In our project, we have combined RNAi and plant immunity to control tomato gray mold disease.

In the experiments of RNAi, we obtained the following results:

  • -We designed shRNA and ligated it into the pET-28a(+) plasmid. The target shRNA was expressed through induction in Escherichia coli HT115(DE3).

  • -We combined cell-penetrating peptide (CPP) BP100-(KH)9 with shRNA and observed their morphological structure using scanning electron microscopy (SEM).

  • -We applied naked shRNA, BP100-(KH)9+shRNA, and BP100-(KH)9+bi-shRNA to tomato fruits, and demonstrated the effectiveness of our RNAi by calculating the distribution of disease spots.

  • -We applied naked shRNA, BP100-(KH)9+shRNA, and BP100-(KH)9+bi-shRNA to tomato fruits, and demonstrated the good silencing effect of our shRNA on the target genes through qRT-PCR.

In the experiments of plant immunity, we conducted the following three aspects of work:

  • -We constructed the BvEP plasmid for E. coli BL21(DE3) and B. subtilis WB800. And we verified the successful transformation.

  • -We obtained the optimal induction conditions for BvEP and verified its successful expression in BL21(DE3).

  • -We validated BvEP's role in triggering plant immunity and demonstrated that the intensity of the immune response increased as protein concentration increased.

RNAi therapy

shRNA stage

When deciding to use RNAi technology to kill Botrytis cinerea, we need to consider which small RNA (sRNA) molecules can trigger the RNAi process. We first noticed that siRNA molecules can enter the cells and load on RISC to effect. Knowing the instability of siRNA and considering production costs, we decided to design shRNA to silence the target gene. This way, we can use E. coli in the laboratory for low-cost but mass production of shRNA.

shRNA can be recognized and processed into siRNA by Dicer, and then combines with Ago protein to form the RNAi silencing complex (RISC). RISC, consisting of Argonaute-2, Dicer, and TRBP proteins, can then specifically silence the expression of target genes.

Our RNAi method is Spray-Induced Gene Silencing (SIGS), which has been widely used in agricultural research since its first application in 2016. It is a new non-transformation strategy that suppresses pathogenic gene expression by spraying RNAi molecules produced exogenously onto plant tissues. The sprayed RNAi molecules are absorbed by cells through stomata or lenticels, and move throughout the body via hyphae or phloem sieve tubes, causing gene silencing and induced mortality without transformation.

Selection of shRNA Molecular Target Genes

We have selected a total of 6 target genes as our RNAi silencing targets. The information of these target genes is shown in the Table 1. BcchsIIIa and Bccyp51 are essential genes for the survival of B. cinerea, while BcOAH1, Bcpme1, Bcdcl1, and Bcdcl2 are key genes involved in the infection process of B. cinerea on tomatoes. Furthermore, we have concatenated 2 shRNAs targeting the survival genes of B. cinerea with the specific sequence ATGCCT, to build a bi-shRNA named shRNA(Box-survival). We have also stringed 4 shRNAs targeting the key genes involved in B. cinerea infection on tomatoes, and named it shRNA(Box-infect).

Table 1. Target Genes and their Target Sequences of shRNA

After selecting the above target genes, we designed the corresponding shRNA molecule through the CDS sequence of the target gene. After BLAST and confirmation of its specificity in the total nucleic acid library, we assembled it through the sequence of XbaI restriction site - sense RNAi fragment - loop - reverse antisense RNAi fragment - BlpI restriction site, and connected it to the pET-28a (+) plasmid to obtain our shRNA expression vectors.

IPTG induced production

After plasmid extraction, we transformed the constructed shRNA expression vector into E. coli HT115(DE3) and performed PCR. Our specific primers successfully amplified a 260 bp band from the plasmid, confirming the successful transformation of the plasmid (Figure 1). This indicates that the shRNA expression vector has been successfully introduced into E. coli and can be detected and confirmed by PCR. This is an important milestone that lays the foundation for further experiments.

Figure 1. Agarose Gel Electrophoresis of Plasmids after Plasmid PCR
1-5: Plasmids control; 5-10: Plasmids extracted from E. coli.

After induction with IPTG, the RNA was extracted using the Trizol method and the results shown in Figure 2 were obtained after electrophoresis. Compared to the non-induced sample, there is a brighter band between 50-100 bp and 100-150 bp in the induced sample lane. Our shRNAs have the size of 69 bp, while the Box-survival, which is a concatenation of two shRNAs, have the size of 124 bp. This confirms the successful extraction of our shRNA, and the generated shRNA is of the expected size.

Figure 2. Electrophoresis of RNA extracted from E. coli HT115 (DE3)

CPP+shRNA Stage

However, the instability of shRNA in the field environment hinders the optimal performance of our product. Understanding our expectations, our PI suggested that we could try using cell-penetrating peptides (CPP) in combination with shRNA for spray application, and provided us with BP100-(KH)9 as our CPP material. BP100-(KH)9 is a carrier peptide-based gene delivery system that enhances the endocytic uptake and cytoplasmic transfer of shRNA in plants, allowing for more efficient transfection of plant callus cells with shRNA. To understand the morphology of the shRNA and BP100-(KH)9 complex, we used scanning electron microscopy (SEM) to observe the morphology of shRNA, BP100-(KH)9, and shRNA+BP100-(KH)9 separately. As shown in the Figure 3, we observed that shRNA and BP100-(KH)9 form spherical aggregates under electron microscopy. These small spherical aggregates further tend to aggregate with each other. We speculate that this stacking aggregation is due to electrostatic forces.

Figure 3. Morphology of shRNA+CPP under Scanning Electron Microscope at 40,000x Magnification

More information on the RNAi process, including phenotype statistics and molecular validation, can be found in Proof of Concept

Plant Immunity

In the early stage of the plant immune induction project, we selected several potential inducers of plant immune response based on their characteristics for proof-of-concept. One such immune-inducing factor is oligogalturonic acid (OGs), which belongs to the damage-associated molecular patterns of plant cells. It is a kind of oligosaccharide produced after the destruction of plant cell wall component pectin by pathogen infection. It can be recognized and bound by pattern recognition receptors (PRRs), thereby stimulating downstream immune pathways. We used PehA, a polygalacturonate endonuclease, as our immune-inducer to induce plant immunity by targeting the plant cell wall to produce OGs.

The other is induced factors which are Pathogen-associated molecular patterns. In this study, we selected Pseudomonas aeruginosa flagellin, which has a 22-amino acid N-terminal peptide that can activate downstream immune pathways by binding to the cell surface receptor FLS2-BAK1. This peptide flg22 was used as an immune-inducing factor, and three flg22 were concatenated to obtain 3x flg22 to verify their immune effects.

We also hope to stimulate the ETI response in plants, so that plant cells can produce a stronger and sustained immune effect. We selected BvEP, a protein phosphomutase from Bacillus velezensis LJ02, in the hope that its expression in Bacillus subtilis would activate tomato sustained defense.

Construction and transformation of plasmids

To verify whether the selected immune-inducing factors PehA, Flg22, 3xFlg22 and BvEP could activate plant immunity, we constructed their gene expression vectors in E. coli and all of their expression were regulated by IPTG.

Figure 4. Gene pathways for immune-inducing factor expression.

After constructing the expression vectors of the immune-inducing factors above, we transferred these recombinant plasmids into E. coli BL21 (DE3), and then screened positive monoclonal colonies in resistant plates for expansion culture and plasmid extraction. The cloned products containing the target fragment were amplified with specific primers and verified by DNA agarose gel electrophoresis. As shown in Figure 5, electrophoresis results showed that the bands of different recombinant plasmids amplified by PCR were all of the expected sizes, indicating that our plasmids were successfully transformed into E. coli BL21(DE3).

Figure 5. Results of amplification of different recombinant plasmids by specific primers.
(a)PCR of pGS21a-PehA. M: DL2000 DNA marker; 1: PehA. (b)PCR of 1x Flg22, 3x Flg22, Flagellin full length and BvEP in vector pET-28a. M: DL2000 DNA marker; 1-4: 1x Flg22, 3x Flg22, Flagellin full length and BvEP.

Expression of Proteins

The expression of immune protein factors is regulated by the lac operon, so IPTG was applied to induce our protein expression. The PehA proteins were extracted using the GST-tag protein purification kit, and the rest of the proteins were extracted using the His-tag protein purification kit. After extraction of the proteins we induced to express, the protein concentration was determined by the BCA assay. BvEP was expressed at very low levels under conventional induction conditions. We then optimized this assay and found that protein expression levels were higher when induced at 100 rpm in a shaker at 20 ° C. The protein concentration of BvEP in 4.5 mL volume of induction culture was measured at 4 h, 8 h, and 16 h of induction, and the expression concentration of BVEP protein was the highest after 16h of induction, reaching 0.530 mg/ml.

Figure 6. BCA standard curve.

In addition, we verified the extracted target proteins by SDS-PAGE after 16 h of induction. As shown in the figure, Figure 7a shows the BvEP protein electrophoresis after 16h of IPTG induction. By comparing with the total protein of E. coli BL21(DE3) without induction, it can be seen that there is a clear band between 14.4kD and 4kD. The predicted size of BvEP protein was 12.1kD, indicating that this band was our target protein. Similarly, in Figure 7b, an obvious band between 35kD and 25kD appeared after 16 h of IPTG induction compared with the non-induced sample, while the size of our Flagellin full length protein was 30.6kD, showing that it was successfully induced.

Figure 7. The induced expression of target proteins detected by SDS-PAGE.
(a)Induced expression of BvEP. (b)Induced expression of Flagellin full length.

In addition, our target proteins were also verified in Western Blot experiments. As can be seen from Figure 8, there is a specific band between 15kD and 10kD, and the protein size of BvEP is 12.1kD, indicating that the protein extracted from the induced E. coli is indeed our target protein.

Figure 8 Western Blot validation of BvEP induced expression

However, when we tried to express PehA, 1x flg22, and 3x flg22, the amount of the proposed protein was found to be too low for subsequent DAB experiments and was therefore abandoned in later experiments.

DAB staining experiment

The burst of ROS is a typical response to the activation of plant immunity, so we performed DAB staining experiments to examine the degree of ROS burst in tomato leaves after treatment with different concentrations of BvEP. The darker the DAB staining results, the more ROS burst in the leaves. In that experiment, our control group 1 was treated with clean water and control group 2 was treated with total protein extracted in E. coli BL21(DE3) without induction (Figure. 9).

Figure 9. DAB staining to detect the intensity of immunity triggered by different concentrations of BvEP.
(a)Soaking method to apply BvEP. Low: 10ug/ul, Mid: 25ug/ml, High: 50ug/ml. (b)Dropping method to apply BvEP. Low: 40ug, Mid: 100ug, High: 200ug.

After staining, ImageJ software was used to perform gray scale analysis of the leaves treated with the two different BvEP methods to quantify the immune intensity, followed by t-test to determine the significant difference between the different BvEP concentrations. Lower gray levels, that is, more brown precipitates in leaves, indicate a stronger burst of ROS. Each treatment contains a sample number of 9, and the resulting data are shown in Figure 10.

Figure 10. Gray levels in different leaves measured by ImageJ software.
(a)The gray value of leaves treated protein after soaking. (b)The gray value of leaves after dropping. (ns P > 0.05; * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001).

As can be seen from the figure above, the degree of ROS burst in leaves increases with the concentration of applied BvEP, whether using the soaking or dropping method. Through the comparison of the two methods, we can obviously observe that the ROS burst in the leaves treated by soaking method is more than that by dropping method.

More details can be viewed in Proof of concept.

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