Economic analysis of uricase production under uncertainty: Contrast of chromatographic purification and aqueous two‐phase extraction (with and without PEG recycle)

Uricase is the enzyme responsible for the breakdown of uric acid, the key molecule leading to gout in humans, into allantoin, but it is absent in humans. It has been produced as a PEGylated pharmaceutical where the purification is performed through three sequential chromatographic columns. More recently an aqueous two‐phase system (ATPS) was reported that could recover Uricase with high yield and purity. Although the use of ATPS can decrease cost and time, it also generates a large amount of waste. The ability, therefore, to recycle key components of ATPS is of interest. Economic modelling is a powerful tool that allows the bioprocess engineer to compare possible outcomes and find areas where further research or optimization might be required without recourse to extensive experiments and time. This research provides an economic analysis using the commercial software BioSolve of the strategies for Uricase production: chromatographic and ATPS, and includes a third bioprocess that uses material recycling. The key parameters that affect the process the most were located via a sensitivity analysis and evaluated with a Monte Carlo analysis. Results show that ATPS is far less expensive than chromatography, but that there is an area where the cost of production of both bioprocesses overlap. Furthermore, recycling does not impact the cost of production. This study serves to provide a framework for the economic analysis of Uricase production using alternative techniques. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:126–133, 2016     

Economic analysis of royalactin production under uncertainty: Evaluating the effect of parameter optimization

Royalactin is a protein with several different potential uses in humans. Research, in insects and in mammalian cells, has shown that it can accelerate cell division and prevent apoptosis. The method of action is through the use of the epidermal growth factor receptor, which is present in humans. Potential use in humans could be to lower cholesterolemic levels in blood, and to elicit similar effects to those seen in bees, e.g., increased lifespan. Mass production of Royalactin has not been accomplished, though a recent article presented a Pichia pastoris fermentation and recovery by aqueous two‐phase systems at laboratory scale as a possible basis for production. Economic modelling is a useful tool with which compare possible outcomes for the production of such a molecule and in particular, to locate areas where additional research is needed and optimization may be required. This study uses the BioSolve software to perform an economic analysis on the scale‐up of the putative process for Royalactin. The key parameters affecting the cost of production were located via a sensitivity analysis and then evaluated by Monte Carlo analysis. Results show that if titer is not optimized the strategy to maintain a low cost of goods is process oriented. After optimization of this parameter the strategy changes to a product‐oriented and the target output becomes the critical parameter determining the cost of goods. This study serves to provide a framework for the evaluation of strategies for future production of Royalactin, by analyzing the factors that influence its cost of manufacture. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:744–749, 2015     

High‐throughput downstream process development for cell‐based products using aqueous two‐phase systems (ATPS) – A case study

The availability of preparative‐scale downstream processing strategies for cell‐based products presents a critical juncture between fundamental research and clinical development. Aqueous two‐phase systems (ATPS) present a gentle, scalable, label‐free, and cost‐effective method for cell purification, and are thus a promising tool for downstream processing of cell‐based therapeutics. Here, the application of a previously developed robotic screening platform that enables high‐throughput cell partitioning analysis in ATPS is reported. In the present case study a purification strategy for two model cell lines based on high‐throughput screening (HTS)‐data and countercurrent distribution (CCD)‐modeling, and validated the CCD‐model experimentally is designed. The obtained data are shown an excellent congruence between CCD‐model and experimental data, indicating that CCD‐models in combination with HTS‐data are a powerful tool in downstream process development. Finally, the authors are shown that while cell cycle phase significantly influences cell partitioning, cell type specific differences in surface properties are the main driving force in charge‐dependent separation of HL‐60 and L929 cells. In order to design a highly robust purification process it is, however, advisable to maintain constant growth conditions.     

Separation of bio‐based chemicals from fermentation broths by salting‐out extraction

The possibility of creating a biorefinery using inexpensive biomass has attracted a great deal of attention, which is mainly focused on the improvement of strains and fermentation, whereas few resources have been spent on downstream processing. Bio‐based chemical downstream processing can become a bottleneck in industrial production because so many impurities are introduced into the fermentation broth. This review introduces a technique referred to as salting‐out extraction, which is based on the partition difference between chemicals in two phases consisting of salts and polymers or hydrophilic solvents, hydrophobic solvents, and amphipathic chemicals. The effects of solvents and salts on the formation of two phases were discussed, as was the use of this method to recover bio‐based chemicals. This review focused on the separation of hydrophilic chemicals (1,3‐propanediol, 2,3‐butanediol, acetoin, and lactic acid) from fermentation broths. Diols could be recovered at a high yield from fermentation broths without pretreatment especially with a hydrophilic solvent‐based system, whereas the recovery of organic acids was slightly lower. Most of the impurities (cells and proteins) were removed during the same step. Extractive fermentations were also used for polymer‐based aqueous two‐phase systems.     

Scale and uncertainty in modeled soil organic carbon stock changes for US croplands using a process‐based model

Process‐based model analyses are often used to estimate changes in soil organic carbon (SOC), particularly at regional to continental scales. However, uncertainties are rarely evaluated, and so it is difficult to determine how much confidence can be placed in the results. Our objective was to quantify uncertainties across multiple scales in a process‐based model analysis, and provide 95% confidence intervals for the estimates. Specifically, we used the Century ecosystem model to estimate changes in SOC stocks for US croplands during the 1990s, addressing uncertainties in model inputs, structure and scaling of results from point locations to regions and the entire country. Overall, SOC stocks increased in US croplands by 14.6 Tg C yr^?1 from 1990 to 1995 and 17.5 Tg C yr^?1 during 1995 to 2000, and uncertainties were ±22% and ±16% for the two time periods, respectively. Uncertainties were inversely related to spatial scale, with median uncertainties at the regional scale estimated at ±118% and ±114% during the early and latter part of 1990s, and even higher at the site scale with estimates at ±739% and ±674% for the time periods, respectively. This relationship appeared to be driven by the amount of the SOC stock change; changes in stocks that exceeded 200 Gg C yr^?1 represented a threshold where uncertainties were always lower than ±100%. Consequently, the amount of uncertainty in estimates derived from process‐based models will partly depend on the level of SOC accumulation or loss. In general, the majority of uncertainty was associated with model structure in this application, and so attaining higher levels of precision in the estimates will largely depend on improving the model algorithms and parameterization, as well as increasing the number of measurement sites used to evaluate the structural uncertainty.     

Uncertainty analysis of penicillin V production using Monte Carlo simulation

Uncertainty and variability affect economic and environmental performance in the production of biotechnology and pharmaceutical products. However, commercial process simulation software typically provides analysis that assumes deterministic rather than stochastic process parameters and thus is not capable of dealing with the complexities created by variance that arise in the decision-making process. Using the production of penicillin V as a case study, this article shows how uncertainty can be quantified and evaluated. The first step is construction of a process model, as well as analysis of its cost structure and environmental impact. The second step is identification of uncertain variables and determination of their probability distributions based on available process and literature data. Finally, Monte Carlo simulations are run to see how these uncertainties propagate through the model and affect key economic and environmental outcomes. Thus, the overall variation of these objective functions are quantified, the technical, supply chain, and market parameters that contribute most to the existing variance are identified and the differences between economic and ecological evaluation are analyzed. In our case study analysis, we show that final penicillin and biomass concentrations in the fermenter have the highest contribution to variance for both unit production cost and environmental impact. The penicillin selling price dominates return on investment variance as well as the variance for other revenue-dependent parameters.     

Selection and optimization of an aqueous two‐phase system for the recovery of 1,3‐propandiol from fermentation broth

In this study a suitable alcohol/salt aqueous two‐phase (ATP) system was selected for the recovery of 1,3‐propandiol (1,3‐PD) from fermentation broth. From the different alcohol/salt systems studied the ethanol and dipotassium hydrogen phosphate ATP system appeared to be favorable. To examine the potential of this ATP system the partition coefficient of 1,3‐PD in synthetic solutions was first optimized with the response surface methodology. The parameters studied were concentrations of ethanol (21.99–38.81% w/w), dipotassium hydrogen phosphate (14.99–31.81% w/w) and 1,3‐PD (6.36–73.64 g/L). The optimum conditions were found to be 35.39% w/w for ethanol, 28.40% w/w for dipotassium hydrogen phosphate and 73.6 g/L for 1,3‐PD. Under these conditions the maximum partition coefficient of 1,3‐PD and the extraction yield were determined as 23.14 and 97.82%, respectively. The optimum extraction conditions were then used to guide the recovery of 1,3‐PD from a real fermentation broth. The partition coefficient and extraction yield of 1,3‐PD reached 20.28–97.20% in this case, respectively. A favorable partition of the organic acids lactate, acetate and butyrate in the bottom phase was also achieved. We have also studied the removal of cells and macromolecules from the broth. Removal ratio of cells and proteins were 96.47 and 93.05%, respectively. Thus, the ethanol/dipotassium hydrogen phosphate ATP system appears to be an interesting alternative or can be used as one useful step in the downstream processing of 1,3‐PD from fermentation broth.     

Preparation and recycling of aqueous two‐phase systems with pH‐sensitive amphiphilic terpolymer PADB

In this study, a novel pH‐sensitive terpolymer PADB was synthesized by random terpolymerization of 2‐(dimethylamino) ethyl methacrylate, acrylic acid, and butyl methacrylate. The terpolymer PADB could form aqueous two‐phase systems (ATPS) with a light‐sensitive terpolymer PNBC, which was synthesized in our laboratory, using n‐isopropylacrylamide, n‐butyl acrylate, chlorophyllin sodium copper salt as monomers. More than 97% of the PADB terpolymer could be recovered by adjusting the pH to isoelectric point (PI) 4.1. The terpolymer PNBC could be recovered by using light radiation at 488 nm, with recovery ratio of 98%. BSA and lysozyme were partitioned in the PNBC–PADB ATPS to examine this new system. It was found that the partition coefficient of BSA and lysozyme could reach 4.46 and 0.49 in the systems, respectively. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Effect of glycosylation on the partition behavior of a human antibody in aqueous two‐phase systems

Human proteins are expressed in some hosts wrongly glycosylated or nonglycosylated. Although it is accepted that glycosylation contributes to the stability of the protein in solution, the effect of glycosylation on the stability of human antibodies is not fully understood. In this work, we present solubility studies of two human antibodies that have the same primary structure but different glycosylation pattern. The studies were done by monitoring the partitioning behavior of both proteins in a series of aqueous two‐phase systems at and away the isoelectric point of the proteins and at different temperatures. Our studies show that in the absence of direct electrostatic forces, the partitioning behavior of the antibodies depends on the presence or absence of the polysaccharide chains. Overall, the nonglycosylated protein is less soluble than the glycosylated one. The potential of aqueous two‐phase systems for the separation of the glycosylated and nonglycosylated proteins was also explored. A simple series of extractions seems to be enough to separate the glycosylated variety from the nonglycosylated one at high purity but low yields. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:943–950, 2013     

Aqueous biphasic cancer cell migration assay enables robust,high‐throughput screening of anti‐cancer compounds

Migration of tumor cells is a fundamental event implicated in metastatic progression of cancer. Therapeutic compounds with the ability to inhibit the motility of cancer cells are critical for preventing cancer metastasis. Achieving this goal requires new technologies that enable high‐throughput drug screening against migration of cancer cells and expedite drug discovery. We report an easy‐to‐implement, robotically operated, cell migration microtechnology with the capability of simultaneous screening of multiple compounds. The technology utilizes a fully biocompatible polymeric aqueous two‐phase system to pattern a monolayer of cells containing a cell‐excluded gap that serves as the migration niche. We adapted this technology to a standard 96‐well plate format and parametrically optimized it to generate highly consistent migration niches. The analysis of migration is done automatically using computerized schemes. We use statistical metrics and show the robustness of this assay for drug screening and its sensitivity to identify effects of different drug compounds on migration of cancer cells. This technology can be employed in core centers, research laboratories, and pharmaceutical industries to evaluate the efficacy of compounds against migration of various types of metastatic cancer cells prior to expensive animal tests and thus, streamline anti‐migratory drug screening.     

A new mixed‐effects regression model for the analysis of zero‐modified hierarchical count data

Count data sets are traditionally analyzed using the ordinary Poisson distribution. However, such a model has its applicability limited as it can be somewhat restrictive to handle specific data structures. In this case, it arises the need for obtaining alternative models that accommodate, for example, (a) zero‐modification (inflation or deflation at the frequency of zeros), (b) overdispersion, and (c) individual heterogeneity arising from clustering or repeated (correlated) measurements made on the same subject. Cases (a)–(b) and (b)–(c) are often treated together in the statistical literature with several practical applications, but models supporting all at once are less common. Hence, this paper's primary goal was to jointly address these issues by deriving a mixed‐effects regression model based on the hurdle version of the Poisson–Lindley distribution. In this framework, the zero‐modification is incorporated by assuming that a binary probability model determines which outcomes are zero‐valued, and a zero‐truncated process is responsible for generating positive observations. Approximate posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the Adaptive Metropolis algorithm. Intensive Monte Carlo simulation studies were performed to assess the empirical properties of the Bayesian estimators. The proposed model was considered for the analysis of a real data set, and its competitiveness regarding some well‐established mixed‐effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian ‐value and the randomized quantile residuals were considered for model diagnostics.     

Comparison of thermoluminescence characteristics in γ‐ray and C5+ ion beam‐irradiated LiCaAlF6:Ce phosphor

We compare the thermoluminescence (TL) behavior of Ce³⁺ ion‐activated LiCaAlF₆ exposed to γ‐rays and a carbon ion beam. The reported phosphor is synthesized using an in‐house precipitation method with varying concentrations of activator ion and is characterized by X‐ray diffraction (XRD) and TL. Rietveld refinement is performed to study the structural statistics. The TL glow curve consists of a prominent glow peak at 232°C with three shoulders at 115, 159 and 333°C when exposed to γ‐rays from a ⁶⁰Co source. When exposed to a C⁵⁺ ion beam, the TL glow curve consists of five peaks with peak temperatures near 156, 221, 250, 287 and 330°C, and is found to vary slightly with changing fluence. Glow curve convolution deconvolution (GCCD) functions are applied to the TL curves for complete analysis of the glow curve structure and TL traps. The order of kinetics (b), activation energy (E) and frequency factor are determined using Chen's peak shape method and theoretical curves are drawn using GCCD functions. A track interaction model (TIM) is used to explain the sublinearity/saturation at higher fluences. Ion beam parameters are analyzed using Monte‐Carlo simulation‐based SRIM‐2013 code. Copyright © 2016 John Wiley & Sons, Ltd.     

Partial‐Likelihood Analysis of Spatio‐Temporal Point‐Process Data

Summary We investigate the use of a partial likelihood for estimation of the parameters of interest in spatio‐temporal point‐process models. We identify an important distinction between spatially discrete and spatially continuous models. We focus our attention on the spatially continuous case, which has not previously been considered. We use an inhomogeneous Poisson process and an infectious disease process, for which maximum‐likelihood estimation is tractable, to assess the relative efficiency of partial versus full likelihood, and to illustrate the relative ease of implementation of the former. We apply the partial‐likelihood method to a study of the nesting pattern of common terns in the Ebro Delta Natural Park, Spain.     

Uncertainty Quantification in Life Cycle Assessments: Interindividual Variability and Sensitivity Analysis in LCA of Air‐Conditioning Systems

The life cycle environmental profile of energy‐consuming products, such as air conditioning, is dominated by the products’ use phase. Different user behavior patterns can therefore yield large differences in the results of a cradle‐to‐grave assessment. Although this variation and uncertainty is increasingly recognized, it remains often poorly characterized in life cycle assessment (LCA) studies. Today, pervasive sensing presents the opportunity to collect rich data sets and improve profiling of use‐phase parameters, in turn facilitating quantification and reduction of this uncertainty in LCA. This study examined the case of energy use in building cooling systems, focusing on global warming potential (GWP) as the impact category. In Singapore, building cooling systems or air conditioning consumes up to 37% of national electricity demand. Lack of consideration of variation in use‐phase interaction leads to the oversized designs, wasted energy, and therefore reducible GWP. Using a high‐resolution data set derived from sensor observations, energy use and behavior patterns of single‐office occupants were characterized by probabilistic distributions. The interindividual variability and use‐phase variables were propagated in a stochastic model for the life cycle of air‐conditioning systems and simulated by way of Monte Carlo analysis. Analysis of the generated uncertainties identified plausible reductions in global warming impact through modifying user interaction. Designers concerned about the environmental profile of their products or systems need better representation of the underlying variability in use‐phase data to evaluate the impact. This study suggests that data can be reliably provided and incorporated into the life cycle by proliferation of pervasive sensing, which can only continue to benefit future LCA.     

A comparison of five distance‐based methods for spatial pattern analysis

Abstract. The behaviour of five statistics (extensions of Pielou's, Clark and Evansapos;, Pollard's, Johnson & Zimmer's, and Eberhardt's statistics, which are denoted as P_i, C_e, P_o, J_z and E_b respectively) that involve the distance from a random point to its jth nearest neighbour were examined against several alternative patterns (lattice‐based regular, inhomogeneous random, and Poisson cluster patterns) through Monte Carlo simulation to test their powers to detect patterns. The powers of all the five statistics increase as distance order j increases against inhomogeneous random pattern. They decrease for P_i and C_e and increase for P_o, J_z, and E_b against regular and Poisson cluster patterns. P_o, J_z, and E_b can reach high powers with the third or higher order distances in most cases. However, P_o is recommended because no extra information is needed, it can reach a high power with the second or third distance even though the sample size is not large in most cases, and the test can be performed with an approximate χ² distribution associated with it. When a regular pattern is expected, J_z is recommended because it is more sensitive to lattice‐based regular pattern than P_o and E_b, especially for the first distance. However, simulation tests should be used because the speed of convergence of J_z to normal distribution is very slow.     

Potential application of aqueous two‐phase systems and three‐phase partitioning for the recovery of superoxide dismutase from a clarified homogenate of Kluyveromyces marxianus

Superoxide dismutase (SOD; EC 1.15.1.1) is an antioxidant enzyme that represents the primary cellular defense against superoxide radicals and has interesting applications in the medical and cosmetic industries. In the present work, the partition behavior of SOD in aqueous two‐phase systems (ATPS) (using a standard solution and a complex extract from Kluyveromyces marxianus as sample) was characterized on different types of ATPS (polymer–polymer, polymer–salt, alcohol–salt, and ionic liquid (IL)–salt). The systems composed of PEG 3350‐potassium phosphate, 45% TLL, 0.5 M NaCl (315 U/mg, 87% recovery, and 15.1‐fold purification) and t‐butanol‐20% ammonium sulfate (205.8 U/mg, 80% recovery and 9.8‐fold purification), coupled with a subsequent 100 kDa ultrafiltration stage, allowed the design of a prototype process for the recovery and partial purification of the product of interest. The findings reported herein demonstrate the potential of PEG‐salt ATPS for the potential recovery of SOD. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1326–1334, 2014     

Alpha B‐crystallin promotes the invasion and metastasis of gastric cancer via NF‐κB‐induced epithelial‐mesenchymal transition

Alpha B‐crystallin (CRYAB) is overexpressed in a variety of cancers. However, little is known about its specific function and regulatory mechanism in gastric cancer. Here, we first explore the role of CRYAB in gastric cancer progression and metastasis. The expression of CRYAB was determined by western blot and immunohistochemistry in gastric cancer tissues. Besides, methods including stably transfected against CRYAB into gastric cancer cells, western blot, migration and invasion assays in vitro and metastasis assay in vivo were also conducted. The expression of CRYAB is up‐regulated in gastric cancer tissues compared with matched normal tissues. High expression level of CRYAB is closely correlated with cancer metastasis and shorter survival time in patients with gastric cancer. Additionally, CRYAB silencing significantly suppresses epithelial‐mesenchymal transition (EMT), migration and invasion of gastric cancer cells in vitro and in vivo, whereas CRYAB overexpression dramatically reverses these events. Mechanically, CRYAB facilitates gastric cancer cells invasion and metastasis via nuclear factor‐κ‐gene binding (NF‐κB)‐regulated EMT. These findings suggest that CRYAB expression predicts a poor prognosis in patients with gastric cancer. Besides, CRYAB contributes to gastric cancer cells migration and invasion via EMT, mediated by the NF‐κB signalling pathway, thus possibly providing a novel therapeutic target for gastric cancer.     

Development of Ionic Liquid‐Water‐Based Thermomorphic Solvent (TMS)‐Systems for Biocatalytic Reactions

The applicability of ionic liquid‐water‐based thermomorphic solvent (TMS)‐systems with an upper critical solution temperature for homogeneous biocatalysis is investigated. Cholinium‐ and imidazolium‐based ionic liquids are used to facilitate a temperature‐dependent phase change, which can be easily fine‐tuned by adding salts or polar organic solvents. Within the TMS‐system, a high enzymatic activity and subsequent full conversion is achieved in the intermittent monophasic reaction system of the TMS‐system. Therefore, the biocatalyst can be easily recycled after separating the phases at lower temperatures.