Graphical Abstract Illustration of the assembly, distribution, and point-of-care use of a rapidly-deployable, cell-free COVID-19 biosensor: 1) Assemble: Assembling CFPS reagents by mixing E. coli lysate, murine RNase Inhibitor (mRI), energy sources, cofactors, and toehold switch riboregulator plasmid. 2) Print: aliquoting CFPS reagents onto paper substrates housed in a plastic test cassette. 3) Dehydrate: lyophilizing CFPS reagents on paper substrates. 4) Distribute. 5) Saliva sample: applying saliva samples onto cassette without pretreatments. 6) Reaction: bioluminescent protein expression in presence of target RNA (+), or ribosome detachment in absence of target RNA (-). 7) Visual result: bioluminescent output in the presence of target RNA and NanoLuc luciferase expression.
Nuclear receptors (NRs) influence nearly every system of the body and our lives depend on correct NR signaling. Thus, a key environmental and pharmaceutical quest is to identify and detect chemicals which interact with nuclear hormone receptors, including endocrine disrupting chemicals (EDCs), therapeutic receptor modulators, and natural hormones. Previously reported biosensors of nuclear hormone receptor ligands facilitated rapid detection of NR ligands using cell-free protein synthesis (CFPS). In this work, the advantages of CFPS are further leveraged and combined with kinetic analysis, autoradiography, and western blot to elucidate the molecular mechanism of this biosensor. Additionally, mathematical simulations of enzyme kinetics are used to optimize the biosensor assay, ultimately lengthening its readable window by five-fold and improving sensor signal strength by two-fold. This approach enabled the creation of an on-demand thyroid hormone biosensor with an observable color-change readout. This mathematical and experimental approach provides insight for engineering rapid and field-deployable CFPS biosensors and promises to improve methods for detecting natural hormones, therapeutic receptor modulators, and EDCs.
Diagnostic blood tests can guide the administration of healthcare to save and improve lives. Most clinical biosensing blood tests require a trained technician and specialized equipment to process samples and interpret results, which greatly limits test accessibility. Colorimetric paper-based diagnostics have an equipment-free readout, but raw blood obscures a colorimetric response which has motivated diverse efforts to develop blood sample processing techniques. This work uses inexpensive readily-available materials to engineer user-friendly dilution and filtration methods for blood sample collection and processing to enable a proof-of-concept colorimetric biosensor that is responsive to glutamine in 50 µL blood drop samples in less than 30 min. Paper-based user-friendly blood sample collection and processing combined with CFPS biosensing technology represents important progress towards the development of at-home biosensors that could be broadly applicable to personalized healthcare.
Cell‐free protein synthesis (CFPS) is a versatile biotechnology platform enabling a broad range of applications including clinical diagnostics, large‐scale production of officinal therapeutics, small‐scale on‐demand production of personal magistral therapeutics, and exploratory research. The shelf stability and scalability of CFPS systems also have the potential to overcome cost and infrastructure challenges for distributing and using essential medical tests at home in both high‐ and low‐income countries. However, CFPS systems are often more time‐consuming and expensive to prepare than traditional in vivo systems, limiting their broader use. Much work has been done to lower CFPS costs by optimizing cell extract preparation, small molecule reagent recipes, and DNA template preparation. In order to further reduce reagent cost and preparation time, this work presents a CFPS system that does not require separately purified DNA template. Instead, a DNA plasmid encoding the recombinant protein is transformed into the cells used to make the extract, and the extract preparation process is modified to allow enough DNA to withstand homogenization‐induced shearing. The finished extract contains sufficient levels of intact DNA plasmid for the CFPS system to operate. For a 10 mL scale CFPS system expressing recombinant sfGFP protein for a biosensor, this new system reduces reagent cost by more than half. This system is applied to a proof‐of‐concept glutamine sensor compatible with smartphone quantification to demonstrate its viability for further cost reduction and use in low‐resource settings.
Several recently introduced approaches use neural networks as probabilistic models for protein sequence design. These models use various objective functions and optimization schemes. The choice of objective function and optimization scheme comes with trade-offs that are not always well explained. We introduce probabilistic definitions of protein stability and conformational specificity and show how these chemical properties relate to the p(structure|seq) objective used in recent protein design algorithms. This links probabilistic objective functions to experimentally testable outcomes. We present a new sequence decoding algorithm, termed "BayesDesign", that uses Bayes' Rule to maximize the p(structure|seq) objective. We provide experimental evaluation of BayesDesign in the context of two protein model systems, the NanoLuc enzyme and the WW structural motif.
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