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

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

Summary

About $9.1 billion dollars worth of crops are lost to disease each year in the US (Agrios, 2005). 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. Often diagnosis requires the sample to be shipped to a central laboratory, which is relatively slow and inefficient. Our goal is to apply DNA nanotechnology to develop an on-site multiplexed detection technology for crop viruses. This detection system will be inexpensive, easy to use, and compatible with on-site testing. To develop this system we propose these objectives:

(1) Demonstrate we can detect crop pathogens with high sensitivity using our DNA nanobarcode technology. We will carry out these initial tests in the lab under controlled conditions.
(2) Translate this technology to a field-ready detection platform. We will combine the above detection method with sample preparation and signal readout components into an integrated device.

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. 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 electrochemical read-out. Importantly, this detection method is general for any pathogen, so it can be applied to other agricultural-relevant fields such as detecting infectious diseases of animals and for food production.

Literature cited:
Agrios, George N. Plant Pathology, 5th Edition. Elsevier, 2005. Page 66

• Fig. 1: Schematic overview of detection method

Objectives/Performance Targets

For an outline summary of our research progress, see the attached table (Figure 2). As outlined in the project proposal, the first year of the project (Oct. 2011 – Sept. 2012) will focus on Objective 1: “Apply our DNA nanobarcode system to detect a panel of common plant pathogens with high sensitivity and specificity.” Specific tasks for this objective include:

-Design and validate probe sequences for recognition of specific pathogens
-Prepare DNA nanostructures (the “active ingredient” of our detection method) with the corresponding probe sequences
-Demonstrate detection of nucleic acid from our model viruses: cucumber mosaic virus (CMV) and tomato yellow leaf curl virus (TYLCV).
These tasks have been completed for our first candidate pathogen: cucumber mosaic virus (CMV). We have designed probes to be selective for pathogenic targets and to be compatible with our DNA nanostructures, and we have demonstrated that these DNA nanostructures form aggregates in the presence of target pathogen nucleic acids sequences. Probes for additional pathogens are currently being designed. One last remaining task in Objective 1 has yet to be completed:

-Using spiked samples, determine the accuracy of our assay in terms of sensitivity and specificity
This task is expected to be completed within the first few months of 2012. We do already have good results demonstrating our detection method for several non-plant pathogens (including HIV and Salmonella), and because our detection method is general, we expect these results will be readily repeatable for CMV and other relevant plant pathogens.

• Fig. 2: Research plan/Timeline

Accomplishments/Milestones

Our main goal was Objective 1: Apply our DNA nanobarcode system to detect a panel of common plant pathogens with high sensitivity and specificity (Oct. 2011 – Sept. 2012). As a first step toward this goal, we wanted to select a “prototypical” plant pathogen as a proof-of-concept target for developing our assay. For this first study, we selected the well-known pathogen Cucumber Mosaic Virus (CMV) (as described in our proposal, we will eventually test other representative pathogens, as well). CMV was selected due to its ubiquity: it infects more kinds of plants than any other virus. It affects bananas, beans, beets, celery, crucifers, melons, peppers, spinach, squash, tomatoes, and of course cucumbers.

For our assay to recognize and detect CMV, we need DNA sequences that are complementary to conserved regions of the CMV genome. For this purpose, we used capture probes that were designed and previously published by Prof. Keith Perry and have already been validated experimentally [Agindotan and Perry, Phytochemistry, 97 1 (2007)]. These probes are shown in Figure 3. Before implementing these probes into our assay, we first used an on-line software tool (http://www.idtdna.com/analyzer/Applications/OligoAnalyzer/) to verify that the probe sequences were compatible with the sequences used in our DNA nanostructures. We found the sequences were compatible, and so we proceeded to incorporate the probe sequences into our DNA nanostructures. We confirmed that this process was indeed successful using gel electrophoresis, as shown in Figure 4.

Once we had demonstrated the formation of DNA nanostructures, we used these structures as recognition elements for the detection of target nucleic acid from cucumber mosaic virus (CMV). As shown in Figure 5, we used gel electrophoresis to show that we obtain an aggregation response in the presence of this pathogen nucleic acid sequence. These aggregates are relatively large (hundreds of nanometers in diameter) and can be detected electrochemically.

As a next step, we will proceed to evaluate the accuracy of our assay in terms of sensitivity and specificity. As we continue to demonstrate our assay with CMV as a proof-of-concept, we will repeat this process in parallel with at least one other plant pathogen (we propose Tomato Yellow Leaf Curl Virus) to demonstrate the generality of our approach.

• Fig. 4: Formation of DNA nanostructures for detection of CMV
• Fig. 5: Aggregation occurs in the presence of target pathogen nucleic acid sequence
• Fig. 3: Probe sequences for cucumber mosaic virus (CMV)

Impacts and Contributions/Outcomes

The potential impact of this project is large, because the development of low complexity tests will enable 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.

Collaborators: