Background β-Caryophyllene is a plant terpenoid with therapeutic and biofuel properties. Production of terpenoids through microbial cells is a potentially sustainable alternative for production. Adaptive laboratory evolution is a complementary technique to metabolic engineering for strain improvement, if the product-of-interest is coupled with growth. Here we use a combination of pathway engineering and adaptive laboratory evolution to improve the production of β-caryophyllene, an extracellular product, by leveraging the antioxidant potential of the compound. Results Using oxidative stress as selective pressure, we developed an adaptive laboratory evolution that worked to evolve an engineered β-caryophyllene producing yeast strain for improved production within a few generations. This strategy resulted in fourfold increase in production in isolated mutants. Further increasing the flux to β-caryophyllene in the best evolved mutant achieved a titer of 104.7 ± 6.2 mg/L product. Genomic analysis revealed a gain-of-function mutation in the a-factor exporter STE6 was identified to be involved in significantly increased production, likely as a result of increased product export. Conclusion An optimized selection strategy based on oxidative stress was developed to improve the production of the extracellular product β-caryophyllene in an engineered yeast strain. Application of the selection strategy in adaptive laboratory evolution resulted in mutants with significantly increased production and identification of novel responsible mutations.

Achieving consistent product quality of a biotherapeutic is a major target for any biopharmaceutical manufacturer, even more for a biosimilar producer as comparability with the innovator product is a regulatory expectation. The complexity of biotherapeutic products and their tedious manufacturing processes, however, make this a non-trivial exercise. The primary motivation of this work is to develop an integrated chromatographic platform for purification of monoclonal antibody (mAb) therapeutics that can deliver the desired separation of both charge variants and aggregates, in addition to the process related impurities like host cell proteins (HCP) and host cell DNA. To achieve the same, an integrated two-stage chromatographic process platform consisting of cation exchange chromatography and multimodal chromatography is being proposed. The versatility of the proposed platform has been successfully demonstrated for three different mAbs. It have been shown that in each case charge variant separation is achieved with the required clearance of aggregates (<1%), HCP (<10 ppm), and DNA (<5 ppb). Moreover, the proposed platform is conducive to use for development of a continuous process and offers smaller process time, lower buffer utilization, and decreased operational costs when compared to the conventional purification platforms.

Development of a chromatographic step in a time and resource efficient manner remains a serious bottleneck in protein purification. Chromatographic performance typically depends on raw material attributes, feed material attributes, process factors, and their interactions. Design of experiments (DOE) based process development is often chosen for this purpose. A challenge is, however, in performing a DOE with such a large number of process factors. A split DOE approach based on process knowledge in order to reduce the number of experiments is proposed. The first DOE targets optimizing factors that are likely to significantly impact the process and their effect on process performance is unknown. The second DOE aims to fine‐tune another set of interacting process factors, impact of whom on process performance is known from process understanding. Furthermore, modeling of a large set of output response variables has been achieved by fitting the output responses to an empirical equation and then using the parametric constants of the equation as output response variables for regression modeling. Two case studies involving hydrophobic interaction chromatography for removal of aggregates and cation exchange chromatography for separation of charge variants and aggregates have been utilized to illustrate the proposed approach. Proposed methodology reduced total number of experiments by 25% and 72% compared to a single DOE based on central composite design and full factorial design, respectively. The proposed approach is likely to result in a significant reduction in resources required as well as time taken during process development. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2730, 2019

Biotherapeutics have become the focus of the pharmaceutical industry due to their proven effectiveness in managing complex diseases. Downstream processes of these molecules consist of several orthogonal, high resolution unit operations designed so as to be able to separate variants having very similar physicochemical properties. Typical process development involves optimization of the individual unit operations based on Quality by Design principles in order to define the design space within which the process can deliver product that meets the predefined specifications. However, limited efforts are dedicated to understanding the interactions between the unit operations. This paper aims to showcase the importance of understanding these interactions and thereby arrive at operating conditions that are optimal for the overall process. It is demonstrated that these are not necessarily same as those obtained from optimization of the individual unit operations. Purification of Granulocyte Colony Stimulating Factor (G-CSF), a biotherapeutic expressed in E. coli., has been used as a case study. It is evident that the suggested approach results in not only higher yield (91.5 vs. 86.4) but also improved product quality (% RP-HPLC purity of 98.3 vs. 97.5) and process robustness. We think that this paper is very relevant to the present times when the biotech industry is in the midst of implementing Quality by Design towards process development. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:355-362, 2016.

Adaptive laboratory evolution (ALE) is a powerful tool used to increase strain fitness in the presence of environmental stressors. If production and strain fitness can be coupled, ALE can be used to increase product formation. In earlier work, carotenoids hyperproducing mutants were obtained using an ALE strategy. Here, de novo mutations were identified in hyperproducers, and reconstructed mutants were explored to determine the exact impact of each mutation on production and tolerance. A single mutation in YMRCTy1-3 conferred increased carotenoid production, and when combined with other beneficial mutations led to further increased β-carotene production. Findings also suggest that the ALE strategy selected for mutations that confer increased carotenoid production as primary phenotype. Raman spectroscopy analysis and total lipid quantification revealed positive correlation between increased lipid content and increased β-carotene production. Finally, we demonstrated that the best combinations of mutations identified for β-carotene production were also beneficial for production of lycopene.

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With the rapid increase in the use of lithium-ion batteries (LIBs), the development of safe LIBs has become an important social issue. Replacing flammable organic liquid electrolytes in current LIBs with water can be an alternative route to resolve this safety concern. The waterin-salt (WIS) electrolytes received great attention as next-generation electrolytes due to their large electrochemical stability window. However, their high cathodic limit remains as a challenge, impeding the use of lowpotential anodes. Here, we report the first biodirected synthesis of carbonaceous layers on anodes to use them as interlayers that prevent a direct contact of water molecules to anode particles. Highaspect ratio microbes are utilized as precursors of carbonaceous layers on TiO 2 nanoparticles (m-TiO 2 ) to enhance the conductivity and to reduce the electrolysis of WIS electrolytes. We selected the cylindrical shape of microbes that offers geometric diversity, providing us a toolkit to investigate the effect of microbe length in forming the network in binary composites and their impacts on the battery performance with WIS electrolytes. Using microbes with varying aspect ratios, the optimal microbe size to maximize the battery performance is determined. The effects of storage time on microbe size are also studied. Compared to uncoated TiO 2 anodes, m-TiO 2 exhibited 49% higher capacity at the 40th cycle and enhanced the cycle life close to anodes made with a conventional carbon precursor while using an 11% less amount of carbon. We performed density functional theory calculations to unravel the underlying mechanism of the performance improvement using microbe-derived carbon layers. Computational results show that high amounts of pyridinic nitrogen present in the peptide bonds in microbes are expected to slow down the water diffusion. Our findings provide key insights into the design of an interlayer for WIS anodes and open an avenue to fabricate energy storage materials using biomaterials.

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