Team:MiamiU OH/Implementation

iGEM 2021 | Miami University

Proposed Implementation

Depiction of the progress toward reducing undernourishment by percentage of countries within each global region, with the majority of the most severely off track nations being in the Middle East, North Africa, and South Asia.Figure 1: Depiction of the progress toward reducing undernourishment by percentage of countries within each global region, with the majority of the most severely off track nations being in the Middle East, North Africa, and South Asia. This data was derived from the 2012 Global Monitoring Report, with the figure being retrieved from ourworld.unu.edu (1). Communities throughout the world struggle to meet daily nutritional needs. Areas such as the Middle East, North Africa and South Asia are often affected most, with a severe margin of undernourishment and the majority of countries in this region not on track to reduce undernourishment (Figure 1). As the human population continues to grow, food production has not risen to match pace; food availability is simultaneously threatened by cultivable land limitations and the increasing use of food crops for fuel sources. Food production is rapidly coming under a higher demand than it can sustain at current productivity levels (2). With no feasible way to increase the amount of land under cultivation, the only option that remains is to increase the actual productive yield of what crops are currently being cultivated. One solution is to improve crop yield by optimizing the process of photosynthesis, the incorporation of light energy into sugar molecules. Our project aims to design genetic systems in cyanobacteria that drive forward RuBP regeneration. A more robust RuBP regeneration pathway results in more continuous RuBP regeneration, meaning photosynthesis is stalled less often. The more continuous the photosynthesis, the better a cell can grow. Biomass production becomes more efficient at a cellular level when the efficiency of this metabolic process is increased. The technology demonstrated by our group in the model photosynthesizer cyanobacteria can then be applied to crop plants, boosting crop yield per plant.

Proposed Implementation

We envision that our technology will be used by plant biologists and other researchers interested in improving photosynthetic efficiency. The resulting crop varieties could be cultivated by growers on a global scale, increasing crop production while decreasing agricultural land usage and maintaining the same labor requirements.

A field of golden rice during sunset.Photo by Elina Sazonova from Pexels Through well developed and documented procedures for genetic engineering in plants, we anticipate that our cyanobacterial over-expression and deletion systems will be translated into common crop varieties. The real application of our technology is in the development of agricultural productivity to sustain the dietary needs of a growing human population. This mission is already being reflected in a current international project called Realizing Increased Photosynthetic Efficiency, or RIPE (3). The crop varieties targeted within the RIPE project are cassava, cowpea, maize, rice and soybean (3). Within the agricultural industry, a shift has already begun toward genetically engineered plants.

Plant genetics has advanced from simply selecting and breeding individuals with desired characteristics. Now researchers can directly introduce genes for pest resistance, drought resistance, and improved flavor and nutritional content (4). A major challenge is the shift from genetic engineering of highly specialized prokaryotic cyanobacteria to complex multicellular plants. However, several methods for plant genetic engineering have already been developed and in use for decades. One approach is the integration of transfer DNA (T-DNA) mediated by Agrobacterium tumefaciens. This bacterium typically infects wound sites in plants to cause gall growth deformities, but this mechanism of infection has been exploited to transfer DNA to plant cells for genetic engineering. Similarly, another method includes collecting embryogenic cells and co-culturing them with A. tumefaciens; this method provides the advantage of early stage selection so that all cells of the adult plant can be confirmed to have the desired genetic changes (5). Projects that use a multigene approach to stimulate electron transport and carbon regeneration in plants may have already provided a direction for incorporating our research (6). Technological advances can provide even more options for gene editing, such as the widely renowned CRISPR-Cas9 system.

This path to agricultural improvement is widely acknowledged across the globe. Research facilities around the world collaborate to target specific areas in the 170-step photosynthetic process to make improvements where it is feasible (3). Considering the extensive community that shares our vision of optimizing plant productivity, we want our work to contribute to this crucial movement. Overall, we are driven by the idea that without an increase in crop yields, we will not be able to sustain the human population.

Safety Aspects

An individual grain of wheat.Photo by Tongpradit Charoenphon from Pexels Overexpression of our target Calvin-Bensen-Bassham (CBB) cycle enzymes, transaldolase and fructose-1,6-bisphosphatase, is not known to lead to the production of toxic by-products. These enzymes are already natively expressed in cyanobacteria for their central metabolism; we are only altering the expression levels of these enzymes to exploit their ability to manipulate intermediates of the CBB cycle. These enzymes are vital for the regular metabolism of photosynthetic organisms, including plants, and are only increasing the concentration at which they are present. Therefore, there is not a reasonable risk of toxicity production if implemented into crops.

Our computer modeling team also processed a secondary potential pathway, termed the glycolaldehyde pathway. This pathway, detailed within the modeling page, utilizes an enzyme found in and a reaction with no identified enzyme yet. If not found in nature, it is likely that this enzyme can be generated through directed evolution experiments. Due to the time constraint to evolve such an enzyme in labs, we only tested this pathway through computational modeling.

Therefore, the main safety considerations stem from the consequences of genetic manipulation. We do not intend our genetically engineered cyanobacteria to be directly used in a practical setting. However, because we envision that the technology will be used in crop plants, there are specific national regulations and protocols that apply. We can expect that implementation of our overexpression and deletion systems in plants requires years of indisputable research and evidence of its safety for consumption. High scrutiny and care is necessary because genetically modified organisms (GMOs) raise concerns regarding their potential impact on the environment and human health, and any other unintended effects of transgene introduction (7).

While the direct product of our target enzymes are nontoxic, it is important that we understand the secondary consequences of gene overexpression on metabolic flow. This is a common focus in genetic engineering, and is addressed by our modeling experiments. However, plants might respond differently to excess metabolite production than our single-celled prokaryote, which would require additional screening methods in future research.

Other Challenges

In order for our results to translate into practical use in crop plants, we must first clearly demonstrate that our system works in cyanobacteria and explain why we expect it to apply to higher plants.

A field of wheat.Photo by Ivan Bandura from Unsplash Another consideration with the incorporation of our system in plants involves choosing the right crops and genetic engineering methods that will optimize safety and efficiency in implementing our project into crops. Although this downstream analysis of safety is beyond the scope of our project, which instead focuses on cyanobacteria, it would be a vital component in future work. For instance, not all crop plants synthesize sugar molecules in the same manner. The CBB cycle we are working with is part of C3 metabolism. This is in contrast to C4 metabolism seen in crops like maize, sugarcane, and sorghum, which spatially separates Rubisco from oxygen in the atmosphere. While work in C4 plants is exciting due to their already inherently high productivity, we must consider that our system only applies to C3 cultivars such as tobacco, cowpeas, and soybeans.

Plant and bacterial differences must be considered; these organisms differ in their photosynthesis methods, genetics, and cellular organization. Years of evolutionary divergence might complicate and reduce the efficiency at which our system is incorporated into crop plants. Current crop cultivars have experienced years of selective breeding and hybridization that has extensively multiplied the chromosome copy number seen in certain species. Multiplication of the original haploid genome is known as polyploidy and it is a common occurrence in higher plants. Even considering that Synechococcus elongatus PCC 7942 also has multiple copies of its genome, the complexity is not as extensive in our single-celled prokaryote as these plants. Secondly, the multicellularity of plants requires additional care in ensuring that every cell has incorporated any genetic alterations. Otherwise, we can expect a mosaic effect in which only certain cells are overexpressing our target enzymes, which would make our system less effective and harder to evaluate.

Additionally, the random insertion of introduced DNA into the plant genome may lead to positional effects in which the expression of the transgene is silenced (8). This is a characteristic of eukaryotic organisms like plants, and increases variability in the results of genetic engineering. This is in part why full resequencing and verification of genetically modified food crops is integral to successful use, as only purposeful modifications are desired.

Finally, numerous unknowns may also affect future experimentation in plants, and we shall rely on ever-expanding scientific knowledge to unravel them. Despite these challenges, we are still confident that our research can support growth in plant genetics.

References

1. Smith C. Too Many Still Struggling to Meet Food and Nutrition Goals (https://ourworld.unu.edu/en/too-many-still-struggling-to-meet-food-and-nutrition-goals)

2. Ort DR, Merchant SS, Alric J, Barkan A, Blankenship RE, Bock R, Croce R, Hanson MR, Hibberd JM, Long SP, Moore TA, Moroney J, Niyogi KK, Parry MAJ, Peralta-Yahya PP, Prince RC, Redding KE, Spalding MH, Wijk KJ van, Vermaas WFJ, Caemmerer S von, Weber APM, Yeates TO, Yuan JS, Zhu XG. 2015. Redesigning photosynthesis to sustainably meet global food and bioenergy demand. PNAS 112:8529–8536. (https://doi.org/10.1073/pnas.1424031112)

3. New facilities support photosynthesis studies. RIPE. (https://ripe.illinois.edu/news/new-facilities-support-photosynthesis-studies)

4. Kahl G, Winter P. 1995. Plant genetic engineering for crop improvement. World J Microbiol Biotechnol 11:449–460. (https://doi.org/10.1007/BF00364620)

5. Bakhsh A, Anayol E, Özcan SF, Hussain T, Aasim M, Khawar KM, Özcan S. 2015. An insight into cotton genetic engineering (Gossypium hirsutum L.): current endeavors and prospects. Acta Physiol Plant 37:171. (https://doi.org/10.1007/s11738-015-1930-8)

6. López-Calcagno PE, Brown KL, Simkin AJ, Fisk SJ, Vialet-Chabrand S, Lawson T, Raines CA. 2020. Stimulating photosynthetic processes increases productivity and water-use efficiency in the field. Nat Plants 6:1054–1063. (https://doi.org/10.1038/s41477-020-0740-1)

7. Conner AJ, Jacobs JM. 1999. Genetic engineering of crops as potential source of genetic hazard in the human diet. Mutat Res 443:223–234. (https://doi.org/10.1016/s1383-5742(99)00020-4)

8. Dean C, Jones J, Favreau M, Dunsmuir P, Bedbrook J. 1988. Influence of flanking sequences on variability in expression levels of an introduced gene in transgenic tobacco plants. Nucleic Acids Res 16:9267–9283. (https://doi.org/10.1093/nar/16.19.9267)

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