Engineering

Figure 1: iGEM Engineering Cycle

What inspired our team to initiate this project?

Currently, one of the most prevalent artificial carbon sequestration methods is Carbon Capture and Storage (CCS), a costly and energy-intensive technology with limited efficacy. As a result, the team resorts to biological carbon fixation approaches, planning on exploiting the dominant photosynthetic method via oxygenic photosynthesis. In fact, according to the Encyclopedia of the Environment, photosynthesis solely contributes to approximately 115 to 120 gigatons of carbon fixation annually from CO₂ in the atmosphere (Jean-François, 2025). The significance of such biochemical processes inspired our team to leverage its efficiency for carbon sequestration.

Why did we choose to use cyanobacteria?

Photorespiration – A Fatal Drawback

Ribulose 1,5-bisphosphate carboxylase-oxygenase (RuBisCO), a key enzyme that takes part in the Calvin cycle through binding with atmospheric CO₂, struggles with the lack of substrate specificity and slow product turnover rates. This leads to the enzyme fixing CO₂ with a low efficiency. RuBisCO doesn’t only work for CO₂. It also binds with oxygen through a metabolic process known as photorespiration (Cummins et al., 2018). Photorespiration results in the loss of 3 fixed carbons per 3 turns of the Calvin cycle and is therefore undesirable, as it does not contribute to carbon fixation; instead, it wastes oxygen and energy.

Inspirations from Alternative Photosynthetic Pathways

To counter RuBisCO’s low affinity to carbon and minimize the effects of photorespiration in harsh, arid, and dry environments, two adaptive pathways, C4 and CAM photosynthesis, emerged among plants to optimize carbon fixation while conserving water. C4 photosynthesis is a two-step process that completes carbon fixation at two distinct locations: the mesophyll and bundle sheath cells. On the other hand, CAM photosynthesis also involves two stages, yet within the same cell at different times (C4 and CAM Photosynthesis | Research Starters | EBSCO Research, n.d.).

C4 and CAM photosynthesis, evolutionary strategies that address the low carbon fixation rates in traditional C3 photosynthesis, provide the team with insights into modulating the biological pathways in photosynthetic organisms to facilitate carbon fixation and mitigate the adverse impacts of industrial carbon emissions more effectively.

How can we use cyanobacteria to address photorespiration?

Cyanobacteria, also known as blue-green bacteria and blue-green algae, is a phylum of bacteria that perform oxygenic photosynthesis. In particular, the CCM in cyanobacteria is considered a model for improving photosynthesis in C3 plants. Thus, combating the drawbacks associated with photorespiration, as mentioned, cyanobacteria become a promising organism that could be used. Furthermore, cyanobacteria are integral primary producers. Currently, an estimated 20-30% of the Earth’s organic carbon is derived from cyanobacterial carbon fixation (Zhou et al., 2016).

Given that increasing RuBisCO’s affinity to CO₂ in the CCM directly optimizes the Calvin cycle, the team proposes the genetic modification of the freshwater cyanobacterial strain Synechococcus elongatus PCC 7942 by modifying the expression of a HCO₃^- transporter BCT1 of the carbon uptake system. By increasing the expression of the cmpABCD operon, which utilizes light-inducible promoters to enhance the amount of BCT1 on the cyanobacterial inner membrane, the team aimed to increase the concentration of CO₂ in the carboxysomes, thereby upregulating RuBisCO activity and improving carbon fixation efficacy while reducing photorespiration. When CO₂ is concentrated and abundant, RuBisCO preferably binds to CO₂ rather than O₂. This is because the binding of CO₂ and O₂ to RuBisCO’s binding site is a competitive process, so under high CO₂ levels, CO₂ outcompetes O₂ in terms of binding and promotes the carboxylation reaction over the oxygenation reaction.

What are some concerns with the utilization of the cmpABCD Operon?

One of the problems our team encountered was the size of the cmpABCD operon, which spans about 5000 base pairs. Cloning large DNA sequences is technically challenging due to insufficient ligation and the difficulties associated with transformation. Therefore, to overcome this difficulty, we adopted a modular design by splitting the operon into two transcriptional units: cmpAB and cmpCD. This separation enables more efficient cloning and theoretically lowers error and mutation rates.

Why did the team decide to use only the psbA1 promoter rather than both the psbA1 and psbII promoters when constructing the plasmids?

While conducting synthetic biology experiments aimed at constructing the psbA1-cmpAB and psbII-cmpCD constructs, the team encountered difficulties with assembling the psbA1-cmpAB construct. To address this issue, the team conducted a thorough analysis of each procedural step, starting with sequence alignments. This detailed investigation uncovered that the pAM1619 recombinant plasmid, sourced from Addgene and purported to contain the psbA1 promoter, did not carry the correct psbA1 promoter sequence. Additionally, the pCOTS-pyl-GFP(35TAG) plasmid, also obtained from Addgene and labeled as containing the psbII promoter, was found to harbor the psbA1 promoter sequence instead. In fact, the team decided to generate psbA1-cmpAB and psbA1-cmpCD on the pCOTS-pyl-GFP(35TAG) plasmid, respectively.

How did our team evaluate the potential advantages of creating cmpAB and cmpCD fusion proteins?

To justify the assembly and stability of the cmpAB and cmpCD fusion genes, the team utilized AlphaFold and DeepTMHMM to predict the 3D protein structures and orientations of the cmpAB and cmpCD fusion proteins using their amino acid sequences and then compared the predicted configurations to the assembly of individual cmpA, B, C, and D compartments. Through qualitative protein structural visualization and quantitative analyses, including root mean square deviation values, predicted topology plots, and signal peptide charts, the team concluded that the cmpAB and CD fusion proteins demonstrate local structural similarity and a coinciding orientation compared to the individual cmpA, B, C, and D compartments. The detailed results can be found under the “Protein Modeling” section. After proving the stability of the cmpABCD (BCT1) complex when split into cmpAB and cmpCD fusion proteins, we moved on to construct the genetic parts—cmpAB and cmpCD fusion genes—that included the light-dependent promoter ppsbA1 in the expression vectors to drive the constructs’ overexpression.

Figure 2: BCT1 Gene Strategy Cycle

What challenges did our team face when conducting the mathematical modeling of the CCM?

One of the significant challenges our team encountered when attempting to model the CCM mathematically was our lack of prior experience in computational biology. Initially, we knew very little about how to develop a plausible mechanism. In fact, we acquired some basic knowledge, such as enzyme kinetics and MATLAB coding, from our advisors. Subsequently, we sought advice from Prof. Mangan at Northwestern University, who specializes in CCM modeling, after we found and read her paper “Systems analysis of the CO₂ concentrating mechanism in cyanobacteria.” (Mangan & Brenner, 2014) During our consultation, Prof. Mangan explained that efficiency in computational models is not solely defined by RuBisCO activity, but also depends heavily on auxiliary components such as carbonic anhydrase and the structural/functional constraints of carboxysomes. Following her guidance, we incorporated her CCM diagram logic into our MATLAB simulations.

Moreover, since experimental measurements of metabolite concentrations and enzyme kinetics in cyanobacteria are often incomplete or inconsistent, we were forced to build from scratch. For example, to simplify diffusion dynamics, we assumed the outer membrane, inner membrane, and carboxysome to be perfect concentric spheres. This idealization allowed us to approximate how CO₂ would diffuse inward and be trapped by the carboxysome.

Figure 3: CCM Modeling Cycle

How did our team successfully overcome initial obstacles to grow cyanobacteria?

Upon receiving a plate of S. elongatus PCC 7942 from Dr. Lan at National Yang-Ming Chiao-Tung University, we grew the cells in a flask containing 100 mL of BG-11. After not observing any growth for weeks (BG-11 liquid cultures were transparent in color weeks after inoculation), we attributed the failure to the low initial cell density of cyanobacteria, as it impeded the cells’ multiplication and growth. To combat this, we switched to smaller 5 mL liquid cultures to increase the cell density.

Additionally, since our newly streaked plates did not yield enough cells to collect with an inoculation loop, we had to transfer entire agar chunks into 15 mL conical tubes to obtain sufficient biomass. For about a month, all our cultures contained agar pieces, which made it difficult to scale up because pipette tips frequently collided with the agar during liquid transfers.

Eventually, we observed growth in the 15 mL tubes, visible as green, cloudy sediment at the bottom and small bubbles rising along the surface. These signs of respiration confirmed that the cyanobacteria were alive and metabolically active. We then transferred the cultures into 100 mL flasks and diluted them with BG-11 medium, which supported faster growth.

In conclusion, to grow cyanobacteria successfully, start with small liquid cultures inoculated from colonies, and then expand them stepwise into larger volumes to ensure healthy growth of the cyanobacteria.

Figure 4: Growth Optimization Cycle

What challenges did our team face on plasmid transformation, and what methods did we try?

Cyanobacterial transformation has been one of the main challenges we encountered throughout our project. We have applied various transformation methods, including chemical transformations, natural transformation, and electroporation, over several months. But no colonies were observed throughout these attempts. On our last attempt at using natural transformation, colonies were observed, but the plates were contaminated, making it impossible to determine the success of the transformation.

With the consistent failure, the team contacted Dr. Hsuan-Chen Wu, associate professor at National Taiwan University. Through several discussions, he informed the team that, besides contamination, the constant failure of transformation can be attributed to the use of aged cyanobacteria. Our team relied on the initial one-plate Dr. Lan sent us for experiments over a period of nine months. Therefore, when we reached the transformation phase, the cyanobacteria were already several months old, making them very difficult to transform.

Older cyanobacterial cultures often enter the stationary or decline phase of growth, during which metabolic activity, membrane fluidity, and DNA uptake efficiency are reduced compared to cells in the exponential phase. During the stationary phase, nutrient depletion and oxidative stress can lead to the formation of thickened cell walls and changes in the extracellular polysaccharide (EPS) layer, both of which can act as physical barriers to DNA uptake. Additionally, competence in many bacteria is tightly regulated and usually peaks during active growth, meaning that aged cyanobacteria may have been physiologically less receptive to foreign DNA. Taken together, these factors could explain the low transformation efficiency observed (Berla et al., 2013).

Figure 5: Transformation Pipeline Cycle

How did we test the functionality of our engineered cyanobacteria?

To evaluate the effectiveness of our engineered cyanobacteria within a carbon fixation device, we conducted a CO₂ uptake assay adopted from previously established protocols for cyanobacterial systems. With the assay performed on a cyanobacteria-containing experimental group using a BG-11 control group as a reference, we obtained key parameters, such as CO₂ decreasing patterns and equilibrium concentrations, for the wild-type cyanobacterial strain S. elongatus PCC 7942. These data retrieved could then be employed in our cyanobacterial CCM mathematical model as a baseline to quantify the enhancement in CO₂ uptake efficiency for our engineered strain, thereby confirming the functional overexpression of BCT1 transporters.

Figure 6: Validation & Hardware Cycle

Applications

Our cyanobacteria-powered bioreactor is designed for carbon capture and fixation in the industries that are categorized as scope 1 CO₂ emitters. We anticipate its primary application will be at coal-fired and natural gas power plants, which are the primary point sources of CO₂ emissions. The device can also be adapted for use at other industrial sites with high CO₂ output, such as cement manufacturing facilities and steel mills. The bioreactor’s modular design allows it to be scaled to match the emission levels of the facility’s output.

The device will be implemented as a closed-loop system integrated into a power plant’s existing infrastructure. A portion of the flue gas, previously purified to remove other toxic particles, will be diverted into the bioreactor’s cultivation medium to serve as the essential carbon source for the cyanobacteria. Inside the bioreactor, the cyanobacteria will perform their natural biological processes, including photosynthesis, consuming the CO₂ to produce biomass. Once the culture reaches a sufficient density, this biomass will be harvested and processed into animal feed, and the nutrient mediums will be replaced. By transforming a waste stream into a resource, our technology creates a circular economy model for the energy sector, providing a practical and economically viable solution to reduce greenhouse gas emissions while creating sustainable industries.

How did we validate our ideas?

We validated our ideas by consulting specialists across materials science, microbiology, and computational modeling, who provided feedback that shaped our project into something both feasible and responsible. Since our project centered on enhancing carbon fixation in cyanobacteria, we also engaged with cyanobacteria researchers to test the biological feasibility of our approach. From these conversations, we learned several critical points. First, RuBisCO is already operating close to saturation under normal conditions, meaning that increasing carbon fixation is not as simple as overexpressing the enzyme. Second, the pore size of the carboxysome shell imposes diffusion limits on bicarbonate and CO₂, reminding us that structural constraints must be considered in our design. Finally, we were informed that the cyanobacterial carbon concentrating mechanism (CCM) is only activated under low ambient CO₂, which clarified the environmental conditions under which our modifications could realistically work. This expert feedback prompted us to shift focus from manipulating RuBisCO directly to improving bicarbonate transport and CCM efficiency.

To further ground our design in feasibility, we consulted with modeling specialists who helped us identify the variables that were most critical to simulate. They highlighted parameters such as bicarbonate transport rates, internal CO₂ concentrations, and carboxysome permeability as key to predicting whether our design could succeed. Their input guided us in refining our models, enabling us to validate core assumptions before moving into the wet lab.

Through this iterative process, expert feedback reshaped our project direction. Instead of pursuing overly ambitious or biologically unrealistic approaches, we refined our design to align with the constraints of cyanobacterial metabolism and the opportunities within synthetic biology. These consultations not only validated our ideas but also ensured that our project was responsible, scientifically sound, and implementable.

References