Subscriber access provided by UNIVERSITY OF THE SUNSHINE COAST
Perspective
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
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Journal of Agricultural and Food Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
Page 1 of 22
Journal of Agricultural and Food Chemistry
1
Personalized medicine for crops? Opportunities for the application of molecular recognition in
2
agriculture.
3
Emily Mastronardi1, Carlos Monreal2, Maria C. DeRosa1*
4
1
Carleton University, Department of Chemistry, 1125 Colonel By Drive, Ottawa, ON Canada, K1S5B6
5
2
Agriculture and Agrifood Canada, 960 Carling Ave, Neatby Building, Ottawa, ON Canada, K1Y4X2
6
*to whom correspondence should be addressed: maria.derosa@carleton.ca
7 8
Keywords: Aptamers, Molecularly Imprinted Polymers, Antibodies, Rhizosphere, Root Exudates
9 10
1 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
11
Abstract: This perspective examines the detection of rhizosphere biomarkers, namely root
12
exudates and microbial metabolites, using molecular recognition elements such as molecularly
13
imprinted polymers, antibodies, and aptamers. Tracking these compounds in the rhizosphere could
14
provide valuable insight into the status of the crop and soil in a highly localized way. The outlook and
15
potential impact of the combination of molecular recognition and other innovations such as
16
nanotechnology and precision agriculture and the comparison to advances in personalized medicine are
17
considered.
18
Introduction: The prospect of personalized medicine and the rise of point-of-care diagnostics
19
are two emerging themes in the field of medicine that promise to revolutionize human health.
20
Personalized or precision medicine refers to the patient-centred tailoring of treatment. The European
21
Union defines personalized medicine as: ‘Providing the right treatment to the right patient, at the right
22
dose at the right time.1 An enabler of this revolution has been the rapid growth of diagnostic and
23
“omics” technology that can provide a molecular level understanding of disease and each patient’s
24
unique clinical, genetic, and environmental information to allow for individual tailoring of response. The
25
accurate and low cost detection of biomarkers, measurable indicators of a biological state or condition
26
(e.g. genes, proteins, and metabolites), are essential tools for accurate prognosis, dose selection,
27
tracking of therapeutic response, and detection of adverse outcomes. In particular, point-of-care (POC)
28
biomarker testing can provide close to immediate information about on an individual’s condition, can
29
provide more widespread access to diagnosis, and can facilitate real-time treatment decisions, all at
30
modest cost and in a non-invasive or minimally invasive fashion.2
31
In many ways, agriculture parallels health as an area of study with similar challenges,
32
complexities, and questions. For example, the challenge of efficient delivery of payloads such as
33
fertilizers, pesticides, and herbicides mirrors that seen in drug delivery, e.g. the complex environment,
2 ACS Paragon Plus Environment
Page 2 of 22
Page 3 of 22
Journal of Agricultural and Food Chemistry
34
the danger of off-target effects and thus the need for efficient targeting, etc. It is not surprising then
35
that technologies and other innovations that first see an incipience in medical sciences are eventually
36
applied to analogous problems in agriculture.
37
innovation that was first applied to questions and challenges in medicine before applications in
38
agriculture were examined.3 There are, of course, striking differences between the fields of medicine
39
and agriculture, including the type of regulatory oversight and the level of cost and/or risk that is
40
tolerated by stakeholders. These parallels and disparities will shape to what degree advances from one
41
field can impact the other.
Nanotechnology is one example of an enabling
42
Based on the congruence between medicine and agriculture, could there be an agricultural
43
equivalent to personalized medicine? Could point-of-care-type technologies be used to better manage
44
variable field and crop conditions and to respond to needs in real-time? Indeed, precision farming has
45
many critical features that mirror those in personalized medicine. Precision farming is an approach to
46
agriculture where crop management decisions are informed by data from global positioning systems,
47
remote sensing, computer modelling of biotic and abiotic conditions, and soil properties to provide
48
highly localized information and precisely identify the nature and location of problems.4,5
49
measurement of and response to inter and intra-field variation in soils and crops allows the farmer to
50
make decisions that support the success of the whole farm that in many ways parallels the guiding
51
principles of personalized medicine. In this case, the goal is to ensure that crops are growing at
52
maximum efficiency and yield while increasing the use efficiency of inputs such as fertilizers, pesticides,
53
and herbicides. Yet, to date, the majority of these data acquired relate to macro-scale factors such as
54
land surface temperature, soil moisture, drainage, topography, etc. rather than reporters at the
55
molecular level.
3 ACS Paragon Plus Environment
The
Journal of Agricultural and Food Chemistry
56
Furthermore, the “omics” revolution has also had a demonstrable effect on agriculture.6 The
57
importance of biomarkers is being realized, for example gene expression biomarkers as indicators of
58
nitrogen status7 and water status8 are being studied. Similarly, a number of protein biomarkers for
59
abiotic stress have been identified.9 In fact, “field-omics” is seeking to integrate genomic, transcriptomic,
60
proteomic, and metabolomics data with crop science for informing crop systems biology and crop
61
management strategies. 10 Nevertheless, at present, the analyses for these biomarkers are still relatively
62
costly and laborious, and the extraction of samples is invasive, e.g. collection of tissue from roots or
63
shoots for analysis. Interest in non-invasive testing for phenomics is on the rise11, but an alternative
64
approach would be to look outside the plant itself for biomarkers. In field detection of these biomarkers
65
could serve as a “point-of-care” equivalent that could use a molecular-level understanding of crop and
66
field conditions to inform farm management decisions.
67
Biomarkers in rhizosphere? The rhizosphere, the millimetres thick region of soil in the direct vicinity of
68
plant roots, is a complex and chemical-rich environment laden with potential information about the
69
interplay between the plant, soil, and microbial community. Root exudates, chemical compounds
70
secreted into the rhizosphere by root cells, in addition to the metabolites excreted by the microbial
71
communities present in the soil environment, could contain valuable biomarkers for assessing the state
72
of the crop and soil in a very localized way. 12, 13 These compounds are involved in the chemical signalling
73
that regulates many processes including microbial and fungal colonization, deterring herbivory, and
74
inhibiting the growth of encroaching plant species.14 For example, amino acids have been found to
75
suppress the growth of nematodes and competing plant species, while the flavonoid quercetin has been
76
implicated in resistance to aluminum toxicity in maize.15, 16 It has been estimated that plants release
77
between 5 and 25% of net fixed carbon into the rhizosphere in the form of exudates, ranging in
78
complexity from organic anions to polymers.17 Notably, up to 70% of the photosynthesized 13CO2 was
4 ACS Paragon Plus Environment
Page 4 of 22
Page 5 of 22
Journal of Agricultural and Food Chemistry
79
found to be exuded by wheat roots in recent work.18 The identification, quantification and the functional
80
understanding of these complex solutions could underlie crop yield and farm management.
81
Current data suggest that low molecular weight compounds are the most diverse group of soil
82
solution components, including sugars, amino acids, organic acids and phenolics, while higher molecular
83
weight compounds such as polysaccharides and proteins make up a larger proportion by mass.
84
soil, plant species, and nutrient availability all seem to have an impact on the quantity and type of
85
compounds present, suggesting that these compounds could serve as indicators that could be examined
86
as surrogates for crop status.
87
solutions in wheat rhizospheres over the growing season were able to identify hundreds of chemical
88
compounds distributed in 11 chemical classes.13 Though the specific function of many of these
89
compounds is unknown, several have been implicated in mediating the positive and negative
90
interactions affecting plant and microbe growth.
91
rhizosphere could provide useful information on crop health and could be combined with the platform
92
of precision agriculture to allow farmers to better monitor and respond to existing field conditions.
93
Affinity ligands and biosensors for rhizophere biomarkers
20
19
The
For example, recent work on chemical composition analysis of soil
13, 20
Thus, the presence of key biomarkers in the
94
The diversity, low concentrations, and localized presence of rhizosphere biomarkers has made
95
their identification a challenge. With the development of sensitive mass spectrometry techniques,
96
isotope labelling strategies, and high throughput metabolomics approaches, the characterization of
97
these complex solutions has become easier.21, 22 Yet, the cost and complexity of these approaches would
98
make them prohibitive in terms of their use in real-time precision agriculture.
99
greater attention should be paid to the development of simpler and lower cost alternatives in the form
For these reasons,
100
of biosensors and bioassays.
Biosensors take the information from the biochemical interaction of a
101
target molecule with a recognition or affinity element and translates it into a measurable output with a
5 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
102
defined sensitivity; two classic examples are the electrochemical glucose meter and the lateral flow
103
pregnancy test.23
104
In order to develop new biosensor platforms for rhizosphere biomarkers, nanoscale molecular
105
recognition agents or affinity ligands are needed that are capable of binding the specific target of
106
interest at low concentrations and in a complex environment. These ligands interact with their targets
107
through shape complementarity and non-covalent interactions. Three main types of affinity ligand are
108
described here. They are antibodies, molecularly imprinted polymers, and aptamers (Figure 1). The
109
most widely used and well-studied probes for molecular recognition are antibodies, naturally occurring
110
immune system proteins with exquisitely specific molecular recognition.24 Sometimes known as “plastic
111
antibodies”, molecularly imprinted polymers (MIPs) are an alternative affinity reagent that are
112
synthesized through the polymerization of suitable monomers in the presence of the target molecule
113
acting as a molecular template.25 This templating yields nanoscale three-dimensional binding sites in
114
the polymer that are size- and shape-complementary to the target molecule, as well as chemically
115
compatible, to allow for specific binding. Aptamers are synthetic oligonucleotides that are capable of
116
selective, high affinity binding to a molecular target.26 These reagents are discovered through an in vitro
117
selection procedure known as SELEX (Systematic Evolution of Ligands by Exponential enrichment),
118
where iterative steps of target incubation, partitioning, and amplification are used to enrich a large
119
combinatorial oligonucleotide library in sequences with affinity for the target. The lists of biosensor and
120
assay applications that include antibodies, MIPs, and aptamers as affinity reagents are extensive.24-28
121
Thus, affinity reagents for potential rhizosphere biomarkers are examined here.
122
Figure 1
123
As rhizosphere biomarkers encompass a wide variety of compound types, many affinity ligands
124
already exist for these targets and could be applied directly to agricultural applications. Table 1 and 2 6 ACS Paragon Plus Environment
Page 6 of 22
Page 7 of 22
Journal of Agricultural and Food Chemistry
125
shows a selection of existing affinity ligands that could be used directly for sensing soil components,
126
using only corn and wheat rhizosphere biomarkers, respectively, as examples.
127
Table 1
128
Table 2
129
Using affinity ligands such as aptamers, antibodies, or MIPs to detect rhizosphere biomarkers
130
could provide information on plant health and development, nutrient requirements, and encroaching
131
invasive species. For example, some root exudates are suspected indicators of a plant’s nutrient status.
132
Carvalhais et al. examined how the composition of root exudates was affected in maize under varying
133
nutrient deficiencies.28 Iron deficiency stimulated increased release of glutamate, glucose, ribitol, and
134
citrate. An examination of available affinity ligands in literature showed that an aptamer has been
135
selected for glutamate, while MIPs for glutamate and glucose have also been developed.31,
136
phosphorus deficiency resulted in the increased release of γ-aminobutyric acid, as well as
137
carbohydrates: inositol, erythritol, ribitol, fructose, glucose, and arabinose. γ-aminobutyrate, glucose
138
and fructose-binding MIPs have been developed47,
139
commercially available. On the other hand, nitrogen deficiency showed a decrease of amino acids, such
140
as aspartate, tyrosine, and isoleucine; aptamers, MIPs, and antibodies exist for many of these amino
141
acids.28, 30, 36-38
51, 53
32
A
while an antibody for γ-aminobutyrate is
142
In the future, the combination of technologies of precision agriculture, such as satellite-
143
positioning systems, geographic information systems, and remote sensing devices with nanosensors
144
dispersed in the soil or plant canopy capable of recognizing these biomarkers with their spatial
145
variabilities could help in the efficient use of water, nutrients, and agrochemicals. In the nearer term,
146
simple biosensing platforms, such as lateral flow assays, could be developed to allow farmers access to
147
quick spot tests to help with decision-making. In order to achieve this short term or long term vision, 7 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
Page 8 of 22
148
existing affinity reagents for rhizosphere biomarkers will need to be characterized for their specificity
149
under realistic testing scenarios in the presence of the complex chemical mixture of the soil matrix, as
150
well as their stability under varying environmental conditions.
151
developed for key rhizosphere biomarkers as their functions are elucidated. Other affinity systems are
152
also emerging including nanobodies,66 recombinant antibodies,67 and affibodies,68 each with their own
153
advantages and disadvantages, which could also be applied to these molecular targets
New recognition agents should be
154
Precision farming, with the help of biosensors for rhizosphere biomarkers, could usher in a new
155
era of “personalized medicine” for crops and crop rotations, where, to paraphrase the EU definition of
156
personalized medicine, the right treatment (nutrient, agrochemical, etc) is provided to the right group of
157
plants, at the right dose, at the right time and spatial scale.1
158
nutrient uptake could be useful in more effectively timing the application of fertilizers, while detecting
159
specific phytotoxins could help determine appropriate pesticide application, for example.
160
limitations of our current knowledge of how to detect these biomarkers in the complex chemical
161
environment of the soil, as well as how to transduce this binding event into a measurable signal, could
162
be overcome by the further development of agricultural nanotechnology and bionanotechnology. This
163
perspective focused on crop care for secure food production is based on the potential development of
164
antibodies, aptamers, or MIPS for known rhizosphere biomarkers.
165
understanding of the connection between rhizosphere biomarker composition and crop status, and
166
improved tools relying on molecular recognition to detect these biomarkers, will be necessary in order
167
to achieve precision agriculture’s full potential.
Detecting biomarkers implicated in
168
8 ACS Paragon Plus Environment
The
A combination of a better
Page 9 of 22
Journal of Agricultural and Food Chemistry
References 1) The Right Prevention and Treatment for the Right Patient at the Right Time. Strategic Research
Agenda for Innovative Medicines Initiative 2, EFPIA, Spring 2014. Innovative Medicines Initiative. http://www.imi.europa.eu/sites/default/files/uploads/documents/IMI2_SRA_March2014.pdf accessed July 1, 2017. 2) St John, A.; Price, C. P. Existing and Emerging Technologies for Point-of-Care Testing. Clin. Biochem. Rev. 2014, 35, 155–167. 3) DeRosa, M. C.; Monreal, C.; Schnitzer, M.; Walsh, R.; Sultan, Y. Nanotechnology in Fertilizers. Nat. Nanotechnol. 2010, 5, 91. 4) Krisna, K. R. Precision Farming: Soil Fertilizer and Productivity Aspects. Apple Academic Press CRC Press Taylor & Francis Group: Oakville, ON, Canada, 2013, 1-173. 5) Adamchuk, V. I.; Hummel, J. W.;Morgan, M. T.; Upadhyaya, S. K. On-the-go soil sensors for precision agriculture. Comput. Electron. Ag. 2004, 44, 71-91. 6) Van Emon, J.M. The Omics Revolution in Agricultural Research. J. Agric. Food Chem. 2016, 64, 36–44. 7) Yang, X. S.; Wu, J.; Ziegler, T. E.; Yang, X.; Zayed, A.; Rajani, M.S.; Zhou, D.; Basra, A. S.; Schachtman, D. P.; Peng, M.; Armstrong, C. L.; Caldo, R. A.; Morrell, J. A.; Lacy, M.; Staub, J. M. Gene Expression Biomarkers Provide Sensitive Indicators of in Planta Nitrogen Status in Maize. Plant Physiol. 2011, 157 1841-1852. 8) Marchand, G.; Mayjonade, B.; Vares, D.; Blanchet, N.; Boniface, M-C.; Maury, P.; Andrianasolo, F. N.; Burger, P.; Debaeke, P.; Casadebaig, P.; Vincourt, P.; Langlade, N. B. A biomarker based on gene expression indicates plant water status in controlled and natural environments. Plant Cell Environ. 2013, 36, 2175–2189. 9) Barkla, B. J. Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity. Proteomes. 2016, 4, 26.
9 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
10) Alexandersson, E.; Jacobson, D.; Vivier, M. A.; Weckwerth, W.; Andreasson, E. Field-omics— understanding large-scale molecular data from field crops. Front. Plant Sci. 2014 , 5, 286. 11) Sytar O.; Zivcak M.; Brestic M. Noninvasive Methods to Support Metabolomic Studies Targeted at Plant Phenolics for Food and Medicinal Use. In: Hakeem K., Tombuloğlu H., Tombuloğlu G. (eds) Plant Omics: Trends and Applications. Springer: Cham, Switzerland, 2016, 407-433. 12) Monreal, C. M. Labile Organic Matter in Soil Solution: I. Metabolites of Chemical Signaling Pathways from Plant–Microbe Interactions. In: Labile Organic Matter—Chemical Compositions, Function, and Significance in Soil and the Environment, SSSA Spec. Publ. 62. SSSA, Madison, WI. 2015, 157-172. 13) Monreal, C. M., and M. I. Schnitzer. Labile Organic Matter in Soil Solution: II. Separation and Identification of Metabolites from Plant–Microbial Communication in Soil Solutions of Wheat Rhizospheres. In: Labile Organic Matter—Chemical Compositions, Function, and Significance in Soil and the Environment, SSSA Spec. Publ. 62. SSSA, Madison, WI. 2015, 173-194. 14) Haichar, F. Z.; Santaella, C.; Heulin, T.; Achouak, W. Root exudates mediated interactions belowground. Soil Biol. Biochem. 2014, 77, 69-80. 15) Bertin, C., Yang, X., Weston, L.A. The role of root exudates and allelochemicals in the rhizosphere. Plant Soil. 2003, 256, 67–83. 16) Kidd, P.S., Llugany, M., Poschenrieder, C., Gunse´, B., Barcelo´, J. The role of root exudates in aluminium resistance and silicon-induced amelioration of aluminium toxicity in three variety of maize (Zea mays L.). J. Exp. Bot. 2001, 52, 1339–1352. 17) Jones, D. L.; Nguyen, C.; Finlay, R. D. Carbon flow in the rhizosphere: carbon trading at the soil–root interface. Plant Soil. 2009, 321, 5–33. 18) Matus, F.; Monreal, C.; Lefebvre, M.; Wu, S.-S.; Desjardins, R.; DeRosa, M. Producing Isotopically Enriched Plant, Soil Solution, and Rhizosphere Soil Materials over a Few Hours. Commun. Soil Sci. Plant Anal. 2014, 45, 865-880.
10 ACS Paragon Plus Environment
Page 10 of 22
Page 11 of 22
Journal of Agricultural and Food Chemistry
19) Badri, D. V.; Vivanco, J. M. Regulation and function of root exudates. Plant Cell Environ. 2009, 32, 666–681. 20) Bais, H. P.; Weir T. L.; Perry, L. G.; Gilroy, S.; Vivanco, J. M. The role of root exudates in rhizosphere interactions with plants and other organisms. Annu. Rev. Plant Biol. 2006, 57, 233-266. 21) Rugova, A.; Puschenreiter, M.; Koellensperger, G.; Han, S. Elucidating rhizosphere processes by mass spectrometry – A review. Anal. Chim. Acta 2017, 956, 1-13. 22) van Dam, N. M.; Bouwmeester, H. J. Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication. Trends Plant Sci. 2016, 21, 256-265. 23) Lee, T. M.-H. Over-the-Counter Biosensors: Past, Present, and Future. Sensors. 2008, 8, 5535-5559. 24) Luppa, P. B.; Sokoll, L. J.; Chan, D. W. Immunosensors—principles and applications to clinical chemistry. Clin. Chim. Acta 2001, 314, 1-26. 25) Uzun, L.; Turner, A. P. F. Molecularly-imprinted polymer sensors: realising their potential. Biosens. Bioelectron. 2016, 76, 131-144. 26) Iliuk, A. B.; Hu, L.; Tao, W. H. Aptamer in Bioanalytical Applications. Anal. Chem. 2011, 83, 4440– 4452. 27) Dhiman, A.; Kalra, P.; Bansal, V.; Bruno, J. G.; Sharma, T. K. Aptamer-based point-of-care diagnostic platforms. Sens. Actuators, B. 2017, 246, 535-553. 28) Selvolini, G.; Marrazza, G. MIP-Based Sensors: Promising New Tools for Cancer Biomarker Determination. Sensors. 2017, 17, 718. 29) Kraffczyk, I.; Trolldenier, G.; Beringer, H. Soluble root exudates of maize: Influence of potassium supply and rhizosphere microorganisms. Soil Biol. Biochem. 1984, 16, 315-322. 30) Carvalhais, L. C.; Dennis, P. G.; Fedoseyenko, D. Hajirezaei, M. R.; Borriss, R.; von Wirén, N. Root exudation of sugars, amino acids, and organic acids by maize as affected by nitrogen, phosphorus, potassium, and iron deficiency. J. Plant Nutr. Soil Sci. 2011, 174, 3–11.
11 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
31) Fan B.; Carvalhais, L. C.; Becker, A.; Fedoseyenko, D.; von Wirén, N.; Borriss, R. Transcriptomic profiling of Bacillus amylolique faciens FZB42 in response to maize root exudates. BMC Microbiol. 2012, 12, 116. 32) Prasad, B. B; Srivastava, A.; Tiwari, M. P. Molecularly imprinted polymer-matrix nanocomposite for enantioselective electrochemical sensing of D- and L-aspartic acid. Mater. Sci. Eng. C. Mater. Biol. Appl. 2013, 33, 4071-4080. 33) Ouyang, R.; Lei, J.; Ju, H.; Xue, Y., A Molecularly Imprinted Copolymer Designed for Enantioselective Recognition of Glutamic Acid. Adv. Funct. Mater. 2007, 17, 3223–3230. 34) Ohsawa, K.; Kasamatsu, T.; Nagashima, J.-I.; Hanawa, K.; Kuwahara, M.; Ozaki, H.; Sawai, H. Arginine-modified DNA Aptamers That Show Enantioselective Recognition of the Dicarboxylic Acid Moiety of Glutamic Acid. Anal. Sci. 2008, 24, 167-172. 35) Garcia, I. T. S.; Porto, F. G. d. S.; do Amaral, Q. D. F.; Carreño, N. L. V.; Martins, M. M.; Wallau, M. Preparation of glutamine films on silicon substrates. Surf. Interface Anal. 2008, 40, 899–905. 36) Ames, T. D.; Breaker, R. R. Bacterial aptamers that selectively bind glutamine. RNA Biol. 2011, 8, 8289. 37) Zhu, F.; Yan, X.; Liu, S. Preparation and recognition characteristics of alanine surface molecularly imprinted polymers. Anal. Methods. 2015, 7, 8740-8749. 38) Zheng, X. F.; Lian, Q.; Wu, H.; Liu, H.; Song, S. Molecularly imprinted polymer for L-tyrosine recognition and controlled release. Russ. J. Appl. Chem. 2015, 88, 160. 39) Mannironi, C.; Scerch, C.; Fruscoloni, P.; Tocchini-Valentini, G. P. Molecular recognition of amino acids by RNA aptamers: the evolution into an L-tyrosine binder of a dopamine-binding RNA motif. RNA. 2000, 6, 520-527. 40) Lozupone, C.; Changayil, S.; Majerfeld, I.; Yarus, M. Selection of the simplest RNA that binds isoleucine. RNA. 2003, 9, 1315–1322.
12 ACS Paragon Plus Environment
Page 12 of 22
Page 13 of 22
Journal of Agricultural and Food Chemistry
41) Mbukwa, E. A.; Msagati, T. A. M.; Mamba, B. B. Preparation of guanidinium terminus-molecularly imprinted polymers for selective recognition and solid-phase extraction (SPE) of [arginine]-microcystins. Anal. Bioanal. Chem. 2013, 405, 4253–4267. 42) Famulok, M. Molecular Recognition of Amino Acids by RNA-Aptamers: An L-Citrulline Binding RNA Motif and Its Evolution into an L-Arginine Binder. J. Am. Chem. Soc. 1994, 116, 1698–1706. 43) Chen, J.; Liang, R. P.; Wang, X. N.; Qiu, J. D. A norepinephrine coated magnetic molecularly imprinted polymer for simultaneous multiple chiral recognition. J. Chromatogr. A. 2015, 1409, 268-276. 44) Majerfeld, I.; Yarus, M. An RNA pocket for an aliphatic hydrophobe. Nat. Struct. Biol. 1994, 1, 287292. 45) Prasad, B. B.; Tiwari, K.; Singh, M.; Sharma, P. S.; Patel, A. K.; Srivastava, S. Zwitterionic molecularly imprinted polymer-based solid-phase micro-extraction coupled with molecularly imprinted polymer sensor for ultra-trace sensing of L-histidine. J. Sep. Sci. 2009, 32, 1096–1105. 46) Majerfeld, I.; Puthenvedu, D.; Yarus, M. RNA affinity for molecular L-histidine; genetic code origins. J. Mol. Evol. 2005, 61, 226-235. 47) Yang, L.; Hu, X.; Guan, P.; Li, J.; Wu, D.; Gao, B. Molecularly imprinted polymers for the selective recognition of L-phenylalanine based on 1-buty-3-methylimidazolium ionic liquid. J. Appl. Polym. Sci. 2015, 132, 42485. 48) Illangasekare, M.; Yarus, M. Phenylalanine-binding RNAs and genetic code evolution. J. Mol. Evol. 2002, 54, 298-311. 49) Zheng, X.; Lin, R.; Zhou, X.; Zhang, L.; Lin, W. Electrochemical sensor of 4-aminobutyric acid based on molecularly imprinted electropolymer. Anal. Methods. 2012, 4, 482-487. 50) Prasad, B. B.; Pandey, I. Molecularly imprinted polymer-based piezoelectric sensor for enantioselective analysis of malic acid isomers. Sens. Actuators B. 2013, 181, 596-604.
13 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
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.
14 ACS Paragon Plus Environment
Page 14 of 22
Page 15 of 22
Journal of Agricultural and Food Chemistry
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.
15 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
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.
16 ACS Paragon Plus Environment
Page 16 of 22
Page 17 of 22
Journal of Agricultural and Food Chemistry
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.
17 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
Page 18 of 22
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
18 ACS Paragon Plus Environment
Page 19 of 22
Journal of Agricultural and Food Chemistry
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
19 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
Page 20 of 22
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
20 ACS Paragon Plus Environment
Page 21 of 22
Journal of Agricultural and Food Chemistry
TOC graphic
21 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
264x148mm (96 x 96 DPI)
ACS Paragon Plus Environment
Page 22 of 22