We describe scalable and cost-efficient production of full length, His-tagged SARS-CoV-2 spike glycoprotein trimer by CHO cells that can be used to detect SARS-CoV-2 antibodies in patient sera at high specificity and sensitivity. Transient production of spike in both HEK and CHO cells mediated by PEI was increased significantly (up to 10.9-fold) by a reduction in culture temperature to 32ºC to permit extended duration cultures. Based on these data GS-CHO pools stably producing spike trimer under the control of a strong synthetic promoter were cultured in hypothermic conditions with combinations of bioactive small molecules to increase yield of purified spike product 4.9-fold to 53 mg/L. Purification of recombinant spike by Ni-chelate affinity chromatography initially yielded a variety of co-eluting protein impurities identified as host cell derived by mass spectrometry, which were separated from spike trimer using a modified imidazole gradient elution. Purified CHO spike trimer antigen was used in ELISA format to detect IgG antibodies against SARS-CoV-2 in sera from patient cohorts previously tested for viral infection by PCR, including those who had displayed COVID-19 symptoms. The antibody assay, validated to ISO 15189 Medical Laboratories standards, exhibited a specificity of 100% and sensitivity of 92.3%. Our data show that CHO cells are a suitable host for the production of larger quantities of recombinant SARS-CoV-2 trimer which can be used as antigen for mass serological testing.

Lactic acid producing bacteria are important in many fermentations, such as the production of biobased plastics. Insight in the competitive advantage of lactic acid bacteria over other fermentative bacteria in a mixed culture enables ecology-based process design and can aid the development of sustainable and energy-efficient bioprocesses. Here we demonstrate the enrichment of lactic acid bacteria in a controlled sequencing batch bioreactor environment using a glucose based medium supplemented with peptides and B vitamins. A mineral medium enrichment operated in parallel was dominated by Ethanoligenens species and fermented glucose to acetate, butyrate and hydrogen. The complex medium enrichment was populated by Lactococcus, Lactobacillus and Megasphaera species and showed a product spectrum of acetate, ethanol, propionate, butyrate and valerate. An intermediate peak of lactate was observed, showing the simultaneous production and consumption of lactate, which is of concern for lactic acid production purposes. This study underlines that the competitive advantage for lactic acid producing bacteria primarily lies in their ability to attain a high biomass specific uptake rate of glucose, which was two times higher for the complex medium enrichment when compared to the mineral medium enrichment. The competitive advantage of lactic acid production in rich media can be explained using a resource allocation theory for microbial growth processes.

Chemical group-transfer reactions by hydrolytic enzymes have considerable importance in biocatalytic synthesis and are exploited broadly in commercial-scale chemical production. Mechanistically, these reactions have in common the involvement of a covalent enzyme intermediate which is formed upon enzyme reaction with the donor substrate and is subsequently intercepted by a suitable acceptor. Here, we studied the glycosylation of glycerol from sucrose by sucrose phosphorylase (SucP) to clarify a peculiar, yet generally important characteristic of this reaction: partitioning between glycosylation of glycerol and hydrolysis depends on the type and the concentration of the donor substrate used (here: sucrose, α-D-glucose 1-phosphate (G1P)). We develop a kinetic framework to analyze the effect and provide evidence that, when G1P is used as donor substrate, hydrolysis occurs not only from the β-glucosyl-enzyme intermediate (E-Glc), but additionally from a noncovalent complex of E-Glc and substrate which unlike E-Glc is unreactive to glycerol. Depending on the relative rates of hydrolysis of free and substrate-bound E-Glc, inhibition (Leuconostoc mesenteroides SucP) or apparent activation (Bifidobacterium adolescentis SucP) is observed at high donor substrate concentration. Using G1P at a concentration excluding the substrate-bound E-Glc, the product ratio changes to a value consistent with reaction exclusively through E-Glc, independent of the donor substrate used. Collectively, these results give explanation for a kinetic behavior of SucP not previously accounted for, provide essential basis for design and optimization of the synthetic reaction, and establish a theoretical framework for the analysis of kinetically analogous group transfer reactions by hydrolytic enzymes.

The mechanical properties of biofilms can be used to predict biofilm deformation, for example under fluid flow. We used magnetic tweezers to spatially map the compliance of Pseudomonas aeruginosa biofilms at the micron scale, then used modeling to assess its effects on biofilm deformation. Biofilms were grown in capillary flow cells with Reynolds numbers (Re) ranging 0.28 to 13.9, bulk dissolved oxygen (DO) concentrations from 1 mg/L to 8 mg/L, and bulk calcium ion (Ca2+) concentrations of 0 and 100 mg CaCl2/L. Higher Re numbers resulted in more uniform biofilm morphologies. The biofilm was stiffer at the center of the flow cell than near the walls. Lower bulk DO led to more stratified biofilms. Higher Ca2+ led to increased stiffness and more uniform mechanical properties. Using the experimental mechanical properties, fluid-structure interaction models predicted up to 64% greater deformations for heterogeneous biofilms, compared to a homogeneous biofilms with the same average properties. However, the error depended on the biofilm morphology and flow regime. Our results show significant spatial mechanical variability exists at the micron scale, and that this variability can potentially affect biofilm deformation. The average mechanical properties, provided in many studies, should be used with caution when predicting biofilm deformation.

Biofilms commonly develop in flowing aqueous environments, where the flow causes the biofilm to deform. Because biofilm deformation affects the flow regime, and because biofilms behave as complex heterogeneous viscoelastic materials, few models are able to predict biofilm deformation. In this study, a phase field continuum model coupled with the Oldroyd-B constitutive equation was developed and used to simulate biofilm deformation. The accuracy of the model was evaluated using two types of biofilms: a synthetic biofilm, made from alginate mixed with bacterial cells, and a Pseudomonas aeruginosa biofilm. Shear rheometry was used to experimentally determine the mechanical parameters for each biofilm, as inputs for the model. Biofilm deformation under fluid flow was monitored experimentally using optical coherence tomography. The fit between the experimental and modeling geometries after fluid-driven deformation was very good, with relative errors of 12.8% for synthetic biofilm and 22.2% for homogenized P. aeruginosa biofilm. This is the first demonstration of the effectiveness of a viscoelastic phase field biofilm model. This model provides an important tool for predicting biofilm viscoelastic deformation. It also can benefit the design and control of biofilms in engineering systems.

β-carotene is a natural pigment and health-promoting metabolite, and has been widely used in the nutraceutical, feed and cosmetic industries. Here, we engineered a GRAS yeast Saccharomyces cerevisiae to produce β-carotene from xylose, the second most abundant and inedible sugar component of lignocellulose biomass. Specifically, a β-carotene biosynthetic pathway containing crtYB, crtI and crtE from Xanthophyllomyces dendrorhous were introduced into a xylose-fermenting S. cerevisiae. The resulting strain produced β-carotene from xylose at a titer three-fold higher than from glucose. Interestingly, overexpression of tHMG1, which has been reported as a critical genetic perturbation to enhance metabolic fluxes in the mevalonate (MVA) pathway and β-carotene production in yeast when glucose is used, did not further improve the production of β-carotene from xylose. Through fermentation profiling, metabolites analysis and transcriptional studies, we found the advantages of using xylose as a carbon source instead of glucose for β-carotene production to be a more respiratory feature of xylose consumption, a larger cytosolic acetyl-CoA pool, and up-regulated expression levels of rate-limiting genes in the β-carotene producing pathway, including ACS1 and HMG1. As a result, 772.81 mg/L of β-carotene was obtained in a fed-batch bioreactor culture with xylose feeding. Considering the inevitable production of xylose at large scales when cellulosic biomass-based bioeconomy is implemented, our results suggest xylose utilization is a promising strategy for overproduction of carotenoids and other isoprenoids in engineered S. cerevisiae.

Process analytical technology (PAT) has been defined by the Food and Drug Administration (FDA) as a system for designing, analyzing, and controlling manufacturing through timely measurements to ensure final product quality. Based on quality-by-design (QbD) principles, real-time or near-real-time data monitoring is essential for timely control of critical quality attributes (CQAs) to keep the process in a state of control. To facilitate next-generation continuous bioprocessing, deployment of PAT tools for real-time monitoring is integral for process understanding and control. Real-time monitoring and control of CQAs is essential to keep the process within the design space and align with the guiding principles of QbD. The contents of this manuscript are pertinent to the online/at-line monitoring of upstream titer and downstream product quality with timely process control. We demonstrated that a UPLC system interfaced with a process sample manager (UPLC-PSM) can be utilized to measure titer and CQAs directly from bioreactors and downstream unit operations, respectively. We established online titer measurements from fed-batch and perfusion-based alternating tangential flow (ATF) bioreactors as well as product quality assessments of downstream operations for real-time peak collection. This integrated, fully automated system for online data monitoring with feedback control is designed to achieve desired product quality.

Taxadien-5α-hydroxylase and taxadien-5α-ol O-acetyltransferase catalyse the oxidation of taxadiene to taxadien-5α-ol and subsequent acetylation to taxadien-5α-yl-acetate in the biosynthesis of the blockbuster anti-cancer drug, paclitaxel (Taxol). Despite decades of research, the promiscuous and multispecific CYP725A4 enzyme remains a major bottleneck in microbial biosynthetic pathway development. In this study, an interdisciplinary approach was applied for the construction and optimisation of the early pathway in Saccharomyces cerevisiae, across a range of bioreactor scales. High-throughput microscale optimisation enhanced total oxygenated taxane titre to 39.0±5.7 mg/L and total taxane product titres were comparable at micro and mini-bioreactor scale at 95.4±18.0 and 98.9 mg/L, respectively. The introduction of pH control successfully mitigated a reduction of oxygenated taxane production, enhancing the potential taxadien-5α-ol isomer titre to 19.2 mg/L, comparable to the 23.8±3.7 mg/L achieved at microscale. A combination of bioprocess optimisation and increased GC-MS resolution at 1L bioreactor scale facilitated taxadien-5α-yl-acetate detection with a final titre of 3.7 mg/L. Total oxygenated taxane titres were improved 2.7-fold at this scale to 78 mg/L, the highest reported titre in yeast. Critical parameters affecting the productivity of the engineered strain were identified across a range of scales, providing a foundation for the development of robust integrated bioprocess control systems.

SARS-CoV-2 is an RNA coronavirus that causes severe acute pneumonia, also known as COVID 19 disease. The World Health Organization declared the COVID-19 outbreak in January 2020 and a pandemic 2 months later. Serological assays are valuable tools to study virus spread among the population and, importantly, to identify individuals that were already infected and would be potentially immune to a virus re-infection. SARS-CoV-2 Spike protein and its Receptor Binding Domain (RBD) are the antigens with higher potential to develop SARS-CoV-2 serological assays. Moreover, structural studies of these antigens are key to understand the molecular basis for Spike interaction with angiotensin converting enzyme 2 receptor, hopefully enabling the discovery and development of COVID-19 therapeutics. Thus, it is urgent that significant amounts of this protein became available at the highest quality. In this work we evaluated the impact of different and scalable bioprocessing approaches on Spike and RBD production yields and, more importantly, in these antigens’ quality attributes. Using negative and positive sera collected from human donors, we show an excellent performance of the produced antigens, assessed in serologic ELISA tests, as denoted by the high specificity and sensitivity of the test. We have shown that, despite of the human cell host and the cell culture strategy used, for production scales ranging from 1 L to up to 30 L, final yields of approx. 2 mg and 90 mg per liter of purified bulk for Spike and RBD, respectively, could be obtained. To the best of our knowledge these are the highest yields for RBD production reported to date. An in-depth characterization of SARS CoV-2 Spike and RBD proteins was also performed, namely the antigens oligomeric state, glycosylation profiles and thermal stability during storage. The correlation of these quality attributes with ELISA performance show equivalent reactivity to SARS CoV 2 positive serum, for all Spike and RBD produced, and for all the storage conditions tested. Overall, we provide herein straightforward protocols to produce high-quality SARS CoV-2 Spike and RBD antigens, that can be easily adapted to both academic and industrial settings; and integrate, for the first time, studies on the impact of bioprocess with an in-deep characterization of these proteins, correlating antigens glycosylation and biophysical attributes to performance of COVID-19 serologic tests. We strongly believe that our work will contribute to advance the current and recent knowledge on SARS-CoV-2 proteins and support the scientific society that is persistently searching for solutions for COVID-19 pandemics.

The plant-sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2-pyrone synthase gene from Gerbera hybrida ( GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl-CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl-CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12- ACL1-ACC1 using fed-batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 g/L or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for production of TAL and other acetyl-CoA-derived polyketides from low-cost carbon sources.

Algae are promising feedstock of biofuel. The screening of competent species and proper fertilizer supply are of the most important tasks. To accelerate this rather slow and laborious step, we developed an integrated high-throughput digital microfluidic (DMF) system that uses discrete droplet to serve as micro-bioreactor, encapsulating microalgal cells. Based on the fundamental understanding of various droplet hydrodynamics induced by the existence of different sorts of ions and biological species, an incorporation of capacitance-based position estimator, electrode-saving-based compensation and deterministic splitting approach was performed to optimize the DMF bioreactor. Thus, it enables all processes (e.g. nutrient gradient generation, algae culturing and analyzing of growth and lipid accumulation) occurring automatically on-chip especially in a high-fidelity way. The ability of the system to compare different micro algal strains on chip was investigated. Also, the Chlorella sp. were stressed by various conditions and then growth and oil accumulation were analyzed and compared, which demonstrated its potential as a powerful tool to investigate microalgal lipid accumulation at significantly lower laborites and reduced time.

Biosensors are the analytical tools with great application in healthcare, food quality control, and environmental monitoring. They are of considerable interest to be designed by using cost-effective and high efficient approaches. Designing biosensors with improved functionality or application in new target detection has been converted to a fast-growing field of biomedicine and biotechnology branches. Experimental efforts have led to valuable successes in biosensor designing; however, some deficiencies limit their utilization for this purpose. Computational design of biosensors has been introduced as a promising key to eliminate the gap. A set of reliable structure prediction of the biosensor segments, their stability, and accurate descriptors of molecular interactions are required to computationally design of biosensors. In this review, we provide a comprehensive insight into the progress of computational methods to guide the biosensor design, including molecular dynamics (MD) simulation, quantum mechanics (QM) calculations, molecular docking, virtual screening, and a combination of them as the hybrid methodologies. With relying on the recent advances in computational methods, an opportunity has been emerged for them to be complementary or alternative to the experimental methods in the field of biosensor design.

Glutathione (GSH) plays a central role in the redox balance maintenance in mammalian cells. The study of industrial CHO cell lines have demonstrated a close link between GSH metabolism and clone productivity. However, a deep investigation is still required to understand this correlation and highlights new potential targets for cell engineering. In this study, we have modulated the GSH intracellular content of an industrial cell line under bioprocess conditions in order to further elucidate the role of the GSH synthesis pathway. Two strategies were used : the variation of cystine supply and the direct inhibition of the GSH synthesis using buthionine sulfoximine (BSO). Cysteine supply modulation have revealed a correlation between intracellular GSH and product titer over time. Analysis of metabolites uptake/secretion rates and proteome comparison between BSO-treated cells and non-treated cells has highlighted a slow down of the TCA cycle leading to a secretion of lactate and alanine in the extracellular environment. Moreover, an adaptation of the glutathione related proteome has been observed with a up-regulation of the regulatory subunit of glutamate cysteine ligase and a down-regulation of a specific glutathione transferase subgroup, the Mu family. Surprisingly, the main impact of BSO treatment was observed on a global down-regulation of the cholesterol synthesis pathways. As cholesterol is required for protein secretion, it can be the missing part of the jigsaw to finally elucidate the link between GSH synthesis and productivity.

The development of generic biopharmaceuticals is increasing the pressures for enhanced bioprocess productivity and yields. Autophagy (“self-eating”) is a cellular process that allows cells to mitigate stresses such as nutrient deprivation. Reputed autophagy inhibitors have also been shown to increase autophagic flux under certain conditions, and enhance recombinant protein productivity in Chinese Hamster Ovary (CHO) cultures. Since peptides are commonly added to bioprocess culture media in hydrolysates, we evaluated the impact on productivity of an autophagy-inducing peptide (AIP), derived from the cellular autophagy protein Beclin 1. This was analyzed in CHO cell batch and fed-batch serum-free cultures producing a human IgG1. Interestingly, the addition of 1 to 4 µM AIP enhanced productivity in a concentration-dependent manner. Cell-specific productivity increased up to 1.8-fold in batch cultures, while in fed-batch cultures a maximum 2-fold increase in volumetric productivity was observed. An initial drop in cell viability also occurred before cultures recovered normal growth. Overall, these findings strongly support the value of investigating the effects of autophagy pathway modulation, and in particular, the use of this AIP medium additive to increase CHO cell biotherapeutic protein production and yields.

Predicting the fate of a microbial population (i.e., growth, gene expression…) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of continuous cultivation process implies the potential deviation of the microbial population involving genotypic and phenotypic diversification. This work has been focused on the induction of the arabinose operon in Escherichia coli as a model system. As a preliminary step, the GFP level triggered by an arabinose-inducible ParaBAD promoter has been tracked by flow cytometry in chemostat with glucose-arabinose co-feeding. For a large range of glucose-arabinose co-feeding, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In a second set of experiments, continuous cultivation was performed by adding either glucose or arabinose, based on the ability of individual cells for switching from low GFP to high GFP states, according to a technology called segregostat. In segregostat mode of cultivation, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching capabilities of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to a prolonged maintenance of the induction level with limited impact on phenotypic diversity for more than 60 generations. This result suggests that constraining individual cells into a given phenotypic trajectory is maybe not the best strategy for directing cell population. Instead, allowing individual cells switching around a predefined threshold seems to be a robust strategy leading to oscillating, but predictable, cell population behavior.

A robust monoclonal antibody (mAb) bioprocess requires physiological parameters such as temperature, pH, or dissolved oxygen (DO) to be well-controlled as even small variations in them could potentially impact the final product quality. For instance, pH substantially affects N-glycosylation, protein aggregation and charge variant profiles, as well as mAb productivity. However, relatively less is known about how pH jointly influences product quality and titer. In this study, we investigated the effect of pH on culture performance, product titer and quality profiles by applying longitudinal multi-omics profiling, including transcriptomics, proteomics, metabolomics and glycomics, at three different culture pH set points. The subsequent systematic analysis of multi-omics data showed that pH set points differentially regulated various intracellular pathways including intracellular vesicular trafficking, cell cycle, and apoptosis, thereby resulting in differences in specific productivity, product titer and quality profiles. In addition, a time-dependent variation in mAb N-glycosylation profiles, independent of pH was identified to be mainly due to the accumulation of mAb proteins in the endoplasmic reticulum (ER) over culture time, disrupting cellular homeostasis. Overall, this multi-omics-based study provides an in-depth understanding of the intracellular processes in mAb-producing CHO cell line under varied pH conditions and could serve as a baseline for enabling the quality optimization and control of mAb production.

7-Methylxanthine, a derivative of caffeine (1,3,7-trimethylxanthine), is a high-value compound that has multiple medical applications, particularly with respect to eye health. Here, we demonstrate the biocatalytic production of 7-methylxanthine from caffeine using Escherichia coli strain MBM019, which was constructed for production of paraxanthine (1,7-dimethylxanthine). The mutant N-demethylase NdmA4, which was previously shown to catalyze N 3-demethylation of caffeine to produce paraxanthine, also retains N 1-demethylation activity toward paraxanthine. This work demonstrates that whole cell biocatalysts containing NdmA4 are more active toward paraxanthine than caffeine. We used four serial resting cell assays, with spent cells exchanged for fresh cells between each round, to produce 2,120 μM 7-methylxanthine and 552 μM paraxanthine from 4,331 μM caffeine. The purified 7-methylxanthine and paraxanthine were then isolated via preparatory-scale HPLC, resulting in 177.3 mg 7-methylxanthine and 48.1 mg paraxanthine at high purity. This is the first reported strain genetically optimized for the biosynthetic production of 7-methylxanthine from caffeine.

The in vitro transcription (IVT) reaction used in the production of mRNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale up, optimization, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. A novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.