance of using engineering judgment to manage problem complexity by controlling the size of state-operation networks     

Spatio-temporal characterization of intercostal activity during breathing in the cat

It is envisaged that the motor control of the intercostal musculature--an assembly of mobile structures--can be characterized in terms of a conceptual spatially continuous control function, that underlies the discretely distributed muscular activity and reflects an inferred global dynamic control of the thoracic cage during breathing. The global control function is estimated by the spatio-temporal pattern obtained by averaging in time and space and interpolation of multichannel simultaneous intercostal EMG recording in the anaesthetized cat. Different examples of the experimental preparation in the presence of stimuli of different kinds are analysed. The resultant signal patterns are found to be self-consistent and capable of exhibiting systematically differing features in systematically differing experimental conditions, thus supporting the validity of the analysis and the choice of the estimator. It is concluded that a more detailed analysis of the requirements of this approach is then warranted. Such requirements are discussed, and, specifically, results that bear on the adequacy of spatial sampling rate are presented. It is suggested that such methods offer a promising approach in the study of motor control strategies of the respiratory apparatus.     

Principles of the design and operational considerations of large scale high performance liquid chromatography (HPLC) systems for proteins and peptides purification.

This review introduces concepts of design of large scale HPLC systems for purification of proteins and peptides. It is addressed to users of large scale HPLC systems to aid in system selection and help in customizing the design. Major techniques used for large scale HPLC purification of proteins and peptides are briefly reviewed. Engineering aspects of system design are discussed in detail. The review of selected relevant literature is provided as well as author's experience with the existing designs and his own systems. Commercial publications have been used in preparation of this review but only the most significant are listed as examples. The design process for any new system should be related to the performance of existing systems, if possible of a large scale. Laboratory data are also very useful in aiding the design process since they provide a lead, as to which chromatography techniques may succeed in providing required separation levels. The expertise needed for system design and operation comes from many areas: protein and peptide chemistry, chromatographic theory, mass transfer and hydrodynamics, machine design and material science. All these factors have to be blended together during the system design process. The controls must ensure flexibility in adapting to changing system configuration, depending on the operational requirements for various products. Extensive interfacing with the operator during the process run is essential. This work is focused mostly on system design and operation for reversed-phase chromatography and hydrophobic interaction chromatography, but it also covers aspects associated with other chromatographic techniques. The reviewed design principles would also apply to design other than HPLC large scale chromatography systems for biotechnology and pharmaceutical operations.     

The bacteriorhodopsin model membrane system as a prototype molecular computing element

The quest for more sophisticated integrated circuits to overcome the limitation of currently available silicon integrated circuits has led to the proposal of using biological molecules as computational elements by computer scientists and engineers. While the theoretical aspect of this possibility has been pursued by computer scientists, the research and development of experimental prototypes have not been pursued with an equal intensity. In this survey, we make an attempt to examine model membrane systems that incorporate the protein pigment bacteriorhodopsin which is found in Halobacterium halobium. This system was chosen for several reasons. The pigment/membrane system is sufficiently simple and stable for rigorous quantitative study, yet at the same time sufficiently complex in molecular structure to permit alteration of this structure in an attempt to manipulate the photosignal. Several methods of forming the pigment/membrane assembly are described and the potential application to biochip design is discussed. Experimental data using these membranes and measured by a tunable voltage clamp method are presented along with a theoretical analysis based on the Gouy-Chapman diffuse double layer theory to illustrate the usefulness of this approach. It is shown that detailed layouts of the pigment/membrane assembly as well as external loading conditions can modify the time course of the photosignal in a predictable manner. Some problems that may arise in the actual implementation and manufacturing, as well as the use of existing technology in protein chemistry, immunology, and recombinant DNA technology are discussed.     

A minimal spliceosomal complex A recognizes the branch site and polypyrimidine tract.

The association of U2 snRNP with the pre-mRNA branch region is a critical step in the assembly of spliceosomal complexes. We describe an assembly process that reveals both minimal requirements for formation of a U2 snRNP-substrate RNA complex, here designated the Amin complex, and specific interactions with the branch site adenosine. The substrate is a minimal RNA oligonucleotide, containing only a branch sequence and polypyrimidine tract. Interactions at the branch site adenosine and requirements for polypyrimidine tract-binding proteins for the Amin complex are the same as those of authentic prespliceosome complex A. Surprisingly, Amin complex formation does not require U1 snRNP or ATP, suggesting that these factors are not necessary for stable binding of U2 snRNP per se, but rather are necessary for accessibility of components on longer RNA substrates. Furthermore, there is an ATP-dependent activity that releases or destabilizes U2 snRNP from branch sequences. The simplicity of the Amin complex will facilitate a detailed understanding of the assembly of prespliceosomes.     

Structured Under‐Specification of Life Cycle Impact Assessment Data for Building Assemblies

The existence of uncertainties and variations in data represents a remaining challenge for life cycle assessment (LCA). Moreover, a full analysis may be complex, time‐consuming, and implemented mainly when a product design is already defined. Structured under‐specification, a method developed to streamline LCA, is here proposed to support the residential building design process, by quantifying environmental impact when specific information on the system under analysis cannot be available. By means of structured classifications of materials and building assemblies, it is possible to use surrogate data during the life cycle inventory phase and thus to obtain environmental impact and associated uncertainty. The bill of materials of a building assembly can be specified using minimal detail during the design process. The low‐fidelity characterization of a building assembly and the uncertainty associated with these low levels of fidelity are systematically quantified through structured under‐specification using a structured classification of materials. The analyst is able to use this classification to quantify uncertainty in results at each level of specificity. Concerning building assemblies, an average decrease of uncertainty of 25% is observed at each additional level of specificity within the data structure. This approach was used to compare different exterior wall options during the early design process. Almost 50% of the comparisons can be statistically differentiated at even the lowest level of specificity. This data structure is the foundation of a streamlined approach that can be applied not only when a complete bill of materials is available, but also when fewer details are known.     

Modeling capsid self-assembly: design and analysis

A series of simulations aimed at elucidating the self-assembly dynamics of spherical virus capsids is described. This little-understood phenomenon is a fascinating example of the complex processes that occur in the simplest of organisms. The fact that different viruses adopt similar structural forms is an indication of a common underlying design, motivating the use of simplified, low-resolution models in exploring the assembly process. Several versions of a molecular dynamics approach are described. Polyhedral shells of different sizes are involved, the assembly pathways are either irreversible or reversible and an explicit solvent is optionally included. Model design, simulation methodology and analysis techniques are discussed. The analysis focuses on the growth pathways and the nature of the intermediate states, properties that are hard to access experimentally. Among the key observations are that efficient growth proceeds by means of a cascade of highly reversible stages, and that while there are a large variety of possible partial assemblies, only a relatively small number of strongly bonded configurations are actually encountered.     

Empirical and computational design of iron-sulfur cluster proteins

Here, we compare two approaches of protein design. A computational approach was used in the design of the coiled-coil iron-sulfur protein, CCIS, as a four helix bundle binding an iron-sulfur cluster within its hydrophobic core. An empirical approach was used for designing the redox-chain maquette, RCM as a four-helix bundle assembling iron-sulfur clusters within loops and one heme in the middle of its hydrophobic core. We demonstrate that both ways of design yielded the desired proteins in terms of secondary structure and cofactors assembly. Both approaches, however, still have much to improve in predicting conformational changes in the presence of bound cofactors, controlling oligomerization tendency and stabilizing the bound iron-sulfur clusters in the reduced state. Lessons from both ways of design and future directions of development are discussed. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.     

Differential transform semi-numerical analysis of biofluid-particle suspension flow and heat transfer in non-Darcian porous media

The differential transform method (DTM) is semi-numerical method which is used to study the steady, laminar buoyancy-driven convection heat transfer of a particulate biofluid suspension in a channel containing a porous material. A two-phase continuum model is used. A set of variables is implemented to reduce the ordinary differential equations for momentum and energy conservation (for both phases) to a dimensionless system. DTM solutions are obtained for the dimensionless system under appropriate boundary conditions. We examine the influence of momentum inverse Stokes number (Sk_m), Darcy number (Da), Forchheimer number (Fs), particle loading parameter (p_L), particle-phase wall slip parameter (Ω) and buoyancy parameter (B) on the fluid-phase velocity (U) and particle-phase velocity (U_p). Padé approximants are also employed to achieve satisfaction of boundary conditions. Excellent correlation is obtained between the DTM and numerical quadrature solutions. The results indicate that there is a strong decrease in fluid-phase velocities with increasing Darcian (first-order) drag and the second-order Forchheimer drag, and a weaker reduction in particle-phase velocity field. Fluid and particle-phase velocities are also strongly affected with inverse momentum Stokes number. DTM is shown to be a powerful tool providing engineers with an alternative simulation approach to other traditional methods for multi-phase computational biofluid mechanics. The model finds applications in haemotological separation and biotechnological processing.     

Eugene--a domain specific language for specifying and constraining synthetic biological parts, devices, and systems

Background

Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts.

Results

We illustrate Eugene''s capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene''s ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively.

Conclusions

Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly.     

Dissipative structures in morphogenetic models of the Turing type

We investigate the general conditions for morphogenesis. It is found that not only the Turing condition shall be satisfied, but also that some other requirements must be fulfilled. Their physical meaning is that the system should have more than one stationary state. In biological terms this means that the competence of differentiation is necessary in order to finish the morphogenesic process. These ideas are illustrated by a simple mathematical model. For this model the bifurcation analysis and computer results are discussed. Furthermore the parametric regulation of the morphogenesis is considered in connection with the role played by the genetic information.