Properties & Performance

Bottleneck/Challenge: De novo engineering of nucleic acid assemblies that interface with biological environments remains challenging.

Potential Solution: Develop modular nucleic acid assemblies with easily reconfigurable interfaces that form in physiological conditions and are robust to degradation.

Potential Solution: Develop peptide/protein-DNA, peptide/protein-RNA conjugates that can introduce functionalities to the reconfigurable interfaces.

Potential Solution: Develop nucleic acid structures that have programmable material/mesh features but reduced nanoscale complexity/rigidity, minimizing complex folding protocols and that would be compatible with physiological production.

Potential Solution: Integrate and control nucleic acid production and assembly with biological or biomaterial signals.

Potential Solution: Engineer synthetic proteins and polymers comprising of synthetic chemistries that enable tunable structural, chemical, and biophysical properties.

Bottleneck/Challenge: It is challenging to obtain molecular materials with predictable responses, for example graded response (predictable response to input change) and homeostatic response (minimal effects of perturbations such as changes in temperature or nutrient).

Potential Solution: Introduction of negative feedback genetic circuits to cells to allow for self-regulation of expression of specific proteins participating in multi-component materials.

Potential Solution: Use of RNA or de novo proteins to enable integral feedback control of expression of material components.

Bottleneck/Challenge: Lack of molecular feedback architectures tailored to orchestrate multi-component material expression.

Potential Solution: Expand integral feedback control circuits for multi-output regulation.

Potential Solution: Nested, hierarchically organized feedback loops for expression of complex materials.

Bottleneck/Challenge: Scarcity of models and theoretical tools to guide the design of complex material responses that are robust to uncertain processes and perturbations, including growth rate variability, resource fluctuations, temperature and pH.

Potential Solution: Develop data-driven models linking material response (output) to a range of undesired perturbations (disturbances).

Potential Solution: Develop model-based strategies to minimize the effects of disturbances, test them experimentally, and revise.

Bottleneck/Challenge: Poorly matched components degrade signal transmission and/or host cell fitness.

Potential Solution: Use cell-free systems to prototype new components, but this will not address host cell fitness.

Potential Solution: Develop a platform to transfer devices developed in cell-free extracts to model organisms and validate their operation and fitness.

Bottleneck/Challenge: Poor robustness to context changes within and outside of the cell (i.e., behavior of an assembled feedback logic circuit is often different than predicted, due to parts and subsystems being context-dependent).

Potential Solution: High-throughput methods to engineer or refine part performance in the context of host cell and assembled circuit.

Potential Solution: Develop/refine “contactless” measurements (e.g., impedance spectroscopy) to measure overall features, from shape of trace, and distinguish contributions from properties like interface, bulk, or charge transfer.

Bottleneck/Challenge: Increased control over protein post-translational modification is needed.

Potential Solution: Development of enzyme scaffolds that can better control the sequence and specificity of protein post-translational modifications.

Bottleneck/Challenge: The same circuit works very differently in different chassis and under different conditions.

Potential Solution: Make designs robust for high portability across conditions and organisms.

Potential Solution: Develop more high-throughput methods to engineer and/or refine part performance in new organisms.

Potential Solution: Establish machine-learning methods to predict change in part performance across different conditions and organisms.

Bottleneck/Challenge: Compatibility issues with different extrinsic signals and whether they need to be orthogonal to what the cells naturally sense and respond to.

Potential Solution: Use a consortium of cells, each specific for sensing a particular signal and have a central processing strain that then combines the signals from the different sensing cells.

Bottleneck/Challenge: Interference between orthogonally-designed inducer/promoter pairs over limited resources for protein synthesis and expression.

Potential Solution: Isolate orthogonal pathways and make sensory pathways more robust to cellular and extracellular contexts.

Potential Solution: When possible, attach a secondary “signal” or “reaction” to one pathway over another that can be measured independently and without interference from other pathways.

Bottleneck/Challenge: Genetic feedback mechanisms act over a longer timescale and are not amenable to short term cellular processes and can require active degradation of protein products.

Potential Solution: Adopt protein post-translational modifications for controlling protein activity or sequestration for modulating their functions.

Bottleneck/Challenge: There are limited reactions (adhesion, degradation, light sensitivity) that are currently available for engineered ECM materials.

Potential Solution: Develop materials with reactive/adaptive capabilities.

Potential Solution: Develop hybrid ECM materials (e.g., with semiconductors or metals).

Bottleneck/Challenge: Temporal response to stimulus (dosage and duration) is still not well understood.

Potential Solution: Make use of completely de novo proteins for cell signaling.

Bottleneck/Challenge: Limited chemistry with existing natural materials.

Potential Solution: Enable a wider array of engineered synthetic biological materials, including non-canonical amino acids and de novo designed proteins.

Bottleneck/Challenge: Repair mechanism might cause deterioration of properties to prevent utility of self-repairing material e.g. repair mechanism may be introducing defects into the pristine material so it loses necessary performance characteristics for intended application.

Potential Solution: Improve and increase high-throughput characterization of biocomponents and materials.

Bottleneck/Challenge: Limitation in the range of physical properties that can be attained in natural materials.

Potential Solution: Design sequence-defined synthetic biopolymers comprising combinations of natural and synthetic monomers such that structure-property-performance metrics can be defined, evolved and tuned with an expanded chemical palette toward programmable function.

Bottleneck/Challenge: Rate of repair in natural systems may be too slow for practical use.

Potential Solution: Better understanding and ability to control rate of re-synthesis or re-polymerization in biotic systems and materials.

Bottleneck/Challenge: Cells need a way to estimate environmental conditions and to predict how they may be changing.

Potential Solution: Engineer suites of biosensor molecules for use in target strain chassis that allow cellular sensing of relevant environmental conditions.

Bottleneck/Challenge: Materials need to be able to self-produce more of the material for repair.

Potential Solution: Create microenvironments within the finished materials that activate dormant microbes upon damage and exposure to stimulus (e.g., oxygen) to synthesize replacement materials.

Bottleneck/Challenge: Need for genetic and metabolic circuits that can respond to signals in a controlled, predictable manner.

Potential Solution: Engineer rapid signaling cascades to trigger damage and self-repair responses in materials.

Bottleneck/Challenge: Prediction and validation of function of designed cell consortia/arrays; true orthogonality among different sensory pathways is often a challenge as the expected or predicted function is often different from the observed function.

Potential Solution: Ensure true orthogonality/modularity among different sensory pathways to enable interference-free multiplexing of many different inputs processing, through isolating sensory pathways from sharing common enzymes and resources, from cellular circuitry, and from growth rate variability.

Bottleneck/Challenge: Lack of methods for quantitative, precise engineering of sensors, such as the defined, individualistic response.

Potential Solution: Engineer surfaces to interface between biocomponents and, for example, semiconductor technologies.

Bottleneck/Challenge: Bidirectionally crossing the electron-photon and ion transport energy mismatch without loss of fidelity and in a way that allows uniform information readout for data accumulation and AI processing.

Potential Solution: Utilization of redox reactions (e.g., soxR system and redox biomolecules).

Potential Solution: New semiconductor intermediate interfaces with ion signaling; for example, coupling a biorelevant ion signal to phonons, and then to an electron band-gap.

Bottleneck/Challenge: Many bacterial or cell-free sensors use gene expression to process signals, resulting in significantly delayed (1-2 hours) responses.

Potential Solution: Bypass gene expression and instead use re-engineered signal transduction pathways, which can process a stimulus within minutes.¹Jung, J.K., Alam, K.K., Verosloff, M.S., Capdevila, D.A., Desmau, M., Clauer, P.R., Lee, J.W., Nguyen, P.Q., Pastén, P.A., Matiasek, S.J., Gaillard, J., Giedroc, D.P., Collins, J.J., & Lucks, J.B. (2020). Cell-free biosensors for rapid detection of water contaminants. Nature Biotechnology, 38, 1451–1459. View Publication

Potential Solution: Couple stimulus to known chemistry with colorimetric output.

Potential Solution: Couple protein activity to stimuli-responsive materials (e.g., light sensitive protein dimerization) to engineer material functionalization and/or rapid cellular responses.

Bottleneck/Challenge: We lack the understanding of structure-function properties of proteins in the context of polymeric biomaterials.

Potential Solution: Pursue characterization with a few ‘model’ systems and evaluate the site-specificity of non-standard amino acid enabled bioconjugations onto polymers to understand what part(s) of a given protein should be conjugated to a polymer to maximize efficiency and retain function.

Potential Solution: Evaluate the role of post-translational modification of proteins in retaining/achieving novel biomaterials properties.

Potential Solution: Determine how to scale protein functions to larger scales needed in materials; this requires scale-dependent understanding of protein function depending on their host medium.

Potential Solution: Advance molecular dynamics simulations to accelerate the synthesis and design of biomaterials that are adequately suited for the incorporation of functional proteins.

Bottleneck/Challenge: Storage of information that is robust to cell growth/operations, including characterization of multiple signals (chemical, pH, temperature, mechanical).

Potential Solution: Enable storage of information by creating toggle switches, where the system’s state can be flipped by transient stimuli at will.

Potential Solution: Utilize CRISPR-like technologies to create a permanent change in DNA; however, this is not reversible/reconfigurable.

Bottleneck/Challenge: Enabling micro- and nano-scale communication within a wider range of biological systems.

Potential Solution: Induction of cytoskeletal programs to direct growth of protruding structures for cell morphologies (i.e., axons or dendrites) that interface with membranes.

Potential Solution: Creation of sets of protein factors that can import and traffic vesicles in response to external signals, to direct changes in gene expression or other long-duration cell changes.

Potential Solution: Integrate fine electrometers, such as Single-Electron Transistor, or (sub)micro-scale Hall effect sensors, with biocomponents.

Bottleneck/Challenge: Keeping receptors “alive” during sustained use applications.

Potential Solution: Develop and engineer new porous or networked materials that are surface compatible with a wide variety of receptors.

Potential Solution: Develop new planar surfaces, such as a 2D array of electrical sensors, with similar properties as the network but with much higher efficiencies to compensate for the much lower surface area; the advantage of planar architecture is the easy incorporation into microfluidic devices.

Bottleneck/Challenge: Long-term, robust and stable data storage in biological systems.

Potential Solution: Encoding of information into DNA (i.e., via CRISPR) in order to obtain a permanent storage of information.

Bottleneck/Challenge: Unknown design rules for making easily customizable receptors that can either be multi-responsive themselves or can be deposited onto a patterned surface with other receptors without cross-interference.

Potential Solution: An easily reconfigurable “test-bed” or chip that can rapidly go through a wide variety of potential receptor candidates for both multiplexed behavior or patterned arrays, lowering the cost and time to test new sensing materials.

Bottleneck/Challenge: Integrating information shared between cells that is noisy, relative or variable, and highly localized.

Potential Solution: Develop distributed algorithms for reliably integrating information that are simple enough to be implemented within cells as biochemical or bio-electrical programs.

Potential Solution: Use a consortium of cells each with a specific sensing capability and utilizing a distributed sensing and centralized memory approach to integrate signals.

Bottleneck/Challenge: Within a multi-strain type of setup, multiple strains will need a way to co-exist together while keeping/adapting their ratios as appropriate.

Potential Solution: Creation of robust population controllers that work across environmental conditions (e.g., pH, temperature, nutrients).

Bottleneck/Challenge: Sensing and signal integration in either bacterial or cell-free synthetic biology is highly fragile to environmental conditions (e.g., pH, temperature, nutrients).

Potential Solution: Determine environmental conditions typical of applications that match up with bacterial/cellular viability.

Bottleneck/Challenge: It is challenging to elicit a robust response for signals that may have different amplitudes and duration.

Potential Solution: Simultaneous comparative measurements; for example, in one set-up measure one type of signal (e.g., low amplitude, high gain), in another set-up, a different type of signal (e.g., slow or fast signal).

Bottleneck/Challenge: Design of networks that can integrate more than one or two types of signals.

Potential Solution: Develop computational methods able to parse the multiple forms of data signaling.

Bottleneck/Challenge: Ability to have numerous sensors (of the correct scale) integrating data with minimal crosstalk to reduce false signals/data being used in the sensing/monitoring/feedback scheme.

Potential Solution: Engineer sensors that can effectively function within a “small relevant volume” where by necessity, many chemical reactions are happening at the same time.

Bottleneck/Challenge: Transfer of information from biological sensors to abiotic systems.

Potential Solution: Design functional materials that can bridge to biological systems; for example, electrically responsive materials that can integrate information with bioelectric systems (e.g., nervous system).

Bottleneck/Challenge: Real-time sensing with living cells and/or cell-free systems.

Potential Solution: Remove gene expression from the sensing process and instead use signal transduction or other similarly fast processes.

Bottleneck/Challenge: Lack of natural systems to be exploited or used as the basis for further engineering.

Potential Solution: Rational design of biological elements, mimicking synthetic systems with desired properties.

Bottleneck/Challenge: Stimuli-responsive release and/or transport of biological molecules (e.g., cytokines, transcription factors, hormones).

Potential Solution: Engineer stimuli-responsive chemical scaffolds to encapsulate/release biological molecules.

Potential Solution: Development of synthetic cell systems capable of secretion.

Bottleneck/Challenge: Incorporating reactive components into custom synthesized structural proteins and assembled in a desired structure.

Potential Solution: Understand the structure-property relationship between the synthesized protein and the assembled material system.

Potential Solution: A structural “test-bed” to incorporate new proteins in various configurations to work out design-rules for utilizing stimuli-responsive proteins.

Potential Solution: Explore proteins that are known to have large scale actuation ability when they are self-assembled into supramolecular complexes.

Potential Solution: Explore different types of elastin-like polypeptides that can be deformed elastically and incorporate them into polymeric materials.

Bottleneck/Challenge: Emulating the sensing mechanisms and dynamic interplay between functional proteins and their native lipid environment.

Potential Solution: Understand the design rules and collective lipid dynamics involved in the regulation of protein functions using high-resolution structural and dynamical characterization methods.

Bottleneck/Challenge: Integration of functional membrane proteins into synthetic membrane materials.²McLean, M.A., Gregory, M.C., & Sligar, S.G. (2018). Nanodiscs: a controlled bilayer surface for the study of membrane proteins. Annual Review of Biophysics, 47, 107-124. View Publication

Potential Solution: Development of cell-free strategies for synthesizing membrane proteins.

Potential Solution: Explore membrane protein behavior and function in non-lipid-based amphipathic material; neutron spectroscopy would be useful here, as this can “mask” different parts of protein and amphipathic material through labeling, allowing the study of behavior and structure at the same time.

Bottleneck/Challenge: Identifying pathways that can be effectively used to couple an non-endogenous input to halting cell growth or leading to cell death.

Potential Solution: Use of genetic circuits with sensing/feedback mechanisms orthogonal to natural cell pathways that lead to cell death upon a defined signal.

Potential Solution: Development of chimeric receptors for wiring desired signal to programmed cell death.

Bottleneck/Challenge: Aiding and augmenting biological functionality through synthetic materials.

Potential Solution: Controlled activity of signaling molecules, engineering living cells to reconfigure chemical/physical context, and design feed-back loops or co-dependent cellular systems.

Bottleneck/Challenge: Enabling biocomponent persistence within the material.

Potential Solution: Renewable or regenerative hosts that can encode performance and provide signalling for adaptation of the other components in the materials system.

Bottleneck/Challenge: Mimicking the diverse functions of natural systems on demand.

Potential Solution: Designing the architecture and material compliance, sensing, and other properties of biological systems within polymeric scaffolds and other materials.

Bottleneck/Challenge: Limited chemistry with existing natural chassis.

Potential Solution: Engineer orthogonal translation systems to incorporate amino acids with unnatural R-groups, new classes of amino acids, and/or new monomers altogether.

Potential Solution: Use hybrid biological-chemical synthesis methods (e.g., click chemistry) to incorporate non-biological chemistries into biological substrate molecules.

Bottleneck/Challenge: Limited biological materials that can trap, store, and damp kinetic energy (e.g., trapping high speed objectives).

Potential Solution: Bioprospect natural materials with high energy damping capacities.

Potential Solution: De novo design of protein materials with predictable strength, toughness, and high energy damping capacity.

Bottleneck/Challenge: Difficulty in selecting components from a complex environment due to non-specific interactions.

Potential Solution: Identify optimal structural components (types of peptides or nucleic acid motifs) and their material features (e.g., density, operation temperature) for selective capture/release.

Bottleneck/Challenge: Directing genetic and metabolic circuit activity in response to environmental stimuli.

Potential Solution: Develop tightly controlled, stimuli-responsive, high-yield secretion machinery and couple it with the synthesis of biomolecule-of-interest.

Bottleneck/Challenge: Engineering the energy storage and release mechanism.

Potential Solution: Design and build energy storage mechanisms enabled by biocomponents (e.g., anisotropic, capacitor-like structure that is self-organized by biocomponent within the material).

Bottleneck/Challenge: Current techniques do not enable in situ correlation of cellular behavior upon material distortion.

Potential Solution: Combine indentation/microrheology set-up with high-resolution imaging of living cells.

Bottleneck/Challenge: Cost and availability of precursors to create observable isotopically substituted systems.

Potential Solution: Depending on the system, isotopic substitution may make certain parts of the system “invisible” to neutron scattering techniques.

Bottleneck/Challenge: Biocomponents currently must exist primarily in dynamic fluid environments that are difficult to capture.

Potential Solution: Use hydrostatic pressure to probe biomaterial properties.

Bottleneck/Challenge: Materials with biocomponents are inherently different from conventional homogeneous elastic/viscoelastic materials.

Potential Solution: Develop datasets of standard materials properties of living cells.

Bottleneck/Challenge: Data are not available for dynamic activities.

Potential Solution: Sourcing of data from physics/materials datasets to predict bio-material behavior.

Bottleneck/Challenge: Currently available high-throughput techniques are not designed to map structure-property relationships of biologics.

Potential Solution: Modify existing techniques (e.g., ssNMR, femtosecond optics, fluorescence) or create novel techniques to measure dynamics.

Bottleneck/Challenge: The quantity of materials experimentally produced is significantly smaller than the quantity needed for existing testing methods.

Potential Solution: Characterization methods that have the ability to utilize smaller sample sizes.

Potential Solution: Pilot scale-up of materials more readily realized.

Bottleneck/Challenge: Testing in biologically relevant environments (e.g., in the presence of water, salts) and maintaining cell viability.

Potential Solution: Characterization methods that can be accomplished with samples in standardized formats for biological samples (e.g., 96 well plates).

Bottleneck/Challenge: Improve and develop conventional microscopy techniques for this purpose.

Potential Solution: Expansion microscopy designed to visualize subcellular context of living cells within materials.

Potential Solution: EM tomography repurposed to be utilized for visualizing cell and materials interface.

Bottleneck/Challenge: Most characterization techniques rely on methods that can only be utilized after the material has been produced as they may have deleterious effects on the material production.

Potential Solution: Genetic systems to allow for developmental type studies of hierarchical materials assembly in vivo.

Bottleneck/Challenge: Limitations of visualization tools and technologies.

Potential Solution: Hybrid AFM and confocal imaging; femtosecond optics to measure multiple layers.