Constitutive redox and phosphoproteome 
changes in multiple herbicide resistant 
Avena fatua L. are similar to those of 
systemic acquired resistance and systemic 
acquired acclimation
Authors: Erin E. Burns, Barbara K. Keith, Refai Y. 
Mohammed, Brian Bothner, and Wiliam E. Dyer
NOTICE: this is the author’s version of a work that was accepted for publication in Journal of 
Plant Physiology. Changes resulting from the publishing process, such as peer review, editing, 
corections, structural formating, and other quality control mechanisms may not be reflected in 
this document. Changes may have been made to this work since it was submited for publication. 
A definitive version was subsequently published in Journal of Plant Physiology, v. 220, January 
2018, DOI# 10.1016/j.jplph.2017.11.004
Burns, Erin E. , Barbara K. Keith, Refai Y. Mohammed, Brian Bothner, and Wiliam E. Dyer. 
"Constitutive redox and phosphoproteome changes in multiple herbicide resistant Avena fatua L. 
are similar to those of systemic acquired resistance and systemic acquired acclimation." Journal 
of Plant Physiology 220 (November 2017): 105-114. DOI: 10.1016/j.jplph.2017.11.004.
Made available through Montana State University’s ScholarWorks 
scholarworks.montana.edu 
Constitutive redox and phosphoproteome changes in multiple herbicide
resistantAvena fatuaL. are similar to those of systemic acquired resistance
and systemic acquired acclimation
Erin E. Burnsa, Barbara K. Keitha, Mohammed Y. Refaib, Brian Bothnerb, Wiliam E. Dyera,⁎
aDepartment of Plant Sciences & Plant Pathology, PO Box 173150, Montana State University, Bozeman, MT 59717, United States
bDepartment of Chemistry & Biochemistry Research, PO Box 173400, Montana State University, Bozeman, MT 59717, United States
ABSTRACT
Plants are routinely confronted with numerous biotic and abiotic stressors, and in response have evolved highly
effective strategies of systemic acquired resistance (SAR) and systemic acquired acclimation (SAA), respectively.
A much more evolutionarily recent abiotic stress is the application of herbicides to control weedy plants, and
their intensive use has selected for resistant weed populations that cause substantial crop yield losses and in-
crease production costs. Non-target site resistance (NTSR) to herbicides is rapidly increasing worldwide and is
associated with alterations in generalized stress defense networks. This work investigated protein post-transla-
tional modifications associated with NTSR in multiple herbicide resistant (MHR)Avena fatua, and their com-
monalities with those of SAR and SAA. We used proteomic, biochemical, and immunological approaches to
compare constitutive protein profiles in MHR and herbicide susceptible (HS)A. fatua populations.
Phosphoproteome and redox proteome surveys showed that post-translational modifications of proteins with
functions in core celular processes were reduced in MHR plants, while those involved in xenobiotic and stress
response, reactive oxygen species detoxification and redox maintenance, heat shock response, and intracelular
signaling were elevated in MHR as compared to HS plants. More specificaly, MHR plants contained con-
stitutively elevated levels of three protein kinases including the lectin S-receptor-like serine/threonine-protein
kinase LecRK2, a wel-characterized component of SAR. Analyses of superoxide dismutase enzyme activity and
protein levels did not reveal constitutive differences between MHR and HS plants. The overal results support the
idea that herbicide stress is perceived similarly to other abiotic stresses, and thatA. fatuaNTSR shares analogous
features with SAR and SAA. We speculate that MHRA. fatua’s previous exposure to sublethal herbicide doses, as
wel as earlier evolution under a diversity of abiotic and biotic stressors, has led to a heightened state of stress
preparedness that includes NTSR to a number of unrelated herbicides.
1. Introduction
Plants are regularly confronted with numerous external stresses
from biotic and abiotic sources during their evolution. To combat biotic
invasions by pathogenic bacteria and fungi, they have evolved highly
effective innate and induced immune responses (Dodds and Rathjen,
2010). The components and pathways of pattern-triggered immunity
(PTI) (Boler and Felix, 2009) and systemic acquired resistance (SAR)
(Fu and Dong, 2013) are wel characterized, involving recognition,
signal transduction, and transcriptional reprogramming in response to
biotic chalenge.
Similarly, plants have evolved related strategies to acclimate to
abiotic stresses such as heat, cold, and salt. Systemic acquired
acclimation (SAA) describes an accumulation of transcripts and pro-
teins that confer enhanced resistance to subsequent abiotic stresses
(Suzuki et al., 2013). Although less detail is known about SAA than
SAR, there are a number of commonalities between the two (Atkinson
and Urwin, 2012; Fujita et al., 2006). For example, both systems in-
clude stress recognition proteins such as receptor-like kinases (RLKs)
and lectin receptor kinases (LRKs), and include key roles for reactive
oxygen species (ROS), overal celular redox state, and mitogen-acti-
vated protein (MAP) kinase-mediated signal transduction cascades
(Mittler and Blumwald, 2015).
A much more evolutionarily recent abiotic stress imposed on plants
is the application of herbicides. Herbicides are obviously designed to
control plants, but they can also merely cause injury, due to sublethal
T
dosages (improper applications or equipment problems), adverse en-
vironmental conditions that reduce efficacy, or delayed applications on
older, more tolerant plants (Caseley and Walker, 1990). Under these
conditions, susceptible plants respond much the same as they do to
other abiotic stresses (reviewed in (Alberto et al., 2016)). Both abiotic
(Dietz et al., 2016) and herbicide stresses (Dayan and Watson, 2011;
Sewelam et al., 2016) induce rapid ROS generation, and even though
herbicides are designed to inhibit a specific biochemical target, both
impact multiple pathways and celular components (Délye, 2013;
Suzuki et al., 2014). Plant transcriptome changes caused by herbicide
stress are quite similar to those resulting from abiotic and biotic stresses
(Das et al., 2010; Unver et al., 2010).
Worldwide intensive herbicide use has led to the evolution of re-
sistant weed populations that cause substantial crop yield losses and
increase production costs (Heap, 2014). Resistance can be conferred by
target site overexpression or mutations that alter herbicide binding, or
non-target site resistance (NTSR) mechanisms like enhanced rates of
herbicide metabolism, reduced absorption and/or translocation, se-
questration, or more generalized stress defense networks (Délye, 2013).
Selection of herbicide resistant (HR) plants is thought to operate on
standing genetic variation as affected by biological (species character-
istics) and operational (herbicide dose and use patterns) factors
(Georghiou and Taylor, 1986; Jasieniuk et al., 1996). NTSR evolves
gradualy, appears to be controled by multiple genes, and is conferred
by one or more constitutive and/or induced physiological mechanisms
(reviewed in (Délye, 2013)). Recent transcriptome analyses of con-
stitutive changes in HR or multiple herbicide resistant (MHR) popula-
tions show that transcripts representing functions in xenobiotic meta-
bolism and stress response are more abundant prior to herbicide
treatment (Gaines et al., 2014; Hofer et al., 2014; Peng et al., 2010).
We recently described populations of MHR Avena fatuaL. that are
resistant to members of al selective herbicide families available in the
U.S. forA. fatuacontrol in smal grain crops (Keith et al., 2015;
Lehnhoffet al., 2013). MHR3 and MHR4 plants do not contain known
target site mutations for acetolactate synthase (ALS) or acetyl-CoA
carboxylase (ACCase) inhibitors, and the cytochrome P450 mono-
oxygenase (P450) inhibitor malathion partialy reversed the resistance
phenotype for several herbicides (Keith et al., 2015), indicating that
NTSR mechanisms are involved. Transcriptome and proteome analyses
show that MHRA. fatuaplants have constitutively altered levels of
stress-related differentialy expressed genes (DEGs) and proteins (Keith
et al., 2017). Specificaly, DEGs and proteins with functions in xeno-
biotic catabolism, stress response, redox maintenance, and transcrip-
tional regulation are constitutively elevated in untreated MHR plants.
We now extend these transcriptional and translational investigations to
include surveys of post-translational modifications (PTMs) including
protein phosphorylation and redox state of individual proteins.
2. Materials and methods
2.1. Plant material
The MHR3 and MHR4 populations were derived from seeds col-
lected in 2006 from twoA. fatua populations not controled by
60 g a i ha−1pinoxaden (Axial, Syngenta Crop Protection; ACCase in-
hibitor) in two productionfields separated by approximately 8 km in
Teton County, Montana, USA. Field-colected seeds (about 90% of
which were resistant to 60 g a i ha−1pinoxaden, data not shown) were
subjected to two generations of recurrent group selection (50 plants
each generation) by spraying with the same dose of pinoxaden (for
MHR3 and MHR4) or surfactant only (susceptible populations), fol-
lowed byfive additional generations with no herbicide selection in the
greenhouse. From each generation of 50 plants, al seeds were har-
vested and a random selection of 50 seeds was used to initiate the next
generation. The herbicide susceptible population HS1 was derived from
seeds colected from untreated border plants in an adjacentfield, and
was subsequently confirmed to be 100% susceptible to the herbicides
used in these studies (Keith et al., 2015; Lehnhoffet al., 2013). A second
susceptible population, HS2, is the inbred nondormant SH430 line used
in seed dormancy research (Johnson et al., 1995; Naylor and Jana,
1976). Plants were grown under a 16-h photoperiod of natural sunlight
supplemented with mercury vapor lamps (165μmol m−2sec−1)at
25 ± 4C in standard greenhouse soil mix [1:1:1 (by vol) Bozeman silt
loam:Sunshine mix #12 (Sun Gro Horticulture, Inc., Belvue, WA):-
perlite] and fertilized weekly with Jack’s water soluble 20 N-20 P–20 K
fertilizer (JR Peters Inc., Alentown, PA). Plants for each experiment
were grown on the same greenhouse bench and were harvested in mid-
morning to minimize potential environmental- and circadian-related
protein changes.
2.2. Protein extraction
For phosphoproteome analysis, shoot tissue from three replicate
three-leaf stage HS1 and MHR4 plants was harvested, ground under
liquid nitrogen, and 200 mg of tissue from each plant was suspended in
ice cold extraction buffer containing 0.1 M Tris HCl (pH 7.5), 2 mM
EDTA, 1 mM DTT, 1 mM PMSF, and 5% (w/v) PVPP. The slurries were
filtered through Miracloth (EMD Milipore, Merck KGaA, Darmstadt,
Germany) andfiltrates were centrifuged at 21,380 x g for 10 min at 4C.
Proteins were concentrated by precipitation with four volumes of ice-
cold acetone containing 10% TCA at−80C overnight. Two additional
100% acetone precipitations were performed for 3 h each at−80C, and
proteins were resuspended in two-dimensional polyacrylamide gel
electrophoresis (2D-E) buffer (30 mM Tris pH 8.5, 7 M urea, 2 M
thiourea, 4% CHAPS, 1 x protease inhibitor/nuclease mix [GE
Healthcare Life Sciences, Pittsburgh, PA], and 0.1% [w/v] bromo-
phenol blue) to afinal concentration of 2 mg mL−1. Protein con-
centrations were determined (Bradford, 1976) using bovine serum al-
bumin fraction V as standard.
For redox proteome analysis, shoot tissue from three replicate three-
leaf stage HS1 and MHR4 plants was extracted as described above and
subjected to the blocking 5-(iodoacetamido)fluorescein (IAF) labeling
method described in Wang et al. (2011). Thiol groups of oxidized
proteins were labeled with Rhodamine Red®C2maleimide (Thermo
Fisher Scientific, Waltham MA) in afinal concentration of 40μM during
a 30-min dark incubation at room temperature, and then resuspended
in 2D-E buffer to afinal concentration of 2 mg mL−1(Waszczak et al.,
2015). Protein concentrations were determined as above.
2.3. 2D electrophoresis
Extracts containing 150 or 50μg of protein for phosphoproteome or
redox proteome analysis, respectively, were diluted to afinal volume of
450μL with isoelectric focusing (IEF) buffer (2D-E buffer containing
50 mM DTT and 0.5% (v/v) IPG buffer 3-11 NL [GE Healthcare]), and
incubated for 1 h at room temperature. Three replicate extracts each
from MHR4 or HS1 shoots were separately loaded on IPG strips (pH 3-
11 NL, non-linear, 24 cm length [GE Healthcare]), and IEF and SDS-
PAGE were carried out as described byMaaty et al. (2012).
2.3.1. Image acquisition and analysis
After electrophoresis, phosphoproteome gels were stained with the
fluorescent phosphoprotein specific stain Pro-Q Diamond (Invitrogen
Corp. Carlsbad, CA), which detects phosphate groups attached to tyr-
osine, serine, or threonine residues, folowing the methods ofAgrawal
and Thelen (2005). Gels were scanned with a Typhoon Trio Imager
folowing the Invitrogen protocol. Redox proteome gels were scanned
with the same imager using the Thermo Fisher Scientific protocol. Al
gels were scanned at 100μm resolution and 640 V for PMT. Images
were subjected to an automated in-gel analysis using Progenesis Sa-
meSpots v 3.0.2 software (Nonlinear Dynamics Ltd. Newcastle, UK),
which aligns multiple gel images while adjusting for positional
variations so that individual protein spots can be compared among
samples. Individual spot volumes were calculated for multivariate sta-
tistical analysis. Gels used for protein identification each contained
400μg of protein and were stained with coloidal coomassie stain
(Dybala and Metzger, 2009), destained in 10% (v/v) acetic acid, and
stored at 4C in 1% (v/v) acetic acid until spot excision.
2.3.2. Protein mass determination and analysis
After electrophoresis, al significantly differential (p-value < 0.1
identified by Progenesis SameSpots) protein spots were excised, di-
gested with porcine trypsin (Promega Corp. Madison, WI), and eluted as
described inShevchenko et al. (2006). The resulting peptides were
subjected to mass analysis performed on Bruker maXis Impact with
Dionex 3000 nano-uHPLC controled with Chromeleon Xpress (2.13 for
Hystar) folowing the methods ofMaaty et al. (2012).
Protein identification folowed the methods ofMason et al. (2016),
initiated by generating a custom protein sequencefile (.FASTA) from
theOryza sativasubsp. japonica (retrieved 2016;http://www.UniProt.
org;containing 121,989 entries) andBrachypodium distachyon (re-
trieved 2016;http://www.UniProt.org;containing 50,507 entries) da-
tabases. Sequences for the potential contaminants human keratin (re-
trieved 2016;http://www.UniProt.org;containing 49 entries) and
porcine trypsin (retrieved 2016;http://www.UniProt.org;containing 1
entry) were added to the sequencefile to create afinal target-decoy
library. The library was queried against datafiles using the folowing
search parameters: up to two missed cleavages alowed; precursor
charges +2, +3, +4; precursor ion mass tolerance 30 ppm; and frag-
mentation mass tolerance of 0.5 Da. Post translational modifications
were defined as oxidation of M, acetylation of N-terminus, and car-
boxylation of C-terminus (defined in SearchGUI software;Vaudel et al.
(2011)). Two or more significant peptides with an FDR≤1.0% (Pepti-
deShaker software (Vaudel et al., 2015)) were required for annotation
of each protein from the PaxDb database (Wang et al., 2012) as ac-
cessed through UniProtKB and the Rice Genome Annotation Project
(Kawahara et al., 2013).
2.4. 1D page
Protein extracts (20μg per lane) from HS1, HS2, MHR3, and MHR4
plants obtained as described above were heated at 95C for 5 min in 1 x
Laemmli SDS sample buffer (Cleveland et al., 1977) before being
subjected toSDS-PAGE in12.5%gels at 2.5 mA cm−1for 3 h with
water cooling.
2.5. Immunoblots
Proteins were electroblotted from SDS gels onto PVDF membrane
(Pal Corporation, Radnor, PA) and probed with rabbit polyclonal an-
tisera againstSpinacia oleraceacytosolic or chloroplastic CuZn SODs
(Kanematsu and Asada, 1990) diluted 1:5000 (v/v) in blotto (10% [w/
v] nonfat dry powdered milk/phosphate-buffered saline/0.001% [w/v]
sodium azide) folowed by detection with goat anti-rabbit IgG/alkaline
phosphatase (Sigma-Aldrich AP132A) diluted 1:10,000 (v/v) in blotto.
Densitometric analyses of immunoblot signals were performed using
ImageJ (Schneider et al., 2012).
2.6. Superoxide dismutase activity gels
Proteins extracts (20μg per lane) from HS1, HS2, MHR3, and MHR4
plants obtained as described above were subjected to native electro-
phoresis in 12.5% polyacrylamide gels at 2.5 mA cm−1with water
cooling. Superoxide dismutase (SOD) activity was detected photo-
chemicaly as described byChen and Pan (1996)in gels after ilumi-
nation with 30μmol m−2s−1fluorescent light for 5 min. Densitometric
quantification of SOD activity bands were performed using ImageJ
(Schneider et al., 2012).
3. Results and discussion
2D electrophoresis was used to compare constitutive profiles of
soluble phosphorylated (numbered 1–24 inFig. 1andTable 1) and
redox-sensitive (numbered 25–47 inFig. 2andTable 2) proteins from
untreated MHR4 and HS1 plants. Statistical analysis of phosphopro-
teome gels identified 24 differential protein spots, of which 14 proteins
were more abundant in MHR4 than HS1 plants. Analysis of redox
proteome gels identified 23 differential spots, with 15 proteins at higher
levels in MHR4 plants. For both phosphoproteome and redox proteome
gels, differences influorescent signals between MHR4 and HS1 samples
were due to either altered protein amounts or changes in the number of
labeled residues on individual proteins.
Differential signals from phosphorylated and redox-sensitive pro-
teins are discussed below infive functional categories: core celular
Fig. 1.Representative two dimensional electrophoresis gel of the
multiple herbicide resistant (MHR4)Avena fatuaphosphoproteome.
Significantly differential (between MHR and herbicide susceptible
(HS1) plants) protein spots were numbered, excised from gels, and
identified by LC MS/MS. Spot numbers are the same as inTable 1.
Table 1
Differentialy expressed phosphorylated proteins from untreated herbicide susceptible (HS1) and multiple herbicide resistant (MHR4)Avena fatuaplants identified using two dimensional
polyacrylamide gel electrophoresis.
Function Spot no. Uniprot no. Oryza sativano. Annotation FCa P-value Peptidesb Peptide sequences
Core celular
processes
6 P14655 Os04g0659100 Glutamine synthetase 7.4 0.04 3 TISKPVEDPSELPK
WNYDGSSTGQAPGEDSEVILYPQAIFK
WNYDGSSTGQAPGEDSEVILYPQAIFKDPFR
7 I1HI10 Os10g0355800 ATP synthase CF1 beta subunit 2.1 0.06 4 FVQAGSEVSALLGR
IFNVLGEPVDNLGPVDSSATFPIHR
TVLIMELINNIAK
YKELQDIAILGLDELSEEDRLTVAR
14 Q5VNW1 Os06g0133800 Transketolase 3.0 0.05 2 IKVTTTIGFGSPNKANSYSVH
QKDTPEERNVRFGVREHGMGAICNGIALHSPGL
15 Q6ATP4 Os11g0656500 Putative polyprotein −5.2 0.02 2 DVAPSEEDRPHRKVQRPVYFVSEALWDAK
EWTPAPEPVSVPEASSGPSQLPHTAHWVMQFD
16 Q8LH82 Os07g0446800 Hexokinase −2.4 0.07 2 EGCACAAPPAAAAPPMPK
RMVVEVCDIVATRAARLAAAGIV
17 Q40677 Os11g0171300 Fructose-bisphosphate aldolase,
chloroplastic
−2.5 0.05 2 LASIGLENTEANR
TVVSIPNGPSELAVK
18 B9F813 Os04g0234600 Sedoheptulose-1,7-bisphosphatase −5.9 0.08 2 LLFEVAPLGFLIEK
TNFTVGTIFGVWPGDKLTGVTGGDQ
19 B8XEK6 Os06g0133000 Granule-bound starch synthase I −7.3 0.00 2 RFPSVVVYATGAGMNVVFVGAEMAPWSK
APRILNLNNNPYFKGTSGEDVVFVCNDWH
21 Q0IPE5 Os12g0210800 2-dehydro 3-
deoxyphosphooctonate aldolase
−2.4 0.06 3 LYGQLKAAQPFFLLAGPN
PVVTDVHESHQCEAVGRV
EWLREANCPVVADVTHALQQPAGK
22 I1J387 Os04g0672200 Poly(ADP-ribose) polymerase −2.5 0.02 2 SKDFLFVRDLFLSGMGSFATENSIL
LLETLKKLHYCPSLWNKSSIEVMSS
23 Q2QSR7 Os12g0420200 NAD(P)-binding domain
containing protein
−2.6 0.05 2 APITQQLPGESDAEYAEFSSK
VKDLATAFVLALGNPKASKQVFNIS
24 Q7XPR2 Os04g0623800 Aminomethyltransferase −7.8 0.01 2 LAGAAEAAEAELKKTALYDFHVAHG
LEKSEGKVRLTGLGARDSLRLEAG
ROS and redox
maintenance
2 P0C5D1 Os07g0638400 1-Cys peroxiredoxin 2.4 0.04 2 GLTLGDVVPDLELDTTHGK
ALHIVGPDKKVKLSFLFPACTGRNMAEVL
11 B7ERQ1 Os07g0638300 Peroxiredoxin 3.6 0.06 2 STHGKIRIHDFVGDTY
VRAVDALQTAAKHAVATPVNW
Chaperones and
heat shock
3 Q10NA9 Os03g0276500 70 kDa heat shock protein 3.2 0.04 7 ATAGDTHLGGEDFDNR
DAGVISGLNVMR
NQVAMNPINTVFDAK
STVHDVVLVGGSTR
TTPSYVAFTDSER
VQDLLLLDVTPLSQGLETAGGVMTVLIPR
VQQLLQDFFNGK
5 Q2QU06 Os12g0277500 60 kDa chaperonin alpha subunit 6.6 0.03 9 AVLQDIAIVTGAEFLAK
GILNVAAIKAPSFGER
GYISPQFVTNLEK
LANAVGVTLGPR
NVVLDEYGSPK
NVVLDEYGSPKVVNDGVTIAR
VGAATETELEDR
VTIHQTTTTLIADAASKDEIQAR
VVNDGVTIAR
8 Q7G2N7 Os10g0462900 Chaperonin CPN60-1,
mitochondrial
2.1 0.03 6 EGVITIADGNTLYNELEVVEGMK
EGVITIADGNTLYNELEVVEGMKLDR
LLEQDNTDLGYDAAK
SVAAGMNAMDLR
TALVDAASVSSLMTTTESIVEIPKEEK
VTVSKDDTVILDGAGDKK
10 Q6ZFJ9 Os02g0102900 60 kDa chaperonin beta subunit 2.0 0.04 2 EVELEDPVENIGAK
LADLVGVTLGPK
13 Q8H903 Os10g0462900 60 kDa chaperonin, mitochondrial 2.3 0.01 2 DGNTLYNELEVVEGMKLDRGYISPYFVTNPK
AGDKKSIEERAEQIRSAIELSTSDYDKEKL
(continued on next page)
processes, xenobiotic and stress response, ROS detoxification and redox
maintenance, chaperones and heat shock proteins, and signaling pro-
teins. Overal, signals from the majority of proteins with functions in
core celular processes, photosynthesis, and translation were con-
stitutively lower in MHR4 than HS1 plants, while those involved in
xenobiotic response, ROS metabolism, redox maintenance, heat shock
response, and signaling were constitutively elevated in MHR4 plants.
3.1. Core celular processes
Differential signals from six of nine phosphorylated proteins in-
volved in basic metabolism were constitutively reduced in MHR4 plants
(Table 1), including hexokinase, fructose-bisphosphate aldolase, sedo-
heptulose-1,7-bisphosphatase, granule-bound starch synthase I, phos-
phoribulokinase, and 2-dehydro-3-deoxyphosphooctonate aldolase
(spots 16–21,Fig. 1). These enzymes are involved in the biosynthesis or
sensing of primary metabolites, specificaly glycolysis, starch synthesis,
lipopolysaccharide biosynthesis, the Calvin cycle, and glucose sensing.
In contrast, glutamine synthetase, ATP synthase CF1 beta subunit, and
transketolase (spots 6, 7, and 14,Fig. 1) were constitutively elevated in
MHR4 plants. Phosphorylated glutamine synthetase, transketolase, and
fructose-bisphosphate aldolase were identified inArabidopsis thaliana
andO. sativain response to pathogen attack (Jones et al., 2006) and
abscisic acid application (He and Li, 2008), respectively.
Differential signals of redox-sensitive proteins involved in photo-
synthesis were mixed, in that photosystem I reaction center subunit I
(spot 41) and 23 kDa polypeptide of photosystem I (spot 39) were
reduced and elevated in MHR4 plants, respectively (Fig. 2,Table 2).
Photosystem I and I reaction centers are a primary site of ROS gen-
eration (Asada, 2006), and a redox sensitive photosystem I light har-
vesting complex protein was identified in response to methyl jasmonate
treatment inA. thaliana(Alvarez et al., 2009).
Signals of four redox-sensitive proteins involved in protein transla-
tion were differentialy reduced in MHR4 plants, including chloroplast
translational elongation factor Tu, plastid-specific 30S ribosomal pro-
tein 2, and 40S ribosomal protein S14 (spots 40, 45, and 47, respec-
tively) (Fig. 2,Table 2). In contrast, elongation factor 1-beta 1 (spot 31,
Fig. 2) was elevated in MHR4 as compared to HS1 plants. Ribosomal
and elongation factor proteins were redox-sensitive inA. thaliana
(Wang et al., 2011), while the Tu elongation factor was induced by
stress treatments inE. coli(Leichert et al., 2008).
Signals from other phosphorylated proteins identified at reduced
constitutive levels in MHR4 plants include a putative polyprotein, poly
(ADP-ribose) polymerase, a NAD(P)-binding domain containing pro-
tein, and aminomethyltransferase (spots 15, 22–24) (Fig. 1,Table 1). Of
these,the putativeaminomethyltransferaseis of interest since this en-
zyme was also identified at lower levels in salt-stressedBeta vulgaris
(Wakeel et al., 2011) and was phosphorylated in response to pathogen
attack inA. thaliana(Jones et al., 2006).
These overal reductions in phosphorylation and redox signals from
core celular proteins in MHR4 plants may represent an energetic tra-
deoffas predicted by the resource-based alocation theory (Coley et al.,
Table 1(continued)
Function Spot no. Uniprot no. Oryza sativano. Annotation FCa P-value Peptidesb Peptide sequences
Signaling 1 Q7EYF8 Os07g0145400 Protein kinase 2.1 0.03 2 GGLVVSADELGAPR
RGPPLTWAQRLKIAVDVARGLNY
4 Q7FAZ2 Os04g0202300 Lectin S-receptor-like serine/
threonine protein kinase LecRK2
2.2 0.05 2 DPSGNEVWNPRVTDVGYARMLDTGNFR
SPSMISSGSSKWKKDKKYWILGSSLFFGSSVLVN
9 Q6ZF83 Os01g0889900 Serine/threonine protein kinase 2.8 0.07 2 TTGVSQRLVPWRNNANPSPGLFSLELD
ALILAIVLFIVFQKCRRDRTLR
12 Q6H7I7 Os02g0634700 Serine carboxypeptidase I 2.7 0.05 2 FPQYKSHDFYIAGESYAGHYVPQLSEK
NWTHCSDVIGKWRDAPFSTLPIRKLVAGGI
aFold change; positive and negative FC values indicate elevated and reduced levels, respectively, in MHR4 as compared to HS1Avena fatuaplants.
bNumber of uniquely matched peptides.
Fig. 2.Representative two dimensional electrophoresis gel of the
multiple herbicide resistant (MHR4) Avena fatuaredox proteome.
Significantly differential (between MHR and herbicide susceptible
(HS1) plants) protein spots were numbered, excised from gels, and
identified by LC MS/MS. Spot numbers are the same as inTable 2.
Table 2
Differentialy expressed redox sensitive proteins from untreated herbicide susceptible (HS1) and multiple herbicide resistant (MHR4)Avena fatuaplants identified using two dimensional
polyacrylamide gel electrophoresis.
Function Spot no. Uniprot no. Oryza sativano. Annotation FCa P-value Peptidesb Peptide sequence
Core celular processes 31 Q40680 Os07g0614500 Elongation factor 1-delta 1 1.4 0.10 2 NVKMEGLLWGASK
AAEERAAAVKASGK
39 B0FFP0 Os07g0141400 23 kDa polypeptide of photosystem I 1.5 0.08 2 AANVFGKPKTNTEF
HQLITATVNDGKLYICKAQAGD
40 I1IB68 Os02g0595700 Chloroplast translational elongation
factor Tu
−1.4 0.00 6 GITINTATVEYETETR
NATVTGVEMFQK
TMDDAIAGDNVGLLLR
TTDVTGNVTNIMNDKDEEAK
VGDPVDLVGIR
VGDPVDLVGIRETR
41 Q84PB4 Os08g0560900 Photosystem I reaction center subunit
I
−2.3 0.06 3 EQVFEMPTGGAAIMR
FTGKNTFDV
ARKEQCLALGTRLRSKYKINYQ
45 Q6H443 Os09g0279500 Plastid-specific 30S ribosomal protein
2
−2.1 0.10 2 SRLTVGAARWWARRRQPAVVVR
AARKLYVGNIPRTVT
47 B1NEV4 Os02g0534800 40S ribosomal protein S14 −3.0 0.10 4 KRGKVQKEEVQ
HIFASFNDTFVHVTDLS
MLAAQDVAEKCKSLGI
RATGGNKTKTPGPGAQSALRA
Xenobiotic and stress
response
28 I1IUI3 Os11g0145200 Anthocyanin 5-O-glucosyltransferase 5.2 0.07 2 DFPTFLVDTTGSDIASSVNEALR
VLAAYYHFFHDDGGHYK
29 Q10A56 Os10g0140200 Glycoside hydrolase 1.3 0.10 4 GVGEPLNEVVCVDQKCDGLVAR
AEQAFFQRWWAEKSPKIQAIV
RNMDRLINYVNKDGRVHALYSTP
EVEYTIGPIPVDDDDDIGK
32 Q0JG98 Os01g0934900 Esterase PIR7A, putative
carboxylesterase
1.5 0.05 3 FPDKVAAAVFLAACMPAAGK
AAAGAHPARADEVGSLEE
EGNYGSVKRVFLVAMDDASSDE
34 Q8LMC7 Os07g0267400 Ulp1 protease 1.6 0.08 3 RFHFPCAKQDQR
YNTEFHWVLLFFD
YSTLSKTPCLYGSTPRSTKA
37 Q2QS17 Os12g0443000 Cytochrome P450 family protein 1.4 0.05 3 AFTDVLGDLLGGGIFNADGERWFAQRK
QLLAAARGRDDLVSRM
RMEAIWGADAGEFRPGRWLAAAA
ROS and redox
maintenance
26 I1HB66 Os01g0107900 DUF3506 domain containing protein 2.7 0.10 2 GNEDTEEKTQDVGNTK
VKLFISGVVHNKEDMAGAKS
30 Q942J6 Os07g0119400 Putative L-ascorbate oxidase 1.3 0.04 2 AEDPYHFFDWK
TRTIMDVAQKVMLINDMFPGPTI
33 Q5U1J1 Os07g0499500 Peroxidase 7 1.5 0.05 2 LFFHDFAVQGIDASVLVDSPGSERYAK
YWPLMYGRKDGRRSSMVDA
35 Q8W3D0 Os10g0100700 Putative pyridoxal 5′-phosphate
synthase subunit PDX1.2
2.4 0.08 2 AIVQAVTHYSDPK
EVSSGLGEAMVGINLSD
36 B7ERQ1 Os07g0638300 1-Cys peroxiredoxin 1.5 0.07 2 QLNMVDPDEK
KLLGISCDDVQSHKDWIKDIEAYKP
38 Q6EQV9 Os02g0320800 Iron/ascorbate-dependent
oxidoreductase
2.2 0.10 2 DVLRAMARIAGLDDDDQHFVDQLG
RFNYYPPCPRPDLVMGIKPHSDG
Chaperones and heat
shock
25 C6F1N7 Os03g0804800 CCt8 protein like 1.9 0.10 2 TSLGPNGMNKMVINHLDK
YAIAKFAESFEMVPRTLAENAGLSAMEV
42 Q9LWT6 Os06g0114000 60 kDa chaperonin −2.3 0.04 3 EVELEDPVENIGAK
IVNDGVTVAREVELEDPVENIGAK
LAGGVAVIQVGAQTETELKEK
43 Q6ZFJ9 Os02g0102900 60 kDa chaperonin beta −1.2 0.10 2 EVELEDPVENIGAK
LAGGVAVIQVGAQTETELKEK
44 Q9LGR0 Os01g0184900 FACT complex subunit SSRP1-A −1.6 0.01 2 TDGHLFNNILLGGRAGSNPGQFK
SPTDDSGGEDSDASESGGEKEKLSKKEA
Signaling 27 Q67WN0 Os06g0644466 L-zip + NBS + LRR-like protein 1.3 0.10 3 SNFIEDSSMAEDK
IGSSNLALIALKINDSGSSSDIV
WKSIPHLELLNITELTIDKCVDSCPVPK
46 Q69Q47 Os06g0606000 CBL-interacting serine/threonine-
protein kinase 24
−1.4 0.10 2 YFQQLIDAINYCHSKGVYHR
SPFAVVLQVFEVAPSLFMVDVR
aFold change; positive and negative FC values indicate elevated and reduced levels, respectively, in MHR4 as compared to HS1Avena fatuaplants.
bNumber of uniquely matched peptides.
1985). Briefly, heritable resistance to an environmental stress or SAA
may require the realocation of carbon away from core processes to
stress-related pathways, resulting in a new homeostasis (Kosová et al.,
2011). More specificaly, PTMs are often employed to modulate enzyme
activities under stress conditions because they confer immediate and
selective changes (Holcik and Sonenberg, 2005). The physiological re-
sult of these changes can be manifested infitness costs and a resulting
ecological disadvantage (Bazzaz et al., 1987), both of which are
documented for SAR (Bergelson and Purrington, 1996), SAA (Zhen
et al., 2011), and herbicide resistance (Vila-Aiub et al., 2009). ForA.
fatua, our previous greenhouse experiments showing that MHR plants
produced fewer tilers and seeds than HS plants (Lehnhoffet al., 2013)
are consistent with the idea that reduced activities of core celular
processes can be reflected in plant growth reductions.
3.2. Xenobiotic and stress response
Signals offive redox-sensitive proteins, anthocyanin 5-O-glucosyl-
transferase, cytochrome P450 monooxygenase, carboxylesterase, Ulp1
protease, and glycoside hydrolase (spots 28, 37, 32, 34, and 29, re-
spectively,Fig. 2), were constitutively elevated in MHR4 as compared
to HS1 plants (Table 2). The large family of plant glycosyltransferases
has roles in Phase I herbicide metabolism (Yuan et al., 2007) as wel as
conferring tolerance to abiotic stresses like salt, cold, and drought by
modifying anthocyanin accumulation (Li et al., 2017). We recently re-
ported on a closely related anthocyanidin 3-O-glucosyltransferase dif-
ferentialy expressed gene (DEG) as one of four glucosyltransferase
DEGs constitutively elevated in MHR4 plants, and differential expres-
sion of three of these co-segregated withflucarbazone-sodium herbicide
resistance in F3families (Keith et al., 2017). Similarly, P450s are wel-
known participants in Phase I xenobiotic and herbicide metabolism
(Yuan et al., 2007). Our transcriptome study (Keith et al., 2017) iden-
tified two P450s elevated in MHR4 plants, and differential expression
levels of one co-segregated with herbicide resistance in F3families.
Higher constitutive levels of an oxidized carboxylesterase in MHR4
plants may be related to differential de-esterification of pro-herbicides
like fenoxaprop-P-ethyl and imazamethabenz-methyl to their respective
toxic carboxylic acids (Cummins et al., 2001). Elevated levels of Ulp1
proteases, regulators of protein sumoylation (Novatchkova et al., 2004)
are documented after plant pathogen attack (Hanania et al., 1999) and
in abiotic stress response (Kurepa et al., 2003). Andfinaly, glycoside
hydrolases, enzymes with functions in polysaccharide metabolism, are
involved in plant defense against pathogens (Minic, 2008).
3.3. ROS detoxification and redox maintenance
Abiotic stresses including herbicides cause rapid ROS generation
and thus disrupt redox homeostasis (Dayan and Watson, 2011;
Demidchik, 2015; Dietz, 2014). Given this relationship, MHR4 plants
should exhibit enhanced capacity for ROS management, given that they
are resistant to known ROS-producing herbicides and families like
paraquat (Dodge, 1971), difenzoquat (Kovacic and Somanathan, 2014),
ALS inhibitors (Zulet et al., 2015), and ACCase inhibitors (Luo et al.,
2004). In this regard, two phosphorylated peroxiredoxins (spots 2 and
11,Fig. 1), thioredoxin-dependent peroxidases that reduce H202and
organic peroxides, were constitutively elevated in MHR4 plants
(Table 1). Increased levels of these enzymes should improve the capa-
city for ROS degradation (Muthuramalingam et al., 2009) in MHR
plants. Similarly, redox-sensitive spots 33 and 36 (Fig. 2), annotated as
a peroxidase and 1-Cys peroxiredoxin, respectively, were constitutively
elevated in MHR4 plants (Table 2). Both enzymes were elevated inA.
thalianafolowing H202treatment (Wang et al., 2011). We also iden-
tified a peroxiredoxin DEG that was constitutively elevated in MHR
plants in our transcriptome study (Keith et al., 2017).
Nearly half of the redox-sensitive proteins identified in this study
have roles in redox maintenance, with the majority of them elevated in
MHR4 plants (Table 2). Two proteins, L-ascorbate oxidase and iron/
ascorbate-dependent oxidoreductase (spots 30 and 38,Fig. 2) are in-
volved in ascorbate metabolism, and thus play a significant role in
defense against oxidative stress (Smirnoff, 2000). We recently demon-
strated that the specific activity of dehydroascorbate reductase, a key
enzyme of the glutathione-ascorbate ROS protective pathway (Asada,
2006), was 1.4-fold higher in MHR4 versus HS1 plants (Burns et al.,
2017). Together, these results indicate that ascorbic acid-mediated ROS
activity is constitutively elevated in MHR plants, with the potential to
ameliorate the damaging oxidative effects of herbicides.
Signals of two redox-sensitive proteins with roles in singlet oxygen
metabolism were constitutively elevated in MHR4 plants (Table 2). Spot
26 (Fig. 2), annotated as a DUF3506 domain-containing protein, shares
strong similarity with the EX1 and EX2 proteins fromA. thalianapro-
teins that detoxify light-stress generated singlet oxygen (Wagner et al.,
2004). Spot 35 (Fig. 2) was annotated as pyridoxal 5′-phosphate syn-
thase subunit PDX1.2, an enzyme of vitamin B6 biosynthesis that in-
directly contributes to ROS tolerance (Titiz et al., 2006).
To investigate the potential role of superoxide dismutase (SOD) in
ROS metabolism (Gil et al., 2015) potentialy related to NTSR, we
compared constitutive enzyme activities and protein levels in MHR and
HS plants. SOD enzyme activities as determined in native gels showed
one major band and diffuse minor bands of activity, with no detectable
differences between HS and MHR plants (Fig. 3a). Polyclonal antibodies
against chloroplastic and cytosolic CuZn SODs (Kanematsu and Asada,
1990) were subsequently used in immunoblots to compare levels of
Fig. 3.(a) Superoxide dismutase activity native gel of extracts from untreated herbicide
susceptible (HS1 and HS2) and multiple herbicide resistant (MHR3 and MHR4)Avena
fatuaplants. (b) 1D immunoblot of proteins from untreated herbicide susceptible (HS1
and HS2) and multiple herbicide resistant (MHR3 and MHR4)Avena fatuaplants re-
cognized by anti-chloroplastic CuZn superoxide dismutase antibodies. (c) 1D immunoblot
of proteins from untreated herbicide susceptible (HS1 and HS2) and multiple herbicide
resistant (MHR3 and MHR4)Avena fatuaplants recognized by anti-cytosolic CuZn su-
peroxide dismutase antibodies.
immunoreactive proteins in MHR and HS plants (Fig. 3b-c). These an-
tibodies have been successfuly used to identify cytosolic and chlor-
oplastic CuZn SODs inS. oleracea,O. sativa, andEquisetum arvense
(Kanematsu and Asada, 1990). Both antibodies recognized two proteins
of approximately 16 and 18 kDa in extracts fromA. fatuaplants
(Fig. 3b-c), and densitometric scans confirmed that constitutive protein
amounts were not different among plants (data not shown). This lack of
difference in chloroplastic and cytosolic CuZn SOD enzyme activities
and amounts between MHR and HS plants may indicate that other SODs
or ROS management pathways like the ascorbate-related changes noted
above are sufficient to prevent or ameliorate herbicide-induced ROS
damage. In this regard, we previously identified a chloroplastic Fe SOD
DEG at constitutively elevated levels in MHR4 as compared to HS1
plants (Keith et al., 2017).
3.4. Chaperones and heat shock proteins
Six protein spots were annotated with chaperone activity:five
phosphorylated heat shock proteins including Hsp60 (spots 5, 8, 10,
and 13;Fig. 1) and Hsp70 (spot 3;Fig. 1), and a single redox-sensitive
protein annotated as a CCt8 protein (spot 25;Fig. 2). Signals from al
proteins were constitutively elevated in MHR4 plants (Tables 1 and 2).
Hsps have wel-known roles as molecular chaperones that prevent
protein misfolding, regulation of transcription factors (TFs) for a di-
verse set of genes (Morimoto, 2002), and are themselves regulated by
phosphorylation (Muler et al., 2013). Higher constitutive amounts or
phosphorylation status of Hsps in MHR plants may alow them to better
protect key proteins during herbicide-mediated stress. Although in-
formation about phosphorylated Hsps in plants is sparse, phosphory-
lated Hsps were shown to protect against oxidative stress in humans
(Kalmar and Greensmith, 2009) andTrichinela spiralis(Martinez et al.,
2002).
In contrast to the above proteins, signals from two redox-sensitive
Hsp60 proteins (spots 42 and 43;Fig. 2) and a FACT complex subunit
SSRP1-A (spot 44;Fig. 2) were constitutively reduced in MHR4 plants
(Table 2). FACT complexes act as histone chaperones during tran-
scription elongation and were reduced by salt stress in rice (Pandit
et al., 2011).
3.5. Signaling
Signals fromfive proteins involved in cel signaling were con-
stitutively elevated in MHR4 plants (Tables 1 and 2), including phos-
phorylated serine carboxypeptidase I (spot 12;Fig. 1), redox-sensitive
nucleotide-binding site leucine-rich repeat (NBS-LRR) protein (spot 27;
Fig. 2), and three phosphorylated protein kinases (spots 1, 4, and 9;
Fig. 1). Inadditionto their roles in storage protein turnover, serine
carboxypeptidases can be involved in brassinosteroid and receptor-like
kinase signaling (Zhou and Li, 2005). NBS-LRR proteins constitute the
majority of disease resistance genes in plants, confer resistance to a
diverse array of pathogens (Marone et al., 2013), provide enhanced
drought and salt tolerance (Xinlong et al., 2016), and play key roles in
plant defense responses (Belkhadir et al., 2004). Our transcriptome
study similarly identified an NBS-LRR DEG that was constitutively
elevated in MHR4 plants and its differential expression co-segregated
with herbicide resistance in F3families (Keith et al., 2017). In contrast,
a redox-sensitive CBL-interacting serine/threonine-protein kinase (spot
46;Fig. 2) was constitutively reduced in MHR4 plants (Table 2). TheO.
sativaortholog of this kinase was shown to phosphorylate and thus
activate a plasma membrane Na+/H+ antiporter involved in salt tol-
erance (Martínez-Atienza et al., 2007).
Phosphorylated spots 1, 4, and 9 (Fig. 1), annotated as protein ki-
nases, were constitutively elevated in MHR4 plants (Table 1). Specifi-
caly spot 4 was annotated as the lectin S-receptor-like serine/threo-
nine-protein kinase LecRK2, a wel-characterized receptor in SAR and
PTI (Boler and Felix, 2009). PTI is initiated by perception of microbial,
pathogen, or damage-associated patterns by cel surface-localized re-
ceptor-like proteins or RLKs, some of which possess an extracelular
lectin motif (LecRKs) and an intracelular kinase domain (Singh and
Zimmerli, 2013). In general, the linkage between RLK ligand perception
and signaling initiation/specificity is tightly regulated by the state of
RLK phosphorylation (Macho and Zipfel, 2014), and the activities of
certain LecRKs are enhanced by phosphorylation (Nishiguchi et al.,
2002; Vaid et al., 2016).
PTI and SAA can be‘primed’by initial plant exposure to pathogens,
abiotic stress, or disparate chemicals (Pastor et al., 2013), and primed
plants exhibit enhanced and durable resistance to pathogens and sub-
sequent abiotic stresses (Savvides et al., 2016; Zimmerli et al., 2008).
Priming is thought to involve the accumulation of inactive protein ki-
nases, TFs, or other defense signaling components, that are rapidly
activated upon stress (Pastor et al., 2014). For example, MAPK3 and
MAPK6 inA. thalianawere strongly activated in plants primed by ex-
posure to biotic and abiotic stresses (Beckers et al., 2009). LecRK2 and
two additional LecRK genes were shown to confer broad-spectrum and
durable resistance against insects pests in rice (Liu et al., 2015). In
MHR4A. fatua, the elevation and/or differential phosphorylation of
LecRK2 and two other protein kinases confirm that MHR4 plants exhibit
constitutive changes in known SAR- and SAA-related proteins. If in fact
these changes are associated with‘priming’the MHR4 phenotype,
LecRK2 may be binding to the herbicide itself or features induced by
herbicide entry. Similar activation has been documented in response to
diverse compounds like salt (Deng et al., 2009), alyl-isothiocyanate
(Kissen et al., 2016), and extracelular ATP (Cao et al., 2014) for related
L-type LecRKs.
4. Conclusion
This work seeks to better understand the molecular mechanisms of
NTSR in MHRA. fatuaby surveying differential signals from phos-
phorylated and redox-sensitive proteins. Our results demonstrate that
PTMs of a number of proteins with functions in core celular processes,
xenobiotic and stress response, ROS detoxification and redox main-
tenance, chaperones/heat shock response, and intracelular signaling
are constitutively altered in MHR4 as compared to HS1 plants. Clearly,
additional work wil be required before causal relationships can be
assigned between these proteins and NTSR. Using a candidate gene
approach, individual proteins are being pursued biochemicaly, and the
rudimentary mappingpopulations wehavedeveloped (Burns et al., in
press) provide the basis for additional genetic or QTL-based strategies,
with the aid of the recently publishedAvena sativalinkage map (Chaffin
et al., 2016).
Regardless of their potential roles in NTSR, the protein functions
described here are shared with plant biotic (SAR) and abiotic (SAA)
stress response pathways. For example, elevated stress responses, en-
hanced ROS detoxification, alterations in protein kinases, andfitness
penalties (as a result of implied reduced biosynthetic activities) are wel
documented in SAR and SAA. The MHRA. fatuaPTMs related to ROS
detoxification, LecRK2, and other protein kinases are especialy re-
levant, since these features play fundamental roles in the cross-talk
between plant biotic and abiotic stress responses (Atkinson and Urwin,
2012; Rejeb et al., 2014). More specificaly, MAP kinase cascades de-
scribed for SAA and SAR are known to translate ROS signals into PTMs
like protein phosphorylation and oxidation, resulting in signal trans-
duction modulations needed for stress perception and response (Dietz
et al., 2016; Kosová et al., 2011; Waszczak et al., 2015). The specific
protein PTMs reported here for MHRA. fatuaare fuly consistent with
this model.
Priming of PTI can require multiple, consecutive exposures to
modest stresses (Boler and Felix, 2009), as has been noted for the
evolution of NTSR (Délye et al., 2013; Neve and Powles, 2005). For
MHRA. fatua, more than 35 years of annual herbicide applications were
required before this phenotype was detected (Keith et al., 2015).
Different herbicide modes of action were applied consecutively but
rarely in mixtures in thefields where MHRA. fatuaevolved (Keith
et al., 2015), demonstrating that the longstanding resistance-prevention
recommendation of rotating herbicides (Shaner, 2014) was ineffective
under these conditions. The similarities between herbicide resistance
and acclimation (Vila-Aiub and Ghersa, 2005) or SAR (Molina et al.,
1999) have received some attention (Délye et al., 2013; Dubey et al.,
2016; Perez and Brown, 2014), although specific evidence connecting
the two is scant. We suggest that the constitutive changes documented
here further support the idea (Alberto et al., 2016) that herbicide stress
is perceived by plants in the same fashion as other abiotic stresses, and
that NTSR shares a number of similar features with SAR and SAA.
Further, we speculate that MHRA. fatua’s previous exposure to sub-
lethal herbicide doses, as wel as earlier evolution under a diversity of
abiotic and biotic stressors has led to a heightened state of stress pre-
paredness that includes NTSR to a number of dissimilar herbicides.
Further investigations into the evolution of these related responses
through the lens of phenotypic convergence (Baucom, 2016; Losos,
2011) may yield valuable insights into the commonalities among plant
responses to selection by biotic, abiotic, and herbicide stressors.
Acknowledgements
Polyclonal antisera to the spinach chloroplastic and cytosolic CuZn
SODs (Kanematsu and Asada, 1990) were graciously provided by Dr.
Sumio Kanematsu, Minami-Kyushu University, Japan.
The excelent technical assistance of Tara Donohoe, Alex Griffin,
and Katie Steward is much appreciated. This work was partialy sup-
ported by USDA-NIFA-AFRI grants 2012-67013-19467 and 2016-
67013-24888, US EPA Strategic Agricultural Initiative grant X8-
97873401-0, Bayer CropScience, the Montana Noxious Weed Trust
Fund, the Montana Wheat and Barley Committee, and the Montana
Agricultural Experiment Station. The proteomics, metabolomics, and
mass spectrometry facility at MSU receives support from the Murdock
Charitable Trust and Montana INBRE under Award Number
P20GM103474 from the National Institutes of Health (NIGMS).
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