Three-Dimensional Exploration of Soft-Rot Decayed Conifer and Angiosperm Wood by X-Ray Micro-Computed Tomography

Highlights

• The three-dimensional study of decayed wood is difficult to realize with common microscopy.

• X-ray computed tomography is used to visualize the internal structure of wood after soft-rot decay.

• The elemental characterization of inorganic particles is achieved through SEM-EDX.

• Three-dimensional visualizations reveal fungal-induced cavities and spatial distribution of inorganic particles in decayed wood.

Abstract

X-ray micro-computed tomography (XμCT) was used to explore the decomposed structure of conifer and angiosperm wood after colonization by soft-rot fungi. The visualization of degradation features of soft-rot decay was challenging to achieve through XμCT. Difficulties in visualization emerged due to a decreased grayscale contrast (i.e. X-ray density) of the degraded wood. Nevertheless, we were able to image fungal-induced cell deformations in earlywood and cavities in the thick wall of latewood cells in three-dimensions (3D). Unlike the organic wood material, the higher X-ray density of inorganic deposits, identified as mainly calcium-based particles by energy-dispersive spectroscopy, allowed a facilitated 3D survey. The visualization of inorganic particles in 3D revealed a localized distribution in certain cells in conifer and angiosperm found mostly in earlywood.

Introduction

Wood is a lignocellulosic biomaterial utilized for various application purposes. In exterior applications, wood products have limitations in service life resulting from decomposition by natural terrestrial micro-flora mainly wood-rotting fungi. Wood-rotting fungi can be classified into three rot types (i.e. brown, white, and soft rot) regarding their mode of wood degradation (Blanchette et al., 1990; Eriksson et al., 1990; Schwarze, 2007). An overview of the major fungus species associated with the decay of trees has been reviewed by Morris et al. (2019). With regard to the three rot types, fungi of basidiomycetes cause brown rot and white rot. The latter differs from brown rot in its ability to oxidize the phenolic compounds (i.e. lignin) of the wooden cell wall. Unlike brown and white rot, soft rot is taxonomically associated with ascomycetes (Eriksson et al., 1990; Schwarze, 2007). Soft rot causes severe degradation of wood in service when wood is exposed to moist in-ground conditions (Bellmann, 1961; Schwarze, 2007). Soft rot decays the cell-wall matrix through causing longitudinal cavities within the secondary cell walls of wood (type I) or cell-wall thinning by hyphae growing in the cell lumina (type II) (Blanchette et al., 1990; Eriksson et al., 1990; Daniel, 2016; Schwarze, 2007). During the depolymerization of the wood’s cell-wall components, some wood-destroying fungi can produce inorganic particles (mostly calcium oxalates) resulting from metabolic activities (Eriksson et al., 1990; Schilling and Jellison, 2005).

The understanding of fungal activity and the structure of decomposed wood has been studied extensively. Traditionally, decayed wood has been studied in two-dimensions (2D) by means of stained sections using light microscopy (Mohebby, 2003; Schwarze, 2007). Electron microscopy systems, such as scanning electron microscopy (SEM), allow imaging of cell-wall degradation features of wood at high magnifications (e.g. Blanchette et al., 2004; Mohebby, 2003). Among electron microscopy, transmission electron microscopy provides information on the ultra-structure of cell-wall degradation and fungal hyphae (e.g. Daniel, 1994; Hale and Eaton, 1985a, 1985b). Even though microscopy techniques enable high detail imaging of decomposed wood (Daniel, 2016; Schwarze, 2007), the internal, non-invasive, and three-dimensional (3D) survey of biologically degraded wood remains challenging. However, Schubert et al. (2014) revealed the spatial hyphal growth of the white-rot fungus Physisporinus vitreus in spruce wood using confocal laser scanning microscopy. Apart from the mostly 2D microscopy, imaging through X-ray tomography technologies has been successfully established in different fields of wood research as presented by Brodersen (2013), Koddenberg (2019), and Van den Bulcke et al. (2013). Thereby, X-ray micro-computed tomography (XμCT) performed with laboratory devices and synchrotron beamlines answers the call for a 3D study. Furthermore, X-ray radiation provides a non-invasive method to analyze the structure of fragile and brittle samples. Previous mycological studies have already made use of XμCT to explore decayed wood by blue-stain and whit-rot fungi in three-dimensions (Falconer et al., 2010; Sedighi Gilani et al., 2014; Van den Bulcke et al., 2009, 2008). For instance, Sedighi Gilani et al. (2014) used synchrotron radiation to map spatial changes of wood density after decay by the white-rot Physisporinus vitreus and the soft-rot Xylaria longipes. Van den Bulcke et al. (2009) reported that the visualization of hollow fungal hyphae from the white rot Trametes versicolor is difficult to achieve due to their small size and low X-ray density. Because XμCT is sensitive to the elemental density of which the sample is composed of, researchers used this advantage to detect three-dimensionally inorganic structures in the otherwise organic plant material (Koddenberg et al., 2019a; Morris et al., 2016; Yamauchi et al., 2013). With regard to wood, Koddenberg et al. (2019a) used this capability to examine silica deposits in wood of the Australian tree species Syncarpia glomulifera, whereas Morris et al. (2016) rendered calcium oxalate crystals in ray parenchyma cells of Ziziphus obtusifolia three-dimensionally.

This study provides the reader with 3D explorations of decayed wood after soft-rot testing. We assumed that no clear visualization of the fungal hyphae in 3D would be possible, due to their low X-ray density. Contrarily, we expected tomographic evidence of the presence and distribution of fungal-driven inorganic particles due to their higher X-ray density than the organic wood tissue. In addition to XμCT, we used common SEM analyses for comparison.