Background

Colletotrichum fungi cause anthracnose disease in a broad range of plants, including important crops, and have a serious economic impact (Cannon et al., 2012). Among Colletotrichum species, C. higginsianum infects Brassicaceae plants, including the model plant Arabidopsis thaliana (O’Connell et al., 2004). Thus, this pathogen has been used for various studies that have revealed molecular mechanisms of plant immunity and pathogenicity (Birker et al., 2009; Narusaka et al., 2009; Kleemann et al., 2012; Takahara et al., 2016; Plaumann et al., 2018). Moreover, recently released high-quality genome assemblies of C. higginsianum provide genomic resources that should increase the use of this fungus in functional studies by facilitating the identification of candidate genes of interest (Zampounis et al., 2016; Tsushima et al., 2019). In order to determine the virulence of C. higginsianum, initial studies employed disease reaction scores based on visual observation and subjective judgement (O’Connell et al., 2004; Narusaka et al., 2004). The necessity for more objective approaches has led to the development of alternative methods including lesion diameter measurement, entry rate assays, and measurement of relative fungal biomass using real-time quantitative PCR (Narusaka et al., 2010; Hiruma and Saijo, 2016). These methods are commonly employed in studies using C. higginsianum, yet they have disadvantages, such as the variability of lesion shapes leading to differences in measured values between observers, time-consuming steps, or the economic burden of purchasing reagents. ImageJ has been used as an open source tool for the analysis of scientific images (Schneider et al., 2012). In the field of plant pathology, many studies have utilized ImageJ to analyze pathogenicity or resistance, for instance by measuring lesion sizes (Dagdas et al., 2016; Kumakura et al., 2019). However, these procedures can be further automated. Therefore, we developed an objective, automated, and affordable method to detect and measure lesion areas from images of A. thaliana leaves infected by C. higginsianum using ImageJ. In this article, we describe how to perform infection assays to study the A. thaliana-C. higginsianum interaction and how to detect and measure lesions using ImageJ macros to record multiple lesion areas at one time. This method enables us to reproducibly perform infection assays with the A. thaliana-C. higginsianum pathosystem and may be adapted to other pathosystems. For example, ImageJ color thresholds were also used to measure lesion areas on C. shisoi-infected A. thaliana (Gan et al., 2019). This protocol will allow us to perform objective and high throughput analyses to gain further insights into plant-microbe interactions.