Assemble tailored cell sensor and actuator arrays and consortia using 3D printing or other top-down methods.
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.
Rapidly create new sensors with precisely defined characteristics.
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.
Enable transfer of information from biological sensor to machine readable form and vice-versa, to reliably interpret biological signaling.
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.
Enable cellular or cell-free system responses within 2-3 minutes from stimulus exposure.
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.
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.
Adapt proteins that have evolved stimuli-responsive functions into biomaterials to achieve novel sensing and signaling properties.
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.
Record multiple types of time- and space-domain events using libraries of biomolecular signals (e.g., RNA or proteins) to store different types of signals for readout by, for example, high-throughput sequencing.
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.
Develop means to use ion-based communication via excitable membranes in addition to chemical communication for faster, more location specific communication.
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.
Ability to engineer new surface receptors for sensing and cell-to-cell signaling.
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.
Development of novel mechanisms for storage of signals in biomolecules (e.g., polypeptides).
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.
Ability to engineer new hetero-complex surface receptors for multiplexed sensing sensing and cell-to-cell signaling.
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.
Custom integration of signals over different time and spatial scales by cells or cell-free circuits, to process inputs and direct cellular response.
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).
Engineer materials with sentinel sensor networks that can sense and integrate numerous signals.
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.
Develop new forms of communication from biological systems, such as light (including infrared and radio frequency) or mechanical force (e.g., sound) production.
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.