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At least 523 records · Page 29

Enzyme selection, optimization, and production toward biodegradation of post–consumer poly(ethylene terephthalate) at scale

Poly(ethylene terephthalate) (PET) is one of the world's most widely used polyester plastics. Due to its chemical stability, PET is extremely difficult to hydrolyze in a natural environment. Recent discoveries in new polyester hydrolases and breakthroughs in enzyme engineering strategies have inspired enormous research on biorecycling of PET. This study summarizes our research efforts toward large-scale, efficient, and economical biodegradation of post-consumer waste PET, including PET hydrolase selection and optimization, high-yield enzyme production, and high-capacity enzymatic degradation of post-consumer waste PET. First, genes encoding PETase and MHETase from Ideonella sakaiensis and the ICCG variant of leaf-branch compost cutinase (LCC ICCG ) were codon-optimized and expressed in Escherichia coli BL21(DE3) for high-yield production. To further lower the enzyme production cost, a pelB leader sequence was fused to LCC ICCG so that the enzyme can be secreted into the medium to facilitate recovery. To help bind the enzyme on the hydrophobic surface of PET, a substrate-binding module in a polyhydroxyalkanoate depolymerase from Alcaligenes faecalis (PBM) was fused to the C-terminus of LCC ICCG . The resulting four different LCC ICCG variants (LCC, PelB-LCC, LCC-PBM, and PelB-LCC-PBM), together with PETase and MHETase, were compared for PET degradation efficiency. A fed-batch fermentation process was developed to produce the target enzymes up to 1.2 g L –1 . Finally, the best enzyme, PelB-LCC, was selected and used for the efficient degradation of 200 g L –1 recycled PET in a well-controlled, stirred-tank reactor. Furthermore, the results will help develop an economical and scalable biorecycling process toward a circular PET economy.

59 BASIC BIOLOGICAL SCIENCES↗

High–level β–carotene production from xylose by engineered Saccharomyces cerevisiae without overexpression of a truncated HMG1 (t HMG1 )

Beta-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 beta-carotene from xylose, the sec- ond most abundant and inedible sugar component of lignocellulose biomass. Specifically, a beta-carotene biosynthetic pathway containing crtYB, crtI, and crtE from Xanthophyllomyces dendrorhous was introduced into a xylose-fermenting S. cerevisiae. Here, the resulting strain produced beta-carotene from xylose at a titer threefold higher than from glucose. Interestingly, overexpression of tHMG1, which has been reported as a critical genetic perturbation to enhance metabolic fluxes in the mevalonate pathway and beta-carotene production in yeast when glucose is used, did not further improve the production of beta-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 beta-carotene production to be a more respiratory feature of xylose consumption, a larger cytosolic acetyl!CoA pool, and an upregulated expression level of rate-limiting genes in the beta-carotene!producing pathway, including ACS1 and HMG1. As a result, 772.8 mg/L of beta-carotene was ob- tained in a fed-batch bioreactor culture with xylose feeding. Considering the in- evitable large scale production of xylose 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.

09 BIOMASS FUELS↗

Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.

59 BASIC BIOLOGICAL SCIENCES↗

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone

Abstract 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 ATP‐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 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources.

2‐pyrone synthase↗

Reductive amination cascades in cell‐free and resting whole cell formats for valorization of lignin deconstruction products

Abstract The selective introduction of amine groups within deconstruction products of lignin could provide an avenue for valorizing waste biomass while achieving a green synthesis of industrially relevant building blocks from sustainable sources. Here, we built and characterized enzyme cascades that create aldehydes and subsequently primary amines from diverse lignin‐derived carboxylic acids using a carboxylic acid reductase (CAR) and an ω‐transaminase (TA). Unlike previous studies that have paired CAR and TA enzymes, here we examine multiple homologs of each of these enzymes and a broader set of candidate substrates. In addition, we compare the performance of these systems in cell‐free and resting whole‐cell biocatalysis formats using the conversion of vanillate to vanillyl amine as model chemistry. We also demonstrate that resting whole cells can be recycled for multiple batch reactions. We used the knowledge gained from this study to produce several amines from carboxylic acid precursors using one‐pot biocatalytic reactions, several of which we report for the first time. These results expand our knowledge of these industrially relevant enzyme families to new substrates and contexts for environmentally friendly and potentially low‐cost synthesis of diverse aryl aldehydes and amines.

Biotechnology & Applied Microbiology↗

Enhancing Biomass Productivity by Forecast‐Informed Pond Operations

ABSTRACT Microalgal cultivation for biofuels and proteins holds significant promise but faces challenges in achieving economically viable biomass productivity under variable environmental conditions. This study introduces a forecast‐informed pond operation (FIPO) system that uses numerical weather prediction (NWP) ensemble forecasts and the biomass assessment tool (BAT) to optimize daily dilution rates for enhanced biomass production. In contrast to the current practice, where fixed dilution rates are based on operator experience, the FIPO system determines the optimal dilution rate based on future weather forecasts and biomass growth conditions. Our experiments validate the effectiveness of FIPO in both short‐ and long‐term growth scenarios. In short‐term experiments, FIPO increased biomass production by 21.3% compared to batch growth and 7.4% over fixed dilution (60% every 3 days) operations. The NWP forecast‐informed operations achieved biomass production nearly identical to that using perfect weather forecasts, highlighting the accuracy of current NWP forecasts for guiding pond operations. In long‐term experiments, FIPO resulted in biomass production increases of 13.3% and 17.8% compared to two fixed dilution rates (60% every 3 days and 20% daily). These findings underscore the viability of using NWP forecasts to optimize microalgal cultivation systems. By adjusting daily dilution rates in response to forecasted weather, operators can achieve higher biomass yields and mitigate risks associated with environmental variability. This study provides a foundation for future research and practical applications in commercial‐scale microalgal production.

Yan, Hongxiang [Energy and Environment Directorate↗

Hydrotreatment of Nylon 66 and Amide Model Compounds Over Sulfided NiMo Catalysts

Molybdenum sulfide-based catalysts, such as nickel–molybdenum on alumina (NiMoS x /Al 2 O 3 ), are widely used in hydrotreating and have potential for catalyzing waste plastic conversion via hydrogenolysis, yet their performance, such as reaction kinetics and network, for amide-rich polymer feeds is poorly defined. Here we combine Nylon 66 with the amide model compound, N,N-dibutylhexanediamide (DBDAD), to quantify hydrodeoxygenation (HDO) and hydrodenitrogenation (HDN) chemistry in a stirred batch reactor (53 bar H 2 , 280–320°C). DBDAD conversion is near-linear with time, indicating strong adsorption of the substrates on the active sites. Time-resolved product identification indicates parallel C─O first-cleavagedeoxygenation (DO) and C─N first-cleavagedenitrogenation (DN) sequences proceeding through amine and diol intermediates, respectively, to C 4 ─C 6 alkanes. Increasing temperature shifts selectivity toward DN, decreasing the initial r(DO)/r(DN) from 1.38 (280°C) to 0.69 (320°C), with an apparent activation energy of 173 kJ mol −1 for DBDAD conversion. At 300°C, nylon 66 converts faster than DBDAD, producing a complex mixture of oxygen- and nitrogen-containing species and an initial rate ratio r(DO)/r(DN) of 1.6. No heteroaromatic nitrogen products are detected by the method used. These results provide reaction pathways and product signatures relevant to hydro-processing catalysts exposed to polyamide-derived streams.

Nylon 66↗

Catalytic Activation of Polyethylene Model Compounds Over Metal-Exchanged Beta Zeolites

Decomposition of polymers by heterogeneous catalysts presents a promising approach for reuse of waste plastics. Here, we demonstrated non-hydrogenative decomposition of model polyolefins over proton-form and metal (Cu, Ni) ion-exchanged beta zeolites at moderate temperatures (ca. 300 degrees C). Near complete polyolefin decomposition was observed in batch reactions monitored by thermogravimetric analysis, while decomposition at partial conversion was studied in flow reactions. Ni-exchanged zeolites produced H 2 at substantially higher rates (> 10x) than other catalysts while also uniquely resisting deactivation over time. Application of the delplot formalism offered insights into the reaction network for polyolefin decomposition over Ni/BEA, most notably that H 2 is solely a primary product. We deduce that H 2 production is catalyzed by activation of C-H bonds at ionic Ni sites, and H 2 prevents buildup of polyaromatic coke species in Ni-exchanged zeolites that deactivate Cu-exchanged and protonic zeolites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strategies to achieve high productivity, high conversion, and high yield in yeast fermentation of algal biomass hydrolysate

The conversion of carbohydrates in biomass via fermentation is an important component of an overall strategy to decarbonize the production of fuels and chemicals. Owing to the cost and resources required to produce biomass hydrolysates, the economic and environmental sustainability of these fermentation processes requires that they operate with high yields, sugar conversion, and productivity. Immobilized-cell technology in a continuous bioprocess can achieve significantly higher volumetric productivities than is possible from standard batch fermentation using free cells. Here, we demonstrate approaches for improvement of ethanol yield from algal hydrolysates and a mock hydrolysate medium. Saccharomyces cerevisiae was immobilized in alginate and incorporated into a two-column immobilized cell reactor system. Furthermore, the yeast quorum-sensing molecule, 2-phenylethanol, was added to improve ethanol yield by restricting growth and diverting sugar to ethanol. The bioreactor system could achieve high ethanol volumetric productivity (>20 g/ Lreactor ·h) and high glucose conversion (>99%) in mock hydrolysate, while the addition of 0.2% 2-phenylethanol resulted in 4.9% higher ethanol yield. With an algal hydrolysate of <10 g/L sugar, the ethanol volumetric productivity reached 9.8 g/ Lreactor ·h, and the addition of 0.2% 2-phenylethanol increased the ethanol yield by up to 7.4%. These results demonstrate the feasibility of novel strategies to achieve sustainability goals in biomass conversions.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced prediction of Cs removal by CST from Hanford tank waste with K accountability

Abstract The treatment of Hanford tank waste is one of the most challenging environmental cleanup activities to date. To expedite the processing of liquid waste stored in underground tanks in Washington State it is necessary to remove the significant dose contributor, 137 Cs. Crystalline silicotitanate ion exchanger is currently used to remove 137 Cs from the aqueous phase of Hanford tank wastes in preparation for vitrification at the Waste Treatment and Immobilization Plant (WTP). Improving the understanding of potassium impacts on ion exchange behavior of Cs will help in the operation of a critical component of one of the most complex treatment processes in the world today. Optimization of this process can result in significant cost savings and less waste production. Toward this effort, a series of batch contact tests varied in potassium concentration were conducted to look at the impact of potassium concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using the ZAM model. A significant underprediction of Cs capacity in the presence of potassium was seen with the existing model. A revision of the equilibrium constants was determined and provided a statistically better fit for determining the Cs K d values in tank waste matrices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effect of dietary fiber fermentation on short‐chain fatty acid production and microbial composition in vitro

Abstract BACKGROUND The efficient utilization of fiber‐rich co‐products is important for optimizing feed resource utilization and animal health. This study was conducted to evaluate the fermentation characteristics of fiber‐rich co‐products, which had equal quantities of total dietary fiber (TDF), at different time points using batch in vitro methods. It considered their gas production, short‐chain fatty acid (SCFA) production, and microbial composition. RESULTS The fermentation of wheat bran (WB) and oat bran (OB) showed higher and faster ( P < 0.05) gas and SCFA production than corn bran (CB), sugar beet pulp (SBP), and soybean hulls (SH). The α ‐diversity was higher in the CB, SBP, and SH groups than in the WB and OB groups ( P < 0.05). At the phylum level, OB and WB fermentation showed lower ( P < 0.05) relative abundance of Actinobacteria than the CB, SBP, and SH groups. At the genus level, OB and WB fermentation increased the Enterococcus population in comparison with the CB, SBP, and SH groups, whereas CB and SBP fermentation improved the relative abundance of the Christensenellaceae R‐7 group more than the WB, OB, and SH groups ( P < 0.05). CONCLUSION Overall, WB and OB were rapidly fermented by fecal microbiota, in contrast with SBP, SH, and CB. Fermentation of different fiber‐rich co‐products with an equal TDF content gives different responses in terms of microbial composition and SCFA production due to variations in their physicochemical properties and molecular structure. © 2020 Society of Chemical Industry

Bai, Yu↗

Oxidation of methylamine

A detailed chemical kinetic model for oxidation of methylamine has been developed, based on theoretical work and a critical evaluation of data from the literature. In this work, the rate coefficients for the reactions of CH 3 NH 2 + O 2 → CH 2 NH 2 / CH 3 NH + HO 2 , CH 3 NH 2 + H → CH 3 + NH 3 , CH 3 NH → CH 2 NH 2 , and CH 3 NH + O 2 → CH 2 NH + HO 2 were calculated from ab initio theory. The mechanism was validated against experimental results from batch reactors, flow reactors, shock tubes, and premixed flames. The model predicts satisfactorily explosion limits for CH 3 NH 2 and its oxidation in a flow reactor. However, oxidation in the presence of nitric oxide, which strongly promotes reaction at lower temperatures, is only described qualitatively. Furthermore, calculated flame speeds are higher than reported experimental values; the model does not capture the inhibiting effect of the NH 2 group in CH 3 NH 2 compared to CH 4 . More work is desirable to confirm the products of the CH 3 NH + NO reaction and to look into possible pathways to NH 3 in methylamine oxidation.

10 SYNTHETIC FUELS↗

Unveiling the Role of Compositional Drifts on the Tack of Pressure‐Sensitive‐Adhesives

Abstract Pressure‐sensitive‐adhesives (PSAs) are pervasive in electronic, automobile, packaging, and biomedical applications due to their ability to stick to numerous surfaces without undergoing chemical reactions. These materials are typically synthesized by the free radical copolymerization of alkyl acrylates and acrylic acid, leading to an ensemble of polymer chains with varying composition and molecular weight. Here, reversible addition−fragmentation chain‐transfer (RAFT) copolymerizations in a semi‐batch reactor are used to tailor the molecular architecture and bulk mechanical properties of acrylic copolymers. In the absence of cross‐links, the localization of acrylic acid toward the chain ends leads to microphase separation, creep resistance, and enhanced tack. However, in the presence of Al(acac) 3 crosslinker, the creep resistance remains unchanged and mostly the large‐strain mechanical properties are affected. This behavior is attributed to microphase separation, but also to a change in the energy required to break physical associations, and untangle and elongate associative polymers to large deformations.

Polymer Science↗

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗

Intensive agricultural management‐induced subsurface accumulation of labile phosphorus in Midwestern agricultural soils dominated by tile lines

Abstract In addition to surface runoff, subsurface P loss through tile lines in agricultural lands has received attention over the last decade. It is not clearly understood how this strong ligand, phosphate, is distributed in subsoils (≤180 cm), contributing to subsurface P loss. We hypothesized that subsurface accumulation of labile P as a result of long‐term intensive agricultural management contributes to subsurface P loss. The depth sequence distribution of P and its speciation and reactivity were investigated in tile‐line‐dominated Midwestern agricultural fields via chemical extraction and digestion, batch desorption experiments, and X‐ray absorption near‐edge structure spectroscopy. The results suggest that labile P in subsoils exceeds the eutrophication‐inducing level (>0.01 mg L –1 ). Because of intensive agricultural management, total P was ∼400 mg kg –1 in surface soils and ∼200‐300 mg kg –1 in subsoils. The depth sequence distribution of P indicated the translocation of P to subsoils. Although phosphate and phytic acid adsorbed by Al or Fe (oxyhydro)oxides and calcite were found in surface soils, phosphate adsorbed to calcite, hydroxyapatite, or both were the dominant P species in subsoils. Phosphate was highest in surface soils and decreased sharply with increasing depth. Slightly alkaline soil in subsoils suppressed the release of P but the process was continuous after 30 d. Subsurface P loss was influenced by the dissolution and desorption process of inorganic P phases and preferentially transported P from surface soils. Subsurface P loss should be considered in strategies to reduce agricultural P loss in the Gulf of Mexico.

Xu, Suwei↗

Core–Multishell-Structured Digital-Gradient Cathode Materials with Enhanced Mechanical and Electrochemical Durability

Ni-rich cathode materials provide high energy density, but their structural and surface instability limits their cyclability and thermal stability. As one of the approaches to mitigate this problem, cathode materials comprising Ni-rich high-capacity core wrapped in Mn-rich multiple shells are produced successfully. In contrast to the conventional batch-type process for concentration-gradient materials, a digital-gradient cascade coprecipitation process described here achieves the improvements in productivity and quality consistency needed to move toward large-scale manufacturing. The core-multishell cathode materials produced in this manner not only have longer cycle life and improved rate performance compared to homogeneous Ni-rich cathode materials having the same overall composition, but also show remarkably enhanced thermal stability and low impedance growth characteristics. In a novel attempt to determine the correlation between the mechanical properties of the core-multishell cathode particles and their electrochemical cyclabilities, their breaking force and elasticity were successfully measured using a statistical approach, which indicates that a cathode particle with stable surface composition as well as high breaking force has improved capacity retention and durability. These results guide the realization of long life and high thermal stability in Ni-rich cathode materials through heterogeneous particle engineering.

25 ENERGY STORAGE↗