Application of mechanistic modelling in membrane and fiber chromatography for purification of biotherapeutics - A review.

Mechanistic modelling is a simulation tool which has been effectively applied in downstream bioprocessing to model resin chromatography. Membrane and fiber chromatography are newer approaches that offer higher rates of mass transfer and consequently higher flow rates and reduced processing times. This review describes the key considerations in the development of mechanistic models for these unit operations. Mass transfer is less complex than in resin columns, but internal housing volumes can make modelling difficult, particularly for laboratory-scale devices. Flow paths are often non-linear and the dead volume is often a larger fraction of the overall volume, which may require more complex hydrodynamic models to capture residence time distributions accurately. In this respect, the combination of computational fluid dynamics with appropriate protein binding models is emerging as an ideal approach.

Influence of yeast growth conditions and proteolytic enzymes on the amino acid profiles of yeast hydrolysates: Implications for taste and nutrition.

This study investigated the effects of aerobic and anaerobic growth and proteolytic enzymes on the amino acid content of yeast hydrolysates in relation to taste and nutrition. Saccharomyces cerevisiae ATCC5574 was grown under fed-batch aerobic or batch anaerobic conditions. Intracellular glutamic acid (Glu) concentrations were 18-fold higher in aerobic yeast. Hydrolysis with papain and alkaline protease released more amino acids (AA) than simple autolysis or hydrolysis with bromelain, most significantly when applied to aerobic yeast (∼2-fold increase). Autolysates and bromelain hydrolysates from aerobic yeast had low levels of bitter and essential AAs, with high levels of umami Glu. Papain and alkaline protease hydrolysates of aerobic yeast had high levels of umami, bitter and essential AAs. Autolysates/hydrolysates from anaerobic yeast had moderate, high, and low levels of bitter, essential and umami AAs. Selection of both yeast growth conditions and hydrolysis enzyme can manipulate the free AA profile and yield of hydrolysates.

The effect of calcium removal from skim milk by ion exchange on the properties of the ultrafiltration retentate.

New processes are needed to produce concentrated milk feedstocks with tailored calcium content, due to the direct link between calcium concentration and final product texture and functionality. Skim milk treatment with cation exchange resin 1% (w/v) or 2% (w/v) prior to ultrafiltration to a volumetric concentration factor (VCF) of 2.5 or 5 successfully decreased the calcium concentration by 20-30% and produced concentrates with solids content at ∼22-24 g 100 g-1 at a VCF of 5. Calcium reduction partially solubilized the casein micelles, increasing the concentration of soluble protein and individual caseins, leading to decreased turbidity but increased protein hydration and hydrophobicity. Decalcification (2% (w/v) resin treatment) reduced thermal stability, significantly decreasing the denaturation temperature of α-lactalbumin and ß-lactoglobulin in the milk by ∼3 °C and ∼1 °C respectively. Filtration was also altered, reducing permeation flux and the gel concentration and increased filtration time. When combined, calcium reduction and filtration altered functional properties including soluble calcium, soluble protein and sedimentable solids, with increased milk protein hydration also contributing to increased viscosity. This study provides a route to produce calcium-reduced milk concentrates with potential for use in retentate-based dairy products with tailored functionality.

An industrially applicable Escherichia coli platform for bioconversion of thebaine to oripavine and codeine to morphine.

A whole cell Escherichia coli biotransformation platform converting thebaine to oripavine and codeine to morphine was demonstrated with industrially applicable yields (∼1.2 × 10-2 g L-1 h-1 or ∼1.2 × 10-1 g L-1 h-1), improving >13 400-fold upon morphine production in yeast. Mutations enhanced enzyme performance and the use of a purified substrate with rich raw poppy extract expanded applicability.

Industrial freezing and tempering for optimal functional properties in thawed Mozzarella cheese.

Mozzarella cheese was industrially frozen (-18 °C), stored for up to six months, tempered at 4 °C for one or three weeks and the structure and functionality compared to cheese stored at 4 °C and cheese aged at 4 °C for four weeks prior to freezing. When combined with ageing or tempering, the slow industrial freezing minimised changes to the protein network as detected by confocal microscopy and arrested proteolysis. Cheese functionality improved with three weeks of tempering, with properties similar to cheese refrigerated for one month, potentially due to increased proteolysis and protein rehydration. Frozen storage induced ß-sheet and ß-turn structures, as detected by S-FTIR microspectroscopy, with longer tempering leading to structural recovery in the cheese. This study indicates the proteolysis and functionality of frozen cheese can be optimised with tempering time. It also provides new insights into heat transfer during the industrial freezing and tempering of cheese.

Digital technologies to assess yoghurt quality traits and consumers acceptability.

BACKGROUND: Sensory biometrics provide advantages for consumer tasting by quantifying physiological changes and the emotional response from participants, removing variability associated with self-reported responses. The present study aimed to measure consumers' emotional and physiological responses towards different commercial yoghurts, including dairy and plant-based yoghurts. The physiochemical properties of these products were also measured and linked with consumer responses. RESULTS: Six samples (Control, Coconut, Soy, Berry, Cookies and Drinkable) were evaluated for overall liking by n = 62 consumers using a nine-point hedonic scale. Videos from participants were recorded using the Bio-Sensory application during tasting to assess emotions and heart rate. Physicochemical parameters Brix, pH, density, color (L, a and b), firmness and near-infrared (NIR) spectroscopy were also measured. Principal component analysis and a correlation matrix were used to assess relationships between the measured parameters. Heart rate was positively related to firmness, yaw head movement and overall liking, which were further associated with the Cookies sample. Two machine learning regression models were developed using (i) NIR absorbance values as inputs to predict the physicochemical parameters (Model 1) and (ii) the outputs from Model 1 as inputs to predict consumers overall liking (Model 2). Both models presented very high accuracy (Model 1: R = 0.98; Model 2: R = 0.99). CONCLUSION: The presented methods were shown to be highly accurate and reliable with respect to their potential use by the industry to assess yoghurt quality traits and acceptability. © 2022 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

New Insights into Cheese Microstructure.

Microscopy is often used to assist the development of cheese products, but manufacturers can benefit from a much broader application of these techniques to assess structure formation during processing and structural changes during storage. Microscopy can be used to benchmark processes, optimize process variables, and identify critical control points for process control. Microscopy can also assist the reverse engineering of desired product properties and help troubleshoot production problems to improve cheese quality. This approach can be extended using quantitative analysis, which enables further comparisons between structural features and functional measures used within industry, such as cheese meltability, shreddability, and stretchability, potentially allowing prediction and control of these properties. This review covers advances in the analysis of cheese microstructure, including new techniques, and outlines how these can be applied to understand and improve cheese manufacture.

Plant and Dairy-Based Yogurts: A Comparison of Consumer Sensory Acceptability Linked to Textural Analysis.

Yogurt, readily available in plant and dairy-based formulations, is widely consumed and linked with health benefits. This research is aimed to understand the sensory and textural spectrum of commercially available dairy and plant-based yogurts. In a preliminary study, qualitative focus group discussions (4 groups; n = 32) were used to determine perceptions of 28 dairy and plant-based yogurts, identifying positive consumer perceptions of plant-based yogurts. A smaller subset of five spoonable and one drinkable yogurts-(Reference, Soy, Coconut, Cookies, Berry, and Drinkable) was subsequently selected for rheological and structural measurements, showing wide variations in the microstructure and rheology of selected yogurt samples. A quantitative blind sensory tasting (n = 117) showed varying yogurt acceptability, with Berry being the least-liked and Cookies being the most-liked yogurt, in terms of overall liking. The multi-factor analysis confirmed that compositional and textural elements, including protein content, gel firmness, and consistency coefficient, displayed a positive relationship with overall liking. In contrast, fat, sugar, and calories were negatively correlated to the overall liking. This research showed that texture and other compositional factors are significant determinants of the consumer acceptability of yogurt products and are essential properties to consider in product development.

Differences in Hedonic Responses, Facial Expressions and Self-Reported Emotions of Consumers Using Commercial Yogurts: A Cross-Cultural Study.

Hedonic scale testing is a well-accepted methodology for assessing consumer perceptions but is compromised by variation in voluntary responses between cultures. Check-all-that-apply (CATA) methods using emotion terms or emojis and facial expression recognition (FER) are emerging as more powerful tools for consumer sensory testing as they may offer improved assessment of voluntary and involuntary responses, respectively. Therefore, this experiment compared traditional hedonic scale responses for overall liking to (1) CATA emotions, (2) CATA emojis and (3) FER. The experiment measured voluntary and involuntary responses from 62 participants of Asian (53%) versus Western (47%) origin, who consumed six divergent yogurt formulations (Greek, drinkable, soy, coconut, berry, cookies). The hedonic scales could discriminate between yogurt formulations but could not distinguish between responses across the cultural groups. Aversive responses to formulations were the easiest to characterize for all methods; the hedonic scale was the only method that could not characterize differences in cultural preferences, with CATA emojis displaying the highest level of discrimination. In conclusion, CATA methods, particularly the use of emojis, showed improved characterization of cross-cultural preferences of yogurt formulations compared to hedonic scales and FER.

The effect of pH on the fat and protein within cream cheese and their influence on textural and rheological properties.

The effect of variation in acid gel pH during cream cheese production was investigated. The gel microstructure was denser and cheese texture firmer, as the pH decreased from pH 5.0 to pH 4.3, despite the viscoelasticity of these gels remaining similar during heating. Protein hydration and secondary structure appeared to be key factors affecting both cheese microstructure and properties. Proteins within the matrix appeared to swell at pH 5.0, leading to a larger corpuscular structure; greater ß-turn structure was also observed by synchrotron-Fourier transform infrared (S-FTIR) microspectroscopy and the cheese was softer. A decrease in pH led to a denser microstructure with increased aggregated ß-sheet structure and a firmer cheese. The higher whey protein loss at low pH likely contributed to increased cheese hardness. In summary, controlling the pH of acid gel is important, as this parameter affects proteins in the cheese, their secondary structure and the resulting cream cheese.

Cytochrome P450-mediated N-demethylation of noscapine by whole-cell biotransformation: process limitations and strategies for optimisation.

Cytochrome P450 enzymes catalyse reactions of significant industrial interest but are underutilised in large-scale bioprocesses due to enzyme stability, cofactor requirements and the poor aqueous solubility and microbial toxicity of typical substrates and products. In this work, we investigate the potential for preparative-scale N-demethylation of the opium poppy alkaloid noscapine by a P450BM3 (CYP102A1) mutant enzyme in a whole-cell biotransformation system. We identify and address several common limitations of whole-cell P450 biotransformations using this model N-demethylation process. Mass transfer into Escherichia coli cells was found to be a major limitation of biotransformation rate and an alternative Gram-positive expression host Bacillus megaterium provided a 25-fold improvement in specific initial rate. Two methods were investigated to address poor substrate solubility. First, a biphasic biotransformation system was developed by systematic selection of potentially biocompatible solvents and in silico solubility modelling using Hansen solubility parameters. The best-performing biphasic system gave a 2.3-fold improvement in final product titre compared to a single-phase system but had slower initial rates of biotransformation due to low substrate concentration in the aqueous phase. The second strategy aimed to improve aqueous substrate solubility using cyclodextrin and hydrophilic polymers. This approach provided a fivefold improvement in initial biotransformation rate and allowed a sixfold increase in final product concentration. Enzyme stability and cell viability were identified as the next parameters requiring optimisation to improve productivity. The approaches used are also applicable to the development of other pharmaceutical P450-mediated biotransformations.

High-Efficiency Biocatalytic Conversion of Thebaine to Codeine.

An enzymatic biosynthesis approach is described for codeine, the most widely used medicinal opiate, providing a more environmentally sustainable alternative to current chemical conversion, with yields and productivity compatible with industrial production. Escherichia coli strains were engineered to express key enzymes from poppy, including the recently discovered neopinone isomerase, producing codeine from thebaine. We show that compartmentalization of these enzymes in different cells is an effective strategy that allows active spatial and temporal control of reactions, increasing yield and volumetric productivity and reducing byproduct generation. Codeine is produced at a yield of 64% and a volumetric productivity of 0.19 g/(L·h), providing the basis for an industrially applicable aqueous whole-cell biotransformation process. This approach could be used to redirect thebaine-rich feedstocks arising from the U.S. reduction of opioid manufacturing quotas or applied to enable total biosynthesis and may have broader applicability to other medicinal plant compounds.

Structural-rheological characteristics of Chaplin E peptide at the air/water interface; a comparison with ß-lactoglobulin and ß-casein.

The Chaplin E peptide is a surface-active agent that can adsorb to the air/water interface and form interfacial films that display distinct interfacial properties as a function of pH. The ~2 nm thick homogeneous Chaplin E film formed under acidic conditions contains ordered structures that give a high dilatational elasticity. In contrast, the heterogeneous film formed under basic conditions contained fibrils resulting in a rough ~17 nm thick film with predominantly viscoelastic properties, probably due to the reduced intermolecular interactions. These fibrils were also susceptible to breakage, fragmenting into shorter fibrils, which gave a greater elasticity. The fibrils also lead to a greater shear viscosity compared to the ordered structures aligned within the Chaplin E film at pH 3.0. A higher stability was observed for the foam formed by the Chaplin E compared to the foam formed by ß-lactoglobulin, consistent with the greater rheological properties observed for the Chaplin E film at the interface. Our findings suggest that Chaplin E has potential to provide long time stability to dispersions in food, consumer goods or pharmaceutical applications, forming films with greater rheological properties and at least similar thickness to those formed by other surface-active proteins such as ß-casein and ß-lactoglobulin.

Exciton-Driven Chemical Sensors Based on Excitation-Dependent Photoluminescent Two-Dimensional SnS.

Excitation wavelength-dependent photoluminescence (PL) in two-dimensional (2D) transition-metal chalcogenides enables a strong excitonic interaction for high-performance chemical and biological sensing applications. In this work, we explore the possible candidates in the domain of post-transition-metal chalcogenides. Few-layered 2D p-type tin monosulfide (SnS) nanoflakes with submicrometer lateral dimensions are synthesized from the liquid phase exfoliation of bulk crystals. Excitation wavelength-dependent PL is found, and the excitonic radiative lifetime is more than one order enhanced compared to that of the bulk counterpart because of the quantum confinement effect. Paramagnetic NO2 gas is selected as a representative to investigate the exciton-driven chemical-sensing properties of 2D SnS. Physisorption of NO2 results in the formation of dipoles on the surface of 2D SnS, causing the redistribution of photoexcited charges in the body and therefore modifying PL properties. For practical sensing applications, 2D SnS is integrated into a resistive transducing platform. Under light irradiation, the sensor exhibits excellent sensitivity and selectivity to NO2 at a relatively low operating temperature of 60 °C. The limit of detection is 17 parts per billion (ppb), which is significantly improved over other previously reported 2D p-type semiconductor-based NO2 sensors.

Production of metabolites of the anti-cancer drug noscapine using a P450BM3 mutant library.

Cytochrome P450 enzymes are a promising tool for the late-stage diversification of lead drug candidates and can provide an alternative route to structural modifications that are difficult to achieve with synthetic chemistry. In this study, a library of P450BM3 mutants was produced using site-directed mutagenesis and the enzymes screened for metabolism of the opium poppy alkaloid noscapine, a drug with anticancer activity. Of the 18 enzyme mutants screened, 12 showed an ability to metabolise noscapine that was not present in the wild-type enzyme. Five noscapine metabolites were detected by LC-MS/MS, with the major metabolite for all mutants being N-demethylated noscapine. The highest observed regioselectivity for N-demethylation was 88%. Two hydroxylated metabolites, a catechol and two C-C cleavage products were also detected. P450-mediated production of hydroxylated and N-demethylated noscapine structures may be useful for the development of noscapine analogues with improved biological activity. The variation in substrate turnover, coupling efficiency and product distribution between the active mutants was considered alongside in silico docking experiments to gain insight into structural and functional effects of the introduced mutations. Selected mutants were identified as targets for further mutagenesis to improve activity and when coupled with an optimised process may provide a route for the preparative-scale production of noscapine metabolites.

Opportunities and Challenges in DNA-Hybrid Nanomaterials.

Nature has inspired the development of many life-like materials. Although still simplistic, key biological functionalities have been incorporated, enabling a wide variety of applications. DNA-based systems, in particular, show high promise due to their ability to merge specific Watson-Crick base pairing with unique properties that are also programmable, scalable, or dynamic. By combining the fields of DNA-based covalent polymers, DNA origami, and DNA-functionalized supramolecular polymers, new frontiers in next-generation DNA-based hybrid materials that can outperform current bioartificial systems will be realized. Many challenges must still be overcome before this emerging technology can be materialized.

The characterisation of Mozzarella cheese microstructure using high resolution synchrotron transmission and ATR-FTIR microspectroscopy.

Synchrotron Fourier transform infrared (S-FTIR) microspectroscopy allows the label-free examination of material microstructure but has not been widely applied to dairy products. Here, S-FTIR microspectroscopy was applied to observe the microstructure of Mozzarella cheese and assess the protein and lipid distribution within individual cheese blocks. High lipid and high protein areas were identified in transmission and attenuated total reflectance (ATR) analysis modes and the secondary structures of cheese proteins determined. Hierarchical cluster analysis and principal component analysis identified variation in random coil, water content, lipid carbonyl and methylene stretching across the sampled area. Similar spectral features were obtained in both analysis modes; spatial resolution was higher with ATR and small differences were noted, potentially as a result of differences in sample preparation. S-FTIR is a useful microscopy tool that can detect structural alterations that may affect product properties and may assist reverse engineering of a range of dairy products.

Computational Modelling of Large Scale Phage Production Using a Two-Stage Batch Process.

Cost effective and scalable methods for phage production are required to meet an increasing demand for phage, as an alternative to antibiotics. Computational models can assist the optimization of such production processes. A model is developed here that can simulate the dynamics of phage population growth and production in a two-stage, self-cycling process. The model incorporates variable infection parameters as a function of bacterial growth rate and employs ordinary differential equations, allowing application to a setup with multiple reactors. The model provides simple cost estimates as a function of key operational parameters including substrate concentration, feed volume and cycling times. For the phage and bacteria pairing examined, costs and productivity varied by three orders of magnitude, with the lowest cost found to be most sensitive to the influent substrate concentration and low level setting in the first vessel. An example case study of phage production is also presented, showing how parameter values affect the production costs and estimating production times. The approach presented is flexible and can be used to optimize phage production at laboratory or factory scale by minimizing costs or maximizing productivity.

Computational Modeling of Bacteriophage Production for Process Optimization.

Computational models can be used to optimize the production of bacteriophages. Here a model is described for production in a two-stage self-cycling process. Theoretical and practical considerations for modeling bacteriophage production are first introduced. The key experimental protocols required to estimate key kinetic parameters for the model, including determining variable infection rates as a function of substrate concentration, are described. ppSim is an open-source R-script that can simulate bacteriophage production to optimize productivity or minimize costs. The steps included to run the simulation using the experimentally determined infection parameters are described. An example is also presented, where a level sensor and cycle time are optimized to maximize bacteriophage productivity in two sequential 1-L bioreactors, resulting in a production rate of 4.46 × 1010 bacteriophage particles/hour. The protocols and programs described here will allow users to potentially optimize production of their own bacteriophage-bacteria pairing by effectively applying bacteriophage modeling.