Resistance to acetyl-CoA carboxylase-inhibiting herbicides

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Resistance to acetyl-CoA carboxylase inhibiting herbicides Shiv S Kaundun

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Abstract

Resistance to acetyl-CoA carboxylase herbicides is documented in at least 43 grass weeds

and is particularly problematic in Lolium, Alopecurus and Avena species. Genetic studies

have shown that resistance generally evolves independently and can be conferred by target

site mutations at ACCase codon positions 1781, 1999, 2027, 2041, 2078, 2088 and 2096. The

level of resistance depends on herbicides, recommended field rates, weed species, plant

growth stages, specific amino acid changes and the number of gene copies and mutant

ACCase alleles. Non-target site or in essence metabolic resistance is prevalent, multi-genic

and favoured under low-dose selection. Metabolic resistance can be specific but also broad,

affecting other modes of action. Some target site and metabolic resistant biotypes are

characterised by a fitness penalty. However, the significance on resistance regression in the

absence of ACCase herbicides is yet to be determined over a practical time frame. More

recently, a fitness benefit has been reported in some populations containing the I1781L

mutation, in terms of vegetative and reproductive outputs and delayed germination. Several

DNA-based methods have been developed to detect known ACCase resistance mutations

unlike metabolic resistance as the genes remain elusive to date. Therefore, confirmation of

resistance is still carried out via whole plant herbicide bioassays. A growing number of

monocotyledonous crops have been engineered to resist ACCase herbicides, thus increasing

the options for grass weed control. Whilst the science of ACCase herbicide resistance has

progressed significantly over the past 10 years, several avenues provided in the present

review remain to be explored for a better understanding of resistance to this important mode

of action.

Key words: Acetyl-CoA carboxylase, ACCase, resistance mechanism, fitness, resistance

detection, resistant crops


1. Introduction

Weeds compete with crops for light, water and soil nutrients. They are by far the most

challenging pests in agricultural production systems1. If uncontrolled, ensuing average yield

losses are estimated at 35% for six major crops worldwide2. The advent of herbicides has

contributed significantly in protecting crop yields and increasing farmers’ profitability3. One

such single-site herbicide mode of action introduced in the mid-1970s consists of inhibitors

of acetyl-CoA carboxylase (ACCase)4. ACCase herbicides are mainly used for grass weed

control in dicotyledonous crops with a few compounds applied in small-grain cereal crops

and rice5. Given their convenience for managing grass weeds post-emergence, ACCase

herbicides were quickly adopted as they also represented a marked improvement over the

then commonly used method of selective grass weed control. Current overall annual sales

exceed one billion USD and account for 5% of all commercial herbicides6. Over time,

however, extensive and recurrent use of ACCase herbicides has selected for resistance in key

grass weed species encompassing 20 genera7. Resistance is reported in 33 countries,

especially in areas with intensive use of ACCase herbicides often applied as the sole method

for grass weed control. Two comprehensive reviews on the mechanisms and evolutionary

dynamics of resistance to ACCase resistance have been carried out in 19948 and 20059. The

present analysis will therefore summarise the current understanding of resistance with

emphasis on studies conducted over the last eight years.

2. ACCase target and herbicides

Acetyl-CoA carboxylase (EC 6.4.1.2) is a ubiquitous, biotin dependent enzyme that catalyses

the carboxylation of acetyl-CoA into malonyl-CoA using ATP as a source of energy and

bicarbonate as a source of carbon10, 11. Catalysis is conducted in two steps: carboxylation of

the biotin co-factor followed by the transfer of the carboxyl group onto acetyl-CoA using the


transcarboxylase activity of the enzyme. Biotin must visit both the biotin carboxylase and the

carboxyltransferase sites and as such, a swinging arm model has been proposed to represent

this translocation12. Malonyl-CoA is required for de novo fatty acid synthesis in the plastid

and for elongation of very long chain fatty acid and secondary plant metabolites such as

flavonoids and suberins in the cytoplasm13.

Plants have two different ACCases, namely, cytoplasmic and plastidic14. Both isoforms

consist of three major functional domains: biotin carboxyl-carrier (BCC), biotin carboxylase

(BC) and carboxyl transferase (CT) which is further subdivided into α and β subunits15. In

grasses of the Poaceae family, plastidic ACCase is homomeric with BCC, BC and CT located

on a single polypeptide16. In contrast, the domains are encoded by different genes that are co-

ordinately expressed to form a functional heteromeric enzyme in most other plant species17.

Exceptions to this dichotomy include some members of the Geraniaceae family which have a

homomeric plastidic ACCase characteristic of grasses, and some Brassica and Arabidopsis

species that contain both a homomeric and heteromeric ACCase in their chloroplasts10, 17, 18.

Active cytoplasmic and chloroplastic ACCases from grass weeds function as a homodimer as

suggested by initial biochemical studies and confirmed recently by crystallography19, 20. The

dimer is made up of two head to tail monomers generating two active sites.

ACCase herbicides inhibit de novo fatty acid synthesis in sensitive grass weeds leading to

rapid necrosis and plant death21. The compounds can be divided into three classes, namely,

aryloxyphenoxypropionates (FOPs), cyclohexanediones (DIMs) and phenylpyrazolin (DEN),

based on their chemical structures22. Currently ten FOPS, nine DIMs and one DEN herbicides

are commercially available both for controlling grass weeds and volunteer crops. The latest

and leading ACCase herbicide is pinoxaden introduced in 2006 for selective grass weed

control in wheat, barley and triticale23. Fenoxaprop-P-ethyl, launched some 30 years ago,

remains an important product for use in small-grain cereal crops, rice and soybean24.


FOP and DIM herbicides have long been suspected to affect lipid synthesis in plants25.

Convincing proof of disruption of plastidic ACCase activity was generated by pioneering

work on isolated chloroplasts from corn26 and barley27. Subsequent kinetic studies indicated

that FOP and DIM herbicides showed nearly competitive inhibition with respect to the acetyl-

CoA substrate28, 29. Additionally, FOP and DIM herbicides were suggested to have

overlapping sites at the CT domain as they were mutually exclusive. Recently, the precise

binding of haloxyfop, tepraloxydim and pinoxaden was determined using yeast CT domain as

a surrogate30-32. Haloxyfop and tepraloxydim were attached to the active site, particularly at

the interface of the dimer. The DIM and FOP herbicides shared two main anchoring points

but overall probed distinct regions of the dimer interface. Pinoxaden and tepraloxydim were

bound at a very similar location in spite of their very different chemical structures30, 31.

Contrary to tepraloxydim and especially pinoxaden, haloxyfop binding required large

conformational changes32. More precisely, movement of the side chains of tyrosine 1738 and

phenylalanine 1956 is necessary to generate a large hydrophobic pocket for the pyridinyl ring

of haloxyfop to sit in.

Whilst most grass weeds are controlled with ACCase herbicides, some Vulpia, Poa and

Festuca species are inherently tolerant due to an insensitive ACCase resulting from a fixed

leucine residue at codon position 1781 (A. myosuroides equivalent: as is conventional for

weed ACCases) as confirmed for the last two species33-35. Selectivity in monocotyledonous

crops is in most cases provided by the use of safeners allowing faster and higher levels of

herbicide detoxification in the crop versus the target weeds36. Broadleaved species on the

other hand are innately less sensitive due to major differences in plastidic isoforms between

grass and dicotyledonous species37. A more comprehensive review on the ACCase target and

herbicides can be found in several earlier publications10, 12, 16, 17, 22.


3. Occurrence, evolution and spread of resistance

The first case of resistance to ACCase herbicides was reported in 1982 in a Lolium rigidum

population from an Australian wheat field38. The number of resistance cases both in terms of

species and acreages has increased steadily over the last 30 years7. Resistance is particularly

widespread in L. rigidum throughout the Australian wheat belt, in practically every single

cereal farm infested with A. myosuroides in the UK39 and in A. fatua in large areas in Western

Canada40. Other affected grass weed populations described recently include Phalaris minor

from India41, Greece42 and Iran43, Phalaris paradoxa from Italy44 and Israel45, Sorghum

halepense from Greece46 and USA47, Brachiaria plantaginea from Brazil48, Digitaria

sanguinalis from France49, Apera spica-venti from Central and Eastern Europe50, Alopecurus

japonicus51 and Beckmannia syzigachne52 from China along with many other species from

various regions as summarised on the International Survey of Herbicide Resistant Weeds

website7. The areas concerned remain nevertheless an under-representation of the real status

of resistance to ACCase herbicides as there are some weed species and populations such as

Lolium spp., Sclerochloa kengiana and Fimbristilis miliacea from North Africa, China and

Vietnam respectively which are not documented but are highly suspected to be affected by

resistance.

It is noteworthy that where comprehensive surveys have been carried out repeatedly within

the same agricultural zones, a significant escalation of resistance was observed in a relatively

short period of time. This is exemplified by an increase of 15 and 28 percentage points in

resistance in wild oats and rye grass in Western Canada (41%) and Australia (96%)

respectively40, 53. Overall, resistance tends to be widespread with regard to the ACCase

herbicides used earlier, progressively increasing to the ones introduced more recently44, 54-56.

For instance, resistance to clethodim, the most effective ACCase herbicide 57, has risen from

0.5% to 8% and 65% in three different random L. rigidum surveys carried out in Western


Australia in 1998, 2003 and 2010 respectively53, 58, 59. Similar trends are observed for

tepraloxydim which is increasingly being used to control some resistant black-grass

populations in the UK39. Equally, where ACCase herbicides have not been used extensively,

as is the case with the European A. spica-venti, resistance has been recorded in only 2% of a

total of 250 fields tested50. Interestingly, submitted to very similar selection pressures in

Australia, very high and lower levels of resistance to clodinafop-propargyl, pinoxaden and

sethoxydim are observed in L. rigidum and A. fatua respectively, thus reflecting differences

in the species’ abilities for evolving resistance to ACCase herbicides59, 60.

With a view to further investigate the mode of evolution of resistance to ACCase herbicides,

Cavan et al (1998) used anonymous simple sequence repeat (SSR) markers to examine the

genetic profiles of four different A. myosuroides patches that had survived a herbicide

application within a small agricultural field61. The genotypes were markedly diverse among

the four sites allowing for the conclusion of localised evolution of resistance, even within

short distances. Similar inferences could be made from several black-grass studies at the

local, country and regional levels based on signature ACCase sequences62 and known target

site resistance mutations63-66. Overall, the different studies have shown that there is enough

standing genetic variation within the grass populations for resistance to evolve

independently62, 63, 65-67. However, once resistance has reached a certain level, it can spread

very quickly within a field upon continuous ACCase herbicide selection pressure 68 or even

adjacent sites as demonstrated in two studies on black-grass and rye grass from France and

Australia69, 70. In the latter case, resistance to ACCase herbicides in a neighbouring organic

farm was as high as 2% while being at 21% in an adjacent conventional field69. Resistance

spreading via pollen is faster for allogamous as compared to autogamous species as

represented by A. myosuroides and A. fatua respectively71, 72. A less frequent form of

resistance spread but still worth underlining is via seed import from regions with high


infestation of resistant grass weeds. For instance, analysis of a 20 kg batch of Australian

wheat exported to Japan in 2006 identified as many as 4673 L. rigidum seeds, 35% of which

were resistant to diclofop-methyl73.

Importantly, once resistance to ACCase herbicides has been established, it is difficult to

overcome even with the use of other herbicide modes of action and alternative methods of

weed control combined. A black-grass study conducted over a six-year period has shown that

while different cropping systems and other herbicide modes of action can result in an overall

decline of the weed seed bank, the frequency of ACCase resistant individuals within the field

did not decrease over this time frame74. Similar observations were made in a wheat field from

South-Eastern Italy infested with Lolium multiflorum resistant to ACCase herbicides75.

4. Mechanism of resistance

The knowledge of resistance mechanisms is important for the design of effective weed

control strategies to manage and delay the onset of resistance to ACCase herbicides.

Understandably, an overwhelming number of studies have been conducted on the most

problematic Lolium, Alopecurus and Avena species. Nonetheless, some minor species such as

Phalaris spp.44, 76, Eleusine indica77, B. syzigachne52 and Rottboellia cochinchinensis78 to

name but a few, have also been investigated recently. As with all other herbicide modes of

action, resistance to ACCase herbicides can be divided into target and non-target based

mechanisms.

4.1 Target site resistance

Target site resistance is essentially caused by single amino acid changes in the

carboxyltransferase domain impacting on the effective binding of ACCase herbicides57, 79. It

is therefore not surprising that some earlier studies have shown that target site resistance is

more or less inherited as a monogenic trait68, 80-82. Two exceptions to this rule are three-fold


increases in ACCase-specific activity in two resistant S. halepense and Leptochloa chinensis

populations from the USA and Thailand respectively83, 84. These exceptions could be

dismissed on the basis of intrinsic differences between sensitive and resistant populations

being compared. In fact, the involvement of a resistant ACCase was suggested in a L.

multiflorum population more than 20 years ago85. However, it was not until the early 2000s

before a first potential target site resistance mutation was uncovered in a Setaria viridis86 and

a L. rigidum87 population. At the last major review on ACCase herbicides, five different

resistance codons were described mainly in A. myosuroides and classified into two main

categories: FOP-specific (2027, 2041 and 2096) and FOP/DIM (1781 and 2078)9. The

discovery was facilitated by the relatively conserved nature of ACCase in A. myosuroides88, 89

compared to species such as Lolium spp. in which several other amino acid changes not

implicated in resistance are often present alongside the resistance mutations90-94.

Over the last eight years, around 30 different mechanism studies involving a dozen weed

species have also identified target site resistance to at least one ACCase herbicide (see

supplementary table). The precise amino acid changes implicated could often be determined

thanks to the relatively conserved nature of plastidic ACCase and universal PCR

methodologies for analysing the CT binding domain in grasses (Table 1)35. Most studies

detected the same five mutations described earlier in A. myosuroides. Additionally, two other

resistance codons at positions 1999 and 2088 were uncovered, principally in Lolium spp. and

Avena spp.. Fourteen allelic variants have thus far been implicated in resistance, namely,

I1781L/V/A/T, W1999C/L/S, W2027C, I2041N/V, D2078G, C2088R, G2096A/S57, 92, 95-97.

The frequency of the mutations varied according to the weed species and regions examined,

and appeared to be governed by the local herbicide selection pressure applied65. For example,

the I1781L mutation is overwhelmingly present in black-grass in the UK and France whilst

the G2096A is predominant in Germany98. Analysis of a large number of Lolium spp.


populations from the UK and Australia showed a predominance of the D2078G and I2041N

mutations respectively99, 100, potentially reflecting the alternating use of FOPs and DIMs in

small-grain cereal and dicotyledonous break crops in the UK, and a more prolonged FOPs

use in continuous wheat cropping systems in Australia. Importantly, DNA analysis from a

few hundred herbarium black-grass plants pre-dating any synthetic herbicide use revealed the

presence of an I1781L mutation in one of the individuals tested101 thus indicating that some

ACCase mutations are intrinsically more prevalent than initially assumed102.

One of the issues with several resistance mechanism studies is with regard to heterogeneous

weed populations being compared to an unrelated sensitive population to estimate the

resistance indices associated with the different target site mutations. Thus, resistance was in

some cases diluted or overestimated due to the presence of wild and heterozygous mutant

individuals and additional underlying non-target site resistance present in the populations. To

address this problem, a yeast-gene replacement assay was developed allowing comparison of

wild and mutant strains differing only at the single mutated amino acid position being

investigated103-105. In addition to being very quick, this method does not require actual weed

populations for testing. The downside is that some mutations such as the C2088R and

G2096A are not viable with this approach and, as with enzyme assays, translation to whole

plants is not always straightforward especially for mutations that carry a moderate level of

resistance. For instance, Jang et al (2013) estimated slightly higher levels of resistance to

sethoxydim relative to pinoxaden for the W2027C mutation in the yeast-gene replacement

assay103. Conversely, whole plant herbicide and molecular data suggested that the efficacy of

the DEN, but not the DIMs, was affected by the W2027C mutation in black-grass and

Japanese foxtail56, 106, 107. Alternatively, individual plants from the same population and

genetic background could be genotyped for wild type and mutant alleles prior to carrying out

dose responses with a range of herbicides, thus overcoming the issue posed by confounding


effects of target site resistance and non-target site resistance. In this manner, the importance

of mutations at codon positions 1781, 1999, 2078 and 2088 could be more precisely

assessed91, 92, 96, 97.

Contrary to earlier classifications9, numerous recent investigations have clearly shown that

with the exception of the D2078G and C2088R mutations that confer broad resistance to all

herbicides tested76, 77, 91, 97, 106, 108-110, the levels of resistance depend on specific amino acid

changes, the number of resistant alleles, weed species, plant growth stages and recommended

field rates of herbicides. For instance, plants with the I2041N were found to be sensitive to

cycloxydim in A. myosuroides but resistant in P. paradoxa45, 106. Clethodim at the Australian

field rate was found to control L. rigidum plants that were heterozygous for the I1781L

mutation but was mostly ineffective on homozygous LL1781 mutant individuals109. In

contrast, I1781L mutant A. myosuroides and L. multiflorum plants were mostly controlled at

the European field rates106, 108, 111. Similarly, whilst the W1999C mutation impacted highly on

the efficacy of fenoxaprop-P-ethyl, it was found to be sensitive to clodinafop-propargyl and

sethoxydim in Avena sterilis105. Likewise, the W1999S mutation conferred high levels of

resistance to FOP and DEN herbicides, partial resistance to sethoxydim and cycloxydim

whilst being sensitive to clethodim and tepraloxydim92. Variable levels of resistance were

also associated with the I1781T mutation at the heterozygous state96. The 1781 threonine

allelic variant impacted moderately on clodinafop-propargyl and cycloxydim, but was

sensitive to pinoxaden, tepraloxydim and clethodim. It is noteworthy that Hordeum and a few

Bromus species35, 109 which are fixed for the C2088F mutation and also present in some

individual ryegrass and wild oat plants (data not published), are sensitive to all effective

ACCase herbicides. Thus, conclusions on the importance of a novel allelic variant at a known

resistance codon, such as the I1781A95 or W1999L108, 112 or any other position, can only be


established via proper rigorous co-segregation or dose response studies based on wild and

mutant subpopulations sharing the same genetic background.

Interestingly, in hexaploid weed species such as Echinochloa spp. and Avena spp., all three

homeologous ACCase genes were found to be expressed105, 113, 114. Individual plants from a

single Australian A. fatua population could carry one, two or all three of the I1781L, D2078G

and C2088R mutations detected114. The individual mutations endowed relatively lower levels

of resistance in the hexaploid species compared to diploid species. This potential dilution

effect could explain the relatively slower evolution of ACCase resistance in Avena spp.

compared to diploid species53, 60. It could also account for the difference in the levels of

resistance computed for pinoxaden with regard to the I2041N mutation in Avena fatua on the

one side110, and Alopecurus56, Lolium108 and Phalaris45 species on the other side.

Additionally, wheat mutagenesis studies have shown that the level of resistance to ACCase

herbicides depends on the specific A, B or D genome where the mutation is located, further

adding to the complexity of resistance in hexaploid species115.

Yeast ACCase crystal structures in complex with FOP, DIM and DEN herbicides revealed

that out of the seven codons involved in target site resistance, only the 1781, 1999 and 2041

amino acid residues were directly implicated in the binding of the herbicides103. Taking

advantage of the conserved nature of amino acid sequences around the vicinity of the CT

domain binding site, homology models were built for Setaria italica and A. myosuroides with

a view to rationalise the importance of I1781L, W2027C, I2041N and D2078G mutations on

ACCase herbicide efficacy116-120. Molecular docking and molecular dynamic simulations

indicated that the W2027C mutation for example, though remote, caused conformational

changes in the binding site of FOP herbicides117. In particular, significant changes were

associated with phenylalanine 377, tyrosine 161 and tryptophan 346 which are critical for

FOP binding. Consequently, the pi-pi interaction between the herbicides and phenylalanine


377 and tyrosine 161 was decreased accounting for the molecular basis of resistance caused

by the W2027C mutation (figure 1).

4.2 Non-target site resistance

Non-target site resistance (NTSR) is now increasingly recognised as being the predominant

resistance mechanism to ACCase herbicides121. Several recent large scale black-grass surveys

have shown that most resistant individuals did not contain a known target site mutation65, 122.

Similar observations were made in Lolium multiflorum populations from the UK based on

both molecular and glasshouse biological studies 123. Additionally, when investigated in

detail, non-target site resistance to at least one ACCase herbicide is often present in

populations containing target site resistance 92, 96, 124, 125. Also, it has often been assumed that

NTSR confers lower levels of resistance that can sometimes be controlled when plants are

treated at an early growth stage. Over time, however, the build-up of NTSR resistance has

reached very high levels, especially to earlier ACCase herbicides such as diclofop-methyl91,

126. In some cases the level of resistance conferred by NTSR has even surpassed those of the

most common target site mechanisms. In a black-grass population for example, NTSR was

found to be a significantly bigger contributor to resistance to clodinafop-propargyl and

pinoxaden than target site mutations at position 178196.

Non-target site resistance to herbicides encompasses a range of diverse mechanisms

including reduced penetration, impaired translocation, sequestration and enhanced

metabolism of the toxophores79. The suggestion in the 1990s of the ability of some weed

populations to resist ACCase herbicides via membrane repolarisation could not be

substantiated by subsequent experiments127, 128. Similarly, the few anecdotal reports of

resistance caused by reduced ACCase herbicide penetration and sequestration need further

confirmation129, 130. More recently, the involvement of phi and lambda classes of GST have


been reported in some multiple herbicide resistant black-grass and ryegrass populations131, 132.

Resistance was suggested to be endowed via the scavenging peroxidase activities of these

specific GST enzymes as well as a concomitant production of protective flavonoids to

counteract the free noxious radicals generated by the herbicide action. This hypothesis was

further strengthened with heterologous expression of GSTF1 in Arabidopsis thaliana and

demonstration of increased tolerance to ACCase and other herbicide modes of action that

inhibit elongation of fatty acids and photosystem II132.

In most cases though, NTSR to ACCase herbicides is conferred by the ability of some weed

populations to degrade metabolisable FOP, DIM and DEN compounds into non-toxic

entities79. Metabolic resistance was first convincingly established in black-grass and ryegrass

populations using radiolabelled 14C herbicides133, 134. Since then, direct evidence of

metabolism-based resistance has been generated in a handful of weed species and populations

only124, 129, 135, very probably due to the lack of radio-chemicals, licensed equipment and

trained personnel required for such procedures. Alternatively, metabolic resistance has been

inferred indirectly from the use of synergists that inhibit detoxifying enzymes involved in

ACCase herbicide metabolism, the absence of known target site mutations and differential

responses to closely metabolisable and non-metabolisable FOP and DIM herbicides91, 122, 125,

136. The synergists used include compounds such as amitrole, 1-aminobenzotriazole (ABT),

piperonyl butoxide (PBO) and malathion that impact on p450 enzymes137. However, the data

from these approaches should be taken with caution as resistance could be due to target site

mutations yet to be uncovered and also because the ability to augment herbicide activity can

be synergist, herbicide, population and species specific. For instance, ABT, but not malathion

or tetcyclasis, was shown to improve the efficacy of diclofop-methyl in a resistant L. rigidum

population133. The activity of tralkoxydim also affected by metabolic resistance in this

population was unaltered by any of the synergists used. Similarly none of the three


cytochrome p450 inhibitors, i.e. ABT, malathion or tetcyclasis could reverse fenoxaprop-P-

ethyl metabolism in a black-grass population from the UK138. Conversely, malathion in

mixture with fenoxaprop-P-ethyl and pinoxaden allowed suppression of A. fatua populations

suspected to be characterised by metabolic resistance125.

Metabolic resistance to ACCase herbicides can result from constitutively over-expressed

enzymes or be induced by external factors. In particular, elevated levels of cyp p450 enzymes

involved in phase 1, and GST and O-glucosyl transferases that operate in phase II

detoxification were identified in the Peldon black-grass population139. A similar observation

was recorded in several other black-grass populations with respect to GST enzymes140.

Resistance could also be induced via the use of safeners such as mefenpyr diethyl in

increasing the peroxidase protective activities of phi and lambda gluthathione transferases141.

The level of GST involved in metabolism can also vary depending on plant growth stages and

environmental conditions142.

Metabolic resistance is favoured under low-dose selection of minor genes that individually

confer low levels of resistance, but when accumulated confer significant levels of resistance

to ACCase herbicides. This was elegantly demonstrated under glasshouse conditions by the

recurrent selection at low doses of diclofop-methyl of progressively recalcitrant individuals

from an initially sensitive L. rigidum population143, 144. Resistance to practical field rates of

diclofop-methyl was attained after three generations, starting from a genetic pool of a few

hundred sensitive plants only. A comparable scenario is thought to function under field

conditions because not all plants receive effective rates of ACCase herbicides due to sub-

optimal spray conditions, shading upon high plant densities and staggered seed

germination145. Subsequent studies confirmed metabolism of diclofop-methyl to the acid

equivalent followed by further degradation into non-toxic metabolites similar to what is

achieved in wheat146. Worryingly, metabolism-based resistance acquired via low-dose


selection could also endow resistance to two other modes of action 145. This gives further

credence to earlier observations of NTSR selected by ACCase herbicides affecting the

acetolactate synthase herbicides iodo-/mesosulfuron in A. myosuroides56, 147. Whilst

metabolic resistance selected by ACCase herbicides is clearly demonstrated to cut across

herbicide modes of action, it can also be compound-specific within and between ACCase

subclasses. Non-target site resistance to fenoxaprop-P-ethyl was found to be more prevalent

than clodinafop-propargyl and pinoxaden in French black-grass populations 56. Likewise,

several ryegrass and wild oat studies involving NTSR biotypes have shown that pinoxaden is

less affected than clodinafop-propargyl, although both compounds use the same safener

cloquintocet-mexyl55, 91, 92, 126, 148.

Metabolic resistance is multigenic and complex as indirectly inferred from numerous cross

resistance analyses. This was further confirmed by two recent genetic studies in the ryegrass

population SLR31149 and several black-grass populations from France 147 following initial

studies by Preston et al. (2003)150. In particular, p450-based metabolic resistance showed

dominant nuclear inheritance in SLR31, thus indicating that resistance can be spread by both

pollen and seeds149. Additionally, segregation patterns of F2 and BC families were consistent

with resistance conferred by two additive genes even at high diclofop-methyl rates. In the

same manner, examination of a large number of F1 families from black-grass crosses

revealed that up to three dominant loci may be involved in conferring non-target site

resistance to ACCase herbicides in a single plant147. Whilst some of the enzyme systems

involved in NTSR to ACCase herbicides could be identified via biochemical assays in a few

cases or deduced indirectly via use of inhibitors of putative implicated enzymes141, 151, 152,

only two genes involved in protective scavenging actions of GST enzymes have been

identified so far131, 132.


5. Fitness associated with traits conferring resistance to ACCase herbicides

Adaptive traits to external stresses are often accompanied by negative pleiotropic changes in

the phenotype resulting in a fitness drag153. The potential fitness cost associated with evolved

ACCase resistant traits has been examined in seven different weed species (Table 2).

However, results from some of the studies could not be interpreted adequately, primarily

because the mechanism of resistance was not determined and sensitive and resistant

populations being compared did not share the same genetic background154-158. Ideally, life

history traits, most particularly, fecundity should be assessed in competition under different

field conditions using properly characterised and comparable weed lines159. In this respect,

Menchari et al (2008) determined the cost of resistance associated with three different target

site mutations, namely, I1781L, I2041N and D2078G, using wild, heterozygous and

homozygous mutant subpopulations arising from the same parental population160. Three

parameters were measured under different field conditions in two different years. There were

no fitness costs associated with the L1781 and N2041 alleles. On the other hand, plants

containing the G2078 allele were on average shorter, produced less biomass and fewer seeds

than their wild D2078 counterparts. Furthermore, the fitness costs were dependent on

population genetic backgrounds and field environments. The authors also examined

germination dynamics and seedling emergence among the same wild and 1781, 2041 and

2078 mutant genotypes161. Wild type I2041 and mutant N2041 plants behaved in a very

similar manner. Plants containing the mutant G2078 allele were characterised by an

incompletely dominant acceleration of seed germination and a segregation distortion against

mutant embryos. In contrast, L1781 individuals showed an incompletely dominant delay in

seed germination and a decrease in fatal germination. The delayed germination associated

with the L1781 allele was interpreted as being beneficial in agricultural systems that use

early-season herbicides as part of weed management practices in that it would allow a higher


proportion of the L1781 seeds to escape the herbicide treatment. Likewise, a fitness benefit

was recorded for a mutant L1781 foxtail sub-line both in terms of early growth under

glasshouse conditions and early growth, flowering, tiller and seed production under field

conditions162. However, the higher seed production of the L1781 genotype was

counterbalanced by lower seed survival in the field. The advantages of the L1781 mutant

versus wild I1781 sub-lines were rationalised by the presence of a tightly linked higher

fitness gene in the resistant biotype. This is a reasonable hypothesis given that enzyme assays

did not identify a difference in activities between wild and mutant ACCases at codon position

1781109, 163.

Conversely, no fitness cost in growth characteristics and reproductive output was associated

with the L1781 genotypic component of the multiple resistant ryegrass population SLR31

characterised by additional p450-based metabolism, except for germination levels under

shallow burial 164, 165. The p450 metabolic sub-line produced less above-ground biomass than

the wild type component from SLR31 but overall the reproductive output was similar164.

When tested under intraspecific and interspecific competition with wheat, the p450-based

genotype was at a disadvantage both in terms of biomass and reproductive output166, in line

with an impaired ability to contest for resources as suggested by the resource-based theory

that predicts a negative trade-off between growth and plant defence166-168. Importantly, it is

hypothesised that an associated fitness cost will result in the resistant populations declining in

the absence of herbicides169. This remains to be investigated for characterised ACCase target

site resistant and non-target site resistant weed populations under different field environments

and management strategies.

6. Methods for detecting resistance to ACCase herbicides


The large number of resistant cases, especially in Australia, UK and Western Canada, should

not obscure the fact that to date a significant proportion of grass weed populations can still be

controlled by effective ACCase herbicides. Whilst it is widely recognised that diversity in

weed management practices is key for maintaining the long-term efficacy of herbicides170,

the reality is that reactive measures are taken only when farmers are confronted with

resistance in their own fields171. Therefore, the availability of rapid early diagnostics tools for

confirming product failures is imperative for slowing down the evolution of resistance to

ACCase herbicides. The discovery of precise nucleotide changes involved in target site

resistance and the growing accessibility of molecular biology techniques have allowed

development of a wide range of methodologies for detecting the known resistance

mutations35, 63, 65, 72, 99, 112, 172-175. However, these methods have rarely been used outside

research due to the high costs involved, restrictions to target site resistance only and

ambiguity arising from multiple amino acid changes at specific resistance codon positions176,

177. Equally, methods based on pollen178, seeds179, enzyme140, 180 and metabolism 176 assays

have not been widely adopted because they do not cover all possible resistance mechanisms

and are therefore prone to false negative prediction of resistance. To date, the classical whole

plant test using seeds collected at the end of the growing season remains the most commonly

employed method for confirming resistance to ACCase herbicides181, 182. Recently, two other

promising methods have been described commencing with plants collected from the field

either after or before herbicide application183, 184. In the latter method, denoted the Syngenta

Resistance In-Season Quick (RISQ) test, weed seedlings at the 1-3 leaf stage sampled from

fields very early in the growing season are transplanted onto agar containing discriminating

rates of herbicides. Ten days later, survivors are recorded in comparison with standard

sensitive and resistant populations184. The test is commercially available in Australia allowing


willing practitioners to determine the resistance status of their grass weed populations prior to

herbicide application in the field.

7. Development of crops resistant to ACCase herbicides

Post-emergence grass weed management in several monocotyledonous crops is limited and

often based on a few selective ACCase and ALS herbicides. Therefore, introducing a

resistance trait that endows high levels of tolerance to poorly metabolisable ACCase

herbicides has been identified as an interesting prospect for increasing the arsenal for grass

weed control in these crops. This would allow targeting weeds that are genetically close or

respond to safening in a similar manner to the crop, examples of which include jointed

goatgrass and some Brome species in wheat and weedy rice in rice. It also provides the

opportunity for controlling the large number of grass weed populations that have evolved

resistance primarily due to enhanced herbicide metabolism. Several crop lines resistant to

ACCase herbicides have been created starting with sethoxydim resistant corn in the early

1990s185, 186. Resistance was either imparted by a target site mutation using a non-GM

approach or via genetic engineering of the aryloxyalkanoate dioxygenase (aad-1) gene into

corn providing tolerance to both quizalofop and 2,4-D (Table 3). To date however, the

commercial significance of these ACCase resistant crop lines is low but may increase with

growing importance of weeds such as Bromus spp., and weedy rice. Importantly, if these

lines are to be adopted, strategies should be put in place to mitigate the risk of resistance

evolution. These should include proscribing use of the same ACCase herbicide in

monocotyledonous and subsequent dicotyledonous break crops. Caution should also be

exercised to prevent transmission of the ACCase resistant trait into closely related grass weed

species.


8. Future research

Studies on resistance to ACCase herbicides have so far been dominated by three grass weeds

represented by Lolium, Avena and Alopecurus species benefitting from active research groups

in their respective regions. The knowledge gathered from these model species could be

leveraged to investigate the mechanisms and evolutionary dynamics of resistance in the other

growing number of grass weed species that have evolved resistance to ACCase herbicides.

The existing method for directly confirming enhanced metabolism of ACCase herbicides in

grass weeds is very time consuming and restricted to laboratories equipped with radio-

chemical facilities129, 135, 146. There is therefore a need for developing simpler non-

radiolabelled assays, potentially based on Liquid Chromatography-Mass Spectrometry (LC-

MS) procedures, for quickly confirming metabolic resistance. Also, more than 20 years after

demonstrating resistance to ACCase herbicides due to enhanced p450-based metabolism, the

genes involved are yet to be identified. New sequencing and other genome-wide

technologies could be exploited to unravel the genes associated with non-target site resistance

by using well characterised genetic materials in downstream molecular applications187,

bearing in mind that resistance is likely to be very complex, constitutive or induced,

depending on plant growth stages, herbicide use rates and other environmental conditions.

Molecular biology techniques have greatly improved our understanding of target site

resistance. Yet, it is not always easy to comprehend how some subtle differences in the

binding site impact on different ACCase herbicides. ACCase crystal structures from relevant

grass weeds could be generated and used instead of surrogate yeast ACCase for determining

how minor changes in the target enzyme of grass weeds can have profound effects on

ACCase herbicide efficacy. Additionally, the knowledge gathered from crystallography

studies could be applied to develop the next generation of ACCase herbicides that are less

prone to resistance evolution. Fitness cost is central in understanding the evolutionary


dynamics of resistance to ACCase herbicides. This has been assessed properly in rye and

black-grass for some target site mutations and a single non-target site resistant biotype only

but not for any polyploid species which encompass some of the most problematic weeds that

have evolved resistance to ACCase herbicides. In order to circumvent practical issues

involved in carrying out field studies, a robust agreed glasshouse-based procedure, including

intraspecific and interspecific competition, should be put in place for assessing fitness costs

associated with different target site mutations and non-target site resistance genes in multiple

grass weed species. Additionally, more surveys should be conducted in the field to follow the

evolution of resistance genes/individuals under different herbicide and non-chemical weed

management strategies. The forecast for global ACCase herbicide usage is a slight decline in

the years to come, partly due to continued adoption of glyphosate tolerant crops6. However,

topically, a significant increase in ACCase use of up to four applications in a single growing

season is recorded for controlling glyphosate resistant weeds as is the case with S. halepense

in Argentina. An early-season in-field kit could be established for quickly confirming new

cases of resistance to ACCase herbicides so that an educated choice of herbicides can be

made for effective weed management. Ideally, a computer-based modelling approach

combining chemical and non-chemical methods could be used for developing pro-active

weed management strategies for maintaining the long-term sustainable use of ACCase

herbicides.

Acknowledgement

The author is very grateful to Karthik Putta for preparing some of the tables; Rita Kaundun

and several Syngenta colleagues for reviewing an earlier draft of this manuscript.


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Figure 1: Impact of the W2027C (equivalent to W374C on picture) mutation on the binding

of FOP herbicides exemplified here with diclofop. Overlay between wild and mutant diclofop

and its corresponding W374C complex. The wild type complex is in grey and cyan while the

mutant W374C complex is in blue and yellow (extracted from: 117)

Π- Π


Table 1. List of monocotyledonous species with published carboxyltransferase domain

sequences (>90% coverage of CT domain)

Species Accession number Source Length Alignmen

t length*

% Identity

*

Aegilops tauschii EU660897.1 genomic

DNA 12379

8 1647 91.2 Alopecurus japonicus JQ068820.1 mRNA 7589 1638 99.51 Alopecurus myosuroides AJ310767.1 mRNA 7589 1638 100

Avena fatua JF785552.1 genomic

DNA 2039 1647 93.26

Beckmannia syzigachne KF501579.1 genomic

DNA 10174 1638 96.52 Brachypodium distachyon

XM_003581327.1 mRNA 7553 1647 90.29

Echinochloa crus-galli HQ395758.1 mRNA 7527 1643 87.89

Lolium multiflorum AY710293.1 genomic

DNA 3044 1644 92.52

Lolium rigidum DQ184646.1 genomic

DNA 1563 1563 92.58

Phalaris minor AY196481.1 genomic

DNA 2027 1647 94.05

Phalaris paradoxa AM745339.1 genomic

DNA 1520 1520 94.01 Setaria italica AF294805.1 mRNA 7630 1642 88.31

Setaria viridis AM408428.1 genomic

DNA 12934 1642 88.31

Sorghum bicolor XM_002446133.

1 mRNA 7537 1640 88.11

Triticum aestivum EU660900.1 genomic

DNA 97428 1647 91.5

Triticum turgidum EU660898.1 genomic

DNA 16576

4 1647 91.62

Triticum urartu EU660896.1 genomic

DNA 98890 1647 91.5 Zea mays U58598.1 mRNA 5442 1640 87.56

*Alignment length and sequence identity with respect to the carboxyltransferase domain of

Alopecurus myosuroides accession AJ310767


Table 2. Fitness cost and benefit associated with evolved traits conferring resistance to ACCase herbicides

Species Mechanism Impact associated with herbicide resistance References

Relative growth rate

Shoot dry biomass Seed yield Seed germination

Relative competitive ability

A. myosuroides I1781L Not affected Not affected Not affected Delayed germination; decrease fatal germination ND 160, 161

D2078G Decreased Decreased Decreased Earlier germination ND 160, 161

I2041N Not affected Not affected Not affected Not affected ND 160, 161

L. rigidum P450

metabolism Decreased Decreased Not affected Not affected ND 164, 195

L. rigidum I1781L Not affected Not affected Not affected Low germination under shallow burial ND 164, 195

L. rigidum P450

metabolism Decreased Decreased Decreased ND Decreased 166

L. rigidum Not

investigated ND ND ND Decreased under normal temperature ND 156

A. sterilis Not

investigated Not affected ND Not affected Not affected Slight competitive edge 157

A. fatua

Multiple Herbicide resistance Not affected less tillers Decreased Earlier germination ND 154

S. viridis x S. italica I1781L Increased ND Increased

Earlier germination, Lower emergence potential ND 162

S. faberi Not

investigated Not affected Not affected Not affected ND Not affected 155

D. sanguinalis Not

investigated ND Not affected Not affected ND Not affected 158

ND: Not determined


Table 3. Examples of monocotyledonous crops that have been modified to resist ACCase

herbicides

Crop Mechanism of resistance

Selecting Herbicide Method References

Corn TSR-I1781L Sethoxydim tissue culture 185, 186

Corn Metabolism Quizalofop aad-1 gene 196, 197

Rice TSR-I1781L Cycloxydim tissue culture 198

Rice TSR-G2096S Quizalofop AZ mutagenesis 199

Wheat TSR-A2004V Quizalofop EMS mutagenesis 115, 200

Sorghum TSR-W2027C Fluazifop wild biotypes 82, 201

Turfgrass TSR-I1781L Sethoxydim tissue culture 202, 203

TSR: target site resistance; AZ: sodium azide; EMS: ethyl methanesulfonate; aad-1:

aryloxyalkanoate dioxygenase

Documents

Resistance to acetyl-CoA carboxylase-inhibiting herbicides