Yellow fever (YF) is a life-threatening viral disease endemic in large areas of Africa and Latin America. Although there is a very efficacious vaccine since the 1930s, YF still causes 29,000-60,000 annual deaths. During recent YF outbreaks there were issues of vaccine shortage due to limited supply of the current egg-derived vaccine; rare but fatal vaccine adverse effects occurred; and cases were imported to Asia, where the mosquito vector circulates and where local transmission could potentially start. In this work, we investigated the production of YF virus-like particles (VLPs) using suspension-adapted stably-transfected HEK293 cells. In order to develop an intensified process, we combined two strategies: the use of sequential FACS rounds to enrich the stable cell pool in terms of high producers, and the use of perfusion processes. At first, shaken tube experiments revealed that FACS enrichment of the cell pool allowed doubling VLP production, and that in pseudoperfusion cultures (with daily medium exchange) lasting 14 days VLP production increased by 8.3 fold as compared to batch cultures lasting 11 days. When true perfusion cultures were carried out in bioreactors, the use of an inclined cell settler as cell retention device showed operational advantages as compared to an ATF system.
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.
The serious drawbacks of conventional pancreatic ductal adenocarcinoma (PDAC) therapy like nonspecific toxicity and high resistance to chemo and radiation therapy, prompted the development and application of countless siRNA-based therapeutics. Significant technological success has been achieved in this area; however, the major challenges to siRNA-based therapeutics becoming a new paradigm in the pancreatic cancer therapy stem from enzymatic digestion, off-target effects, difficulty to enter cells, induction of innate immune responses, and renal clearance. Recent advances in drug delivery systems hold great promise for improving siRNA-based therapeutics and developing a new class of drugs, nano-siRNA drugs. However, a number of fundamental questions, regarding toxicity, immunostimulation, and poor knowledge of nano-bio interactions, need to be addressed before clinical translation. In this review, we provide recent achievements in designing and development of various non-viral delivery vehicles for pancreatic cancer therapy. More importantly, co-delivery of conventional anticancer drugs with siRNA as a new revolutionary pancreatic cancer combinational therapy is completely discussed.
pH is an important factor affecting the growth and production of microorganisms; especially, it is effective on the efficiency of ethanologenic microorganisms. It can change the ionization state of metabolites via the change in the charge of their functional groups that may lead to metabolic alteration. Here, we estimated the ionization state of metabolites and balanced the charge of reactions in genome-scale metabolic models of Saccharomyces cerevisiae, Escherichia coli, and Zymomonas mobilis at pH levels 5, 6, and 7. The robustness analysis was first implemented to anticipate the effect of proton exchange flux on growth rates for the constructed metabolic models at various pH. In accordance with previous experimental reports, the models predict that Z. mobilis is more sensitive to pH rather than S. cerevisiae and the yeast is more regulated by pH rather than E. coli. Then, a systemic approach was proposed to predict the pH effect on metabolic change and to find effective reactions on ethanol production in S. cerevisiae. The correlated reactions with ethanol production at predicted optimal pH in a range of proton exchange rates determined by robustness analysis were identified using the Pearson correlation coefficient. Then, fluxes of these reactions were applied to cluster the various pHs by principal component analysis and to identify the role of these reactions on metabolic differentiation because of pH change. Finally, 12 reactions were selected for up and down-regulation to improve ethanol production. Enzyme Regulators of the selected reactions were identified using the Brenda database and 11 selected regulators were screened and optimized via Plackett-Burman and 2-level full factorial designs, respectively. The proposed approach has enhanced yields of ethanol from 0.18 to 0.36 mol/mol carbon. Hence, not only a comprehensive approach for understanding the effect of pH on metabolism was proposed in this work, but also it successfully introduced key manipulations for ethanol overproduction.
We evaluated filtration behavior and virus removal capability for a mAb and plasma IgG under constant flow rate directly following flow-through column chromatography in an integrated process. For mAb solution with quantified host cell protein (HCP) content processed in flow-through mode on in-series mixed-mode AEX and modified CEX columns connected to the Planova BioEX filter (pool-less), HCP logarithmic reduction value (LRV) of 2.3 and 93.9% protein recovery were achieved for the process. Filtration behavior for 5 to 15 mg/mL plasma IgG run at flux of 10 to 100 LMH to 100 L/m2 throughput on Planova BioEX filters showed similar behavior across the protein concentrations tested although filtration pressure increased with throughput at 50 LMH and above, indicating the suitability of lower flux processes for continuous processing. Comparing both plasma IgG and mAb filtration behavior to four clogging models showed little difference in fit among the models, but with slightly better fit to the cake filtration model. Viral clearance tested by in-line spiking X-MuLV or MVM into purified plasma IgG showed robust removal at low flux. Integrating the Planova BioEX filter into continuous processes with column chromatography can achieve efficient downstream processing with reduced footprint and process time.
The heavy metals pollution represents one of the important issues in the environmental field since they are involved in many pathologies from cancer, neurodegenerative and metabolic diseases. We propose an innovative portable biosensor for the determination of traces of trivalent Arsenic (AsIII) and bivalent mercury (HgII) in water. The system implements a strategy combining two advanced sensing modules consisting in (a) a whole cell based on engineered Escherichia coli as selective sensing element towards the metals and (b) an electrochemical miniaturised silicon device with three microelectrodes and a portable reading system. The sensing mechanism relies on the selective recognition from the bacterium of given metals producing the 4-aminophenol (PAP) redox active mediator detected through a cyclic voltammetry analysis. The miniaturized biosensor is able to operate a portable, robust and high-sensitivity detection of AsIII with a sensitivity of 0.122 µA ppb-1, LoD of 1.5 ppb and a LoQ of 5 ppb. The LoD value is one order of magnitude below of the value indicated to WHO to be dangerous (10 μg/L). The system was proved to be fully versatile being effective in the detection of Hg(II) as well. A first study on Hg(II) showed sensitivity value of 2.11 µA/ppb a LOD value of 0.1 ppb and LoQ value of 0.34 ppb. Also in this case, the detected LOD was ten time lower than that indicated by WHO (1 ppb). These results pave the way for advanced sensing strategies suitable for the environmental monitoring and the public safety.
A bone regeneration scaffold is typically designed as a platform to effectively heal a bone defect while preventing soft tissue infiltration. Despite the wide variety of scaffold materials currently available, such as collagen, critical problems in achieving bone regeneration remain, including a rapid absorption period and low tensile strength as well as high costs. Inspired by extracellular matrix protein and topographical cues, we developed a polycaprolactone-based scaffold for bone regeneration using a soluble eggshell membrane protein (SEP) coating and a nanotopography structure for enhancing the physical properties and bioactivity. The scaffold exhibited adequate flexibility and mechanical strength as a biomedical platform for bone regeneration. The highly aligned nanostructures and SEP coating were found to regulate and enhance cell morphology, adhesion, proliferation, and differentiation in vitro. In a calvarial bone defect mouse model, the scaffolds coated with SEP applied to the defect site promoted bone regeneration along the direction of the nanotopography in vivo. These findings demonstrate that bone-inspired nanostructures and SEP coatings have high potential to be applicable in the design and manipulation of scaffolds for bone regeneration.
Integrated continuous downstream processes with process analytical technology offer a promising opportunity to reduce production costs and increase process flexibility and adaptability. In this case study, an integrated continuous process was used to purify a recombinant protein on laboratory scale in a two-system setup that can be used as a general downstream setup offering multi-product and multi-purpose manufacturing capabilities. The process consisted of continuous solvent/detergent virus inactivation followed by periodic countercurrent chromatography in the capture step, and a final chromatographic polishing step. A real-time controller was implemented to ensure stable operation by adapting the downstream process to external changes. A concentration disturbance was introduced to test the controller. After the disturbance was applied, the product output recovered within 6 hours, showing the effectiveness of the controller. In a comparison of the process with and without the controller, the product output per cycle increased by 27%, the resin utilization increased from 71.4% to 87.9%, and the specific buffer consumption was decreased by 21% with the controller, while maintaining a similar yield and purity as in the process without the disturbance. In addition, the integrated continuous process outperformed the batch process, increasing the productivity by 95% and the yield by 28%.
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.
The control of nutrient availability is critical to large-scale manufacturing of biotherapeutics. However, the quantification of proteinogenic amino acids is time-consuming and thus is difficult to implement for real-time in situ bioprocess control. Genome-scale metabolic models describe the metabolic conversion from media nutrients to proliferation and recombinant protein production, and therefore are a promising platform for in silico monitoring and prediction of amino acid concentrations. This potential has not been realized due to unresolved challenges: (1) the models assume an optimal and highly efficient metabolism, and therefore tend to underestimate amino acid consumption, and (2) the models assume a steady state, and therefore have a short forecast range. We address these challenges by integrating machine learning with the metabolic models. Through this we demonstrate accurate and time-course dependent prediction of individual amino acid concentration in culture medium throughout the production process. Thus, these models can be deployed to control nutrient feeding to avoid premature nutrient depletion or provide early predictions of failed bioreactor runs.
Silk fibroin (SF) from Bombyx mori has superior properties as both a textile and a biomaterial, and has been used to functionalize the surfaces of various medical inorganic materials including titanium (Ti). In this paper, we endowed SF with reversible binding ability to Ti by embedding a titanium binding motif (minTBP-1, RKLPDA). Artificial SF proteins were first created by conjugating gene cassettes for SF motif (AGSGAG) and minTBP-1 motif with different ratios, which have been shown to bind reversibly to Ti surfaces in quartz crystal microbalance analyses. Based on these results, the functionalized SF (TiBP-SF) containing the designed peptide [TS[(AGSGAG)3AS]2RKLPDAS]8 was prepared from the cocoon of transgenic B. mori, which accelerates the ossific differentiation of MC3T3-E1 cells when coated on titanium substrates. Thus, TiBP-SF presents an alternative for endowing the surfaces of titanium materials with osseointegration functionality, which would allow the exploration of potential applications in the medical field.
Alcohol dehydrogenases (ADHs) play key roles in the production of various chemical precursors that are essential in pharmaceutical and fine chemical industries. To achieve practical application of ADHs in industrial processes, tailoring enzyme properties through rational design or directed evolution is often required. Here, we developed a secretion-based dual fluorescence assay (SDFA) for high-throughput screening of ADHs. In SDFA, an ADH of interest is fused to a mutated superfolder green fluorescence protein (MsfGFP), which could result in secretion of the fusion protein to culture broth. After a simple centrifugation step to remove the cells, the supernatant can be directly used to measure activity of the ADH based on a red fluorescence signal, whose increase is coupled to formation of NADH (a redox co-factor of ADHs) in the reaction. SDFA allows easy quantification of ADH concentration based on the green fluorescence signal of MsfGFP. This feature is useful in determining specific activity and may improve screening accuracy. Out of five ADHs we have tested with SDFA, four ADHs can be secreted and characterized. We successfully screened a combinatorial library of an ADH from Pichia finlandica and identified a variant with a 197-fold higher kcat/km value toward (S)-2-octanol compared to its wild-type.
Sulfate-reducing prokaryotes (SRPs) are crucial participants in the cycling of sulfur, carbon, and various metals in the natural environment and in engineered systems. Despite recent advances in genetics and molecular biology bringing a huge amount of information about the energy metabolism of SRPs, little effort has been made to link this important information with their biotechnological studies. This study aims to construct multiple metabolic models of SRPs that systematically compile genomic, genetic, biochemical, and molecular information about SRPs to study their energy metabolism. Pan-genome analysis is conducted to compare the genomes of SRPs, from which a list of orthologous genes related to central and energy metabolism is obtained. 24 SRP metabolic models via the inference of pan-genome analysis are constructed efficiently. The reference model of the well-studied model SRP Desulfovibrio vulgaris Hildenborough (DvH) is validated via Flux balance analysis (FBA). The DvH model predictions match reported experimental growth and energy yields, which demonstrates that the core metabolic model works successfully. Further, steady-state simulation of SRP metabolic models under different growth conditions shows how the use of different electron transfer pathways leads to energy generation. Three energy conservation mechanisms are identified, including menaquinone-based redox loop, hydrogen cycling, and proton pumping. Flavin-based electron bifurcation (FBEB) is also demonstrated to be an essential mechanism for supporting energy conservation. The developed models can be easily extended to other species of SRPs not examined in this study. More importantly, the present work develops an accurate and efficient approach for constructing metabolic models of multiple organisms, which can be applied to other critical microbes in environmental and industrial systems, thereby enabling the quantitative prediction of their metabolic behaviors to benefit relevant applications.
Biofouling represents an important limitation in photobioreactor cultures. The biofouling propensity of different materials (polystyrene, borosilicate glass, polymethyl methacrylate and polyethylene terephthalate glycol-modified) and coatings (two spray-applied and nanoparticle-based superhydrophobic coatings and a hydrogel-based fouling release coating) was evaluated by means of a short-term protein test, using bovine serum albumin (BSA) as a model protein, and by the long-term culture of the marine microalga Nannochloropsis gaditana under practical conditions. The results from both methods were similar, confirming that the BSA test predicts microalgal biofouling on surfaces exposed to microalgae cultures; these secrete macromolecules, such as proteins, that have a high capacity for forming a conditioning film prior to cell adhesion. The hydrogel-based coating showed significantly reduced BSA and N. gaditana adhesion, whereas the other surfaces failed to control biofouling. Microalgal biofouling was associated with an increased concentration of sticky extracellular proteins at low N/P ratios (below 15).
Producing recombinant proteins in transgenic plant cell suspension cultures in bioreactors provides controllability, reproducibility, scalability, and low-cost production, although low yields remain the major challenge. The studies on scaling-up to pilot-scale bioreactors, especially in conventional stainless-steel stirred tank bioreactors (STB), to produce recombinant proteins in plant cell suspension cultures are very limited. In this study, we scaled-up the production of rice recombinant butyrylcholinesterase (rrBChE), a complex hydrolase enzyme that can be used to prophylactically and therapeutically treat against organophosphorus nerve agents and pesticide exposure, from metabolically-regulated transgenic rice cell suspension cultures in a 40-L pilot-scale STB. Employing cyclical operation together with a simplified-process operation (controlling gas sparging rate rather than dissolved oxygen and allowing natural sugar depletion) identified in lab-scale (5-L) bioreactor studies, we found consistent maximum total active rrBChE production level of 46-58 µg/g fresh weight in four cycles over 82 days of continuous operation. Additionally, maintaining the overall volumetric oxygen mass transfer coefficient (kLa) in the pilot-scale STB to be equivalent to the lab-scale STB improves the maximum total active rrBChE production level and the maximum volumetric productivity to 85 µg/g fresh weight and 387 µg L-1 day-1, respectively, which are comparable to the lab-scale culture. Here, we demonstrate pilot scale bioreactor performance using a metabolically-regulated transgenic rice cell culture for long-term, reproducible, and sustained production of rrBChE.
Mixed-culture fermentation provides a means to recycle carbon from complex organic waste streams into valuable feedstock chemicals. Using complex microbial consortia, individual systems can be tuned to produce a range of biochemicals to meet market demand. However, the metabolic mechanisms and community interactions which drive product expression changes under differing conditions are currently poorly understood. Furthermore, predictable product transitions are currently limited to pH-driven changes between butyrate and ethanol, and chain-elongation (fed by CO2, acetate, and ethanol) to butyrate, valerate, and hexanoate. Lactate, a high-value biopolymer feedstock chemical, has been observed in transition states, but sustained production has not been described. In this work, a continuous stirred bioreactor was operated at low pH (5.5) with substrate concentration varied between limiting and non-limiting conditions. Using glucose as a model substrate, two sustained operational states were defined: butyrate production during substrate limitation, and lactate production in the non-limited state. Through SWATH-MS metaproteomics and 16S rDNA community profiling, the mechanism of change between butyrate and lactate was described primarily by redirected carbon flow through the methylglyoxal bypass by Megasphaera under substrate non-limiting concentrations. Crucially, butyrate production resumed upon return to substrate-limited conditions, demonstrating the reversibility of this transition.
Recent research has demonstrated that synthetic methanotroph-photoautotroph cocultures offer a highly promising route to convert biogas into value-added products. However, there is a lack of techniques for fast and accurate characterization of cocultures, such as determining the individual biomass concentration of each organism in real-time. To address this unsolved challenge, we propose an experimental-computational protocol for fast, easy and accurate quantitative characterization of the methanotroph-photoautotroph cocultures. Besides determining the individual biomass concentration of each organism in the coculture, the protocol can also obtain the individual consumption and production rates of O2 and CO2 for the methanotroph and photoautotroph, respectively. The accuracy and effectiveness of the proposed protocol was demonstrated using two model coculture pairs, Methylomicrobium alcaliphilum 20ZR - Synechococcus sp. PCC7002 that prefers high pH high salt condition, and Methylococcus capsulatus - Chlorella sorokiniana that prefers low salt and neutral pH medium. The performance of the proposed protocol was compared with a flow cytometry based cell counting approach. The experimental results show that the proposed protocol is much easier to carry out and delivers faster and more accurate results in measuring individual biomass concentration than the cell counting approach without requiring any special equipment.
Incurable breast cancer bone metastasis causes widespread bone loss, resulting in fragility, pain, increased fracture risk, and ultimately increased patient mortality. Increased mechanical signals in the skeleton are anabolic and protect against bone loss, and they may also do so during osteolytic bone metastasis. Skeletal mechanical signals include interdependent tissue deformations and interstitial fluid flow, but how metastatic tumor cells respond to each of these individual signals remains under-investigated, a barrier to translation to the clinic. To delineate their respective roles, we report computed estimates of the internal mechanical field of a bone-mimetic scaffold undergoing combinations of high and low compression and perfusion using multiphysics simulations. Simulations were conducted in advance of multi-modal loading bioreactor experiments with bone metastatic breast cancer cells to ensure that mechanical stimuli occurring internally were physiological and anabolic. Our results show that mechanical stimuli throughout the scaffold were within the anabolic range of bone cells in all loading configurations, were homogenously distributed throughout, and that combined high magnitude compression and perfusion synergized to produce the largest wall shear stresses within the scaffold. These simulations, when combined with experiments, will shed light on how increased mechanical loading in the skeleton may confer anti-tumorigenic effects during metastasis.