Stanislav Sokolenko

Co-expression vs. co-infection using baculovirus expression vectors in insect cell culture: Benefits and drawbacks

Abstract The baculovirus expression vector system (BEVS) is a versatile and powerful platform for protein expression in insect cells. With the ability to approach similar post-translational modifications as in mammalian cells, the BEVS offers a number of advantages including high levels of expression as well as an inherent safety during manufacture and of the final product. Many BEVS products include proteins and protein complexes that require expression from more than one gene. This review examines the expression strategies that have been used to this end and focuses on the distinguishing features between those that make use of single polycistronic baculovirus (co-expression) and those that use multiple monocistronic baculoviruses (co-infection). Three major areas in which researchers have been able to take advantage of co-expression/co-infection are addressed, including compound structure-function studies, insect cell functionality augmentation, and VLP production. The core of the review discusses the parameters of interest for co-infection and co-expression with time of infection (TOI) and multiplicity of infection (MOI) highlighted for the former and the choice of promoter for the latter. In addition, an overview of modeling approaches is presented, with a suggested trajectory for future exploration. The review concludes with an examination of the gaps that still remain in co-expression/co-infection knowledge and practice.

Metabolomic Analysis of Human Fecal Microbiota: A Comparison of Feces-Derived Communities and Defined Mixed Communities

The extensive impact of the human gut microbiota on its human host calls for a need to understand the types of communication that occur among the bacteria and their host. A metabolomics approach can provide a snapshot of the microbe-microbe interactions occurring as well as variations in the microbes from different hosts. In this study, metabolite profiles from an anaerobic continuous stirred-tank reactors (CSTR) system supporting the growth of several consortia of bacteria representative of the human gut were established and compared. Cell-free supernatant samples were analyzed by 1D (1)H nuclear magnetic resonance (NMR) spectroscopy, producing spectra representative of the metabolic activity of a particular community at a given time. Using targeted profiling, specific metabolites were identified and quantified on the basis of NMR analyses. Metabolite profiles discriminated each bacterial community examined, demonstrating that there are significant differences in the microbiota metabolome between each cultured community. We also found unique compounds that were identifying features of individual bacterial consortia. These findings are important because they demonstrate that metabolite profiles of gut microbial ecosystems can be constructed by targeted profiling of NMR spectra. Moreover, examination of these profiles sheds light on the type of microbes present in the gut and their metabolic interactions.

Understanding the variability of compound quantification from targeted profiling metabolomics of 1D- 1 H-NMR spectra in synthetic mixtures and urine with additional insights on choice of pulse sequences and robotic sampling

The growing use of ‘targeted profiling’ approaches for the deconvolution of 1D-1H-NMR spectra by comparison to a pure compound library has created a need for an in-depth characterization of quantification variability that is beyond what is currently available in the literature. In this study, we explore the underlying source of quantification variability (tube insertion, spectra acquisition, and profiling) as well as a number of other factors, such as temporal consistency of repeated NMR scans, human consistency in repeated profiles, and human versus machine sampling. We also look at the effect of different pulse sequences on the differences between acquired spectra and the peak reference library. Two sample types were considered for this work—a synthetic five compound mixture as well as human urine. The result is a comprehensive examination of 1D-1H-NMR quantification error. Our investigation into variability sources revealed that apart from profiling, sample insertion and/or shimming can play a significant role in final quantification, a finding that is equally applicable to all integration-based methods of quantification. Both sources of error were also found to have temporal relationships, with bias identified as a function of both scan and profiling order, reinforcing the need for randomization in scanning and profiling. As well as presenting a practical estimate of variability in human urine samples, we have uncovered a considerable amount of complexity in underlying NMR variability that will hopefully serve as impetus for future exploration in this area.

Treating cell culture media with UV irradiation against adventitious agents: Minimal impact on CHO performance

Sterility of cell culture media is an important concern in biotherapeutic processing. In large scale biotherapeutic production, a unit contamination of cell culture media can have costly effects. Ultraviolet (UV) irradiation is a sterilization method effective against bacteria and viruses while being non‐thermal and non‐adulterating in its mechanism of action. This makes UV irradiation attractive for use in sterilization of cell culture media. The objective of this study was to evaluate the effect of UV irradiation of cell culture media in terms of chemical composition and the ability to grow cell cultures in the treated media. The results showed that UV irradiation of commercial cell culture media at relevant disinfection doses impacted the chemical composition of the media with respect to several carboxylic acids, and to a minimal extent, amino acids. The cumulative effect of these changes, however, did not negatively influence the ability to culture Chinese Hamster Ovary cells, as evaluated by cell viability, growth rate, and protein titer measurements in simple batch growth compared with the same cells cultured in control media exposed to visible light.

Construction and analysis of a genetically tuneable lytic phage display system

The Bacteriophage λ capsid protein gpD has been used extensively for fusion polypeptides that can be expressed from plasmids in Escherichia coli and remain soluble. In this study, a genetically controlled dual expression system for the display of enhanced green fluorescent protein (eGFP) was developed and characterized. Wild-type D protein (gpD) expression is encoded by λ Dam15 infecting phage particles, which can only produce a functional gpD protein when translated in amber suppressor strains of E. coli in the absence of complementing gpD from a plasmid. However, the isogenic suppressors vary dramatically in their ability to restore functional packaging to λDam15, imparting the first dimension of decorative control. In combination, the D-fusion protein, gpD::eGFP, was supplied in trans from a multicopy temperature-inducible expression plasmid, influencing D::eGFP expression and hence the availability of gpD::eGFP to complement for the Dam15 mutation and decorate viable phage progeny. Despite being the worst suppressor, maximal incorporation of gpD::eGFP into the λDam15 phage capsid was imparted by the SupD strain, conferring a gpDQ68S substitution, induced for plasmid expression of pD::eGFP. Differences in size, fluorescence and absolute protein decoration between phage preparations could be achieved by varying the temperature of and the suppressor host carrying the pD::eGFP plasmid. The effective preparation with these two variables provides a simple means by which to manage fusion decoration on the surface of phage λ.

Disruption of the Reductive 1,3-Propanediol Pathway Triggers Production of 1,2-Propanediol for Sustained Glycerol Fermentation by Clostridium pasteurianum

ABSTRACT Crude glycerol, the major by-product of biodiesel production, is an attractive bioprocessing feedstock owing to its abundance, low cost, and high degree of reduction. In line with the advent of the biodiesel industry, Clostridium pasteurianum has gained prominence as a result of its unique capacity to convert waste glycerol into n-butanol, a high-energy biofuel. However, no efforts have been directed at abolishing the production of 1,3-propanediol (1,3-PDO), the chief competing product of C. pasteurianum glycerol fermentation. Here, we report rational metabolic engineering of C. pasteurianum for enhanced n-butanol production through inactivation of the gene encoding 1,3-PDO dehydrogenase (dhaT). In spite of current models of anaerobic glycerol dissimilation, culture growth and glycerol utilization were unaffected in the dhaT disruption mutant (dhaT::Ll.LtrB). Metabolite characterization of the dhaT::Ll.LtrB mutant revealed an 83% decrease in 1,3-PDO production, encompassing the lowest C. pasteurianum 1,3-PDO titer reported to date (0.58 g liter−1). With 1,3-PDO formation nearly abolished, glycerol was converted almost exclusively to n-butanol (8.6 g liter−1), yielding a high n-butanol selectivity of 0.83 g n-butanol g−1 of solvents compared to 0.51 g n-butanol g−1 of solvents for the wild-type strain. Unexpectedly, high-performance liquid chromatography (HPLC) analysis of dhaT::Ll.LtrB mutant culture supernatants identified a metabolite peak consistent with 1,2-propanediol (1,2-PDO), which was confirmed by nuclear magnetic resonance (NMR). Based on these findings, we propose a new model for glycerol dissimilation by C. pasteurianum, whereby the production of 1,3-PDO by the wild-type strain and low levels of both 1,3-PDO and 1,2-PDO by the engineered mutant balance the reducing equivalents generated during cell mass synthesis from glycerol. IMPORTANCE Organisms from the genus Clostridium are perhaps the most notable native cellular factories, owing to their vast substrate utilization range and equally diverse variety of metabolites produced. The ability of C. pasteurianum to sustain redox balance and glycerol fermentation despite inactivation of the 1,3-PDO pathway is a testament to the exceptional metabolic flexibility exhibited by clostridia. Moreover, identification of a previously unknown 1,2-PDO-formation pathway, as detailed herein, provides a deeper understanding of fermentative glycerol utilization in clostridia and will inform future metabolic engineering endeavors involving C. pasteurianum. To our knowledge, the C. pasteurianum dhaT disruption mutant derived in this study is the only organism that produces both 1,2- and 1,3-PDOs. Most importantly, the engineered strain provides an excellent platform for highly selective production of n-butanol from waste glycerol.

Rapid and cost-effective baculovirus sample preparation method as a viable alternative to conventional preparation for quantitative real-time PCR

The increasing use of the baculovirus expression vector system (BEVS) has generated significant interest into techniques for quantifying baculovirus stocks. One method involves the use of quantitative real-time polymerase chain reaction (PCR). This study investigated simplifying baculovirus sample preparation for quantitative Real Time PCR to provide an alternative to current kit-based preparation methods. To achieve this goal, combinations of freeze/thaw cycles and Triton X-100 treatment were investigated. A treatment with only Triton X-100 was found to be sufficient to provide a simple, rapid and cheap alternative to kit-based preparation methods. This study also examined other factors such as primer choice to further examine the process of baculovirus quantitation by qPCR.

An omics approach to rational feed: Enhancing growth in CHO cultures with NMR metabolomics and 2D-DIGE proteomics.

Expression of recombinant proteins exerts stress on cell culture systems, affecting the expression of endogenous proteins, and contributing to the depletion of nutrients and accumulation of waste metabolites. In this work, 2D-DIGE proteomics was employed to analyze differential expression of proteins following stable transfection of a Chinese Hamster Ovary (CHO) cell line to constitutively express a heavy-chain monoclonal antibody. Thirty-four proteins of significant differential expression were identified and cross-referenced with cellular functions and metabolic pathways to identify points of cell stress. Subsequently, 1D-(1)H NMR metabolomics experiments analyzed cultures to observe nutrient depletion and waste metabolite accumulations to further examine these cell stresses and pathways. From among fifty metabolites tracked in time-course, eight were observed to be completely depleted from the production media, including: glucose, glutamine, proline, serine, cystine, asparagine, choline, and hypoxanthine, while twenty-three excreted metabolites were also observed to accumulate. The differentially expressed proteins, as well as the nutrient depletion and accumulation of these metabolites corresponded with upregulated pathways and cell systems related to anaplerotic TCA-replenishment, NADH/NADPH replenishment, tetrahydrofolate cycle C1 cofactor conversions, limitations to lipid synthesis, and redox modulation. A nutrient cocktail was assembled to improve the growth medium and alleviate these cell stresses to achieve a ∼75% improvement to peak cell densities.

Graphical analysis of flow cytometer data for characterizing controlled fluorescent protein display on λ phage

As native virus particles typically cannot be resolved using a flow cytometer, the general practice is to use fluorescent dyes to label the particles. In this work, an attempt was made to use a common commercial flow cytometer to characterize a phage display strategy that allows for controlled levels of protein display, in this case, eGFP. To achieve this characterization, a number of data processing steps were needed to ensure that the observed phenomena were indeed capturing differences in the phages produced. Phage display of eGFP resulted in altered side scatter and fluorescence profile, and sub‐populations could be identified within what would otherwise be considered uniform populations. Surprisingly, this study has found that side scatter may be used in the future to characterize the display of nonfluorescent proteins.

A correction method for systematic error in 1 H-NMR time-course data validated through stochastic cell culture simulation

BackgroundThe growing ubiquity of metabolomic techniques has facilitated high frequency time-course data collection for an increasing number of applications. While the concentration trends of individual metabolites can be modeled with common curve fitting techniques, a more accurate representation of the data needs to consider effects that act on more than one metabolite in a given sample. To this end, we present a simple algorithm that uses nonparametric smoothing carried out on all observed metabolites at once to identify and correct systematic error from dilution effects. In addition, we develop a simulation of metabolite concentration time-course trends to supplement available data and explore algorithm performance. Although we focus on nuclear magnetic resonance (NMR) analysis in the context of cell culture, a number of possible extensions are discussed.ResultsRealistic metabolic data was successfully simulated using a 4-step process. Starting with a set of metabolite concentration time-courses from a metabolomic experiment, each time-course was classified as either increasing, decreasing, concave, or approximately constant. Trend shapes were simulated from generic functions corresponding to each classification. The resulting shapes were then scaled to simulated compound concentrations. Finally, the scaled trends were perturbed using a combination of random and systematic errors. To detect systematic errors, a nonparametric fit was applied to each trend and percent deviations calculated at every timepoint. Systematic errors could be identified at time-points where the median percent deviation exceeded a threshold value, determined by the choice of smoothing model and the number of observed trends. Regardless of model, increasing the number of observations over a time-course resulted in more accurate error estimates, although the improvement was not particularly large between 10 and 20 samples per trend. The presented algorithm was able to identify systematic errors as small as 2.5 % under a wide range of conditions.ConclusionBoth the simulation framework and error correction method represent examples of time-course analysis that can be applied to further developments in 1H-NMR methodology and the more general application of quantitative metabolomics.