We went through 4 rounds of the DBTL cycle for our "Best composite part”. This part encodes the master regulator for the plant transformation machinery of Agrobacterium. For the final composite part we used a characterized inducible promoter system to fine-tune the expression of the master regulator in order to allow fine-tuning for the individual plant species of choice.

We hope this part will allow future iGEM teams to work with their local plant species of choice by improving the ability to control Agrobacterium during plant transformation.

Figure 1: The figure illustrates our best composite part.


Agrobacterium mediated transformation is one of the most prolific methods for plant engineering, by far the most common method for iGEM teams as well. However, working with plant synbio is still far from a straightforward endeavor. This year, we set our sights on creating molecular tools that facilitate achieving successful transformation in non-model plant species, one of them is our Best Composite Part.

In nature, members of the genus Agrobacterium (Alphaproteobacteria) are soil-borne plant pathogens that integrate hormone-producing genes in the host plant genome to cause growth deformities and tumors. This mechanism can be explored by substituting the oncogenes by genes of interest, thus integrating them in the plant chromosomes. The most well known strain, Agrobacterium tumefaciens, promotes crown-gall disease in most dicotyledonous plants, however, other strains such as Agrobacterium rhizogenes are also able to transform plant cells (Bahramnejad et al., 2019; Barton et al., 2018). Despite their wide use, Agrobacterium-mediated plant transformation is still only well established for a handful of model organisms, making it hard for iGEM teams to engineer local species.

Part of the problem lies in the fact that some plant genotypes need specific Agrobacterium strains for transformation. As we found out, getting hold of the correct Agrobacterium strain for a plant species (if one is even known) is extremely hard, reaching up to hundreds of Euros and months of shipping time. This is made even worse by the confusing and often conflicting nomenclature of existing strains (De Saeger et al., 2021).

Therefore, we created a composite part that aims to improve the efficiency and host range of Agrobacterium strains by leveraging the VirG transcription factor as a Master-Switch of plant transformation. With it, we hope to enable future teams to further extend the garden of plant projects in iGEM.

The Molecular Machinery of Plant Transformation

Figure 2: The figure illustrates the key steps of Agrobacterium-mediated insertion of a target DNA (T-DNA) into the genome of a host plant. Originally, T-DNA and virulence genes are both located on the same plasmid, the Ti plasmid in A. tumefaciens or the Ri plasmid in A. rhizogenes. The picture shows transformation using a binary plasmid system, meaning that the vir region of the Ti plasmid is separated on a helper plasmid. Virulence is induced if either phenolic compounds are secreted by the wounded plant (dicots, 1a) or have to be added manually (monocots, 1b). After diffusing through the outer membrane, these phenolic compounds are sensed by the membrane-bound sensor kinase VirA (2). VirA in turn autophosphorylates and activates VirG (3). VirG is the master regulator of the vir operon and binds as a transcription factor to the promoters of the virulence genes. These genes are involved in the transfer of the T-DNA into the host plant's genome (step 4-5). Agrobacterium-mediated transformation can be used to insert any gene region of interest into a plant's genome.

Both the molecular machinery for plant infection and the DNA fragment that is excised and integrated into the plant genome (T-DNA) are located in a nonessential, mobile plasmid called the Ti or Ri plasmid (for Agrobacterium tumefaciens and A. rhizogenes, respectively). In its infection cycle, the metabolites released by plant wounds attract Agrobacterium chemotactically. These same phenolic compounds also activate the virulence response in Agrobacterium.

The T-DNA is composed of genes for the tumor formation and for the production of metabolites that are used as a carbon source by the bacterium, these are flanked by direct repeats (T-DNA borders) that are recognized by vir genes and are essential for the excision, transport, and integration in the plant genome. The T-DNA border sequence plays a fundamental role in the biotechnology applications of Agrobacterium, as the genes of interest to be transformed in plants must also be flanked by direct repeats (Ozyigit et al., 2013). Which genes are included in the T-DNA are the main factor in differentiating Agrobacterium strains, while the T-DNA of A. tumefaciens strains promotes the formation of overground tumors, the gene products of A. rhizogenes T-DNA result in the formation of the hairy root phenotype (Bouchez & Tourneur, 1991; Slightom et al., 1986).

The virulence (vir) region is a cluster of ~30 coding sequences responsible for the DNA transfer mechanisms, two of those genes, virA and virG, form a two component system in which VirA is a transmembrane histidine kinase and VirG the cytoplasmic response regulator (Cho & Winans, 2005). Upon binding to plant phenolic compounds (acetosyringone etc.), VirA phosphorylates VirG, which in turn functions as a transcription factor that binds to vir gene promoters and activates their transcription. Therefore, VirG can be seen as a “Master-Regulator” of Agrobacterium virulence.

Controlling the expression of this master regulator through its overexpression or the inclusion of extra copies from more potent strains has been shown to increase transformation efficiency and host range (Anand et al., 2019).

The VirG Master-Switch construct

We propose the use of a helper plasmid that decouples the expression of VirG from the VirA two component system, skipping the need for optimizing the bacteria growth medium and the use of phenolic compounds that emulate the plant response. By fine tuning the expression of this “Master-Switch” of Agrobacterium virulence, we aim to take control of the transformation machinery and tailor it to individual plant species. Here, we present the result of our engineering efforts and the multiple iterations of the design-build-test-learn cycle that culminated in our part.

Constitutive Expression (Cycle 1)

The initial design for our construct relied on maximizing the expression of a second copy of the endogenous virG from A. rhizogenes ARqua1. This was based on the assumption that a maximum induction of the virulence genes would lead to the best transformation results. This approach was also used to improve transformation efficiency in celery and rice (Liu et al., 1992). As a backbone, we chose the pSRK L1 entry vector, which was provided by the lab of our PI Anke Becker. It has a pBBR1 broad host range ori. Based on the data gathered from our Anderson Promoter characterization, we identified J23102 as the strongest constitutive promoter, and designed a construct that used this promoter to drive the expression of the endogenous virG CDS basic part we amplified from A. rhizogenes ARqua1.

The endogenous virG CDS was PCR amplified from gDNA extracted from A. rhizogenes ARqua1 and cloned in the level 0 entry vector from the Marburg Collection. The primers used were designed to also remove internal BsmBI cutting sites.

Figure 3: Comparison of the Anderson promoter library in A. rhizogenes and E. coli. J23103 was identified to be the strongest constitutive promoter in A. rhizogenes.

However, after more thorough research, and - most importantly - after consulting with Sebastian Cocioba, we found that strong virulence induction might be an extremely high metabolic burden for the cell, leading to slower growth and possibly even an overall decrease in transformation efficiency. This prompted us to return to the drawing board and rethink how our composite part could work.

Inducible Expression (Cycle 2)

Next, we decided to change the design by using an inducible promoter system. By doing that, not only could we delay the virulence response until it was actually needed, but also open up the potential for fine-tuning the virulence response for each plant species of interest. Here we faced another challenge, the lack of basic parts that are well characterized in Agrobacterium. While some efforts have been made in shedding light on the function of inducible systems in this organism, its volume still pales in comparison to other model organisms.

We selected 9 promoters from the “Marionette Collection”, which contains a number of inducible systems highly optimized (in E. coli) for high dynamic range and low leakiness (Meyer et al., 2019). Additionally, Ptrc and Ptau were also included (Mostafavi et al., 2014; Stukenberg et al., 2021). Another consideration made when selecting the promoter systems to characterize was to include ones that use non-phenolic compounds as inducers (Ptau, IPTG, Pbetl, and Pbad), in the hope of minimizing cross talk with the native VirA/VirG two component system.

Figure 4: Relative luminescence of 11 inducible promoters and a dummy promotor with maximum inducer concentration and mock induction with H2O in A. rhizogenes. The results reveal that except for Ptac, Pvan, PnahR and Ptau, most promoters do not significantly respond to the maximum inducer concentration.

The results in Fig. 3 show relative luminescence (RLU) output from H2O mock induction and maximum induction. This experiment demonstrated that most promoters did not respond significantly to induction in A. rhizogenes ARqua1, notable exceptions were Ptac, Pvan, PnahR and Ptau. With first two showing the highest overall induction strength and Ptau the widest dynamic range, in fact, the baseline expression of Ptau was as low as the dummy promoter, both at the threshold of detection for the plate reader used in the experiment, this demonstrates that the expression of Ptau is tightly regulated and has virtually zero leakiness. Overall, PnahR appeared to have a good middle ground between expression strength and orthogonality, and was selected for driving the expression of VirG in our Master-Switch construct.

Sodium Salicylate Inhibits Cell Growth (Cycle 3)

Unfortunately, we noticed in the previous experiment that despite the high luminescence output, cultures grown in 100 µM of sodium salicylate showed significantly slower growth rates (Fig 4 A). This prompted us to investigate the issue further and record the growth curve of A. rhizogenes carrying the PnahR characterization plasmid used in the previous experiment in a medium containing a serial dilution of sodium salicylate (Fig 4 B).

Figure 5: A. OD600 of A. rhizogenes over the course of 24 h with and without the respective inducer. Notably, cultures induced with the maximum concentration of sodium salicylate show significantly lower growth rates. B. Impact of different concentrations of sodium salicylate on the growth rate of A. rhizogenes. The addition of
100 µM notably inhibits growth in comparison to lower concentrations.

As shown in Figure 5 B, the maximum induction concentration of 100 µM and the first 1:10 dilution resulted in severe growth inhibition.

Agrobacterium are usually are equipped to tolerate such plant defense compounds as sodium salicylate and vanillin, and no toxicity was reported on previous characterizations using Agrobacterium tumefaciens C58, pointing at a possible strain specific behavior in A. rhizogenes ARqua1 (Colognori et al., 2023; Gelvin, 2018; Schuster & Reisch, 2021). Based on this data, we chose to streamline our VirG expression candidates to Ptac and Ptau, combining high expression potential with low leakiness.

Selection of suitable VirG CDS (Cycle 4)

In addition to the promoters, we also looked into literature for different variants of the VirG transcription factor, and built a combinatorial library of constructs.

There is a multitude of Agrobacterium strains with differing characteristics and virulence strengths. The strain A281 in particular, is able to transform a broader range of plant species and has higher efficiency due to its pTiBo542 Ti plasmid. Introducing copies of its virG and virB operons in regular strains has been shown to recreate the improved efficiency. This heightened activity is primarily attributed to the existence of V7I and I106T mutations in the coding sequence of the variant (Chen et al., 1991).

Figure 6: Bioinformatic comparison of the VirG aminoacid sequences from the pTiBo542 and the ARqua1 plasmid. We identified the amino acid leading to a “constituitively” active VirG(pTiBo542) at position 80 and subsequently used it to create mutated VirG(pTiBo542) constructs.

While the virulence of Agrobacterium usually depends on external signals for its activation through the VirA/VirG two component system, certain mutations in virG may result in a “constitutive” phenotype, where VirG binds to vir gene promoters and triggers virulence independent of being activated by VirA. One of these mutations, the change of one amino acid at position 54 from an asparagine (N) to aspartate (D) has been shown to cause in enhanced transformation efficiency in many plants (Chen et al., 1991; De Saeger et al., 2021). However, no “constitutitve” variety of virG (pTiBo542) has been produced so far. So, we used bioinformatic tools to identify the aminoacid in the longer VirG (pTiBo542) that is equivalent to the position 54 in VirG (N54D), and reproduced the mutation. Based on sequence alignments, we identified this site at position 80 of VirG (pTiBo542)

Constructs containing combinations of the endogenous A. rhizogenes ARqua1 virG, virG (pTiBo542), virG (pTiBo542 N80D), and the promoters Ptau and Ptac. This combinatory library was then transformed in A. rhizogenes ARqua1 for determining if an increase of plant transformation efficiency could be detected.

Figure 7: Transformation efficiency after 3 days. Constructs containing combinations of the endogenous A. rhizogenes ARqua1 virG, virG (pTiBo542), virG (pTiBo542 N80D), and the promoters Ptau and Ptac. This combinatory library was then transformed in A. rhizogenes ARqua1 for determining if an increase of plant transformation efficiency could be detected.

After the initial observation of results three days post-transformation with Ptau_super80_pSRK , Ptac_TiBo542_pSRK and Ptac_super80_pSRK (Figure 7), there was a noticeable decline in transformation efficiency which went from previous 46% to a range between 29% to 37%. To address this issue promptly and avoid any unnecessary delays, our team initiated troubleshooting procedures. This involved conducting stability assay tests to gain a deeper understanding of the factors contributing to the reduction in transformation efficiency.

The pVS1 and pBBR1 oris cannot be stably maintained together in A. rhizogenes (Cycle 5)

The pSRK entry vector carries the pBBR1 (broad host range) ori and was initially selected for our VirG overexpression constructs, due to its medium copy number in Alphaproteobacteria and compatibility with E. coli (Antoine & Locht, 1992; Blázquez et al., 2023). However, after observing that strains carrying both 35S:RUBY:KanR and Master-Switch plasmids displayed lower transformation efficiency when compared to strains solely carrying the 35S:RUBY plasmid, we decided to investigate further. This led to the suspicion that the two plasmids might be unstable when co-existing in Agrobacterium, negatively affecting cell health and thus decreasing overall transformation efficiency. In order to verify this hypothesis, we conducted a stability assay in A. rhizogenes ARqua1 carrying 35S:RUBY:KanR and Ptau_super80_pSRK. Cultures were grown overnight and used to inoculate a new liquid culture, until 5 overnight cultures were obtained. Samples from all days were verified via colony PCR.

Figure 8: By the 4th overnight culture, the cell density in all cultures of Agrobacterium carrying the pSRK constructs was already visible low, meanwhile, Agrobacterium carrying pABCa constructs grew normally. The colony PCR revealed that after 4 days, both plasmids were lost in plain LB and LB (gen+strep) cultures. In LB (gen+spec), the 35S:RUBY:KanR plasmid was detected in the 4th day and lost in the 5th. Based on these results, we opted to use the pABCa backbone as part of our next DTBL cycle for our VirG expression constructs, despite its lower copy number when compared to pSRK (Antoine & Locht, 1992; Döhlemann et al., 2017).

By the 4th overnight culture, the cell density in all cultures of Agrobacterium carrying the pSRK constructs was already visible low, meanwhile, Agrobacterium carrying pABCa constructs grew normally. The colony PCR revealed that after 4 days, both plasmids were lost in plain LB and LB (gen+strep) cultures. In LB (gen+spec), the 35S:RUBY:KanR plasmid was detected in the 4th day and lost in the 5th. Based on these results, we opted to use the pABCa backbone as part of our next DBTL cycle for our VirG expression constructs, despite its lower copy number when compared to pSRK (Antoine & Locht, 1992; Döhlemann et al., 2017).

Figure 9: Transformation events of ARqua1 harbouring the 35:RUBY:Kan plasmid and either Ptac_TiBo542_pABCa or Ptac_super80_pABCa three days post-transformation. Instead of pSRK, pABCa was chosen as a backbone. The number of transformation events is below baseline level but the plasmid seems to be more stable with the pABCa backbone.

Three days after transforming Arabidopsis with the two pABCa constructs, Ptac_super80_pABCa (Figure 9A) and Ptac_TiBo542_pABCa (Figure 9B), we observed transformation rates that were still notably low when compared to our baseline experiments. However, this outcome indicated a positive aspect of our work – our strains seemed not to lose our construct plasmid. This result aligned with our cultivation practices, as we only cultured Agrobacterium for 1-2 days, and plasmid loss seems to occur after 4 days. Moreover, the pABCa plasmid exhibited stability and demonstrated comparable transformation efficiency after 3 days when compared to constructs with the pSRK backbone.

Figure 8: Trandformation efficiency after 10 days. Constructs containing combinations of the endogenous A. rhizogenes ARqua1 virG, virG (pTiBo542), virG (pTiBo542 N80D), and the promoters Ptau and Ptac. This combinatory library was then transformed in A. rhizogenes ARqua1 for determining if an increase of plant transformation efficiency could be detected.

Upon evaluating our most recent results 10 days post-transformation (see Figure 8) with constructs containing the pSRK backbone, we were surprised to witness an unexpected increase in the number of RUBY-positive plants compared to the 3-day post-transformation results (see Figure7). We were especially surprised by the Ptac_TiBo542_pSRK transformation results which showed a transformation efficiency gain of 11% in comparison to the 35S:RUBY:KanR baseline. The current efficiency levels now seem to be on par with the outcomes from the baseline experiments. With the assumption that pABCa behaves similarly, we anticipate obtaining comparable results ten days after transformation, and we anticipate these results to be available within the next week.

Conclusion and Outlook

In our future endeavors, we plan to seek out a multi-copy ori that combines the advantageous traits of both the pSRK and pABCa backbones. This will ensure stability while allowing for high copy numbers in our plasmids. We are dedicated to testing all of our constructs, with particular emphasis on the most promising ones, in a variety of non-model plants such as the bambara groundnut. Our goal is to establish if we can achieve results comparable to, or even better than, those obtained in our baseline experiments.

Furthermore, our upcoming research will focus on refining the optimal concentration of taurine for Ptau. This fine-tuning process will help us create ideal virulence activity conditions for our transformations. With the current results at our disposal, along with forthcoming data and possible new experiments, we aim to develop a standardized toolkit. This toolkit will provide the iGEM community with the means to efficiently transform non-model plant species, enabling them to tackle local challenges using their native plant varieties.


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