Oxalate Production and Cation Translocation during Wood Biodegredation by Fungi

Wood biodegradation is primarily caused by Basidiomycetous white or brown rot fungi. White rot fungi are unique in degrading lignin, while brown rot fungi circumvent lignin to degrade holocellulose via iron-dependent oxidative chemistry. Both groups of fungi produce oxalate during wood metabolism, and oxalic acid secretion may promote wood decay by reducing pH, mobilizing iron, detoxifying copper, and immobilizing calcium. The function of oxalate during wood decay remains unclear, however, primarily due to difficulties in extracting bound oxalate and to inconsistencies among analytical techniques. This work aims to improve oxalate quantification during wood biodegradation and to better characterize fungal oxalate production in relation to cation availability. Accurate and repeatable soluble and acid-extractable oxalate quantification was achieved with an improved high-performance liquid chromatography (HPLC) method. This procedure was verified in fungal liquid cultures by demonstrating a decrease in soluble/acid-extractable oxalate ratio with increasing filtrate calcium, due to calcium oxalate crystallization. For wood material, HPLC analyses consistently demonstrated that wood oxalate dynamics could not be inferred from data generated in artificial culture. An agar-block trial also established that several brown rot fungi optimized oxalate levels in wood, unlike in agar, suggesting excess oxalate in wood may impede brown rot, perhaps by limiting iron availability. Effects of iron, as well as aluminum and copper, on brown rot oxalate dynamics were tested in agar-block microcosms containing metallic or hydroxide metal treatments. The effect of calcium on oxalate was similarly tested among several decay fungi, including “dry rot” species theorized to use calcium to neutralize excess oxalate. In both trials, test fungi mobilized cations from treatment sources and enriched decaying wood with the respective cations; however, oxalate and wood weight loss were unaffected in either case. These studies suggest that wood-degrading fungi, notably brown rot species, may regulate oxalate in wood during degradation, but perhaps not simply as a function of Fe, Ca, or Cu availability, as previously theorized. This work has implications on the function of oxalate in wood decay and the role of wood-degrading fungi in forest biogeochemistry, and it provides analytical means for better exploring these dynamics in the future

Effects of Wood Mixtures on Deterioration By a Filamentous Brown-Rot Fungus

Wood-degrading fungi import elements to meet physiological demands in wood, but little is known about interactions with different wood types. This is despite increased use of wood composites, in which durability can be tested but not well predicted. Blocks of nondurable aspen and spruce and moderately durable eastern white pine were degraded using the brown-rot fungus Gloeophyllum trabeum in soil- and agar-block microcosms for 16 wk. Block configurations were either a single species (monosubstrate) or mixed (polysubstrate). At 8 and 16 wk, total wood weight losses were the same in monosubstrate and polysubstrate microcosms; however, white pine degradation was consistently less in polysubstrates than in monosubstrates with decay in aspen and spruce compensating to achieve equal overall weight loss. Nondegraded pine had higher extractives and lower nitrogen levels as compared with the other woods. Carbon fractions and cation contents in degraded pine were typical of brown rot, suggesting the fungus reallocated resources to less durable aspen and spruce when given the option. Data demonstrate that wood durability can be influenced significantly by other wood types. Although this could influence the spatial pattern of decay in mixed materials, overall durability in small-particle size wood composites may also be predictable based on single-species performance

Evolution of substrate-specific gene expression and RNA editing in brown rot wood-decaying fungi.

Fungi that decay wood have characteristic associations with certain tree species, but the mechanistic bases for these associations are poorly understood. We studied substrate-specific gene expression and RNA editing in six species of wood-decaying fungi from the 'Antrodia clade' (Polyporales, Agaricomycetes) on three different wood substrates (pine, spruce, and aspen) in submerged cultures. We identified dozens to hundreds of substrate-biased genes (i.e., genes that are significantly upregulated in one substrate relative to the other two substrates) in each species, and these biased genes are correlated with their host ranges. Evolution of substrate-biased genes is associated with gene family expansion, gain and loss of genes, and variation in cis- and trans- regulatory elements, rather than changes in protein coding sequences. We also demonstrated widespread RNA editing events in the Antrodia clade, which differ from those observed in the Ascomycota in their distribution, substitution types, and the genomic environment. Moreover, we found that substrates could affect editing positions and frequency, including editing events occurring in mRNA transcribed from wood-decay-related genes. This work shows the extent to which gene expression and RNA editing differ among species and substrates, and provides clues into mechanisms by which wood-decaying fungi may adapt to different hosts

Stem-inhabiting fungal communities differ between intact and snapped trees after hurricane Maria in a Puerto Rican tropical dry forest

Hurricanes impact forests by damaging trees and altering multiple ecosystem functions. As such, predicting which individuals are likely to be most affected has crucial economic importance as well as conservation value. Tree stem-inhabiting fungal communities, notably rot-causing agents, have been mentioned as a potential factor of tree predisposition to hurricane damage, but this assumption remains poorly explored. To examine this relationship, we sampled the stem wood of intact and damaged trees shortly after Hurricane Maria in a Puerto Rican dry tropical forest in 2017. We categorized samples depending on two types: trees with intact stems and trees in which stems were snapped. We extracted fungal environmental DNA of wood from 40 samples consisting of four different tree species. Fungal community taxonomic and functional richness and composition was assessed using high-throughput DNA metabarcoding. We found that snapped trees harbored significantly higher fungal operational taxonomic unit (OTU) richness than the intact trees and that the composition of the stem-inhabiting fungal communities diverged consistently between intact and snapped trees. On average, snapped trees’ fungal communities were relatively enriched in “other saprotrophs” guild category and depleted in endophytes. Conversely, intact trees had high relative abundances of Clonostachys, a mycoparasitic endophyte, suggesting that endophytic fungi might act as biocontrols in tree stems. Overall, our results support the hypothesis that stem-inhabiting fungal communities could represent a predisposition factor of tree damage caused by hurricanes in tropical dry forests

Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations

The stellarator is a promising concept to produce energy from nuclear fusion by magnetically confining a high-pressure plasma. In a stellarator, the confining field is three-dimensional, and the computational cost of solving the 3D MHD equations currently limits stellarator research and design. Although data-driven approaches have been proposed to provide fast 3D MHD equilibria, the accuracy with which equilibrium properties are reconstructed is unknown. In this work, we describe an artificial neural network (NN) that quickly approximates the ideal-MHD solution operator in Wendelstein 7-X (W7-X) configurations. This model fulfils equilibrium symmetries by construction. The MHD force residual regularizes the solution of the NN to satisfy the ideal-MHD equations. The model predicts the equilibrium solution with high accuracy, and it faithfully reconstructs global equilibrium quantities and proxy functions used in stellarator optimization. The regularization term enforces that the NN reduces the ideal-MHD force residual, and solutions that are better than ground truth equilibria can be obtained at inference time. We also optimize W7-X magnetic configurations, where desiderable configurations can be found in terms of fast particle confinement. This work demonstrates with which accuracy NN models can approximate the 3D ideal-MHD solution operator and reconstruct equilibrium properties of interest, and it suggests how they might be used to optimize stellarator magnetic configurations.Comment: 46 pages, 23 figures, to be submitted to Nuclear Fusio

Brown rot-type fungal decomposition of sorghum bagasse: variable success and mechanistic implications

Sweet sorghum is a promising crop for a warming, drying African climate, and basic information is lacking on conversion pathways for its lignocellulosic residues (bagasse). Brown rot wood-decomposer fungi use carbohydrate-selective pathways that, when assessed on sorghum, a grass substrate, can yield information relevant to both plant biomass conversion and fungal biology. In testing sorghum decomposition by brown rot fungi (Gloeophyllum trabeum, Serpula lacrymans), we found that G. trabeum readily degraded sorghum, removing xylan prior to removing glucan. Serpula lacrymans, conversely, caused little decomposition. Ergosterol (fungal biomarker) and protein levels were similar for both fungi, but S. lacrymans produced nearly 4x lower polysaccharide-degrading enzyme specific activity on sorghum than G. trabeum, perhaps a symptom of starvation. Linking this information to genome comparisons including other brown rot fungi known to have a similar issue regarding decomposing grasses (Postia placenta, Fomitopsis pinicola) suggested that a lack of CE 1 feruloyl esterases as well as low xylanase activity in S. lacrymans (3x lower than in G. trabeum) may hinder S. lacrymans, P. placenta, and F. pinicola when degrading grass substrates. These results indicate variability in brown rot mechanisms, which may stem from a differing ability to degrade certain lignincarbohydrate complexes

Coarse woody debris decomposition assessment tool: Model development and sensitivity analysis

Coarse woody debris (CWD) is an important component in forests, hosting a variety of organisms that have critical roles in nutrient cycling and carbon (C) storage. We developed a process-based model using literature, field observations, and expert knowledge to assess woody debris decomposition in forests and the movement of wood C into the soil and atmosphere. The sensitivity analysis was conducted against the primary ecological drivers (wood properties and ambient conditions) used as model inputs. The analysis used eighty-nine climate datasets from North America, from tropical (14.2° N) to boreal (65.0° N) zones, with large ranges in annual mean temperature (26.5°C in tropical to -11.8°C in boreal), annual precipitation (6,143 to 181 mm), annual snowfall (0 to 612 kg m-2), and altitude (3 to 2,824 m above mean see level). The sensitivity analysis showed that CWD decomposition was strongly affected by climate, geographical location and altitude, which together regulate the activity of both microbial and invertebrate wood-decomposers. CWD decomposition rate increased with increments in temperature and precipitation, but decreased with increases in latitude and altitude. CWD decomposition was also sensitive to wood size, density, position (standing vs downed), and tree species. The sensitivity analysis showed that fungi are the most important decomposers of woody debris, accounting for over 50% mass loss in nearly all climatic zones in North America. The model includes invertebrate decomposers, focusing mostly on termites, which can have an important role in CWD decomposition in tropical and some subtropical regions. The role of termites in woody debris decomposition varied widely, between 0 and 40%, from temperate areas to tropical regions. Woody debris decomposition rates simulated for eighty-nine locations in North America were within the published range of woody debris decomposition rates for regions in northern hemisphere from 1.6° N to 68.3° N and in Australia

Atrophin-1, the Dentato-Rubral and Pallido-Luysian Atrophy Gene Product, Interacts with Eto/Mtg8 in the Nuclear Matrix and Represses Transcription

Dentato-rubral and pallido-luysian atrophy (DRPLA) is one of the family of neurodegenerative diseases caused by expansion of a polyglutamine tract. The drpla gene product, atrophin-1, is widely expressed, has no known function or activity, and is found in both the nuclear and cytoplasmic compartments of neurons. Truncated fragments of atrophin-1 accumulate in neuronal nuclei in a transgenic mouse model of DRPLA, and may underlie the disease phenotype

Coarse Woody Debris Decomposition Assessment Tool: Model Validation and Application

Coarse woody debris (CWD) is a significant component of the forest biomass pool; hence a model is warranted to predict CWD decomposition and its role in forest carbon (C) and nutrient cycling under varying management and climatic conditions. A process-based model, CWDDAT (Coarse Woody Debris Decomposition Assessment Tool) was calibrated and validated using data from the FACE (Free Air Carbon Dioxide Enrichment) Wood Decomposition Experiment utilizing pine (Pinus taeda), aspen (Populous tremuloides) and birch (Betula papyrifera) on nine Experimental Forests (EF) covering a range of climate, hydrology, and soil conditions across the continental USA. The model predictions were evaluated against measured FACE log mass loss over 6 years. Four widely applied metrics of model performance demonstrated that the CWDDAT model can accurately predict CWD decomposition. The R2 (squared Pearson’s correlation coefficient) between the simulation and measurement was 0.80 for the model calibration and 0.82 for the model validation (P\u3c0.01). The predicted mean mass loss from all logs was 5.4% lower than the measured mass loss and 1.4% lower than the calculated loss. The model was also used to assess the decomposition of mixed pine-hardwood CWD produced by Hurricane Hugo in 1989 on the Santee Experimental Forest in South Carolina, USA. The simulation reflected rapid CWD decomposition of the forest in this subtropical setting. The predicted dissolved organic carbon (DOC) derived from the CWD decomposition and incorporated into the mineral soil averaged 1.01 g C m-2 y-1 over the 30 years. The main agents for CWD mass loss were fungi (72.0%) and termites (24.5%), the remainder was attributed to a mix of other wood decomposers. These findings demonstrate the applicability of CWDDAT for large-scale assessments of CWD dynamics, and fine-scale considerations regarding the fate of CWD carbon