Engineering an allosteric transcription factor to respond to new ligands.

Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl ß-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.

Genetically encoded sensors enable real-time observation of metabolite production.

Engineering cells to produce valuable metabolic products is hindered by the slow and laborious methods available for evaluating product concentration. Consequently, many designs go unevaluated, and the dynamics of product formation over time go unobserved. In this work, we develop a framework for observing product formation in real time without the need for sample preparation or laborious analytical methods. We use genetically encoded biosensors derived from small-molecule responsive transcription factors to provide a fluorescent readout that is proportional to the intracellular concentration of a target metabolite. Combining an appropriate biosensor with cells designed to produce a metabolic product allows us to track product formation by observing fluorescence. With individual cells exhibiting fluorescent intensities proportional to the amount of metabolite they produce, high-throughput methods can be used to rank the quality of genetic variants or production conditions. We observe production of several renewable plastic precursors with fluorescent readouts and demonstrate that higher fluorescence is indeed an indicator of higher product titer. Using fluorescence as a guide, we identify process parameters that produce 3-hydroxypropionate at 4.2 g/L, 23-fold higher than previously reported. We also report, to our knowledge, the first engineered route from glucose to acrylate, a plastic precursor with global sales of $14 billion. Finally, we monitor the production of glucarate, a replacement for environmentally damaging detergents, and muconate, a renewable precursor to polyethylene terephthalate and nylon with combined markets of $51 billion, in real time, demonstrating that our method is applicable to a wide range of molecules.

Synthetic biosensors for precise gene control and real-time monitoring of metabolites.

Characterization and standardization of inducible transcriptional regulators has transformed how scientists approach biology by allowing precise and tunable control of gene expression. Despite their utility, only a handful of well-characterized regulators exist, limiting the complexity of engineered biological systems. We apply a characterization pipeline to four genetically encoded sensors that respond to acrylate, glucarate, erythromycin and naringenin. We evaluate how the concentration of the inducing chemical relates to protein expression, how the extent of induction affects protein expression kinetics, and how the activation behavior of single cells relates to ensemble measurements. We show that activation of each sensor is orthogonal to the other sensors, and to other common inducible systems. We demonstrate independent control of three fluorescent proteins in a single cell, chemically defining eight unique transcriptional states. To demonstrate biosensor utility in metabolic engineering, we apply the glucarate biosensor to monitor product formation in a heterologous glucarate biosynthesis pathway and identify superior enzyme variants. Doubling the number of well-characterized inducible systems makes more complex synthetic biological circuits accessible. Characterizing sensors that transduce the intracellular concentration of valuable metabolites into fluorescent readouts enables high-throughput screening of biological catalysts and alleviates the primary bottleneck of the metabolic engineering design-build-test cycle.

Evolution-guided optimization of biosynthetic pathways.

Engineering biosynthetic pathways for chemical production requires extensive optimization of the host cellular metabolic machinery. Because it is challenging to specify a priori an optimal design, metabolic engineers often need to construct and evaluate a large number of variants of the pathway. We report a general strategy that combines targeted genome-wide mutagenesis to generate pathway variants with evolution to enrich for rare high producers. We convert the intracellular presence of the target chemical into a fitness advantage for the cell by using a sensor domain responsive to the chemical to control a reporter gene necessary for survival under selective conditions. Because artificial selection tends to amplify unproductive cheaters, we devised a negative selection scheme to eliminate cheaters while preserving library diversity. This scheme allows us to perform multiple rounds of evolution (addressing ∼10(9) cells per round) with minimal carryover of cheaters after each round. Based on candidate genes identified by flux balance analysis, we used targeted genome-wide mutagenesis to vary the expression of pathway genes involved in the production of naringenin and glucaric acid. Through up to four rounds of evolution, we increased production of naringenin and glucaric acid by 36- and 22-fold, respectively. Naringenin production (61 mg/L) from glucose was more than double the previous highest titer reported. Whole-genome sequencing of evolved strains revealed additional untargeted mutations that likely benefit production, suggesting new routes for optimization.

Modeling industrial centrifugation of mammalian cell culture using a capillary based scale-down system.

Continuous-flow centrifugation is widely utilized as the primary clarification step in the recovery of biopharmaceuticals from cell culture. However, it is a challenging operation to develop and characterize due to the lack of easy to use, small-scale, systems that can be used to model industrial processes. As a result, pilot-scale continuous centrifugation is typically employed to model large-scale systems requiring a significant amount of resources. In an effort to reduce resource requirements and create a system which is easy to construct and utilize, a capillary shear device, capable of producing energy dissipation rates equivalent to those present in the feed zones of industrial disk stack centrifuges, was developed and evaluated. When coupled to a bench-top, batch centrifuge, the capillary device reduced centrate turbidity prediction error from 37% to 4% compared to using a bench-top centrifuge alone. Laboratory-scale parameters that are analogous to those routinely varied during industrial-scale continuous centrifugation were identified and evaluated for their utility in emulating disk stack centrifuge performance. The resulting relationships enable bench-scale process modeling of continuous disk stack centrifuges using an easily constructed, scalable, capillary shear device coupled to a typical bench-top centrifuge.

A pragmatic methodology for the evaluation of digital care management in the context of multimorbidity.

Multimorbidity is a defining challenge for health systems and requires coordination of care delivery and care management. Care management is a clinical service designed to remotely engage patients between visits and after discharge in order to support self-management of chronic and emergent conditions, encourage increased use of scheduled care and address the use of unscheduled care. Care management can be provided using digital technology - digital care management. A robust methodology to assess digital care management, or any traditional or digital primary care intervention aimed at longitudinal management of multimorbidity, does not exist outside of randomized controlled trials (RCTs). RCTs are not always generalizable and are also not feasible for most healthcare organizations. We describe here a novel and pragmatic methodology for the evaluation of digital care management that is generalizable to any longitudinal intervention for multimorbidity irrespective of its mode of delivery. This methodology implements propensity matching with bootstrapping to address some of the major challenges in evaluation including identification of robust outcome measures, selection of an appropriate control population, small sample sizes with class imbalances, and limitations of RCTs. We apply this methodology to the evaluation of digital care management at a U.S. payor and demonstrate a 9% reduction in ER utilization, a 17% reduction in inpatient admissions, and a 29% increase in the utilization of preventive medicine services. From these utilization outcomes, we drive forward an estimated cost saving that is specific to a single payor's payment structure for the study time period of $641 per-member-per-month at 3 months. We compare these results to those derived from existing observational approaches, 1:1 and 1:n propensity matching, and discuss the circumstances in which our methodology has advantages over existing techniques. Whilst our methodology focuses on cost and utilization and is applied in the U.S. context, it is applicable to other outcomes such as Patient Reported Outcome Measures (PROMS) or clinical biometrics and can be used in other health system contexts where the challenge of multimorbidity is prevalent.

Multiplexed Engineering in Biology.

Biotechnology is the manufacturing technology of the future. However, engineering biology is complex, and many possible genetic designs must be evaluated to find cells that produce high levels of a desired drug or chemical. Recent advances have enabled the design and construction of billions of genetic variants per day, but evaluation capacity remains limited to thousands of variants per day. Here we evaluate biological engineering through the lens of the design­build­test cycle framework and highlight the role that multiplexing has had in transforming the design and build steps. We describe a multiplexed solution to the 'test' step that is enabled by new research. Achieving a multiplexed test step will permit a fully multiplexed engineering cycle and boost the throughput of biobased product development by up to a millionfold.

Biosensor-based engineering of biosynthetic pathways.

Biosynthetic pathways provide an enzymatic route from inexpensive renewable resources to valuable metabolic products such as pharmaceuticals and plastics. Designing these pathways is challenging due to the complexities of biology. Advances in the design and construction of genetic variants has enabled billions of cells, each possessing a slightly different metabolic design, to be rapidly generated. However, our ability to measure the quality of these designs lags by several orders of magnitude. Recent research has enabled cells to report their own success in chemical production through the use of genetically encoded biosensors. A new engineering discipline is emerging around the creation and application of biosensors. Biosensors, implemented in selections and screens to identify productive cells, are paving the way for a new era of biotechnological progress.

Downstream antibody purification using aqueous two-phase extraction.

The extraction of antibodies using a polyethylene glycol (PEG)-citrate aqueous two-phase system (ATPS) was investigated. Studies using purified monoclonal antibody (mAb) identified operating ranges for successful phase formation and factors that significantly affected antibody partitioning. The separation of antibody and host cell protein (HCP) from clarified cell culture media was examined using statistical design of experiments (DOE). The partitioning of antibody was nearly complete over the entire range of the operating space examined. A model of the HCP partitioning was generated in which both NaCl and citrate concentrations were identified as significant factors. To achieve the highest purity, the partitioning of HCP from cell culture fluid into the product containing phase was minimized using a Steepest Descent algorithm. An optimal ATPS consisting of 14.0% (w/w) PEG, 8.4% (w/w) citrate, and 7.2% (w/w) NaCl at pH 7.2 resulted in a product yield of 89%, an approximate 7.6-fold reduction in HCP levels relative to the clarified cell culture fluid before extraction and an overall purity of 70%. A system consisting of 15% (w/w) PEG, 8% (w/w) citrate, and 15% (w/w) NaCl at pH 5.5 reduced product-related impurities (aggregates and low molecular product fragments) from ∼40% to less than 0.5% while achieving 95% product recovery. At the experimental conditions that were optimized in the batch mode, a scale-up model for the use of counter-current extraction technology was developed to identify potential improvements in purity and recovery that could be realized in the continuous operational mode.