Personalized Medicine for Crops? Opportunities for the Application of

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Personalized medicine for crops? Opportunities for the application of molecular recognition in agriculture. Emily Mastronardi, Carlos Monreal, and Maria C. DeRosa J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b03295 • Publication Date (Web): 06 Oct 2017 Downloaded from http://pubs.acs.org on October 8, 2017

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Personalized medicine for crops? Opportunities for the application of molecular recognition in

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agriculture.

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Emily Mastronardi1, Carlos Monreal2, Maria C. DeRosa1*

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Carleton University, Department of Chemistry, 1125 Colonel By Drive, Ottawa, ON Canada, K1S5B6

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Agriculture and Agrifood Canada, 960 Carling Ave, Neatby Building, Ottawa, ON Canada, K1Y4X2

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*to whom correspondence should be addressed: maria.derosa@carleton.ca

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Keywords: Aptamers, Molecularly Imprinted Polymers, Antibodies, Rhizosphere, Root Exudates

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Abstract: This perspective examines the detection of rhizosphere biomarkers, namely root

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exudates and microbial metabolites, using molecular recognition elements such as molecularly

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imprinted polymers, antibodies, and aptamers. Tracking these compounds in the rhizosphere could

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provide valuable insight into the status of the crop and soil in a highly localized way. The outlook and

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potential impact of the combination of molecular recognition and other innovations such as

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nanotechnology and precision agriculture and the comparison to advances in personalized medicine are

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considered.

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Introduction: The prospect of personalized medicine and the rise of point-of-care diagnostics

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are two emerging themes in the field of medicine that promise to revolutionize human health.

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Personalized or precision medicine refers to the patient-centred tailoring of treatment. The European

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Union defines personalized medicine as: ‘Providing the right treatment to the right patient, at the right

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dose at the right time.1 An enabler of this revolution has been the rapid growth of diagnostic and

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“omics” technology that can provide a molecular level understanding of disease and each patient’s

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unique clinical, genetic, and environmental information to allow for individual tailoring of response. The

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accurate and low cost detection of biomarkers, measurable indicators of a biological state or condition

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(e.g. genes, proteins, and metabolites), are essential tools for accurate prognosis, dose selection,

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tracking of therapeutic response, and detection of adverse outcomes. In particular, point-of-care (POC)

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biomarker testing can provide close to immediate information about on an individual’s condition, can

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provide more widespread access to diagnosis, and can facilitate real-time treatment decisions, all at

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modest cost and in a non-invasive or minimally invasive fashion.2

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In many ways, agriculture parallels health as an area of study with similar challenges,

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complexities, and questions. For example, the challenge of efficient delivery of payloads such as

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fertilizers, pesticides, and herbicides mirrors that seen in drug delivery, e.g. the complex environment,

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the danger of off-target effects and thus the need for efficient targeting, etc. It is not surprising then

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that technologies and other innovations that first see an incipience in medical sciences are eventually

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applied to analogous problems in agriculture.

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innovation that was first applied to questions and challenges in medicine before applications in

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agriculture were examined.3 There are, of course, striking differences between the fields of medicine

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and agriculture, including the type of regulatory oversight and the level of cost and/or risk that is

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tolerated by stakeholders. These parallels and disparities will shape to what degree advances from one

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field can impact the other.

Nanotechnology is one example of an enabling

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Based on the congruence between medicine and agriculture, could there be an agricultural

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equivalent to personalized medicine? Could point-of-care-type technologies be used to better manage

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variable field and crop conditions and to respond to needs in real-time? Indeed, precision farming has

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many critical features that mirror those in personalized medicine. Precision farming is an approach to

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agriculture where crop management decisions are informed by data from global positioning systems,

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remote sensing, computer modelling of biotic and abiotic conditions, and soil properties to provide

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highly localized information and precisely identify the nature and location of problems.4,5

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measurement of and response to inter and intra-field variation in soils and crops allows the farmer to

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make decisions that support the success of the whole farm that in many ways parallels the guiding

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principles of personalized medicine. In this case, the goal is to ensure that crops are growing at

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maximum efficiency and yield while increasing the use efficiency of inputs such as fertilizers, pesticides,

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and herbicides. Yet, to date, the majority of these data acquired relate to macro-scale factors such as

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land surface temperature, soil moisture, drainage, topography, etc. rather than reporters at the

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molecular level.

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Furthermore, the “omics” revolution has also had a demonstrable effect on agriculture.6 The

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importance of biomarkers is being realized, for example gene expression biomarkers as indicators of

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nitrogen status7 and water status8 are being studied. Similarly, a number of protein biomarkers for

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abiotic stress have been identified.9 In fact, “field-omics” is seeking to integrate genomic, transcriptomic,

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proteomic, and metabolomics data with crop science for informing crop systems biology and crop

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management strategies. 10 Nevertheless, at present, the analyses for these biomarkers are still relatively

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costly and laborious, and the extraction of samples is invasive, e.g. collection of tissue from roots or

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shoots for analysis. Interest in non-invasive testing for phenomics is on the rise11, but an alternative

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approach would be to look outside the plant itself for biomarkers. In field detection of these biomarkers

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could serve as a “point-of-care” equivalent that could use a molecular-level understanding of crop and

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field conditions to inform farm management decisions.

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Biomarkers in rhizosphere? The rhizosphere, the millimetres thick region of soil in the direct vicinity of

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plant roots, is a complex and chemical-rich environment laden with potential information about the

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interplay between the plant, soil, and microbial community. Root exudates, chemical compounds

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secreted into the rhizosphere by root cells, in addition to the metabolites excreted by the microbial

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communities present in the soil environment, could contain valuable biomarkers for assessing the state

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of the crop and soil in a very localized way. 12, 13 These compounds are involved in the chemical signalling

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that regulates many processes including microbial and fungal colonization, deterring herbivory, and

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inhibiting the growth of encroaching plant species.14 For example, amino acids have been found to

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suppress the growth of nematodes and competing plant species, while the flavonoid quercetin has been

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implicated in resistance to aluminum toxicity in maize.15, 16 It has been estimated that plants release

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between 5 and 25% of net fixed carbon into the rhizosphere in the form of exudates, ranging in

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complexity from organic anions to polymers.17 Notably, up to 70% of the photosynthesized 13CO2 was

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found to be exuded by wheat roots in recent work.18 The identification, quantification and the functional

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understanding of these complex solutions could underlie crop yield and farm management.

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Current data suggest that low molecular weight compounds are the most diverse group of soil

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solution components, including sugars, amino acids, organic acids and phenolics, while higher molecular

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weight compounds such as polysaccharides and proteins make up a larger proportion by mass.

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soil, plant species, and nutrient availability all seem to have an impact on the quantity and type of

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compounds present, suggesting that these compounds could serve as indicators that could be examined

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as surrogates for crop status.

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solutions in wheat rhizospheres over the growing season were able to identify hundreds of chemical

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compounds distributed in 11 chemical classes.13 Though the specific function of many of these

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compounds is unknown, several have been implicated in mediating the positive and negative

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interactions affecting plant and microbe growth.

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rhizosphere could provide useful information on crop health and could be combined with the platform

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of precision agriculture to allow farmers to better monitor and respond to existing field conditions.

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Affinity ligands and biosensors for rhizophere biomarkers

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The

For example, recent work on chemical composition analysis of soil

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Thus, the presence of key biomarkers in the

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The diversity, low concentrations, and localized presence of rhizosphere biomarkers has made

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their identification a challenge. With the development of sensitive mass spectrometry techniques,

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isotope labelling strategies, and high throughput metabolomics approaches, the characterization of

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these complex solutions has become easier.21, 22 Yet, the cost and complexity of these approaches would

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make them prohibitive in terms of their use in real-time precision agriculture.

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greater attention should be paid to the development of simpler and lower cost alternatives in the form

For these reasons,

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of biosensors and bioassays.

Biosensors take the information from the biochemical interaction of a

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target molecule with a recognition or affinity element and translates it into a measurable output with a

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defined sensitivity; two classic examples are the electrochemical glucose meter and the lateral flow

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pregnancy test.23

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In order to develop new biosensor platforms for rhizosphere biomarkers, nanoscale molecular

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recognition agents or affinity ligands are needed that are capable of binding the specific target of

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interest at low concentrations and in a complex environment. These ligands interact with their targets

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through shape complementarity and non-covalent interactions. Three main types of affinity ligand are

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described here. They are antibodies, molecularly imprinted polymers, and aptamers (Figure 1). The

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most widely used and well-studied probes for molecular recognition are antibodies, naturally occurring

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immune system proteins with exquisitely specific molecular recognition.24 Sometimes known as “plastic

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antibodies”, molecularly imprinted polymers (MIPs) are an alternative affinity reagent that are

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synthesized through the polymerization of suitable monomers in the presence of the target molecule

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acting as a molecular template.25 This templating yields nanoscale three-dimensional binding sites in

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the polymer that are size- and shape-complementary to the target molecule, as well as chemically

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compatible, to allow for specific binding. Aptamers are synthetic oligonucleotides that are capable of

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selective, high affinity binding to a molecular target.26 These reagents are discovered through an in vitro

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selection procedure known as SELEX (Systematic Evolution of Ligands by Exponential enrichment),

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where iterative steps of target incubation, partitioning, and amplification are used to enrich a large

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combinatorial oligonucleotide library in sequences with affinity for the target. The lists of biosensor and

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assay applications that include antibodies, MIPs, and aptamers as affinity reagents are extensive.24-28

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Thus, affinity reagents for potential rhizosphere biomarkers are examined here.

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Figure 1

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As rhizosphere biomarkers encompass a wide variety of compound types, many affinity ligands

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already exist for these targets and could be applied directly to agricultural applications. Table 1 and 2 6 ACS Paragon Plus Environment

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shows a selection of existing affinity ligands that could be used directly for sensing soil components,

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using only corn and wheat rhizosphere biomarkers, respectively, as examples.

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Table 1

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Table 2

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Using affinity ligands such as aptamers, antibodies, or MIPs to detect rhizosphere biomarkers

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could provide information on plant health and development, nutrient requirements, and encroaching

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invasive species. For example, some root exudates are suspected indicators of a plant’s nutrient status.

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Carvalhais et al. examined how the composition of root exudates was affected in maize under varying

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nutrient deficiencies.28 Iron deficiency stimulated increased release of glutamate, glucose, ribitol, and

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citrate. An examination of available affinity ligands in literature showed that an aptamer has been

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selected for glutamate, while MIPs for glutamate and glucose have also been developed.31,

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phosphorus deficiency resulted in the increased release of γ-aminobutyric acid, as well as

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carbohydrates: inositol, erythritol, ribitol, fructose, glucose, and arabinose. γ-aminobutyrate, glucose

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and fructose-binding MIPs have been developed47,

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commercially available. On the other hand, nitrogen deficiency showed a decrease of amino acids, such

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as aspartate, tyrosine, and isoleucine; aptamers, MIPs, and antibodies exist for many of these amino

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acids.28, 30, 36-38

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A

while an antibody for γ-aminobutyrate is

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In the future, the combination of technologies of precision agriculture, such as satellite-

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positioning systems, geographic information systems, and remote sensing devices with nanosensors

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dispersed in the soil or plant canopy capable of recognizing these biomarkers with their spatial

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variabilities could help in the efficient use of water, nutrients, and agrochemicals. In the nearer term,

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simple biosensing platforms, such as lateral flow assays, could be developed to allow farmers access to

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quick spot tests to help with decision-making. In order to achieve this short term or long term vision, 7 ACS Paragon Plus Environment

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existing affinity reagents for rhizosphere biomarkers will need to be characterized for their specificity

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under realistic testing scenarios in the presence of the complex chemical mixture of the soil matrix, as

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well as their stability under varying environmental conditions.

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developed for key rhizosphere biomarkers as their functions are elucidated. Other affinity systems are

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also emerging including nanobodies,66 recombinant antibodies,67 and affibodies,68 each with their own

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advantages and disadvantages, which could also be applied to these molecular targets

New recognition agents should be

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Precision farming, with the help of biosensors for rhizosphere biomarkers, could usher in a new

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era of “personalized medicine” for crops and crop rotations, where, to paraphrase the EU definition of

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personalized medicine, the right treatment (nutrient, agrochemical, etc) is provided to the right group of

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plants, at the right dose, at the right time and spatial scale.1

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nutrient uptake could be useful in more effectively timing the application of fertilizers, while detecting

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specific phytotoxins could help determine appropriate pesticide application, for example.

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limitations of our current knowledge of how to detect these biomarkers in the complex chemical

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environment of the soil, as well as how to transduce this binding event into a measurable signal, could

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be overcome by the further development of agricultural nanotechnology and bionanotechnology. This

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perspective focused on crop care for secure food production is based on the potential development of

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antibodies, aptamers, or MIPS for known rhizosphere biomarkers.

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understanding of the connection between rhizosphere biomarker composition and crop status, and

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improved tools relying on molecular recognition to detect these biomarkers, will be necessary in order

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to achieve precision agriculture’s full potential.

Detecting biomarkers implicated in

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A combination of a better

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51) Park, H.-E.; Tian, M.; Row, K.-H. Molecularly Imprinted Polymer for Solid-Phase Extraction of Phenolic Acids from Salicornia herbacea L. Sep. Sci. Technol. 2014, 49, 1401-1406. 52) Zhao, W.; Wei, C.; Xia, Y.; Tang, B.; Yuan, J. L. Synthesis and Identification of Benzoic Acid Artificial Antigen. 3rd International Conference on Bioinformatics and Biomedical Engineering. 2009 Beijing, 1-4. 53) Rajkumar, R.; Warsinke, A.; Möhwald, H; Scheller, F. W; Katterle, M. Analysis of recognition of fructose by imprinted polymers. Talanta. 2008 15, 1119-1123. 54) Long, Y.; Pfeiffer, F.; Mayer, G.; Schrøder, T. D.; Özalp, V. C.; Olsen, L. F. Selection of Aptamers for Metabolite Sensing and Construction of Optical Nanosensors. Methods Mol. Biol. 2016, 1380, 3-19. 55) Seong, H.; Lee, H. B.; Park, K. Glucose binding to molecularly imprinted polymers. J. Biomater. Sci. Polym. Ed., 2002, 13, 637-649. 56) Monreal, C. M.; Schnitzer, M. The Chemistry and Biochemistry of Organic Components in the Soil Solutions of Wheat Rhizospheres. In Donald L. Sparks, ed: Advances in Agronomy, Vol. 121, Burlington: Academic Press, 2013, 179-251. 57) Weiss R.; Molinelli, A.; Jakusch, M.; Mizaikoff, B. Molecular imprinting and solid phase extraction of flavonoid compounds. Bioseparation. 2001, 10, 379-387. 58) Gao, D.; Wang, D.-D.; Zhang, Q.; Yang, F.-Q.; Xia, Z.-N.; Zhang, Q.-H.; Yuan, C.-S. In Vivo Selective Capture and Rapid Identification of Luteolin and Its Metabolites in Rat Livers by Molecularly Imprinted Solid-Phase Microextraction. J. Agric. Food Chem. 2017, 65, 1158–1166. 59) Zhu, H.; Wang, Y.; Yuan, Y.; Zeng, H. Development and characterization of molecularly imprinted polymer microspheres for the selective detection of kaempferol in traditional Chinese medicines. Anal. Methods. 2011, 3, 348-355. 60) Song, X.; Li, J.; Wang, J. Chen, L. Quercetin molecularly imprinted polymers: Preparation, recognition characteristics and properties as sorbent for solid-phase extraction. Talanta. 2009, 80, 694-702.

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61) Yin, Y.; Yan, L.; Zhang, Z.; Wang, J.; Luo, N. Polydopamine-coated magnetic molecularly imprinted polymer for the selective solid-phase extraction of cinnamic acid, ferulic acid and caffeic acid from radix scrophulariae sample. J. Sep. Sci. 2016, 39, 1480–1488. 62) Liang, R.; Chen, L.; Qin, W. Potentiometric detection of chemical vapors using molecularly imprinted polymers as receptors. Sci. Rep. 2015, 5, 12462. 63) Asanuma, H.; Kakazu, M.; Shibata, M.; Hishiya, T. Molecularly imprinted polymer of β-cyclodextrin for the efficient recognition of cholesterol. Chem. Commun. 1997, 0, 1971-1972. 64) Hashim, S. N.; Schwarz, L. J.; Danylec, B.; Mitri, K.; Yang, Y.; Boysen, R. I.; Hearn, M. T. Recovery of ergosterol from the medicinal mushroom, Ganoderma tsugae var. Janniae, with a molecularly imprinted polymer derived from a cleavable monomer-template composite. J. Chromatogr. A. 2016, 1468, 1-9. 65) Hashim, S. N.; Boysen, R. I.; Schwarz, L. J.; Danylec, B., Hearn M. T. A comparison of covalent and non-covalent imprinting strategies for the synthesis of stigmasterol imprinted polymers. J. Chromatogr. A. 2014, 1359, 35-43. 66) Zhu, T., Yoon, C. and Row, K. Solid-phase Extraction of β-Sitosterol from Oldenlandia diffusa Using Molecular Imprinting Polymer. Chin. J. Chem. 2011, 29: 1246–1250. doi:10.1002/cjoc.201190231 67) Feng, S.; Gao, F.; Chen, Z.; Grant, E.; Kitts, D. D.; Wang, S.; Lu, S. Determination of α-Tocopherol in Vegetable Oils Using a Molecularly Imprinted Polymers–Surface-Enhanced Raman Spectroscopic Biosensor. J. Agric. Food Chem. 2013, 61, 10467–10475. 68) Muyldermans, S. Nanobodies: Natural Single-Domain Antibodies. Annu. Rev. Biochem. 2013, 82, 775797. 69) Frenzel, A.; Hust, M.; Schirrmann, T. Expression of Recombinant Antibodies. Front. Immunol. 2013, 4, 217.

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70) Löfblom, J.; Feldwisch, J.; Tolmachev, V.; Carlsson, J.; Ståhl, S.; Frejd, F. Y. Affibody molecules: engineered proteins for therapeutic, diagnostic and biotechnological applications. FEBS Lett. 2010, 584, 2670-2680.

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Figure 1: Rhizosphere biomarkers, such as root exudates and microbial metabolites, could be detected using affinity reagents such as aptamers, antibodies, and molecularly imprinted polymers.

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Table 1. Affinity ligands available for select rhizosphere biomarkers identified from maize. Chemical Class

Identified Soil

MIP

Aptamer

Components

Antibody commercially available

Amino Acids

Aspartic Acid 29, 30, 31

Yes 32

No

Yesa

Glutamic Acid 29, 30, 31

Yes 33

Yes 34

Yesa

Glutamine 29, 30, 31

Yes 35

Yes 36

Yesa

Alanine 29, 30, 31

Yes 37

No

Yesa

Tyrosine 29, 30, 31

Yes 38

Yes 39

No, however a Phosphotyrosine antibody is availablea

Isoleucine29, 30, 31

No

Yes 40

Yesb

Arginine 30

Yes 41

Yes 42

Yesa

Valine,30,31

Yes 43

Yes 44

Yesb

Histidine, 31

Yes 45

Yes 46

No

Phenylalanine 31

Yes 47

Yes 48

Yesa

γ-aminobutyrate (GABA)

Yes 49

No

Yesa

Yes 50

No

No

Yes 51

No

No, however

29, 30

Organic Acids

Malic acid29, 30, 31 Benzoic acid

30

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literature reference available52

Carbohydrates

Fructose 29, 30, 31

Yes 53

No but fructose

No

1,6 bisphosphate aptamer is reported 54 Glucose 29, 30, 31 a

Available from Abcam

b

Available from Antibodies-online

Yes 55

No

No

Table 2. Affinity ligands available for select soil components identified from wheat. Chemical Class

Identified

Soil MIP

Aptamer

Components54

Antibody commercially available (yes/no)

Fatty Acids

Arachidonic acid

No

No

Yesa

Flavonoids

Flavones

Yes 57

No

No

Luteolin

Yes 58

No

No

Kaempferide

Yes 59

No

No

Quercetin

Yes 60

No

Yesb

ferulic acid

Yes 56

No

Yesc

Lignin

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Monomer/phen olics alkylbenzene Sterols Tocopherols

Yes 62

No

No

Yes 63

No

Yesd

Ergosterol

Yes 64

No

No

Stigmasterol

Yes 65

No

No

β-Sitosterol

Yes 66

No

No

α-Tocopherol

Yes 67

None

Yesd

methylbenzene and Cholesterol

a

Available from Antibodies-online

b

Available from MyBiosource

c

Available from Creative Diagnostics

d

Available from LifeSpan BioSciences

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TOC graphic

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264x148mm (96 x 96 DPI)

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