Background

Reactive oxygen species (ROS) lie at the core of redox biology. In plants, ROS fulfill a dual role, acting both as signaling molecules and as cytotoxic agents [3]. Owing to its relatively higher stability compared to other ROS, hydrogen peroxide (H₂O₂) represents a central regulator of plant development and stress responses [4]. H₂O₂ can directly interact with proteins, thereby modifying their structure and downstream signaling pathways [3]. Consequently, the spatiotemporal regulation of H₂O₂ accumulation determines whether plant cells mount appropriate responses to environmental cues or instead experience oxidative damage leading to cell death. Accurate quantification of H₂O₂ with spatial resolution is therefore essential for understanding how ROS mediate cell-specific adjustments of plant growth under changing conditions.

A wide range of approaches has been developed to detect and quantify H₂O₂, each with distinct advantages and limitations. In general, substrate specificity and spatial resolution are the primary factors guiding method selection. Available techniques include spectrophotometric assays, enzyme-coupled fluorometric assays, imaging of genetically encoded sensors that allow real-time detection in living tissues, and histochemical staining methods that provide spatial information. Accordingly, the choice of assay depends on whether the experimental focus lies on bulk quantification, dynamic measurements, or spatial localization.

Classical spectrophotometric assays, such as the titanium–peroxide complex method [5], enable straightforward and cost-effective bulk quantification of H₂O₂ but lack spatial resolution. Enzyme-coupled fluorometric assays, including Amplex Red and Amplex Ultra Red [6–8], or enzyme-independent assays, like the europium–tetracycline complex [7], provide high sensitivity and accurate quantification at low H₂O₂ concentrations; however, they require tightly controlled reaction conditions and are generally unsuitable for in situ applications. Genetically encoded sensors, such as HyPer [9] and roGFP2-Orp1 [10], offer high H₂O₂ selectivity together with real-time, quantitative, and compartment-specific measurements in vivo [11]. Despite these advantages, their reliance on transgenic systems limits their applicability across diverse genetic backgrounds. Chemical probes, including H₂DCF-DA (2′,7′-dichlorodihydrofluorescein diacetate), CM-H₂DCF-DA (chloromethyl-H₂DCF-DA), and DAB (3,3′-diaminobenzidine), permit intracellular ROS detection without genetic manipulation. H₂DCF-DA and CM-H₂DCF-DA are cell-permeable and widely used in living tissues [8,12–15]; however, their poor specificity and susceptibility to oxidation by multiple reactive species mean that they primarily reflect general redox status rather than H₂O₂ levels specifically.

Among these approaches, DAB staining has long been established as a classical method for detecting hydrogen peroxide in plant tissues [1,16]. The assay relies on a peroxidase-mediated reaction in which DAB is oxidized by H₂O₂, resulting in the formation of an insoluble brown precipitate. This enables spatial visualization of H₂O₂ accumulation in roots (e.g., [17,18]) as well as in leaves and other pigmented tissues following chlorophyll removal [2,19–21]. Although DAB staining is semi-quantitative and dependent on endogenous peroxidase activity, its simplicity, robustness, and capacity for spatial resolution have led to its widespread use in studies of plant oxidative stress [22].

Despite its widespread use, DAB staining protocols are often applied qualitatively or rely on simplified quantification approaches that lack standardized image analysis workflows, particularly for roots. Here, we present a refined and accessible protocol for semi-quantitative H₂O₂ detection in Arabidopsis thaliana roots that builds on established DAB staining methods while placing specific emphasis on root tissues and reproducible downstream analysis. Compared with bulk biochemical assays or genetically encoded sensors, this approach offers a favorable balance between spatial resolution, experimental accessibility, and applicability across diverse genetic backgrounds without the need for transgenic lines. Although DAB staining remains inherently dependent on endogenous peroxidase activity and does not provide absolute H₂O₂ concentrations, our protocol minimizes variability by integrating controlled staining conditions with a standardized, background-corrected image analysis pipeline implemented in open-source FIJI/ImageJ. This protocol provides a complete workflow, including DAB staining and washing steps for roots, detailed guidance on image acquisition, a transparent and reproducible quantification strategy (ROI definition, background subtraction, peak integration), and step-by-step video tutorials to facilitate adoption and reproducibility across laboratories.