Proof of Concept

The presence of an active siRNA pathway in Phytophthora capsici was demonstrated in a study where siRNAs were used to target the RXLR effector genes. The results indicated successful siRNA uptake and reduction in the pathogen’s virulence (Cheng et al., 2022).

Our siRNA design workflow followed strategies consistent with established methodologies to ensure the selection of efficient siRNAs. Candidate sequences were first generated using two siRNA design tools, namely siRNApred and siDirect, which systematically filtered viable candidates based on critical features including thermodynamic stability, GC content, and URA rules (U + R + A). Off-target analysis was performed using BLAST to confirm specificity. The shortlisted candidates were further evaluated using DuplexFold to ensure stable binding of the siRNA to the target mRNA. We used MaxExpect to ensure the absence of loops in the target mRNA regions that might reduce efficiency. This layered and rigorous screening process ensured that the final siRNAs retained both functional efficiency and target specificity, thereby establishing the validity of our workflow as a proof of concept (Ayyagari, 2022; Ui-Tei et al., 2004).

Extensive literature has proven that bZIP1 from Phytophthora infestans regulates key infection processes, including zoospore motility, cyst germination, appressorium formation, and host invasion. Most importantly, silencing this gene results in complete infection failure despite normal hyphal and sporangial development (Blanco & Judelson, 2005).

We referred to transcriptomic data on Phytophthora capsici, which identified the transcription factor bZIP1 (Protein ID: 128162) (Lamour et al., 2012) as highly upregulated during early infection (Log₂FC: 6.86, padj = 6.51E−12) (Vijayakumar et al., 2024).

Stability of the siRNA complex

The stability of siRNA is crucial to prevent its degradation. Its negative charge allows for the interaction with the electropositive chitosan nanoparticles. This leads to the encapsulation of the siRNA, and the complex is stable enough to survive in environments such as soil, which contains RNases and experiences varying temperatures and pH, leading to its degradation.

Chitosan nanoparticles can penetrate the cell walls of P. capsici (Hernández-Lauzardo et al., 2011). Molecules of chitosan, which are positively charged, act on the plasma membrane by neutralizing the negative charge on the cell surface. This increases the cell permeability for the entry of the siRNA-chitosan complex (Guo et al., 2008).

A combination of high and low molecular weight fractions of chitosan exhibits antifungal properties. The high molecular weight fractions disrupt membrane integrity, facilitating the penetration of the low molecular weight fractions into the pathogen, thereby interfering with essential cellular processes (Poznanski et al., 2023). This physicochemical property of chitosan ensures that the siRNA carried by the chitosan nanoparticles reaches the cell's cytoplasm and has access to its RISC complex.

The release of siRNA from the chitosan nanoparticle complex significantly depends on the change in pH (Aydın et al., 2012). A pH of around 7.4 triggers the release mechanism of chitosan nanoparticles (Kalagatur et al., 2018). Pepper soil ranges from 4.5 to 6.6, while the cytoplasmic pH is 7.6 (Tamil Nadu Agricultural University, 2014; Hesse et al., 2002). This indicates that the siRNA will be released into the cytoplasm and bind to the RISC complex, facilitating gene silencing.

The wet lab experimental flow was designed to produce, characterize, and prove the effectiveness of the siRNA nanoformulation using a combination of instrumental analysis, inhibition assays, and observation techniques.

1. Chitosan Nanoparticle Production

Chitosan nanoparticles (CSNPs) were synthesized using ionic gelation (De Carvalho et al., 2019). The protocol was optimized to produce nanoparticles of ideal zeta potential, hydrodynamic radius, and polydispersity index that can be used to encapsulate siRNA. The CSNPs were characterized using a Particle Size Analyzer. Scanning Electron Microscopy provided further insight into the morphology of the CSNPs (Oh et al., 2019).

2. Phytophthora capsici

In tandem with nanoparticle production, P. capsici was subjected to experiments to understand its morphology and growth. A series of colony diameter measurements was used to observe the growth of P. capsici on different growth media, such as carrot agar and potato dextrose agar (Santos et al., 2023; Lu et al., 2011; Wang et al., 2009). Lactophenol cotton blue staining was performed to visualize the morphology of P. capsici. Subcultures were established to provide fresh cultures for zoospore observation and various assays.

3. Cytotoxicity assay

A cytotoxicity assay was performed to evaluate the effects of various concentrations of our siRNA, resuspended in nuclease-free water, on black pepper (Piper nigrum Panniyur-1 variety) leaves. A successful assay was indicated when none of the leaves tested with the sample showed any signs of necrosis on their surface.

4. siRNA Nanoformulation

Encapsulation of siRNA was done by adding a precise concentration of siRNA to the tripolyphosphate cross-linker solution during nanoparticle production (Katas & Alpar, 2006). In order to check whether encapsulation has occurred, the nanoformulation was loaded on a 4% agarose gel along with suitable controls (free siRNA, unencapsulated nanoparticle) to visualize any free siRNA from the sample (Raja et al., 2015). Successful encapsulation was indicated by the absence of free siRNA on the gel from the sample. Entrapment efficiency of the siRNA encapsulated within the chitosan nanoparticle was calculated to understand how well the encapsulation occurs.

5. Fluorescence Microscopy

The siRNA was tagged with a 6-FAM fluorescent dye. The presence of fluorescence signal in the zoospores not only helps us visualize the siRNA’s uptake and internalization, but also proves the efficacious release of siRNA from the chitosan nanoparticle carrier (Cheng et al., 2022). This proves that our system is working effectively as a whole.

6. Zoospore Testing

Upon sporulation and facilitating the release of zoospores, our siRNA, along with the nanoformulation and necessary controls, was tested on P. capsici zoospore samples. Observing the effect of the siRNA and nanoformulation on zoospore motility verified the silencing of the bZIP1 gene (Blanco & Judelson, 2005).

7. Detached Leaf Assay

Black pepper leaves were deliberately infected with P. capsici to visualize the effectiveness of our nanoformulation (Paul et al., 2019). This was done through a detached leaf assay, and the virulence silencing action of our siRNA on P. capsici was evaluated. A successful detached leaf assay was indicated by a reduction in lesions formed on black pepper leaves treated with the nanoformulation, indicating the effectiveness of the nanoformulation and siRNA on P. capsici within black pepper.

When different siRNA sequences are encapsulated within the same nanoparticle, they exhibit distinct stability due to sequence-specific interactions with the nanoparticle surface. This variability, driven by nucleotide composition, structural dynamics, and chemical modifications, reveals why generic nanoparticle formulations for different nanoparticles are insufficient. To address this, we developed S.E.N.S.E., which customizes optimization for each siRNA-nanoparticle pair.

1. Specific motifs, like U–A or G–U are susceptible to nuclease-catalyzed hydrolysis. These motifs create weak points, especially near the NP surface, where nucleases can cleave the RNA backbone, thereby affecting the life span of RNA for degradation. The covalent and electrostatic bonding alter how nucleic acid regions are exposed to nucleases (Barnaby et al., 2014). For example, in gold NP systems, sequence-specific half-life varies from 2 to 1,000 minutes. This highlights how attachment influences accessibility (Barnaby et al., 2014).
2. Chemical modifications, such as 2’-O-methyl RNA nucleotides, can enhance stability, but their efficacy is sequence-dependent and also influences degradation (Barnaby et al., 2014; Patel et al., 2011).
3. Duplex end breathing refers to the transient opening of siRNA duplex ends, exposing single-stranded regions to nucleases. The distal “breathier” ends, with lower thermal stability, degrade faster. siRNAs with 3’ overhangs, while aiding the Dicer recognition for intracellular processing, degrade up to 15 times faster in serum than blunt-ended siRNAs, which maintain stability while remaining functional (Tokatlian & Segura, 2010).

The proof of concept for the proposed software model will be demonstrated using molecular docking and molecular dynamics (MD) simulations. Molecular docking provides a computational framework to predict the binding affinity, orientation, and interaction sites between siRNA molecules and nanoparticle carriers, thereby offering an initial assessment of compatibility and binding strength (Morris & Lim-Wilby, 2008). However, docking alone represents a static picture of biomolecular interactions. MD simulations will be employed to capture the dynamic and thermodynamically relevant behaviour of the complexes. MD allows the exploration of structural stability, conformational flexibility, and energetics of siRNA–nanoparticle complexes under near-physiological conditions. Thus validating binding persistence and functional stability over time (Hollingsworth & Dror, 2018). Together, these computational approaches will serve as a proof of concept for the predictive capability of the model prior to experimental validation (Gao et al., 2022).

The reason we decided to use machine learning to solve this problem is that most papers have demonstrated the feasibility of applying machine learning algorithms for siRNA efficacy prediction. For instance, neural networks and support vector machines have been used for sequence-based siRNA efficacy classification (Saetrom, 2004). More recently, ensemble and tree-based models like Random Forest and XGBoost have shown the ability to capture non-linear relationships in biomolecular data.

Aydın, R. S. T., & Pulat, M. (2012). 5‐Fluorouracil encapsulated chitosan nanoparticles for pH-stimulated drug delivery: Evaluation of Controlled Release Kinetics. Journal of Nanomaterials, 2012(1). https://doi.org/10.1155/2012/313961

Ayyagari, V. S. (2022). Design of siRNA molecules for silencing of membrane glycoprotein, nucleocapsid phosphoprotein, and surface glycoprotein genes of SARS-CoV2. Journal of Genetic Engineering and Biotechnology, 20(1), 65. https://doi.org/10.1186/s43141-022-00346-z

Barnaby, S. N., Lee, A., & Mirkin, C. A. (2014). Probing the inherent stability of siRNA immobilized on nanoparticle constructs. Proceedings of the National Academy of Sciences of the United States of America, 111(27), 9739–9744. https://doi.org/10.1073/pnas.1409431111

Blanco, F. A., & Judelson, H. S. (2005). A bZIP1 transcription factor from Phytophthora interacts with a protein kinase and is required for zoospore motility and plant infection. Molecular Microbiology, 56(3), 638–648. https://doi.org/10.1111/j.1365-2958.2005.04575.x

Cheng, W., Lin, M., Chu, M., Xiang, G., Guo, J., Jiang, Y., Guan, D., & He, S. (2022). RNAi-Based Gene Silencing of RXLR Effectors Protects Plants Against the Oomycete Pathogen Phytophthora capsici. Molecular Plant-Microbe Interactions, 35(6), 440–449. https://doi.org/10.1094/mpmi-12-21-0295-r

De Carvalho, F. G., Magalhães, T. C., Teixeira, N. M., Gondim, B. L. C., Carlo, H. L., Santos, R. L. D., De Oliveira, A. R., & Denadai, Â. M. L. (2019). Synthesis and characterization of TPP/chitosan nanoparticles: Colloidal mechanism of reaction and antifungal effect on C. albicans biofilm formation. Materials Science and Engineering C, 104, 109885. https://doi.org/10.1016/j.msec.2019.109885

Gao, H., Kan, S., Ye, Z., Feng, Y., Jin, L., Zhang, X., Deng, J., Chan, G., Hu, Y., Wang, Y., Cao,D., Ji, Y., Liang, M., Li, H., & Ouyang, D. (2022). Development of in silico Methodology for siRNA lipid nanoparticle formulations. Chemical Engineering Journal, 442, 136310. https://doi.org/10.1016/j.cej.2022.136310

Guo, Z., Xing, R., Liu, S., Zhong, Z., Ji, X., Wang, L., & Li, P. (2008). The influence of molecular weight of quaternized chitosan on antifungal activity. Carbohydrate Polymers, 71(4), 694-697. https://doi.org/10.1016/j.carbpol.2007.06.027

Hernández-Lauzardo, A. N. (2011). Current status of action mode and effect of chitosan against phytopathogenic fungi. African Journal of Microbiology Research, 5(25), 4243–4247. https://doi.org/10.5897/AJMR11.104

Hesse, S., Ruijter, G., Dijkema, C., & Visser, J. (2002). Intracellular pH homeostasis in the filamentous fungus Aspergillus niger. European journal of biochemistry, 269(14), 3485-94. https://doi.org/10.1046/J.1432-1033.2002.03042.X

Hollingsworth, S. A., & Dror, R. O. (2018). Molecular dynamics simulation for all. Neuron, 99(6), 1129–1143. https://doi.org/10.1016/j.neuron.2018.08.011

Kalagatur, N. K., Nirmal Ghosh, O. S., Sundararaj, N., & Mudili, V. (2018). Antifungal Activity of Chitosan Nanoparticles Encapsulated With Cymbopogon martinii Essential Oil on Plant Pathogenic Fungi Fusarium graminearum. Frontiers in Pharmacology, 9, 356156. https://doi.org/10.3389/fphar.2018.00610

Katas, H., & Alpar, H. O. (2006). Development and characterisation of chitosan nanoparticles for siRNA delivery. Journal of Controlled Release, 115(2), 216–225. https://doi.org/10.1016/j.jconrel.2006.07.021

Lamour, K. H., Mudge, J., Gobena, D., Hurtado-Gonzales, O. P., Schmutz, J., Kuo, A., Miller, N. A., Rice, B. J., Raffaele, S., Cano, L. M., Bharti, A. K., Donahoo, R. S., Finley, S., Huitema, E., Hulvey, J., Platt, D., Salamov, A., Savidor, A., Sharma, R., Kingsmore, S. F. (2012). Genome Sequencing and Mapping Reveal Loss of Heterozygosity as a Mechanism for Rapid Adaptation in the Vegetable Pathogen Phytophthora capsici. Molecular Plant-Microbe Interactions, 25(10), 1350–1360. https://doi.org/10.1094/mpmi-02-12-0028-r

Lu, X. H., Hausbeck, M. K., Liu, X. L., & Hao, J. J. (2011). Wild Type Sensitivity and Mutation Analysis for Resistance Risk to Fluopicolide in Phytophthora capsici. Plant Disease, 95(12), 1535–1541. https://doi.org/10.1094/pdis-05-11-0372

Morris, G. M., & Lim-Wilby, M. (2008). Molecular docking. Methods in Molecular Biology, 443, 365–382. https://doi.org/10.1007/978-1-59745-177-2_19

Oh, J., Chun, S. C., & Chandrasekaran, M. (2019). Preparation and In Vitro Characterization of Chitosan Nanoparticles and Their Broad-Spectrum Antifungal Action Compared to Antibacterial Activities against Phytopathogens of Tomato. Agronomy, 9(1), 21. https://doi.org/10.3390/agronomy9010021

Patel, P. C., Hao, L., Au Yeung, W. S., & Mirkin, C. A. (2011). Duplex End Breathing Determines Serum Stability and Intracellular Potency of siRNA–Au NPs. Molecular Pharmaceutics, 8(4), 1285–1291. https://doi.org/10.1021/mp200084y

Paul, B. B., Mathew, D., Beena, S., & Shylaja. (2019). Comparative transcriptome analysis reveals the signal proteins and defence genes conferring foot rot (Phytophthora capsici sp. nov.) resistance in black pepper (Piper nigrum L.). Physiological and Molecular Plant Pathology, 108, 101436. https://doi.org/10.1016/j.pmpp.2019.101436

Poznanski, P., Hameed, A., & Orczyk, W. (2023). Chitosan and chitosan nanoparticles: Parameters enhancing antifungal activity. Molecules, 28(7), 2996. https://doi.org/10.3390/molecules28072996

Raja, M. A. G., Katas, H., & Wen, T. J. (2015). Stability, Intracellular Delivery, and Release of siRNA from Chitosan Nanoparticles Using Different Cross-Linkers. PLoS ONE, 10(6), e0128963. https://doi.org/10.1371/journal.pone.0128963

Saetrom, P. (2004). Predicting the efficacy of short oligonucleotides in antisense and RNAi experiments with boosted genetic programming. Bioinformatics, 20(17), 3055–3063. https://doi.org/10.1093/bioinformatics/bth364

Santos, M., Diánez, F., Sánchez-Montesinos, B., Huertas, V., Moreno-Gavira, A., García, B. E., Garrido-Cárdenas, J. A., & Gea, F. J. (2023b). Biocontrol of Diseases Caused by Phytophthora capsici and P. parasitica in Pepper Plants. Journal of Fungi, 9(3), 360. https://doi.org/10.3390/jof903036

Tamil Nadu Agricultural University. (2014, October). Pepper — Natural Farming. Horticulture: Spice Crops. https://agritech.tnau.ac.in/horticulture/horti_spice%20crops_pepper_naturalfarming.html

Tokatlian, T., & Segura, T. (2010). siRNA applications in nanomedicine. Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology, 2(3), 305–315. https://doi.org/10.1002/wnan.81

Ui-Tei, K., Naito, Y., Takahashi, F., Haraguchi, T., Ohki-Hamazaki, H., Juni, A., Ueda, R., & Saigo, K. (2004). Guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference. Nucleic Acids Research, 32(3), 936–948. https://doi.org/10.1093/nar/gkh247

Vijayakumar, S., Saraswathy, G. G., & Sakuntala, M. (2024). Transcriptomic analysis reveals pathogenicity mechanisms of Phytophthora capsici in black pepper. Frontiers in Microbiology, 15. https://doi.org/10.3389/fmicb.2024.1418816

Wang, Z., Langston, D. B., Csinos, A. S., Gitaitis, R. D., Walcott, R. R., & Ji, P. (2009). Development of an Improved Isolation Approach and Simple Sequence Repeat Markers to Characterise Phytophthora capsici Populations in Irrigation Ponds in Southern Georgia. Applied and Environmental Microbiology, 75(17), 5467–5473. https://doi.org/10.1128/aem.00620-09