Biological signal processing filters via engineering allosteric transcription factors.

Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-ß-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF-ON-OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON-OFF-ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden-representing a paradigm shift in general gene regulation.

Support Pore Structure and Composition Strongly Influence the Direct Air Capture of CO2 on Supported Amines.

A variety of amine-impregnated porous solid sorbents for direct air capture (DAC) of CO2 have been developed, yet the effect of amine-solid support interactions on the CO2 adsorption behavior is still poorly understood. When tetraethylenepentamine (TEPA) is impregnated on two different supports, commercial γ-Al2O3 and MIL-101(Cr), they show different trends in CO2 sorption when the temperature (-20 to 25 °C) and humidity (0-70% RH) of the simulated air stream are varied. In situ IR spectroscopy is used to probe the mechanism of CO2 sorption on the two supported amine materials, with weak chemisorption (formation of carbamic acid) being the dominant pathway over MIL-101(Cr)-supported TEPA and strong chemisorption (formation of carbamate) occurring over γ-Al2O3-supported TEPA. Formation of both carbamic acid and carbamate species is enhanced over the supported TEPA materials under humid conditions, with the most significant enhancement observed at -20 °C. However, while equilibrium H2O sorption is high at cold temperatures (e.g., -20 °C), the effect of humidity on a practical cyclic DAC process is expected to be minimal due to slow H2O uptake kinetics. This work suggests that the CO2 capture mechanisms of impregnated amines can be controlled by adjusting the degree of amine-solid support interaction and that H2O adsorption behavior is strongly affected by the properties of the support materials. Thus, proper selection of solid support materials for amine impregnation will be important for achieving optimized DAC performance under varied deployment conditions, such as cold (e.g., -20 °C) or ambient temperature (e.g., 25 °C) operations.

Perspective - the need and prospects for negative emission technologies - direct air capture through the lens of current sorption process development.

We provide a perspective on the development of direct air capture (DAC) as a leading candidate for implementing negative emissions technology (NET). We introduce DAC based on sorption, both liquid and solid, and draw attention to challenges that these technologies will face. We provide an analysis of the limiting mass transfer in the liquid and solid systems and highlight the differences.

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations.

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004-2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.

Engineering allosteric transcription factors guided by the LacI topology.

Allosteric transcription factors (aTFs) are used in a myriad of processes throughout biology and biotechnology. aTFs have served as the workhorses for developments in synthetic biology, fundamental research, and protein manufacturing. One of the most utilized TFs is the lactose repressor (LacI). In addition to being an exceptional tool for gene regulation, LacI has also served as an outstanding model system for understanding allosteric communication. In this perspective, we will use the LacI TF as the principal exemplar for engineering alternate functions related to allostery-i.e., alternate protein DNA interactions, alternate protein-ligand interactions, and alternate phenotypic mechanisms. In addition, we will summarize the design rules and heuristics for each design goal and demonstrate how the resulting design rules and heuristics can be extrapolated to engineer other aTFs with a similar topology-i.e., from the broader LacI/GalR family of TFs.

Performance Prediction of Fundamental Transcriptional Programs.

Transcriptional programming leverages systems of engineered transcription factors to impart decision-making (e.g., Boolean logic) in chassis cells. The number of components used to construct said decision-making systems is rapidly increasing, making an exhaustive experimental evaluation of iterations of biological circuits impractical. Accordingly, we posited that a predictive tool is needed to guide and accelerate the design of transcriptional programs. The work described here involves the development and experimental characterization of a large collection of network-capable single-INPUT logical operations─i.e., engineered BUFFER (repressor) and engineered NOT (antirepressor) logical operations. Using this single-INPUT data and developed metrology, we were able to model and predict the performances of all fundamental two-INPUT compressed logical operations (i.e., compressed AND gates and compressed NOR gates). In addition, we were able to model and predict the performance of compressed mixed phenotype logical operations (A NIMPLY B gates and complementary B NIMPLY A gates). These results demonstrate that single-INPUT data is sufficient to accurately predict both the qualitative and quantitative performance of a complex circuit. Accordingly, this work has set the stage for the predictive design of transcriptional programs of greater complexity.

Direct Air Capture of CO2 Using Poly(ethyleneimine)-Functionalized Expanded Poly(tetrafluoroethylene)/Silica Composite Structured Sorbents.

The rapidly increasing atmospheric CO2 concentration has driven research into the development of cost- and energy-efficient materials and processes for the direct air capture of CO2 (DAC). Solid-supported amine materials can give high CO2 uptakes and acceptable sorption kinetics, but they are generally prepared in powder forms that are likely not practically deployable in large-scale operations due to significant pressure drops associated with packed-bed gas-solid contactors. To this end, the development of effective gas-solid contactors for CO2 capture technologies is important to allow processing high flow rates of gas with low-pressure drops and high mass transfer rates. In this study, we demonstrate new laminate-supported amine CO2 sorbents based on the impregnation of low-molecular-weight, branched poly(ethyleneimine) (PEI) into an expanded poly(tetrafluoroethylene) (ePTFE) sheet matrix containing embedded silica particles to form free-standing sheets amenable to incorporation into structured gas-solid contactors. The free-standing sheets are functionalized with PEI using a highly scalable wet impregnation method. This method allowed controllable PEI distribution and enough porosity retained inside the sheets to enable practical CO2 capacities ranging from 0.4 to 1.6 mmol CO2/gsorbent under dry conditions. Reversible CO2 capacities are achieved under both dry and humid temperature swing cycles, indicating promising material stability. The specific thermal energy requirement for the regeneration based on the measured CO2 and water capacities is 287 kJ/mol CO2, where the molar ratio of water to CO2 of 3.1 is achieved using hydrophobic materials. This is the lowest molar ratio among published DAC sorbents. A larger laminate module is tested under conditions closer to larger-scale operations (linear velocities 0.03, 0.05, and 0.1 m/sec) and demonstrates a stable capacity of 0.80 CO2/gsorbent over five cycles of CO2 adsorption and steam regeneration. The PEI-impregnated ePTFE/silica composite sorbent/contactors demonstrate promising DAC performance derived from the amine-filled silica particles contained in hydrophobic ePTFE domains to reduce water sorption and its concomitant regeneration energy penalty.

Defining Targets for Adsorbent Material Performance to Enable Viable BECCS Processes.

Target properties of CO2 capture adsorbents that would ensure economic viability of bioenergy with carbon capture and storage (BECCS) are defined. The key role of sorbent lifetime in the process cost is demonstrated, and an optimal heat of adsorption for BECCS is postulated through a balance of adsorbent-adsorbate affinity and regeneration energy demand. Using an exponential decay model of sorbent capacity increases the process cost and results in an optimum sorbent lifetime. To ensure a levelized cost of carbon below $100/tonne-CO2, adsorbents should be designed to have working capacities above 0.75 mol/kg, lifetimes over 2 years, heats of adsorption of approximately -40 kJ/mol, and exponential degradation decay constants below 5 × 10-6 cycle-1 (equivalent to a half-life of 1.3 years). Our model predicts a BECCS process cost of $65/t-CO2 can be achieved with a degradation-resistant adsorbent, $40/kg sorbent cost, 2.0 mol/kg working capacity, -40 kJ/mol heat of adsorption, and at least a 2 year lifetime.

Designing the bioproduction of Martian rocket propellant via a biotechnology-enabled in situ resource utilization strategy.

Mars colonization demands technological advances to enable the return of humans to Earth. Shipping the propellant and oxygen for a return journey is not viable. Considering the gravitational and atmospheric differences between Mars and Earth, we propose bioproduction of a Mars-specific rocket propellant, 2,3-butanediol (2,3-BDO), from CO2, sunlight and water on Mars via a biotechnology-enabled in situ resource utilization (bio-ISRU) strategy. Photosynthetic cyanobacteria convert Martian CO2 into sugars that are upgraded by engineered Escherichia coli into 2,3-BDO. A state-of-the-art bio-ISRU for 2,3-BDO production uses 32% less power and requires a 2.8-fold higher payload mass than proposed chemical ISRU strategies, and generates 44 tons of excess oxygen to support colonization. Attainable, model-guided biological and materials optimizations result in an optimized bio-ISRU that uses 59% less power and has a 13% lower payload mass, while still generating 20 tons excess oxygen. Addressing the identified challenges will advance prospects for interplanetary space travel.

Biomolecular Systems Engineering: Unlocking the Potential of Engineered Allostery via the Lactose Repressor Topology.

Allosteric function is a critical component of many of the parts used to construct gene networks throughout synthetic biology. In this review, we discuss an emerging field of research and education, biomolecular systems engineering, that expands on the synthetic biology edifice-integrating workflows and strategies from protein engineering, chemical engineering, electrical engineering, and computer science principles. We focus on the role of engineered allosteric communication as it relates to transcriptional gene regulators-i.e., transcription factors and corresponding unit operations. In this review, we (a) explore allosteric communication in the lactose repressor LacI topology, (b) demonstrate how to leverage this understanding of allostery in the LacI system to engineer non-natural BUFFER and NOT logical operations, (c) illustrate how engineering workflows can be used to confer alternate allosteric functions in disparate systems that share the LacI topology, and (d) demonstrate how fundamental unit operations can be directed to form combinational logical operations.

Life cycle energy and greenhouse gas emissions for an ethanol production process based on blue-green algae.

Ethanol can be produced via an intracellular photosynthetic process in cyanobacteria (blue-green algae), excreted through the cell walls, collected from closed photobioreactors as a dilute ethanol-in-water solution, and purified to fuel grade ethanol. This sequence forms the basis for a biofuel production process that is currently being examined for its commercial potential. In this paper, we calculate the life cycle energy and greenhouse gas emissions for three different system scenarios for this proposed ethanol production process, using process simulations and thermodynamic calculations. The energy required for ethanol separation increases rapidly for low initial concentrations of ethanol, and, unlike other biofuel systems, there is little waste biomass available to provide process heat and electricity to offset those energy requirements. The ethanol purification process is a major consumer of energy and a significant contributor to the carbon footprint. With a lead scenario based on a natural-gas-fueled combined heat and power system to provide process electricity and extra heat and conservative assumptions around the ethanol separation process, the net life cycle energy consumption, excluding photosynthesis, ranges from 0.55 MJ/MJ(EtOH) down to 0.20 MJ/ MJ(EtOH), and the net life cycle greenhouse gas emissions range from 29.8 g CO2e/MJ(EtOH) down to 12.3 g CO2e/MJ(EtOH) for initial ethanol concentrations from 0.5 wt % to 5 wt %. In comparison to gasoline, these predicted values represent 67% and 87% reductions in the carbon footprint for this ethanol fuel on a energy equivalent basis. Energy consumption and greenhouse gas emissions can be further reduced via employment of higher efficiency heat exchangers in ethanol purification and/ or with use of solar thermal for some of the process heat.

Engineering allosteric communication.

Protein allostery is a vitally important protein function that has proven to be a vexing problem to understand at the molecular level. Allosteric communication is a hallmark of many protein functions. However, despite more than four decades of study the details regarding allosteric communication in protein systems are still being developed. Engineering of LacI and related homologues to confer alternate allosteric communication has shed light on the pre-requisites for the de novo design of allosteric communication. While the de novo design of an allosteric pathway and complementary functional surfaces has not been realized, this review highlights recent advances that set the stage for true predictive design for a given protein topology.

Solvent Selection for Lignin Value Prior to Pulping.

Solvent selection guides are crucial in chemical process design and development. Lignin from lignocellulosic biomass is a potentially attractive feedstock for sustainable chemical feedstocks. One approach would use a solvent to recover lignin prior to the traditional pulping process to make cellulose fibers: lignin value prior to pulping (LVPP). A solvent selection methodology for LVPP is presented herein that may be expanded for any proposed solvent for this process. Four screening categories are elucidated, providing metrics for 30 solvents across multiple molecular functional groups. Through performance, hazards and environment, cost and availability, and process-economics screens, the initial list of solvents is reduced to two top-tier candidates, 1,6 hexamethylenediamine and diethanolamine. 1-Methylpiperazine also emerged as a potential candidate. This solvent-selection methodology streamlines experimentation and provides promising candidates for LVPP. In addition to creating a tailored solvent selection guide, valuable biomass pretreatment data that may be utilized in different renewable applications are also presented.

Similarities in Recalcitrant Structures of Industrial Non-Kraft and Kraft Lignin.

This work compares the structure of industrially isolated lignin samples from kraft pulping and three alternative processes: butanol organosolv, supercritical water hydrolysis, and sulfur dioxide/ethanol/water fractionation. Kraft processes are known to produce highly condensed lignin, with reduced potential for catalytic depolymerization, whereas the alternative processes have been hypothesized to impact the lignin less. The structural properties most relevant to catalytic depolymerization are characterized by elemental analysis, quantitative 13 C and 2 D HQSC NMR spectroscopy, gel permeation chromatography, and thermogravimetric analysis. Quantification of the ß-O-4 ether bond content shows partial depolymerization, with all samples having less than 12 bonds per 100 aromatic units. This results in theoretical monomer yields of less than 5 %, strongly suggesting the alternative fractionation processes generate highly condensed lignin structures that are no more suitable for catalytic depolymerization than kraft lignin. However, the different thermal degradation profiles suggest there are physicochemical differences that could be leveraged in other valorization strategies.

Emissions from carpet combustion in a pilot-scale rotary kiln: comparison with coal and particle-board combustion.

The use of post-consumer carpet as a potential fuel substitute in cement kilns and other high-temperature processes is being considered to address the problem of huge volumes of carpet waste and the opportunity of waste-to-energy recovery. Carpet represents a high volume waste stream, provides high energy value, and contains other recoverable materials for the production of cement. This research studied the emission characteristics of burning 0.46-kg charges of chopped nylon carpet squares, pulverized coal, and particle-board pellets in a pilot-scale natural gas-fired rotary kiln. Carpet was tested with different amounts of water added. Emissions of oxygen, carbon dioxide, nitric oxide (NO), sulfur dioxide (SO2), carbon monoxide (CO), and total hydrocarbons and temperatures were continuously monitored. It was found that carpet burned faster and more completely than coal and particle board, with a rapid volatile release that resulted in large and variable transient emission peaks. NO emissions from carpet combustion ranged from 0.06 to 0.15 g/MJ and were inversely related to CO emissions. Carpet combustion yielded higher NO emissions than coal and particle-board combustion, consistent with its higher nitrogen content. SO2 emissions were highest for coal combustion, consistent with its higher sulfur content than carpet or particle board. Adding water to carpet slowed its burn time and reduced variability in the emission transients, reducing the CO peak but increasing NO emissions. Results of this study indicate that carpet waste can be used as an effective alternative fuel, with the caveats that it might be necessary to wet carpet or chop it finely to avoid excessive transient puff emissions due to its high volatility compared with other solid fuels, and that controlled mixing of combustion air might be used to control NO emissions from nylon carpet.

Critical Comparison of Structured Contactors for Adsorption-Based Gas Separations.

Recent advances in adsorptive gas separations have focused on the development of porous materials with high operating capacity and selectivity, useful parameters that provide early guidance during the development of new materials. Although this material-focused work is necessary to advance the state of the art in adsorption science and engineering, a substantial problem remains: how to integrate these materials into a fixed bed to efficiently utilize the separation. Structured sorbent contactors can help manage kinetic and engineering factors associated with the separation, including pressure drop, sorption enthalpy effects, and external heat integration (for temperature swing adsorption, or TSA). In this review, we discuss monoliths and fiber sorbents as the two main classes of structured sorbent contactors; recent developments in their manufacture; advantages and disadvantages of each structure relative to each other and to pellet packed beds; recent developments in system modeling; and finally, critical needs in this area of research.

Identifying the interacting positions of a protein using Boolean learning and support vector machines.

It is known that in the three-dimensional structure of a protein, certain amino acids can interact with each other in order to provide structural integrity or aid in its catalytic function. If these positions are mutated the loss of this interaction usually leads to a non-functional protein. Directed evolution experiments, which probe the sequence space of a protein through mutations in search for an improved variant, frequently result in such inactive sequences. In this work, we address the use of machine learning algorithms, Boolean learning and support vector machines (SVMs), to find such pairs of amino acid positions. The recombination method of imparting mutations was simulated to create in silico sequences that were used as training data for the algorithms. The two algorithms were combined together to develop an approach that weighs the structural risk as well as the empirical risk to solve the problem. This strategy was adapted to a multi-round framework of experiments where the data generated in the present round is used to design experiments for the next round to improve the generated library, as well as the estimation of the interacting positions. It is observed that this strategy can greatly improve the number of functional variants that are generated as well as the average number of mutations that can be made in the library.

Pooling for improved screening of combinatorial libraries for directed evolution.

Following diversity generation in combinatorial protein engineering, a significant amount of effort is expended in screening the library for improved variants. Pooling, or combining multiple cells into the same assay well when screening, is a means to increase throughput and screen a larger portion of the library with less time and effort. We have developed and validated a Monte Carlo simulation model of pooling and used it to screen a library of beta-galactosidase mutants randomized in the active site to increase their activity toward fucosides. Here, we show that our model can successfully predict the number of highly improved mutants obtained via pooling and that pooling does increase the number of good mutants obtained. In unpooled conditions, we found a total of three mutants with higher activity toward p-nitrophenyl-beta-D-fucoside than that of the wild-type beta-galactosidase, whereas when pooling 10 cells per well we found a total of approximately 10 improved mutants. In addition, the number of "supermutants", those with the highest activity increase, was also higher when pooling was used. Pooling is a useful tool for increasing the efficiency of screening combinatorial protein engineering libraries.

Simulation modeling of pooling for combinatorial protein engineering.

Pooling in directed-evolution experiments will greatly increase the throughput of screening systems, but important parameters such as the number of good mutants created and the activity level increase of the good mutants will depend highly on the protein being engineered. The authors developed and validated a Monte Carlo simulation model of pooling that allows the testing of various scenarios in silico before starting experimentation. Using a simplified test system of 2 enzymes, betagalactosidase (supermutant, or greatly improved enzyme) and beta-glucuronidase (dud, or enzyme with ancestral level of activity), the model accurately predicted the number of supermutants detected in experiments within a factor of 2. Additional simulations using more complex activity distributions show the versatility of the model. Pooling is most suited to cases such as the directed evolution of new function in a protein, where the background level of activity is minimized, making it easier to detect small increases in activity level. Pooling is most successful when a sensitive assay is employed. Using the model will increase the throughput of screening procedures for directed-evolution experiments and thus lead to speedier engineering of proteins.