Team:KU Leuven/Implementation

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BLADEN implementation


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Preparing for the worst-case scenario

As stated by the Intergovernmental panel on climate change in the physical science basis for climate change 2021 [1]:

All regions39 are projected to experience further increases in hot climatic impact-drivers (CIDs) and decreases in cold CIDs (high confidence). Further decreases are projected in permafrost, snow, glaciers and ice sheets, lake and Arctic sea ice (medium to high confidence) 40. These changes would be larger at 2°C global warming or above than at 1.5°C (high confidence). For example, extreme heat thresholds relevant to agriculture and health are projected to be exceeded more frequently at higher global warming levels (high confidence).

To prepare for such scenarios, BLADEN offers a fast way to evolve and analyze single plant cells. This artificial evolution is used to adapt the plant cells to be more resilient against the effects of climate change. The implementation of such process requires a plan. Our proposed implementation includes a conceptualization of a sustainable real-world implementation, its relevant safety aspects and further challenges that must be solved.


Because BLADEN operates on single plant cells, it is relatively easy to analyze genetic changes. Additionally, BLADEN can obtain genetic information of the best genotypes much faster than companies that apply directed evolution on whole plants, as it is able to continuously mutate the cells indefinitely.

We combined a CRISPR based mutagenesis technique with the power of single celled plant cultures to speed up evolution in plants. The CRISPR based mutagenesis tool called EvolvR uses 2 separate enzymes, which are fused together, to operate. An nCas enzyme, which nicks a specific targeted region in the DNA based on the supplied gRNA. And an error-prone polymerase, which displaces the nicked strand and synthesizes a new error-filled strand in its place.

By using this mutational scheme, and applying it to a culture of single celled plant cells, we can increase the speed at which plants evolve. Furthermore, detailed biological knowledge is not needed beforehand because the evolutionary process works as a black box anyway! The input needed for an experiment is a well-chosen gRNA, which can be determined by carefully examining a very approximate structure of the protein in question. The output of an in planta directed evolution experiment, conducted in the BLADEN way, is sequence-fitness data.

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Figure 1: cartoon diagram of the EvolvR mechanism.

From this output, we derive our two main products. Firstly, by knowing which genetic sequence corresponds to the fitness of the genotype of a plant cell, we can obtain the genetic information of the genotype that performs most optimally in a certain environment. This genetic information may then be used to genetically manipulate other plant cells. Secondly, we gain insight and knowledge on protein function by analyzing the effects of certain genetic changes on the genotypes’ fitness.

End-users and real-world implementation

BLADEN in planta directed evolution gives us a way to easily obtain lots of annotated genetic data. Many variants of proteins can be produced in a short time accompanied with fitness data for specific environments. For example, a critical metabolic protein can be optimized to operate at a very low temperature, or a very high temperature, or anything in between! For each temperature a specific variant is stored in a database. The idea is that other companies use this data to build or upgrade their GMO crops.

The scope of in planta directed evolution need not only be limited by optimizing native proteins. Foreign genes hailing from organisms such as bacteria can also be optimized in a plant environment. This leads to new opportunities, such as the readjustment of entire plant metabolisms using non-native enzymes, or the ability to improve various synthetic biology tools beyond what was first possible to increase their effectiveness even more. To enlarge the collection of improvable traits, a device that is able to select genotypes based on their fitness through measurements would be beneficial. Therefore, we have created a hardware concept and went through many different iterations to see what is most feasible. The result is the CellED. This device uses a mutagenesis library evolved through EvolvR and select based on optical measurements. Of course, a real world implementation of such a device would still require a lot of research and development investments. In fact, we did actually find a mechanism that has a large chance of succeeding, but also a very high fabrication cost. In the future, we expect these costs to drop, making the mechanism more feasible.

Lately, there is an increasing number of reports where farmers lost a large portion of their harvest, have decreased growth or are totally unable to grow any crops, specifically due to disasters and environmental changes of which the severity is impacted through climate change. As stated by Professor A. Ortiz-Baboa [2]:

We find that climate change has basically wiped out about seven years of improvements in agricultural productivity over the past 60 years. It is equivalent to pressing the pause button on productivity growth back in 2013 and experiencing no improvements since then. Anthropogenic climate change is already slowing us down.

Having access to a large database of very specifically optimized genes can help adapt plants to more local conditions. In a situation where the climate is changing, adapting crops to a more dry environment, or to an area were flooding happens more often, can reduce the risk of bad harvests and keep hunger crises at bay. Furthermore, BLADEN in planta directed evolution can adapt plants which are normally grown in specific regions, to other more diverse regions. As an example, Soy is mainly being produced in the America’s. Adapting soy to Europe’s or Africa’s local conditions can circumvent the need to ship this crop all around the world, and reduce the stress on the rainforests created by this massive industry.

Using a royalty fee approach, BLADEN may keep on producing massive amounts of sequence-fitness data based on the needs of the ever changing world.

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Figure 2: An overview of the end-user chain. BLADEN partners with / sells to GMO companies to build/improve their crops. It are then the GMO companies that sell to the farmer.


Genetically modified organisms can in general be harmful to the environment, people, plants, and animals. The results of BLADEN thus contain the same safety and ethical risks as GMOs.

The expected increase of global food demand has been widely discussed, and despite some discrepancies on the exact extension of this rising, there is a current agreement on the need of finding solutions that would allow us to feed the growing world population [3]. Just to name some famous reports, it has been shown by the Food and Agriculture Organization of the United Nations (FAO) that the world food production needs to increase by 60% to feed the world population in 2050 [4], while Tilman et al. published values that indicated the necessity of augmenting the food production in more than a 100% for that same year [5]. A feasible solution to this problem lies in the realm of plant biotechnological research. Nonetheless, we consider of prime importance the consideration of the accompanying ethical concerns, as well as the biosafety risks. In our opinion, one of the fundamental ethical concerns derived from the generation of genetically modified plants is the power imbalance introduced by the biotechnological intellectual property. Multi-national companies dominate the plant seed market, leaving little choice for the farmers. Despite the legal recognition of the farmer’s rights dating to the 1980’s, it is not widespread the scope of the legislation, and many countries have not recognized this international treaty. We believe that it is of paramount importance that the international community addresses this subject, and that the awareness generation of these ethical concerns is also a responsibility of the scientific community.

In the future our project could move beyond the lab, where optimized plant genes developed by our system are inserted into plants in the environment. Genetically modified plants could cause biosafety issues. Among the most relevant ones, we could encounter the genetic erosion of crops, the potential unintended gene flow, the harm to other non-targeted species that could be inadvertently harmed, and the toxic and allergenic potential for human beings. All these factors need to be thoroughly evaluated before releasing a genetically modified plant to the environment. Regarding our project, the use of BLADEN does not bring new ethical or safety concerns to the current landscape of issues that need to be addressed. Even more, the possibility of generating new plant variants using the largely known accuracy of CRISPR technology is an assurance that the engineering of the organisms will be pursued safely and minimizing the possibility of obtaining undesired mutations that could go undetected. Therefore, we believe that if our technology succeeded, we could make the plant engineering industry safer.

Challenges and future potential

One of the challenges to implement in planta continuous directed evolution is that there are few continuous selection methods available at the moment. We are, however, optimistic about more selection methods being discovered. Two main classes of selection methods can be made.

The first class of selection methods links growth inversely proportional to the trait-related efficiency of the target organism. These selection methods generally require a complex biological system to operate. Finding generalized selection methods for a class of traits is very beneficial for continuous directed evolution and it would be a very cool iGEM project.

The second class of selection methods completely discards mutants that are less fit than a certain threshold. Such selection methods are found in directed evolution devices, such as the CellED. While being much more universally applicable at the moment, these devices do need a very detailed online model to explore as much as the fitness-sequence landscape as possible. The device also must keep the cells intact and measure cell content with great accuracy. All these requirements make them very complex.

Another challenge is that we may find a fitter genotype of a plant cell, but for the plant itself to be fitter we need to do careful analysis of the effect of the genetic manipulation inside of the living plant. There is thus a trade-off between the rapidness of finding genetic sequences in single cell cultures and the in-planta effectiveness. Combining whole-plant and single cell culture directed evolution may thus be an even more efficient way of finding fit genotypes.


  • [1] IPCC, Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. In Press. (2021)
  • [2] Blaine Friedlander. Climate change has cost 7 years of ag productivity growth. Cornell University. (2021)
  • [3] van Dijk, M., Morley, T., Rau, M.L. et al. A meta-analysis of projected global food demand and population at risk of hunger for the period 2010-2050. Nat Food 2, 494-501 (2021).
  • [4] FAO How to Feed the World in 2050 (High-Level Expert Forum, 2009).
  • [5] Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260 (2011).