Herein we report the use of Pseudomonas putida F1 biofilms grown on carbonized cellulosic fibers to achieve biodegradation of airborne VOCs in the absence of any bulk aqueous phase media. It is believed that direct exposure of gaseous VOC substrates to biomass may eliminate aqueous phase mass transfer resistance and facilitate VOC capture and degradation. When tested with toluene vapor as a model VOC, the supported biofilm could grow optimally at 300 ppm toluene and 80% relative humidity, with a specific growth rate of 0.425 day -1. During long-term VOC biodegradation tests in a tubular packed bed reactor, biofilms achieved a toluene degradation rate of 2.5 mg g DCW -1 h -1 during the initial exponential growth phase. Interestingly, the P. putida F1 film kept biodegrading activity even at the subsequent stationary non-growth phase. The supported biofilms with a biomass loading of 20% (wt) could degrade toluene at a rate of 1.9 mg g DCW -1 h -1 during the stationary phase, releasing CO 2 at a rate of 6.4 mg g DCW -1 h -1 at the same time (indicating 100% conversion of substrate carbon to CO 2). All the specific degradation rates are much higher than what can be gleaned from previously reported work. It also demonstrates the feasibility of biofilm growth and direct gas phase degradation of VOCs without requiring any bulk aqueous phase.
Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.
Extracellular production of target proteins simplifies downstream processing due to obsolete cell disruption. However, optimal combinations of a heterologous protein, suitable signal peptide and secretion host can currently not be predicted, resulting in large strain libraries that need to be tested. On the experimental side, this challenge can be tackled by miniaturization, parallelization and automation, which provide high-throughput screening data. These data need to be condensed into a candidate ranking for decision making to focus bioprocess development on the most promising candidates. We screened for Bacillus subtilis signal peptides mediating Sec secretion of two polyethylene terephthalate degrading enzymes (PETases), leaf-branch compost cutinase (LCC) and polyester hydrolase (PE-H) mutants, by Corynebacterium glutamicum. We developed a fully automated screening process and constructed an accompanying Bayesian statistical modeling framework, which we applied in screenings for highest activity in 4-nitrophenyl palmitate degradation. In contrast to classical evaluation methods, batch effects and biological errors are taken into account and their uncertainty is quantified. Within only two rounds of screening, the most suitable signal peptide was identified for each PETase. Results from LCC secretion in microliter-scale cultivation were shown to be scalable to laboratory-scale bioreactors. This work demonstrates an experiment-modeling loop that can accelerate early-stage screening in a way that experimental capacities are focused to the most promising strain candidates. Combined with high-throughput cloning, this paves the way for using large strain libraries of several hundreds of strains in a Design-Build-Test-Learn approach.
Pichia pastoris ( Komagataella phaffii) is a fast-growing methylotrophic yeast with the ability to assimilate several carbon sources such as methanol, glucose, or glycerol. It has been shown to have outstanding secretion capability with a variety of heterologous proteins. In previous studies, we engineered P. pastoris to co-express E. coli AppA phytase and the HAC1 transcriptional activator using a bidirectional promoter. Phytase production was characterised in shake flasks and did not reflect industrial conditions. In the present study, phytase expression was explored and optimised using instrumented fermenters in continuous and fed-batch modes. First, the production of phytase was investigated under glucose de-repression in continuous culture at three dilution factors, 0.5 d -1, 1 d -1, and 1.5 d -1. The fermenter parameters of these cultures were used to inform a kinetic model in batch and fed-batch modes for growth and phytase production. The kinetic model developed aided to design the glucose feeding profile of a fed-batch culture. Kinetic model simulations under glucose de-repression and fed-batch conditions identified an optimal phytase productivity at the specific growth rate of 0.041 h -1. Validation of the model simulation with experimental data confirmed the feasibility of the model to predict phytase production in our newly engineered strain. Methanol was used only to induce the expression of phytase at high cell densities. Our results showed that high phytase production required two stages, the first stage used glucose under de-repression conditions to generate biomass while expressing phytase, and stage two used methanol to induce phytase expression. The production of phytase was improved 3.5-fold by methanol induction compared to the expression with glucose alone under de-repression conditions to a final phytase activity of 12.65 MU/L. This final volumetric phytase production represented an approximate 36-fold change compared to the flask fermentations. This two-phase strategy allowed to optimise phytase productivity by producing phytase during both growth and methanol induction phases. Finally, the phytase protein produced was assayed to confirm its molecular weight, and pH and temperature profiles. This study highlights the importance of optimising protein production in P. pastoris when using novel promoters and presents a general approach to performing bioprocess optimisation in this important production host.
Thermobifida fusca cutinase ( TfC ) is a carboxylesterase (CE) that degrades the environmental pollutant, polyethylene terephthalate (PET). TfC also acts upon PET’s degradation intermediates (DIs), such as oligoethylene terephthalate (OET), and bis-/mono-hydroxyethyl terephthalate (BHET/MHET), to convert these into terephthalic acid (TPA), the terminal product of PET degradation. We examined TfC’s surface, compared it to that of other CEs, and performed molecular docking and MD simulations with an OET, 2HE-(MHET) 3, to understand interactions between TfC’s surface and the OET, at TfC’s active site as well as vicinal regions. We mutated 17 residues on TfC’s surface, mostly individually, but sometimes using pairs of mutations, to see how these modulate TfC’s activity. Most mutants/variants showed a decrease in activity against solid PET. Some killed activity completely. However, three mutations (L90F, F209I and F249R), made using a background mutation (G62A) already reported to improve activity by almost ~2.0-fold, yielded increases in activity that were between ~1.3- and ~2.0-fold higher than that of G62A TfC (which we found to display a ~1.7-fold increase in activity over TfC, in our own experiments). TfC variants, G62A/F249R, and G62A/F209I, exhibit the highest activities yet observed in any TfC mutants/variants, against PET, and BHET, respectively.
Autologous cell therapy has proven to be an effective treatment for hematological malignancies. Cell therapies for solid tumors are on the horizon, however the high cost and complexity of manufacturing these therapies remain a challenge. Routinely used open steps to transfer cells and reagents through unit operations further burden the workflow reducing efficiency and increasing the chance for human error. Here we describe a fully closed, autologous bioprocess generating MAGE-B2 TCR-T cells. This bioprocess yielded 5 – 12e9 MAGE-B2-specific TCR-expressing T cells, transduced at low MOIs, within 7 to 10 days, and cells exhibited an enriched memory T cell phenotype and enhanced metabolic fitness. It was demonstrated that activating, transducing, and expanding leuko-apheresed cells in a single bioreactor without a T cell enrichment step promoted lentivirus transduction efficiency while resulting in comparable level of T cell purity (~97%) as that of leukopak cells that went through CD8+ and CD4+ positive selection. The critical process parameters of the bioreactor, including culturing at a high cell density (7e6 cells/mL), adjusting rocking agitations during phases of scale up, lowering glycolysis through addition of 2-Deoxy-D-glucose (2-DG), and modulating IL-2 levels, were shown to positively regulate TCR expression and cell doubling time, and promote resistance to effector-associated apoptosis of TCR-T cells. The bioprocess described herein supports scale-out feasibility by enabling processing of multiple patients’ batches in parallel within a Grade C cleanroom.
Biobutanol produced in acetone-butanol-ethanol fermentation at batch mode cannot compete with chemically derived butanol because of the low reactor productivity. Continuous fermentation can dramatically enhance productivity and lower capital and operating costs but are rarely used in industrial fermentation because of increased risks in culture degeneration, cell washout, and contamination. In this study, cells of the asporogenous Clostridium acetobutylicum ATCC55025 were immobilized in a single-pass fibrous-bed bioreactor (FBB) for continuous production of butanol from glucose and butyrate at various dilution rates. Butyric acid in the feed medium helped maintaining cells in the solventogenic phase for stable continuous butanol production. At the dilution rate of 1.88 h -1, butanol was produced at 9.55 g/L with a yield of 0.24 g/g and productivity of 16.8 g/L∙h, which was the highest ever achieved for biobutanol fermentation and an 80-fold improvement over the conventional ABE fermentation. The extremely high productivity was attributed to the high density of viable cells (~100 g/L at >70% viability) immobilized in the fibrous matrix, which also enabled the cells to better tolerate butanol and butyric acid. The FBB was stable for continuous operation for an extended period of over one month.
Isoprenoids are a large family of natural products with diverse structures, which allow them to play diverse and important roles in the physiology of plants and animals. They also have important commercial uses as pharmaceuticals, flavouring agents, fragrances, and nutritional supplements. Recently, metabolic engineering has been intensively investigated and emerged as the technology of choice for the production of isoprenoids through microbial fermentation. Isoprenoid biosynthesis typically originates in plants from acetyl-coA in central carbon metabolism, however, a recent study reported an alternative pathway, the Isopentenol Utilization pathway (IUP), that can provide the building blocks of isoprenoid biosynthesis from affordable C5 substrates. In this work, we expressed the IUP in Escherichia coli to efficiently convert isopentenols into geranate, a valuable isoprenoid compound. We first established a geraniol-producing strain in E. coli that uses the IUP. Then, we extended the geraniol synthesis pathway to produce geranate through two oxidation reactions catalysed by two alcohol/aldehyde dehydrogenases from Castellaniella defragrans. The geranate titer was further increased by optimizing the expression of the two dehydrogenases and also parameters of the fermentation process. The best strain produced 764 mg/L geranate in 24 h from 2 g/L isopentenols (a mixture of isoprenol and prenol). We also investigated if the dehydrogenases could accept other isoprenoid alcohols as substrates.
The dominant method for generating Chinese hamster ovary (CHO) cell lines that produce high titers of biotherapeutic proteins utilizes selectable markers such as dihydrofolate reductase (Dhfr) or glutamine synthetase (Gs), alongside inhibitory compounds like methotrexate (MTX) or methionine sulfoximine (MSX), respectively. Recent work has shown the importance of asparaginase (Aspg) for growth in media lacking glutamine–the selection medium for Gs-based selection systems. We generated a Gs/Aspg double knockout CHO cell line and evaluated its utility as a novel dual selectable system via co-transfection of Gs-Enbrel and Aspg-Enbrel plasmids. Using the same selection conditions as the standard Gs system, the resulting cells from the Gs/Aspg dual selection showed substantially improved specific productivity and titer compared to the standard Gs selection method, however, with reduced growth rate and viability. Following adaptation in selection medium, the cells improved viability and growth while still achieving ~5-fold higher specific productivity and ~3-fold higher titer than Gs selection alone. We anticipate that with further optimization of culture medium and selection conditions this approach would serve as an effective addition to workflows for the industrial production of recombinant biotherapeutics.
Microorganisms build fatty acids with biocatalytic assembly lines, or fatty acid synthases (FASs), that can be repurposed to produce a broad set of fuels and chemicals. Despite their versatility, the product profiles of FAS-based pathways are challenging to adjust without experimental iteration, and off-target products are common. This study uses a detailed kinetic model of the E. coli FAS as a foundation to model nine oleochemical pathways. These models provide good fits to experimental data and help explain unexpected results from in vivo studies. An analysis of pathways for alkanes and fatty acid ethyl esters, for example, suggests that reductions in titer caused by enzyme overexpression can result from shifts in pools of metabolic intermediates that are incompatible with the substrate specificities of downstream enzymes. In general, different engineering objectives (i.e., production, unsaturated fraction, and average chain length) show experimentally consistent sensitivities to pathway enzymes, and model-based compositional analyses indicate simple shifts in enzyme concentrations can alter the product profiles of pathways with promiscuous components. The study concludes by integrating all models into a graphical user interface. The models supplied by this work provide a versatile kinetic framework for studying oleochemical pathways in different biochemical contexts.
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.
Glioblastoma (GBM) is the most common form of brain cancer. Even with aggressive treatment, tumor recurrence is almost universal and patient prognosis is poor because many GBM cell subpopulations, especially the mesenchymal and glioma stem cell populations, are resistant to temozolomide (TMZ) the most commonly used chemotherapeutic in GBM. For this reason, there is an urgent need for the development of new therapies that can more effectively treat GBM. Several recent studies have indicated that high expression of connexin 43 (Cx43) in GBM is associated with poor patient outcomes. It has been hypothesized that inhibition of the Cx43 hemichannels could prevent TMZ efflux and sensitize otherwise resistance cells to the treatment. In this study, we use a 3-dimensional organoid model of GBM to demonstrate that combinatorial treatment with TMZ and αCT1, a Cx43 mimetic peptide, significantly improves treatment efficacy in certain populations of GBM. Confocal imaging was used to analyze changes in Cx43 expression in response to combinatorial treatment. These results indicate that Cx43 inhibition should be pursued further as an improved treatment for GBM.
We report an automated cell-isolation system based on fluorescence image analysis of cell aggregates cultured in a photodegradable hydrogel. The system incorporates cell culture in a humidified atmosphere with controlled CO 2 concentration and temperature, image acquisition and analysis, micropatterned light exposure, and cell collection by pipetting. Cell aggregates were cultured on hydrogels, and target cells were selected by phase contrast and fluorescence image analysis. After degradation of the hydrogel by exposure to micropatterned ultraviolet light, cell aggregates were transferred to a collection vessel by robotic pipetting. We assessed the system for hydrogel degradation, recovery of target cells, and contamination by off-target cells. We demonstrated two practical applications of our method: (i) in cell aggregates from MCF-7-RFP strains in which 18.8% of cells produced red fluorescent protein (RFP), we successfully obtained 14 proliferative fluorescence-positive cell aggregates from 31 wells, and all of the isolated strains produced a higher proportion of RFP than the original populations; (ii) after fluorescent immunostaining of human epidermal growth factor receptor 2 (HER2) in cancer cells, we successfully isolated HER2-positive cells from a mixed population of HER2-positive and -negative cells, and gene sequence analysis confirmed that the isolated cells mainly contained the target cells.
Computational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow-map (de)compositions to present a framework that can address both of these challenges via learning data-driven models useful for capturing the dynamical behavior of biochemical systems. Data-driven flow-map models seek to directly learn the integration operators of the governing differential equations in a black-box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast-to-evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long-term system dynamics via experimental observations. We present a data-efficient approach to data-driven flow-map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a co-culture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data-driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems.
Hairy root systems have proven to be a viable alternative for recombinant protein production. For recalcitrant proteins, maximizing the productivity of hairy root cultures is essential. The aim of this study was to optimize a Brassica rapa rapa hairy root process for secretion of α-L-iduronidase (IDUA), a biologic of medical value. The process was first optimized with hairy roots expressing eGFP. For the biomass optimization, the highest biomass yields were achieved in modified Gamborg B5 culture medium. For the secretion induction, the optimized secretion media was obtained with additives (1.5g/l PVP + 1mg/l 2,4-D + 20.5g/l KNO 3) resulting in 3.4 fold eGFP secretion when compared to the non-induced control. These optimized conditions were applied to the IDUA-expressing hairy root clone, confirming that the highest yields of secreted IDUA occurred when using the already defined additive combination. The functionality of the IDUA protein, secreted and intracellular, was confirmed with an enzymatic activity assay. A >150-fold increase of the IDUA activity was observed using an optimized secretion medium, compared with a non-induced medium. We have proven that our B. rapa rapa hairy root system can be harnessed to secrete recalcitrant proteins, illustrating the high potential of hairy roots in plant molecular farming.
Cancer is one of the major health-related issues affecting the population worldwide and subsequently accounts for the second-largest death. Genetic and epigenetic modifications in oncogenes or tumor suppressor genes affect the regulatory systems that lead to the initiation and progression of cancer. Conventional methods, including chemotherapy/radiotherapy/appropriate combinational therapy and surgery, are being widely used for theranostics of cancer patients. Surgery is useful in treating localized tumors, but it is ineffective in treating metastatic tumors, which spread to other organs and result in a high recurrence rate and death. Also, the therapeutic application of free drugs is related to substantial issues such as poor absorption, solubility, bioavailability, high degradation rate, short shelf-life, and low therapeutic index. Therefore, these issues can be sorted out using nano lipid-based carriers (NLBCs) as promising drug delivery carriers. Still, at most, they fail to achieve site targeted drug delivery and detection. This can be achieved by selecting a specific ligand/antibody for its cognate receptor molecule expressed on the cancer cell surface. In this review, we have mainly discussed the various types of ligands used to decorate NLBCs. A list of the ligands used to design nanocarriers to target malignant cells specifically has been extensively undertaken, and the approved ligand decorated lipid-based nanomedicines with their clinical status has been explained in tabulated form to provide a wider scope to the readers regarding ligand coupled NLBCs.
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.
In high-performance industrial fermentation processes, stirring and aeration may account for significant production costs. Compared to the widely applied Rushton impellers, axial-pumping impellers are known to yield a lower power draw and at the same time improve mixing. However, their lower gas dispersion capability requires stronger agitation, compromising these benefits. Diverse advanced impeller forms have been developed to cope with this challenge. We apply alternating radial and axial impellers and demonstrate strong gas dispersion and energy-efficient mixing for the first time in a large-scale (160 m 3) bioreactor, based on experimental and CFD simulation data. For equal operating conditions (stirrer speed, aeration rate), this setup yielded similar gas hold-ups and better mixing times (-35 %) compared to a classical Rushton-only configuration. Hence, applying a radial impeller on an upper level for improving gas dispersion maintains the benefits of axial impellers in terms of reducing energy demand (up to -50 %). We conclude that this effect is significant only at large-scale, when bubbles substantially expand due to the release of the hydrostatic pressure and have time to coalesce. The work thus extends current knowledge on mixing and aeration of large-scale reactors using classical impeller types.