After building the NPK sensors and talking with farmers about their sensor needs and feelings toward biosensors, we brainstormed creative applications for our system of genetic circuits.

At its inception, the goal of this project was to design a method of determining macronutrient concentrations that was cheap, simple, and easy to use for farmers around the world. However, when we did research on what products were currently available to sense soil macronutrient concentrations, we concluded that many satisfactory low-cost chemical assays have already been developed.

We decided to explore where the current NPK tests could be improved, so we established the most important criteria for a sensor design. A good sensor for this application is accurate, easy to use, low cost, gives a quick readout of the results, and is composed of relatively stable components. We then identified two common chemical assays, a colorimetric at-home-kit and laboratory tests, and compared them in each of our design criteria categories in a simple Pugh Matrix (Table 1).

insert pugh matrix

Our analysis showed that, while many of these assays provide cheap and rapid measurement of NPK levels, they do so at the cost of accuracy. We designed the biosensors to be useful parts for many future applications and did not design them to specifically improve accuracy. However, we would still like to test if the biological rather than purely chemical basis of our circuits enables them to get a more accurate reading of what nutrients are readily available from the perspective of a growing plant (hopefully a source).

Considering the accessibility of chemical NPK assays and public opinion toward biosensors, we have begun developing two separate applications of the NPK sensors: a paper-based lysate and a controlled biofertilizer system.

PUGH MATRIX goes here

Paper-based Lysate

We want to deploy our sensors in a way that would alleviate biosafety concerns, continue to be quick and low-cost so that it continues to be competitive with current products, but also includes the accuracy that comes with being a biological circuit (source hopefully). With these criteria in mind, we decided to make a paper-based testing assay.


Motivated by a paper-based lysate

Controlled Biofertilizer System

Looking toward, we envisioned an application that would completely remove the need for farmers to constantly test their soil and use fertilizers. Our second application is a system in which a modified soil-bacterium can sense the concentration of a macronutrient in its environment, and then make a decision to add or remove that nutrient from the soil as needed.

Biofertilizers has been defined as the use of microorganisms to increase the availability and uptake of mineral nutrients for plants (Vessey). Depending on the crop, native soil species of nitrogen-fixing, denitrifying, phosphate-solubilizing, and potassium-solubilizing bacteria have been identified (sources). By hooking up our individual nutrient sensors to the nitrate producing machinery of each of these bacterial species, you could theoretically control the increase or decrease of that nutrient’s concentration and availability in the soil, depending on the output of the sensor (schematic).

We quickly realized that in order to deploy our NPK sensors across multiple strains of soil bacteria, we would need to build the genetic circuitry on broad-host range plasmids. Before putting our sensors into soil bacteria, we decided to show proof-of-concept by using a conjugation plasmid with an RP4 transfer system, methyl halide transferase (MHT), green fluorescent protein (GFP), and a chloramphenicol selectable marker. The MHT and GFP serve as gas and visual outputs that make the system versatile for different environments. We were cognizant of the fact that most soil is darkly colored, and therefore, GFP would not be easily seen. Consequently, we hypothesize that a gas marker might be more applicable in future use.

*0040 = BBa_E0040 GFP

We then began doing proof-of-concept experiments to transform our broad-host range plasmid containing GFP into two strains of gram-negative soil bacteria: Rhizobia, a nitrogen-fixing microbe, was conjugated to E. coli S17, which along with the conjugation plasmid, provided all the genes necessary to transfer the GFP containing plasmid into the soil bacteria. Additionally, Azotobacter vinelandii, another nitrogen-fixing bacteria, was transformed by electroporation using the conjugation plasmid. Currently, we see that the conjugation of Rhizobia with the E. coli worked since colonies grew on the agarose plates with streptomycin and chloramphenicol antibiotics. The streptomycin ensured that only the Rhizobia grew on the plates since the E. coli were not resistant to streptomycin, and that only Rhizobia with the plasmids grew. We hope to confirm our findings further by amplifying the nitrogenase gene, only present in Rhizobia. Alternative studies utilizing the plate reader will analyze the fluorescence of the GFP.

While this application of our NPK sensors is still very much in the initial stages of development, we are very excited by the idea of nutrient-controlled biofertilizer bacteria. This project fully utilizes the unique biocomputing power built into bacteria and we hope to continue developing it future years. We envision a day when we resolve biosafety issues and farmers will no longer have to test their soil, determine nutrient deficiencies, and correct them with fertilizers. Instead, our genetically modified soil-bacteria living with the crops will continuously test and replenish or destroy nitrogen, phosphate, and potassium, depending on the specific requirements of the crop. This system would not only make farming easier, by eliminating the need to add fertilizer, it would prevent runoff and have a major positive environmental impact.

References

Vessey: http://link.springer.com/article/10.1023%2FA%3A1026037216893#page-1

Potassium: http://article.sciencepublishinggroup.com/pdf/10.11648.j.ajls.20130103.12.pdf

Collins paper: https://owlspace-ccm.rice.edu/access/content/group/8f11257d-cfeb-4071-9a1a-7aeb99995e5a/Background%20Papers/Paper-based%20synthetic%20gene%20networks.pdf