Quick Start Guide for Engineering Constructs That Have Potential for Eventual Deployment in Real-World Aquatic Environments
A practical engineering guide for channeling synthetic biology solutions from the laboratory to real-world aquatic environments to ensure safe, effective deployment
1. Define the problem and clearly identify the system boundaries.
For the specific challenge, define the ecosystem type (marine, freshwater), biotic/abiotic factors, and potential human interfaces. Always include an initial policy and safety check for the specific geographical location, so that the safety and policy factors remain an overarching consideration throughout the project. Even if one never intends to deploy the device in a real-world environment, these considerations are essential to consider for the eventual deployment of the device. Design the synthetic device as if it could be deployable safely and effectively.
2. Select the appropriate chassis for the proposed solution.
Employ chassis analysis software that predicts whether the particular chassis is likely to survive and thrive in the particular ecosystem. This analysis software should account for abiotic factors (nutrients, minerals, mechanical factors) and importantly, biotic factors, including the community or consortia of organisms in which the chassis must perform its function. Use an aquatic-native chassis when possible, one with the necessary molecular tools (e.g. transformable, sequenced genome, available plasmids.
[William & Mary iGEM 2025 has developed such a software, see Software page]
3. Develop a design that engineers genetically stable expression without antibiotics.
For example, employ chromosomal integration at insulated “landing pads” instead of high-copy plasmids (less burden, no plasmid loss). Use serine-integrase/att sites or validated pad sets. If possible, avoid plasmid-based circuits, but if necessary, use post-segregational maintenance, low-copy origins and remove any repetitive elements or inverted repeats to reduce rearrangements.
4. Employ mathematical modeling to ensure that device is theoretically feasible to address the problem in natural environments.
For example, if the number of bacteria required to bioremediate an environmental problem is 100,000 liters of a 1015 CFU/ml, this would not be feasible! It is time to re-design!
[William & Mary iGEM 2025 has developed a mathematical modeling framework for aquatic systems, see Modeling page]
5. Employ standard synthetic biology design guidelines: Insulate parts and control burden, particularly for units with strong promoters.
One can use RiboJ and bicistronic design to make behavior more predictable under changing conditions. One can also employ burden-driven feedback designs to protect circuits in highly variable aquatic environments. Incorporate genetic biocontainment systems (e.g., kill switches, auxotrophy, CRISPR-based self-destruction). Use synthetic codons if possible.
6. Test circuit in laboratory conditions.
7. Test in simulated real-world conditions.
Once it is determined that the circuit works in lab conditions, test in conditions that mimic natural environments using environmental emulators for example, cold rigs, pressure rigs, containers with wave makers, use of co-community culture to simulate natural consortia. Use all available resources and measurement techniques to assess how the behavior of the engineered chassis differs between the lab environment and the aquatic environment. These measurement techniques can include everything from macroscopic visual behaviors of cells and growth curves using plating to DNA-Seq and RNA-Seq analyses. Ideally perform, scaled-down (for cost reasons) RNA-Seq analysis to discern how gene expression changes from laboratory conditions.
[William & Mary iGEM 2025 has developed prototype hardware for simulated real-world aquatic conditions, see Experiments page]
8. Conduct bioinformatic analysis of existing datasets to obtain critical information on lab vs. environment gene expression differences.
While conducting RNA-Seq experiments may not be possible in every lab, bioinformatic analysis is largely accessible. This could be performed via two methods. [1] Identification of datasets that compare laboratory and natural environment gene expression for one's chassis of choice, and subsequent analysis using a RNA-Seq analysis pipeline (either command line or an online system such as Galaxy. or [2] Judicious use of AI tools using specific, directed prompts specifying differential gene expression between laboratory and real world environments for a given chassis that would allow the engineered chassis to thrive.
[William & Mary iGEM 2025 has developed guidelines and core design principles for RNA-Seq meta-analyses of existing RNA-Seq datasets, see Engineering page]
9. Use the differential gene expression data from wet lab RNA-Seq and/or bioinformatic analysis to infer design principles that would enhance survival in the selected environment.
The goal is to match the gene regulation to the environment. For example, this would likely entail building stress-tolerance modules matched to aquatic stressors such as osmotic and salinity issues (could upregulate solute intake), cold and membrane rigidity (could increase unsaturated fatty acids with desaturase tuning).
[William & Mary iGEM 2025 has developed general design principles from RNA-Seq data, see Results page]
10. Retest re-engineered chassis to determine if they perform better in natural aquatic environments.
Continue with the design-build-test-learn cycles in these emulated environments.
11. Return to assessment of safety concerns!
Just as one began with overarching safety concerns, return to these. In addition to genetic safety containment (#5 above), design ecological containment. Be sure to include a redundant biocontainment approach; combine genetic containment (#5) with physical containments. For example, one could encapsulate in hydrogels and alginate or cellulose/alginate blends. Also, perform mathematical modeling to model potential gene flow, mutation rates and ecological impact.