Future Directions

Steps toward a complete wet-lab workflow

Verification of cylindrical origami structure by AFM

The basic plane of DNA origami (DOPAM) has been visualized by the atomic force microscope (AFM) in our current study. Given the time constraints, we used this planar structure as a preliminary characterization to demonstrate the successful assembly of our DNA origami.

In our prospect, locking strands with disulfide bonds – designed to induce the rolling of DNA origami – will be incorporated to encapsulate the sgRNAL/Cas9 complex. Thus, to further characterize the structure of our fully assembled DNA origami, our future work will include the AFM imaging of the L-DOAPAMRCGH structure.

The open and release processes of L-DOAPAMRCGH

When L-DOAPAMRCGH enters the bacteria, it can be opened through GSH-mediated reduction and release the sgRNAL/Cas9 complex by RNase H cleavage. Given the tight budget, we were unable to complete the validation test of the open and release processes. Therefore, we plan to establish agarose gel electrophoresis analysis to monitor the opening and release of L-DOAPAMRCGH in future studies.

Verification of an enhanced protection of the Cas9 protein

As the rolled-up structure of DNA origami encapsulates the sgRNAL/Cas9 complex, an SDS-PAGE analysis of the loaded sgRNAL/Cas9 complex on DNA origami after incubation with proteinase K was planned to verify the enhanced protection of the Cas9 protein in rolled-up DNA origami. Due to the high price and limited concentration of our DNA origami, we were not capable of conducting the SDS-PAGE analysis in our current studies. Hence, the verification of the protection effect of rolled-up DNA origami is expected to be put into practice in the future.

Future Directions

During the course of our project, we successfully established a novel approach to combat antibiotic resistance by incorporating the CRISPR/Cas9 system into a DNA origami platform that targets bacteria with high affinity. While our DNA origami-CRISPR-Cas9 platform holds great potential in eliminating the horizontal transfer of antibiotic resistance genes among bacteria, further research is still needed to enhance its safety and specificity, thus making it a highly effective and widely applicable tool against antibiotic resistance. Herein, we propose three directions that may improve the therapeutic value of our platform.

Next Steps: Safety Assessment

Safety is the priority for our DNA origami-CRISPR-Cas9 platform to be used clinically. In vitro experiments can be conducted to evaluate the potential toxicity of the platform among different cell types. The platform can be co-cultured with various human cell lines, including the HepG2 cell line that retains characteristics of normal hepatocytes (1), the HK-2 cell line that resembles proximal tubular epithelial cells (2), and the THP-1 cell line that mimics primary monocytes and macrophages (3). Ideally, serial concentrations of the DNA origami carrying CRISPR/Cas9 can be used to determine its dose-dependent toxic effect on cells. Cells can be stained using viability dyes, such as trypan blue (4) or propidium iodide (5), and the number of viable cells can be measured using flow cytometry (Figure 1). The MTT assay, which involves the transformation of the water-soluble yellow dye to an insoluble purple formazan by the mitochondrial reductase (6), can be performed to study the impact of the origami platform on cellular metabolic profiles (Figure 1). The immunocompatibility of the platform can be evaluated by the potential pro-inflammatory responses manifested by immune cell lines when co-cultured with our platform.

Our platform delivers the CRISPR/Cas9 into bacterial cells via the membrane rupture effect of ROS. This exogenous source of ROS, however, may pose a threat to the survival and growth of normal cells. Therefore, to assess the therapeutic value of our platform, it is necessary to measure intracellular ROS levels following incubation with the DNA origami and the subsequent addition of hemin. Traditionally, intracellular ROS concentrations can be determined using dichlorodihydrofluorescein diacetate (DCFH-DA), which freely penetrates the cell membrane and can be oxidized by ROS to generate the fluorescent 2′,7′-dichlorofluorescein (DCF) (7) (Figure 1). Nevertheless, more fluorescent signals will be produced if samples are exposed to light irradiation during measurement (8), thereby leading to unreliable results, especially for samples with a small amount of ROS. A novel approach based on DCFH-DA has been developed, which amplifies the initial fluorescence signal via a self-amplification process of DCF. This strategy has been proven to be more stable and sensitive than conventional methods, while also minimizing the impact of light irradiation on the measurement process (9). Future study could focus on measuring intracellular ROS levels after the addition of hemin using the novel ROS detection method. The density of G4 arrays can be adjusted and optimized if excessive ROS is observed inside cells.

Safety tests schematic

Figure 1. Schematic illustration of safety tests that can be undertaken to evaluate the toxicity of our platform if used in vivo. ROS: reactive oxygen species. MTT: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide. DCFH-DA: dichlorodihydrofluorescein diacetate. DCF: 2′,7′-dichlorofluorescein.

Beyond: Specificity Upgrade

Although CRISPR/Cas9 has been widely accepted as a highly specific genome editing tool (10), certain Cas9 variants can be tested to mitigate off-target effects and fulfill the full therapeutic potential of our platform. Paired Cas9 nickases (Cas9n), a mutated version of Cas9 where the HNH or RuvC domains are inactivated by introducing an H840A or D10A mutation, are guided by two sgRNAs to generate the indel mutation, resulting in fewer off-target effects (11). xCas9 is an engineered version of Streptococcus pyogenes Cas9 (SpCas9), which recognizes a wider range of PAM and possesses higher specificity. For example, at the EMX1 target site in HEK293T cells, SpCas9 showed 5,649 on-target reads and 1,132 off-target reads, whereas xCas9 showed 6,874 on-target reads but no off-target reads (12). Developing screening platforms that select the optimal combination of nickase variants and sgRNA for specific bacterial types may enhance the genome editing process, ensuring that the platform can accurately target the intended sites.

Creating efficient aptamer screening platforms opens a promising avenue to increase the specificity of our DNA origami to particular bacterial structures. Systematic evolution of ligands by exponential enrichment (SELEX) is a widely used process for aptamer screening, which involves a series of selection and amplification steps. To integrate SELEX into our project, the surface molecule exclusive to the target bacterial strain needs to be identified and should be easily obtained or synthesized. Alternatively, whole cells or spores can be used as the target, where prior knowledge or purification of a particular surface epitope is not required. However, cell-SELEX might be difficult to perform, as the negatively charged bacterial surface repulses DNA from the cell surface (13). Furthermore, the surface markers that the selected nucleic acid binds to remain unknown, which makes safety assessment hard to perform and limits its potential therapeutic usage. As such, screening aptamers that target one or several known surface targets may serve as a better approach. Conventional SELEX requires a large pool of nucleic acid molecules flanked by two constant sequences. Aptamer candidates are then allowed to bind to the desired target molecules under specific conditions. The molecules that successfully bind to the target are isolated using several rounds of washing and amplified to generate an enriched population. This cycle is repeated iteratively to narrow down the massive nucleic acid pool to a small population of molecules that exhibit optimal specificity to the target (14) (Figure 2). Generating a considerable amount of nucleic acids for screening is critical for the successful identification of high-affinity aptamers. Screening such a large number of aptamers, however, can be both time- and money-consuming. Therefore, using modified SELEX versions that can rapidly isolate bound molecules may significantly improve the screening efficiency. Capillary electrophoresis-SELEX (CE-SELEX), for instance, separates an aptamer-target complex from unbound nucleic acids based on their electrophoretic mobility. Free oligonucleotides have higher mobility and will pass through a capillary into the waste, while the less mobile aptamer-target complex will remain in the capillary and can be obtained by applying pressure (15). This method reduces the required screening rounds from 20 in conventional SELEX to 4 while retaining the high affinity of the selected aptamer (15). Magnetic bead-based SELEX serves as another efficacious way to screen aptamers. In this method, the target molecule, usually a protein, is fixed on magnetic beads. Aptamers bound to the target can then be isolated using a magnetic separator and amplified for sequencing (16).

SELEX schematic

Figure 2. Schematic illustration of basic concepts of SELEX. An initial aptamer library is selected by target binding and subsequent washing. Bound aptamers are retained and eluted for amplification. Aptamers with high affinity are obtained after multiple rounds of screening.

The development of next-generation sequencing and computational docking techniques paves the way for computational screening of aptamer libraries. In the last few decades, highly efficient in silico approaches have been developed to predict the interaction between the target structure and aptamer candidates. Software tools such as Autodock or HADDOCK facilitate the investigation of structural patterns responsible for aptamer-target interactions based on predicted affinity and Gibbs free energy (17,18). These in silico methods have successfully identified several aptamers with high affinity for certain bacterial surface proteins, such as a conserved pilus backbone protein in Streptococcus agalactiae or the protein A of Staphylococcus aureus (19–21). The aptamers selected by SELEX can undergo further maturation, where their sequences are screened by a genetic algorithm and mutated in silico. The mutated aptamers can then be synthesized and enter another screen cycle, giving rise to aptamers with higher specificity (Figure 3). For example, aptamers generated after multiple rounds of crossover and shuffling exhibit 16-fold specificity against Streptococcus mutans to aptamers selected by cell-SELEX only (22).

In silico SELEX techniques

Figure 3. The use of in silico techniques in SELEX (adapted from Darmostuk et al). Prior selected aptamers are paired, mutated via certain genetic algorithms and sequenced to generate evolved sequences, which are further verified and screened in vitro. Aptamers with improved affinity are obtained after multiple rounds of screening.

Bigger Picture: In Vivo Trials in Animal Models

After being proven to be safe and highly specific, in vivo trials can be undertaken to further verify the efficacy of our origami-CRISPR-Cas9 platform. Wound infections have become a serious issue in recent years. Gram-positive bacteria such as Staphylococcus aureus and Enterococcus spp., and Gram-negative organisms such as Pseudomonas aeruginosa and Acinetobacter spp. are common pathogens responsible for acute wound infections (23). Rapidly increasing antibiotic resistance may complicate wound conditions and result in delays in healing. As our platform demonstrates decent specificity against antibiotic-resistant bacteria, the effectiveness of the platform in targeting the resistant bacteria and facilitating wound healing can be evaluated by using murine wound infection models. Numerous mouse wound models have been established (24–28). Here, we adapted a standardized mouse model previously used for investigating wound infection with Pseudomonas aeruginosa (29) to test the efficacy of our platform in vivo. Kunming mice, with an 8 mm wound created on their backs using sterile scissors, are used as experimental subjects. To test the efficacy of our platform, acclimated mice are randomly assigned to one of three groups: control group, infected group injected with origami-hemin but without CRISPR/Cas9, and infected group injected with origami-CRISPR-Cas9-hemin. As a critical indicator of mouse health, the body weight of the mouse in each group should be measured every 2 days. After injection of the origami mix, 0.5 g of wound tissue will be randomly collected from three mice in each group every 2 days and mixed with 4.5 mL of sterile saline. The mixture will be homogenized using an electric grinder for 2 minutes to generate a 1:9 tissue slurry, which will be diluted to appropriate concentrations and plated onto CFC agar plates for colony counting (29). The wound tissue collected can also be subjected to antigen retrieval and subsequent immunoassays for measuring cytokine levels, such as IL-1β, TNF-α and TGF-β (29). Hematoxylin–Eosin (HE) staining can be used for histological analysis of the wound tissue. The thickness of the granulation tissue can be observed and measured under a light microscope (29). A general pipeline of in vivo murine wound infection trials is summarized in Figure 4. Fewer colonies on the agar plate, less cytokine secretion, and thicker granulation tissue in the group injected with origami-CRISPR-Cas9-hemin than in the group injected with origami-hemin can indicate that our platform is effective against antibiotic-resistant bacteria responsible for wound infections.

In vivo murine wound infection model pipeline

Figure 4. General pipeline for in vivo murine wound infection model trials of the origami-CRISPR-Cas9 platform (adapted from Hou et al (29)). Briefly, acclimated mice with wounds are infected by antibiotic-resistant bacteria, and treated with control, origami-CRISPR-Cas9-hemin, and origami-hemin. Parameters, including body weight, wound colony count, and assays such as ELISA and histopathology, are measured and performed periodically.

In conclusion, the overall goal is to ensure that our origami-CRISPR-Cas9 platform is safe, specific, and effective against antibiotic-resistant strains. Following the aforementioned directions may facilitate successful in vivo trials and potential clinical applications of the platform.

References

  1. Arzumanian VA, Kiseleva OI, Poverennaya EV. The Curious Case of the HepG2 Cell Line: 40 Years of Expertise. Int J Mol Sci. 2021 Dec 4;22(23).
  2. Ryan MJ, Johnson G, Kirk J, Fuerstenberg SM, Zager RA, Torok-Storb B. HK-2: an immortalized proximal tubule epithelial cell line from normal adult human kidney. Kidney Int. 1994;45(1):48–57.
  3. Chanput W, Mes JJ, Wichers HJ. THP-1 cell line: an in vitro cell model for immune modulation approach. Int Immunopharmacol. 2014;23(1):37–45.
  4. Strober W. Trypan blue exclusion test of cell viability. Curr Protoc Immunol. 1997;21(1):A-3B.
  5. Riccardi C, Nicoletti I. Analysis of apoptosis by propidium iodide staining and flow cytometry. Nat Protoc. 2006;1(3):1458–61.
  6. Kumar P, Nagarajan A, Uchil PD. Analysis of cell viability by the MTT assay. Cold Spring Harb Protoc. 2018;2018(6):pdb-prot095505.
  7. Rosenkranz AR, Schmaldienst S, Stuhlmeier KM, Chen W, Knapp W, Zlabinger GJ. A microplate assay for the detection of oxidative products using 2′, 7′-dichlorofluorescin-diacetate. J Immunol Methods. 1992;156(1):39–45.
  8. Marchesi E, Rota C, Fann YC, Chignell CF, Mason RP. Photoreduction of the fluorescent dye 2′-7′-dichlorofluorescein: a spin trapping and direct electron spin resonance study with implications for oxidative stress measurements. Free Radic Biol Med. 1999;26(1–2):148–61.
  9. Yu D, Zha Y, Zhong Z, Ruan Y, Li Z, Sun L, et al. Improved detection of reactive oxygen species by DCFH-DA: New insight into self-amplification of fluorescence signal by light irradiation. Sens Actuators B Chem. 2021;339:129878.
  10. Jiang F, Doudna JA. CRISPR–Cas9 structures and mechanisms. Annu Rev Biophys. 2017;46:505–29.
  11. Mali P, Aach J, Stranges PB, Esvelt KM, Moosburner M, Kosuri S, et al. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat Biotechnol. 2013 Sept;31(9):833–8.
  12. Hu JH, Miller SM, Geurts MH, Tang W, Chen L, Sun N, et al. Evolved Cas9 variants with broad PAM compatibility and high DNA specificity. Nature. 2018 Apr 5;556(7699):57–63.
  13. Asif A, Mohsin H, Tanvir R, Rehman Y. Revisiting the Mechanisms Involved in Calcium Chloride Induced Bacterial Transformation. Front Microbiol. 2017;8:2169.
  14. Sampson T. Aptamers and SELEX: the technology. World Pat Inf. 2003;25(2):123–9.
  15. Mendonsa SD, Bowser MT. In vitro evolution of functional DNA using capillary electrophoresis. J Am Chem Soc. 2004;126(1):20–1.
  16. Bruno JG. In vitroselection of DNA to chloroaromatics using magnetic microbead-based affinity separation and fluorescence detection. Biochem Biophys Res Commun. 1997;234(1):117–20.
  17. Morris GM, Huey R, Olson AJ. Using autodock for ligand‐receptor docking. Curr Protoc Bioinforma. 2008;24(1):8–14.
  18. Dominguez C, Boelens R, Bonvin AM. HADDOCK: a protein− protein docking approach based on biochemical or biophysical information. J Am Chem Soc. 2003;125(7):1731–7.
  19. Moradi M, Mohabatkar H, Behbahani M, Dini G. Application of G-quadruplex aptamer conjugated MSNs to deliver ampicillin for suppressing S. aureus biofilm on mice bone. Arab J Chem. 2022;15(11):104274.
  20. Escamilla-Gutiérrez A, Córdova-Espinoza MG, Sánchez-Monciváis A, Tecuatzi-Cadena B, Regalado-García AG, Medina-Quero K. In silico selection of aptamers for bacterial toxins detection. J Biomol Struct Dyn. 2023;41(20):10909–18.
  21. Soon S, Nordin NA. In silico predictions and optimization of aptamers against Streptococcus agalactiae surface protein using computational docking. Mater Today Proc. 2019;16:2096–100.
  22. Savory N, Takahashi Y, Tsukakoshi K, Hasegawa H, Takase M, Abe K, et al. Simultaneous improvement of specificity and affinity of aptamers against Streptococcus mutans by in silico maturation for biosensor development. Biotechnol Bioeng. 2014;111(3):454–61.
  23. Williams M. Wound infections: an overview. Br J Community Nurs. 2021 June 1;26(Sup6):S22–5.
  24. Wong VW, Sorkin M, Glotzbach JP, Longaker MT, Gurtner GC. Surgical approaches to create murine models of human wound healing. BioMed Res Int. 2011;2011(1):969618.
  25. Clark LD, Clark RK, Heber-Katz E. A new murine model for mammalian wound repair and regeneration. Clin Immunol Immunopathol. 1998;88(1):35–45.
  26. Murine model of wound healing. United States; 2013.
  27. Wu J, Landén NX. Investigation of Skin Wound Healing Using a Mouse Model. Methods Mol Biol Clifton NJ. 2020;2154:239–47.
  28. Tipton CD, Sanford NE, Everett JA, Gabrilska RA, Wolcott RD, Rumbaugh KP, et al. Chronic wound microbiome colonization on mouse model following cryogenic preservation. PloS One. 2019;14(8):e0221565.
  29. Hou J, Wu Q, Xiong R, Malakar PK, Zhu Y, Zhao Y, et al. A Standardized Mouse Model for Wound Infection with Pseudomonas aeruginosa. Int J Mol Sci. 2024 Nov 1;25(21).
  30. Darmostuk M, Rimpelova S, Gbelcova H, Ruml T. Current approaches in SELEX: An update to aptamer selection technology. Biotechnol Adv. 2015 Nov 1;33(6 Pt 2):1141–61.
Back to top