Bottleneck/Challenge: Inability to grow most organisms on earth in non-natural environments (i.e., inside the lab) and a lack of knowledge of conditions for growing novel or non-model organisms.

Potential Solution: Database collection and mapping: a better understanding of how to find what is important for organismal growth and survival, potentially including the ability to apply artificial intelligence to recognize patterns.

Potential Solution: Develop a general protocol for identifying viable media and create databases of media that work with known organisms; leverage machine learning using various databases (e.g., 16S rRNA profiling to identify evolutionary relationships between known and unknown species) to help generate suggestions for potential media.

Bottleneck/Challenge: There are a few hosts that are the primary chassis for engineering applications, but they are not always the best choice for biosynthesis of all potential products.

Potential Solution: Expand beyond well-studied model organisms to those that are closely related including the development of tools for genetic manipulation and transformation, as necessary.

Bottleneck/Challenge: Inability to identify specific organisms that could be beneficial for the production of specific products, metabolites, intermediates, and specific catalytic reactions.

Potential Solution: Development of rapid assays to map desired activity to potential capability.

Potential Solution: Inexpensive metabolomics analysis that lends itself to profiling of all metabolites in a cell. Current solutions that are ongoing include developing of specific sensors (i.e., RNAs) to detect specific metabolites (though this is low-throughput).

Bottleneck/Challenge: Availability of high-throughput screens for functions/products that cannot be screened by color or that cannot be selected using growth/viability assays.

Potential Solution: Incorporate protein or RNA sensors into cells for a particular small molecule that the cell may be engineered to produce or consume.

Bottleneck/Challenge: There are few (or no) systems for simultaneously measuring the output of a sensor and then using a computer to expand production of the desired product.

Potential Solution: Develop biosensors to detect one or more particular desired outputs and gene expression systems that allow for computer control (e.g., light, inducer-repressor).

Bottleneck/Challenge: These methods have not been systematically compared among organisms resulting in a lack of clarity as to when one approach may be superior, or even viable, compared to another.

Potential Solution: Better aggregation of the information available for these different organisms, especially if a standard set of similar broad host vectors can be used (as a control) to standardize these.

Potential Solution: Develop bacteriophages that can be useful for engineering large number of organisms.

Potential Solution: Understand the biological basis for what enables some species (e.g., plants) to be more amenable to transformation and genetic modification.

Bottleneck/Challenge: Currently a limitation in the cloning process.

Potential Solution: Methods exist, but they could be improved and more widespread.

Bottleneck/Challenge: Genome-editing tools, particularly CRISPR/Cas technology, have enabled efficient genetic modification of a variety of immortalized cell lines, but primary mammalian cells are often more difficult to engineer with high efficiency and at scale.

Potential Solution: Develop non-toxic gene-delivery methods (viral or non-viral) utilizing reagents and equipment that are compatible with clinical manufacturing and/or high-volume cell modification.

Bottleneck/Challenge: Basic characterized promoters with characterized expression strengths has not yet been carried out in a systematic manner. Previous efforts have been piecemeal and the transferability of parts (e.g., promoters) between different plant species has not been well explored.

Potential Solution: A large-scale, community driven project to standardize and characterize parts will dramatically advance the state of plant engineering.

Bottleneck/Challenge: The majority of plant engineering efforts rely on random insertion of transgenes into the genome, resulting in the necessity to screen and characterize transformants — a very laborious process when working with plants.

Potential Solution: Develop CRISPR-based genome-editing tools that reliably get targeted insertions with high efficiency.

Bottleneck/Challenge: Gene editing tools are not always specific or work at all in certain organisms.

Potential Solution: Screen/develop new CRISPR-based genome editing proteins.

Bottleneck/Challenge: Relatively few transcriptional, post-transcriptional, or translational regulatory devices exist for robust gene-expression control in mammalian cells; the vast majority of systems make use of inducible promoters that are often leaky or require precise tuning, which cannot be done in many practical applications such as patient-derived cells.

Potential Solution: Develop and catalogue a suite of core promoters and response elements, RNA-based regulatory devices, protein-degradation tags, among others, and record standardized, quantitative information on their performance (e.g., basal expression level with enzymatic vs. fluorescent reporters, fold induction, degradation rate, etc.).

Bottleneck/Challenge: Lack of broad-host-range vectors that function for many different organisms requires the development of vectors specific for each organism.

Potential Solution: Engineer new host vectors targeting broader range of organisms; information from NCBI (e.g., plasmids sequences) could potentially be used to get guidance as to functional capabilities/parts that can be effective in different vector design for different organisms.

Bottleneck/Challenge: It is difficult to evolve non-model (and frankly, model) organisms to a desired phenotype.

Potential Solution: Develop general biosensors for particular desired phenotypes for use in non-model organisms.

Potential Solution: Develop mutator proteins coupled to sensors to evolve non-model organisms until they achieve some desired phenotype.

Bottleneck/Challenge: Current plant transformation techniques work on a limited subset of plants.

Potential Solution: Better understand the biological basis for barriers in transformation in plants.

Potential Solution: Develop novel approaches that are species or host agnostic in incorporating and delivering DNA.

Potential Solution: Develop methods that are tissue-culture-independent.

Bottleneck/Challenge: It can take years to make a non-model into a host for heterologous gene expression.

Potential Solution: Use the tools developed to achieve previous milestones to address this bottleneck.

Bottleneck/Challenge: Academics and companies have constructed heterologous hosts for a limited number of chemical classes, but there are many other chemical classes that need hosts with precursor pathways constructed; additionally, some of these precursor production hosts may not be ideal for particular applications or environments.

Potential Solution: Use bioinformatics and screening to identify organisms that might be particularly useful for producing a chemical under a particular environmental condition or that already has precursor pathways for a particular class of chemicals; build a database of those organisms.

Potential Solution: Development of robust plant hosts in order to bridge the gap before trying to engineer plant metabolic pathways into microbes.

Bottleneck/Challenge: Many desired chemicals are toxic to growth of the producing host. Avoidance of this results in separation of growth and production phases which has been achieved by changing the media conditions¹Clark, D. S., & Blanch, H. W. (1997). Biochemical Engineering (Chemical Industries) (2nd ed., p. 716). New York, New York: Crc Press.; however, such approaches are costly, may require the introduction of extra chemicals that are difficult to remove from the desired products, and cannot easily accommodate cellular heterogeneity, or be used to fine tune the shift from growth to production phases.

Potential Solution: Develop several types of expression systems for controlling the timing of gene expression and thus the timing of chemical production; ultimately, decouple growth and reproduction from energy and carbon metabolism and product generation.²Venayak, N., von Kamp, A., Klamt, S., & Mahadevan, R. (2018). MoVE identifies metabolic valves to switch between phenotypic states. Nature Communications, 9(1), 5332. View publication.

Bottleneck/Challenge: The necessary genetic regulatory elements should be sufficiently orthogonal to the host to permit tuning, but nonetheless responsive to changes in cell state.

Potential Solution: Identifying, and then re-engineering, diverse sets of protein and RNA regulators capable of activating or repressing gene expression in response to targeted changes in growth and nutrient state would expand these capabilities³Weinhandl, K., Winkler, M., Glieder, A., & Camattari, A. (2014). Carbon source dependent promoters in yeasts. Microbial Cell Factories, 13, 5. View publication.; Hsiao, V., Cheng, A., & Murray, R. M. (2016). Design and application of stationary phase combinatorial promoters (SEED 2016 Technical Report). Retrieved from MurrayWiki.; integrating the responses of these regulatory elements, perhaps through the use of engineered information processing networks, would permit the construction of circuitry for fine-tuning the timing of gene expression in microbial hosts.

Bottleneck/Challenge: There is a need for hosts capable of producing all natural products found in nature; there is no need for a single host to produce all of the natural products, but rather at least one host for every class of natural products.

Potential Solution: Use the database of possible hosts, genetic control systems and modular pathways to develop a range of hosts for each class of natural products; these hosts should produce high levels of the precursors to natural products.

Bottleneck/Challenge: There are few engineered cells that produce unnatural derivatives of natural products and the methods for engineering organisms to produce unnatural natural products are nascent.

Potential Solution: Construct hosts with the modular natural precursor pathways and engineered or evolved enzymes to create hosts that can produce unnatural natural products.

Potential Solution: Construct hosts with promiscuous enzymes (either natural, engineered, or evolved enzymers) and feed unnatural precursors that are incorporated into the final product.

Bottleneck/Challenge: It remains difficult to target gene expression to a particular growth phase or culture time in order to maximize production of a desired natural or unnatural product.

Potential Solution: Develop a catalog of promoters (including timing and gene expression strength) that are activated in various phases of cultivation.

Potential Solution: Identify promoters that are activated at the same time or with the same environmental queue and that can be used with multiple genes (i.e., multi-step biosynthetic pathway).

Bottleneck/Challenge: It is challenging and time-consuming to optimize the titer, rate and yield of a desired product in any host.

Potential Solution: Develop a software suite that considers the metabolic pathway(s) and host and incorporate a wide variety of measurements and can predict that changes that need to be made to the metabolic pathway add the host to optimize titer, rate, and yield.

Bottleneck/Challenge: Reliance on nature’s single-cell organisms that are not ideally suited for producing a particular chemical.

Potential Solution: Use retrobiosynthesis software as well as genetic control system design software to de novo design microbial cells that can produce nearly any organic chemical; the cells would be designed for the processing environment to enable inexpensive purification of the final product.

Bottleneck/Challenge: There is a need for modular targeting tags that can be appended to any peptide sequence as N- or C-terminal fusions with efficient targeting to a desired compartment. The challenges are finding sequences that provide modularity; in other words, the ability to perform targeting on any protein sequence of interest, and compartmentalize a high percentage of total expressed protein, preferably at high expression levels.

Potential Solution: Most organelles have identified targeting sequences, but few satisfy the dual requirements of high efficiency and modularity; high-throughput screens for peptide sequences can be conducted using enzyme sequestration assays.⁴DeLoache, W. C., Russ, Z. N., & Dueber, J. E. (2016). Towards repurposing the yeast peroxisome for compartmentalizing heterologous metabolic pathways. Nature Communications, 7, 11152. View publication.

Potential Solution: Bacterial organelles, known as microcompartments, have several known targeting tags for cargo enzymes and encapsulation is tunable with expression levels⁵Jakobson, C. M., Chen, Y., Slininger, M. F., Valdivia, E., Kim, E. Y., & Tullman-Ercek, D. (2016). Tuning the catalytic activity of subcellular nanoreactors. Journal of Molecular Biology, 428(15), 2989–2996. View publication.; however, distinct tags may use the same mechanism for loading, making it difficult to reliably control targeting of multiple enzymes into the same compartment. Additional biophysical characterization of existing and putative tags can be carried out using existing technologies to identify those with unique loading mechanisms or interaction partners.

Synthetic organelles (or compartments) that can be made on-demand and/or provide the means to compartmentalize different heterologous protein cargos would allow the engineer to mimic tissue compartmentalization in a single-cell microbe.

Bottleneck/Challenge: Achieving sufficient understanding of the formation of organelles and microcompartments.

Potential Solution: Placing necessary organelle biogenesis factors under the expression control of a heterologous, inducible promoter should provide on-demand organelle production.

Potential Solution: Inducible control of bacterial microcompartment-forming proteins leads to some well-formed particles, but other factors must be identified to make sufficient quantities and do so robustly. These factors may be environmental factors or additional chaperone proteins, and can be identified by using a high-throughput screen, such as a flow cytometry-based assay that links cellular fluorescence to successful compartment formation.⁶Kim, E. Y., & Tullman-Ercek, D. (2014). A rapid flow cytometry assay for the relative quantification of protein encapsulation into bacterial microcompartments. Biotechnology Journal, 9(3), 348–354. View publication.

Bottleneck/Challenge: Many organelles and microcompartments will naturally have permeability to molecules that are desired to be partitioned either outside or inside the organelle (e.g., pathway intermediates); these organelles and the microcompartments will need to be modified to have lower permeability to these molecules.

Potential Solution: Selective transport of desired metabolites (e.g., pathway substrate, cofactors) must be engineered into the organelle/microcompartment by manipulating the proteins that govern the movement of small molecules across the membrane/shell.

Bottleneck/Challenge: Prokaryotes and eukaryotes contain multiple compartments that can be utilized for sequestering sensitive chemistries or metabolites; unfortunately, it is not always clear which compartments to use.

Potential Solution: Catalog organelles/microcompartments with favorable properties for desired applications/products (a suite of organelles will likely be of value to meet the needs of varied applications).

Bottleneck/Challenge: Tools for engineering organelles and microcompartments are not readily available.

Potential Solution: Develop gene expression tools for a variety of different organelles in eukaryotes or for microcompartments in prokaryotes.

Potential Solution: Engineer multiple pathways to function in concert within the same organelle/microcompartment for optimal performance (e.g., cofactor balancing, co-substrate production, condensation reactions).

Bottleneck/Challenge: Identifying parameters to optimize and means of optimization of microcompartment morphology.

Potential Solution: Genetically control the morphology of organelle/microcompartment (e.g., size, number) to achieve increased capacity for product cargo. Low capacity for enzymes is a limitation for many organelles; a solution would be the genetic manipulation of, for example, the shell protein expression levels or an organelle biogenesis pathway, to increase this capacity.

Bottleneck/Challenge: Altering the chemical environment of a compartment’s lumen would require successful completion of efficient import of heterologous protein, reduction of small molecule permeability, and, for organelles, the functional trafficking of membrane proteins to the organelle’s membrane.

Potential Solution: Combination of heterologous small molecule transport, enzyme, and compartmentalization of both enzymes and small molecule substrate, intermediates, and products will allow alteration of the chemical environment of the lumen.

Bottleneck/Challenge: Achieving compartmentalization of different cargo in distinct organelles or microcompartments within the same cell demands the ability to generate such compartments with distinct “addresses” or protein import machinery recognizing targeting sequences orthogonal to the other native and synthetic organelles in the cell.

Potential Solution: Multiple natural organelles using different protein importomers can be utilized; however, the lumenal conditions are likely not optimal for the needs of each compartmentalized activities. Alternatively, engineered organelles with the ability to import orthogonal, distinct pools of protein in separate organelles should be achievable by either performing directed evolution on the native protein importomers or targeting heterologous importomers native to other organelles.

Potential Solution: Bacteria employ multiple distinct microcompartments within the same cell, and these are encoded by distinct operons which includes genes to make the protein shell boundary; it is feasible, but yet to be demonstrated, that these distinct microcompartments could be engineered simultaneously using existing techniques.

Bottleneck/Challenge: Compared to protein synthesis, post-translational modification and machinery is not well understood and any given protein may exist in the cell in multiple glycoforms, making advanced study challenging; this problem is particularly prevalent in the production of biologic pharmaceuticals (e.g., biosimilars) where the complex array of glycosylation patterns can cause differences in efficacy and safety.⁸Sethuraman, N., & Stadheim, T. A. (2006). Challenges in therapeutic glycoprotein production. Current Opinion in Biotechnology, 17(4), 341–346. View publication.

Potential Solution: Understand the pathways involved in glycosylation of the protein of interest and develop these pathways to enable tightly controlled synthesis of a single glycoform.

Bottleneck/Challenge: There are relatively few bacterial hosts that have well developed protein secretion systems. Those that exist are primarily in Gram positive hosts, and are not necessarily compatible with all desired protein products; gram negative hosts, on the other hand, have an outer membrane that must also be crossed before exiting the cell, and secreting proteins across both the inner and outer membranes remains a challenge at the efficiencies required for commercial application.

Potential Solution: Develop new bacterial hosts with machinery specifically designed for protein secretion.

Bottleneck/Challenge: The systems that do exist are either required for cellular function and thus can only be repurposed to a limited extent, or are highly regulated and difficult to activate or keep activated.

Potential Solution: Utilize systems biology to understand and remove the regulatory controls on secretion systems.

Bottleneck/Challenge: Post-translational modifications are often considered the “analog” control in the cell; as such, they can carefully tune how an individual protein interacts with its environment. The lack of understanding of this control makes affecting post-translational modification for desired use particularly challenging. The ability to tune the analog portion of the cell, however, can allow for more efficient systems, better synthetic yields, and a broader set of uses than would otherwise be possible.