On-site detection for agriculture and food systems using DNA nanotechnology

2012 Annual Report for GNE11-019

Project Type: Graduate Student
Funds awarded in 2011: $12,705.00
Projected End Date: 12/31/2012
Grant Recipient: Cornell University
Region: Northeast
State: New York
Graduate Student:
Faculty Advisor:
Dr. Dan Luo
Cornell University
Faculty Advisor:
Dr. Keith Perry
Cornell University

On-site detection for agriculture and food systems using DNA nanotechnology

Summary

Crops must be monitored for infection, but current methods for pathogen detection often require special training and expensive equipment, and are impractical for on-site use. Our goal is to apply DNA nanotechnology to develop an on-site multiplexed detection technology for crop viruses. An overview of our detection method is portrayed in Figure 1. Briefly, we prepare DNA nanostructures with recognition probes that can bind to target pathogen nucleic acid. This detection strategy is based on the crosslinking ability of branched DNA as described in related publications from our lab.[1,2] These DNA nanostructures can be linked together to form large aggregates only in the presence of a specific nucleic acid target sequence. The resulting aggregates can then be identified via fluorescence read-out. Importantly, this detection method is general for any pathogen, so it can be applied to other agriculturally-relevant fields such as detecting infectious diseases of animals and for food production.

We have initially obtained successful results using micromolar concentrations of synthetic 100mer DNA targets, as shown in Figure 4. Since last year’s report, we have moved beyond synthetic samples to demonstrate detection of nucleic acid derived from real virus samples with lengths up to 500mer at micromolar concentrations, as shown in Figure 9. To further improve the sensitivity and feasibility of our assay, we have also implemented an enzymatic amplification component into our process, and using this technique we have demonstrated nanomolar sensitivity of short RNA targets, as shown in Figures 10 and 11.

References:
1. Lee, J.B. et al. “Multifunctional nanoarchitectures from DNA-based ABC monomers.” Nature Nanotechnology, 4, 430-436 (2009).
2. Li, Y., Cu, Y.T.H. & Luo, D. “Multiplexed detection of pathogen DNA with DNA-based fluorescence nanobarcodes.” Nature Biotechnology, 23, 885-889 (2005).

Objectives/Performance Targets

The final goal of this project is to develop detection method for diagnosis of infectious plant diseases. For an outline summary of our research progress, see the attached table (Figure 2). As outlined in the table, the plan for 2012 was divided between two objectives: (1) Apply our DNA nanobarcode system to detect a panel of common plant pathogens with high sensitivity and specificity; (2) Integrate the sample preparation and signal readout modules into the platform and evaluate the robustness of our technology by testing with real plant tissue samples.

Initial experiments with full length pathogen RNA (CMV RNA-3) at micromolar concentrations showed no aggregation (Figure 5). To troubleshoot this problem, our original plan of work was modified to prioritize work with CMV samples from our collaborator, Prof. Keith Perry. We continued to work with micromolar concentrations of target, and optimized procedures in several ways to make detection possible. Using fluorescence imaging as the read-out method for our assay, we have successfully demonstrated detection of DNA derived from real CMV samples at micromolar concentrations (Figure 9) and RNA at nanomolar concentrations (Figure 11). We are currently optimizing our strategy for sensitivity with lower concentrations, before shifting to specificity testing with spiked samples. We have updated our timeline to reflect these changes, as shown in Figure 2. We remain on track to complete Objective 2 by September 2013.

Accomplishments/Milestones

To accomplish our goals, we have worked closely with our collaborator from the Department of Plant Pathology at Cornell University, Prof. Keith Perry. His laboratory has extensive experiences with plant disease, including cucumber mosaic virus which we have chosen as a model.[1,2] His experience and assistance has been extremely valuable in providing samples derived from CMV as well as advice.
As outlined in Figure 2, our main goal was to determine the sensitivity and specificity of our branched DNA detection approach using progressively more realistic mock plant pathogen samples, starting with relatively short synthetic DNA sequences from pathogen DNA, with the final goal of testing our approach with real diseased plant specimens.

For initial testing, we selected a 100 base region of the cucumber mosaic virus (CMV) to act as a mock pathogen sample. We designed corresponding probes to form aggregates specifically in the presence of the DNA sequence. In these initial tests with short synthetic DNA sequences, we found that our assay was effective in binding most of the branched YDNA probe present in the solution (Figure 4). As a next step, we tested our assay with a 2,000 base RNA representing a realistic sample type. This sequence was RNA-3 from the CMV genome (GenBank accession number NC_001440.1) and was provided by our collaborator Prof. Keith Perry. Working with these samples we obtained a negative result in which aggregation was not observed even when target was present (Figure 5). This suggests that the YDNA probes did not bind successfully to the long RNA-3 target. To resolve this problem, we attempted to increase the favorability of the binding process by adjusting the protocol of our detection approach. We systematically varied several key parameters of our assay, including the molar ratio between target and probe (Figure 6), and the amount of magnesium (Figure 7). These parameters did not result in increased aggregation. We also tested a comparison between target RNA and DNA, and observed aggregation was much more successful using DNA compared to RNA (Figure 8). This suggests that our approach is most effective only for DNA targets, with diminishing effectiveness for RNA targets as target length increases. To address this limitation, we considered modifying our process to include additional sample processing steps to break target nucleic acid into smaller pieces, but ultimately decided against this approach, choosing instead to introduce an enzymatic amplification step in which only a part of the pathogen nucleic acid is amplified. We selected enzymatic amplification because this would both resolve the limitation of our assay and increase our sensitivity.
We implemented enzymatic amplification into our assay inspired by recent publications, including one publication from our laboratory, which use isothermal rolling chain amplification (RCA) for dramatic increase in assay sensitivity.[3-5] We designed a template sequence composed of single-stranded DNA which enabled amplification only in the presence of target. We found that, with this new approach, we could detect very small concentrations (so far 5 nanomolar) of short synthetic RNA. Based on the performance of similar strategies, we anticipate our assay can achieve femtomolar level sensitivity.[4] In addition to pathogen sensing potential, this approach will be useful for sensitive detection of microRNA, which has gained significant attention recently for being an excellent indicator of disease states.[3]

The addition of an enzymatic amplification step to our assay represents a change to our original plan, but one that can be readily integrated into our existing protocols. The amplification of target nucleic acid allows us to more easily sense the presence of pathogenic nucleic acid, and overcomes the original limitation of our assay based on target length. We continue to focus on the use of branched DNA as a novel detection strategy, and to focus on plant disease CMV as a test pathogen. The addition of an enzymatic amplification step makes our strategy more feasible for real-world implementation.

References:

1. Agindotan, B. & Perry, K.L. Macroarray detection of eleven potato-infecting viruses and Potato spindle tuber viroid. Plant Disease 92, 730-740 (2008).
2. Agindotan, B. & Perry, K.L. Macroarray detection of plant RNA viruses using randomly primed and amplified complementary DNAs from infected plants. Phytopathology 97, 119-127 (2007).
3. Neubacher and Arenz. “Rolling-Circle Amplification: Unshared Advantages in miRNA Detection.” ChemBioChem, 10, 1289 – 1291 (2009).
4. Cheng, et al. “Highly Sensitive Determination of microRNA Using Target-Primed and Branched Rolling-Circle Amplification.” Angew. Chem. Int. Ed., 48, 3268 – 3272 (2009).
5. Lee, et al. “A Mechanical Metamaterial Made From a DNA Hydrogel.” Nature Nanotechnology, 7, 816 – 820 (2012).

Impacts and Contributions/Outcomes

About $9.1 billion dollars worth of crops are lost to disease each year in the US.[1] Crops must be monitored for infection, but most current methods for pathogen detection require special training and expensive equipment, and are impractical for on-site use. This project has widespread potential impact, because the development of low complexity diagnostic tests enables more routine testing, allowing for a faster response. In some cases, low complexity diagnostic tests enable early detection by putting the tools for diagnosis into the hands of the farmer or other grower. Early detection allows appropriate control measures to be taken (including systems of quarantine, inspection and certification, preventive spraying for pest vectors, or potentially inoculation of at-risk plants). In addition, molecular diagnostic techniques such as ours are especially valuable for bacterial and viral diseases that can be difficult or impossible to diagnose by other means. Bacteria and viruses account for a considerable portion of losses suffered annually from diseases of the various crops.

The new approach developed in 2012 enables detection of pathogen miRNA, which has gained significant attention recently for being an excellent indicator of disease states. This method is inspired by a recent Luo labs publication.[2] A related project brings PCR amplification and branched-DNA pathogen detection into a single step, and will be submitted for publication in early 2013.[3]

References:
1. Agrios, George N. Plant Pathology, 5th Edition. Elsevier, 2005. Page 66.
2. Lee, et al. “A Mechanical Metamaterial Made From a DNA Hydrogel.” Nature Nanotechnology, 2012, 7, 816 – 820.
3. Hartman, et al. “Branched PCR with Thermostable DNA Nanostructures.” (Paper in preparation.)

Combined Figures

 

Collaborators:

Dr. Dan Luo

dl79@cornell.edu
Professor
226 Riley Robb Hall, Cornell University
Ithaca, NY 14853
Office Phone: 6072558193
Dr. Keith Perry

klp3@cornell.edu
Professor
Department of Plant Pathology, Cornell University
Ithaca, NY 14853
Office Phone: 6072548243