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The establishment of herbicides as the major method of weed control in agriculture (Powles & Shaner, 2001) has resulted in the widespread evolution of herbicide resistance (Powles & Yu, 2010). Mixture strategies that expose a population of a single weed species to two or more herbicides with different modes of action have been widely advocated for resistance management (Gressel & Segel, 1990; Friesen et al., 2000; Powles & Shaner, 2001). These ‘resistance management mixture strategies’ must be differentiated from herbicide mixtures that are applied because they provide control of different weed populations within an agricultural field. Similar resistance management strategies have been proposed for the prevention of insecticide (Denholm & Rowland, 1992), fungicide (Brent & Hollomon, 2007) and antibiotic (Brown & Nathwani, 2005) resistance, and the management of resistance to antiretroviral and anti-cancer drugs (Pastan & Gottesman, 1987). Mixture strategies rely on the assumption that mutations conferring resistance to one component of the mixture do not increase fitness in the presence of the second component. Indeed, the most desirable situation arises when there is antagonistic pleiotropy between resistance mechanisms (Gressel, 2002). Where the assumptions of independent resistance are met, resistance to the mixture can only arise via the spontaneous evolution of resistance mechanisms to both (or all) mixture components (Diggle et al., 2003). The likelihood of this occurring decreases with each additional herbicide in the mixture (Wrubel & Gressel, 1994).
Two broad categories of herbicide resistance mechanisms have been documented: target site and nontarget site (Powles & Yu, 2010). Target site resistance arises from the modification or over-expression of the herbicide target enzyme, and results in resistance that is specific to a single mode of action (specialist resistance; Busi & Powles, 2009; Powles & Yu, 2010). Several target site resistance mutations can accumulate in the same individual, leading to multiple resistance (Powles & Yu, 2010). Nontarget site resistance may be based on the enhanced metabolism of the herbicide, reduced herbicide translocation or sequestration away from the active site of the herbicide. Enhanced metabolism, in particular, can confer resistance to multiple modes of action (generalist resistance) and may require multiple mutations (Powles & Yu, 2010). Generalist resistance may be favoured in more complex, multiherbicide environments, and this may compromise the potential efficacy of mixture strategies.
Mathematical models have been used to demonstrate the potential effectiveness of mixtures for herbicide resistance management (Powles et al., 1997; Diggle et al., 2003; Neve, 2008). However, these models focus predominantly on the evolution of target site resistance. Empirical evidence for the efficacy of herbicide mixture strategies is limited and often anecdotal (Beckie, 2006), although some studies have confirmed the benefits of mixtures over other management strategies (Manley et al., 2002; Beckie & Reboud, 2009). Models exploring the effectiveness of mixtures of insecticides or fungicides for the management of resistance provide conflicting evidence for their benefits (Mani, 1985; Denholm & Rowland, 1992; Russell, 2005), as do experimental studies – some supporting mixtures as an effective method of resistance management (McKenzie & Byford, 1993; Prabhaker et al., 1998), others cautioning against their widespread use (Immaraju et al., 1990; Blumel & Gross, 2001; Castle et al., 2007). It is interesting to compare this with the situation in studies of antibiotic resistance, where clinical trials predominantly report mixtures as effective strategies in slowing resistance evolution (Bergstrom et al., 2004; Brown & Nathwani, 2005; Beardmore & Peña-Miller, 2010).
Increased economic and environmental costs are a major obstacle to the adoption of effective herbicide resistance management mixtures in agricultural settings (Hart & Pimentel, 2002). Short-term economic interests favour the use of a single-herbicide mode of action that achieves a high level of control, as it does not require investment in multiple herbicides (Buttel, 2002). From an environmental perspective, herbicide mixtures raise concerns as they increase inputs of pesticides into the environment (Hart & Pimentel, 2002). In response to these problems, there have been calls to use synergistic mixtures of herbicides, whereby the total combined dose of herbicides in the mixture is reduced (Gressel, 1990). The implications of such strategies for resistance evolution are not well understood. In antibiotic resistance, it has been shown that synergistic mixtures can exacerbate resistance evolution, as the appearance of resistance to one of the components leaves a population exposed to an ineffective dose of the other (Hegreness et al., 2008).
Microbial experimental evolution offers the potential to explore conditions under which herbicide mixture strategies may be effective, overcoming time and space limitations associated with empirical studies with higher plants (Elena & Lenski, 2003). Here, we used the unicellular green chlorophyte, Chlamydomonas reinhardtii, as a model organism. Chlamydomonas reinhardtii grows asexually under laboratory conditions (Harris, 2008), is susceptible to a range of commercial herbicides and has been used previously as a model system for the study of the evolution of herbicide resistance (Reboud et al., 2007). The techniques of experimental evolution (Buckling et al., 2009) are easily applicable to C. reinhardtii and have been adopted to explore a variety of questions relating to herbicide resistance evolution and management (Lagator et al., 2012; Vogwill et al., 2012). We evolved experimentally populations of C. reinhardtii with exposure to mixtures of two or three herbicides with different modes of action (atrazine, glyphosate and carbetamide) at a variety of total combined doses, as well as in single exposures to each of the herbicides. The objectives of this study were to investigate the following: mixtures are effective in delaying and/or preventing the evolution of herbicide resistance; the effectiveness of mixtures is dependent on the total combined dose and the number of herbicides; and an increase in the number of herbicides and a reduction in their combined dose increases the likelihood of evolution of generalist resistance.