Hybrid Autofluorescence and Optoacoustic Microscopy for the Label-Free, Early and Rapid Detection of Pathogenic Infections in Vegetative Tissues

Abstract

Agriculture plays a pivotal role in food security and food security is challenged by pests and pathogens. Due to these challenges, the yields and quality of agricultural production are reduced and, in response, restrictions in the trade of plant products are applied. Governments have collaborated to establish robust phytosanitary measures, promote disease surveillance, and invest in research and development to mitigate the impact on food security. Classic as well as modernized tools for disease diagnosis and pathogen surveillance do exist, but most of these are time-consuming, laborious, or are less sensitive. To that end, we propose the innovative application of a hybrid imaging approach through the combination of confocal fluorescence and optoacoustic imaging microscopy. This has allowed us to non-destructively detect the physiological changes that occur in plant tissues as a result of a pathogen-induced interaction well before visual symptoms occur. When broccoli leaves were artificially infected with Xanthomonas campestris pv. campestris (Xcc), eventually causing an economically important bacterial disease, the induced optical absorption alterations could be detected at very early stages of infection. Therefore, this innovative microscopy approach was positively utilized to detect the disease caused by a plant pathogen, showing that it can also be employed to detect quarantine pathogens such as Xylella fastidiosa.

Keywords: Xanthomonas campestris; Xylella fastidiosa; fluorescence; microscopy; optoacoustic; pathogen detection; photoacoustic; rapid disease diagnosis.

Figure 1

Schematic representation of the hybrid confocal fluorescence and optoacoustic microscopy system for the investigation of vegetative tissues. L (1–7), lenses; M, mirror; PH (1–2), pinholes; ND, neutral density filters; DM (1–2), dichroic mirrors; F, optical filter; PMT, photomultiplier tube; AF, autofluorescence; CW, continuous wave; P, linear polarizer; OL, objective lens; XYZ, 3D translation stages; SH, sample holder; S, specimen; UT, ultrasonic transducer; A, RF amplifier; DAQ, data acquisition card; FG, function generator; PC, recording computer.

Figure 2

Hybrid imaging of control specimens. (a) Image of an extracted young broccoli leaf, 24 h after an injection with pure water. The black square represents the part of the leaf that was sectioned and placed in the sample holder of the microscope. (b) Zoom-in of the dissected region indicated with the black square in (a). The smaller black square shows the region that was finally scanned to obtain the hybrid images. (c) Autofluorescence image of a representative 1500 by 1500 μm² area as indicated in (b). (d) Optoacoustic scan of the same region, showcasing a total absence of signals. (e) Hybrid image resulting through the merging of (c,d). Similar results recorded 48 (f–j) and 72 (k–o) hours post-injection. The scalebar is equal to 200 μm.

Figure 3

Hybrid imaging of Xanthomonas campestris pv. campestris (Xcc) artificially infected specimens. (a) Image of a detached young broccoli leaf, 24 h after an injection with Xcc bacteria. The black square represents the part of the leaf that was sectioned and placed in the sample holder of the microscope. (b) Zoom-in of the region indicated with the black square in (a). The smaller black square shows the region that was finally scanned to obtain the hybrid images. (c) Autofluorescence image of a representative 1500 by 1500 μm² area as indicated in (b). (d) Optoacoustic scan of the same region, demonstrating low-amplitude sparsely distributed signals. (e) Hybrid image resulting through the merging of (c,d). Similar results recorded 48 (f–j) and 72 (k–o) hours post-injection, indicating a noteworthy increase of the optoacoustic signals. The scalebar is equal to 200 μm.

Figure 4

Mean optoacoustic (OA) signal progression for 24, 48 and 72 h after the infection. The mean values were estimated out of five optoacoustic images for each timepoint. Error bars represent the standard error of the mean.

Figure 5

Development of disease symptoms caused by the pathogen Xcc in broccoli plant leaf (Brassica oleraceae var. italica) artificially infected during a 24 day period of observation. The numbers underneath each photo indicate the severity scale of the symptom (0: no symptom, 12: complete leaf damage due to typical black rot V-shaped lesion). The macroscopic detection of the disease symptom onset is indicated with a red arrow on the 7th day post-inoculation as the yellowing initiation inside the red circle.