Abstract
The two principal methods for studying fungal biodegradation of lignocellulosic plant tissues were developed for wood preservative testing (soil-block; agar-block). It is well-accepted that soil-block microcosms yield higher decay rates, fewer moisture issues, lower variability among studies, and higher thresholds of preservative toxicity. Soil-block testing is thus the more utilized technique and has been standardized by American Society for Testing and Materials (ASTM) (method D 1413-07). The soil-block design has drawbacks, however, using locally-variable soil sources and in limiting the control of nutrients external (exogenous) to the decaying tissues. These drawbacks have emerged as a problem in applying this method to other, increasingly popular research aims. These modern aims include degrading lignocellulosics for bioenergy research, testing bioremediation of co-metabolized toxics, evaluating oxidative mechanisms, and tracking translocated elements along hyphal networks. Soil-blocks do not lend enough control in these applications. A refined agar-block approach is necessary. Here, we use the brown rot wood-degrading fungus Serpula lacrymans to degrade wood in agar-block microcosms, using deep Petri dishes with low-calcium agar. We test the role of exogenous gypsum on decay in a time-series, to demonstrate the utility and expected variability. Blocks from a single board rip (longitudinal cut) are conditioned, weighed, autoclaved, and introduced aseptically atop plastic mesh. Fungal inoculations are at each block face, with exogenous gypsum added at interfaces. Harvests are aseptic until the final destructive harvest. These microcosms are designed to avoid block contact with agar or Petri dish walls. Condensation is minimized during plate pours and during incubation. Finally, inoculum/gypsum/wood spacing is minimized but without allowing contact. These less technical aspects of agar-block design are also the most common causes of failure and the key source of variability among studies. Video publication is therefore useful in this case, and we demonstrate low-variability, high-quality results.