OUP user menu

Competition between two wood-degrading fungi with distinct influences on residues

Zewei Song, Andrew Vail, Michael J. Sadowsky, Jonathan S. Schilling
DOI: http://dx.doi.org/10.1111/j.1574-6941.2011.01201.x 109-117 First published online: 1 January 2012


Many wood-degrading fungi colonize specific types of forest trees, but often lack wood specificity in pure culture. This suggests that wood type affects competition among fungi and indirectly influences the soil residues generated. While assessing wood residues is an established science, linking this information to dominant fungal colonizers has proven to be difficult. In the studies presented here, we used isolate-specific quantitative PCR to quantify competitive success between two distinct fungi, Gloeophyllum trabeum and Irpex lacteus, brown and white rot fungi, respectively, colonizing three wood types (birch, pine, oak). Ergosterol (fungal biomass), fungal species-specific DNA copy numbers, mass loss, pH, carbon fractions, and alkali solubility were determined 3 and 8 weeks postinoculation from replicate wood sections. Quantitative PCR analyses indicated that I. lacteus consistently outcompeted G. trabeum, by several orders of magnitude, on all wood types. Consequently, wood residues exhibited distinct characteristics of white rot. Our results show that competitive interactions between fungal species can influence colonization success, and that this can have significant consequences on the outcomes of wood decomposition.

  • fungi
  • qPCR
  • wood decay
  • competition
  • Gloeophyllum trabeum
  • Irpex lacteus


Wood decomposition is a unique capacity among microorganisms and is accomplished in temperate forests primarily by distinct groups of fungi (Eriksson et al., 1990). Fungi causing white or brown rot represent the two principal types of fungi that decompose woody substrates. While white rot fungi degrade lignin, often simultaneously with wood cellulose and hemicellulose, brown rot fungi remove relatively little lignin and extract cellulose and hemicellulose, producing brown lignin-rich residues. Humic residues derived from white and brown rot fungi have different metal-binding capacities, redox reactions, permeability, soil sorption characteristics, and forest floor residence times, and each of these factors can influence the breakdown of other pools of soil organic matter (Rypáček & Rypáčková, 1975; Gilbertson, 1980; Zabel & Morrell, 1992; Jurgensen et al., 1997; Filley et al., 2002). Consequently, colonization success among wood-degrading fungi has important consequences for soils and carbon release.

Factors like wood type, fungal germination success, synergism, and antagonism likely play roles in fungal colonization and the overall rate of wood decomposition, in addition to temperature and moisture (Boddy & Heilmann-Clausen, 2008). In laboratory trials, wood-degrading fungi often exhibit metabolic flexibility, degrading nonhost woods and nonwoody plant tissues as efficiently as their normal wood substrates (e.g. Valášková & Baldrian, 2006). In forests, however, wood-degrading fungi are often associated with specific wood types, and this is reflected in many species names (e.g. Piptoporus betulinus is found primarily on Betula papyrifera) (Gilbertson, 1981). There are also large-scale associations between brown rot fungi and conifers, and between white rot fungi and angiosperms (Gilbertson, 1980; Hibbett & Donoghue, 2001). While these fungus–wood correlations are far from absolute, the predictability of the presence of specific sporophores on individual wood species suggests that wood type has a major influence on the competitive success of individual fungi among a diversity of wood-colonizing fungi.

Methods for assessing wood-degrading fungi in situ vary in their ability to provide functionally relevant information. Morphological identification requires expertise, and isolating and culturing fungi from wood typically reveals a small fraction of the fungi present (Tringe et al., 2005). Active and total fungal biomass in wood can be calculated using ergosterol (Newell et al., 1988) and chitin assays (Ekblad & Nasholm, 1996), but these techniques are not specific to fungal taxa. Molecular approaches can better resolve which fungi are present, but, at present, have difficulty in weighting the presence of specific taxa relative to others present. Phospholipid fatty acid analysis (Frostegard et al., 1993), denaturing gradient gel electrophoresis (Muyzer et al., 1993), randomly amplified polymorphic DNA (Groppe et al., 1995; Marzorati et al., 2008), and carbon source utilization profiling (Spears et al., 2003) can ‘fingerprint’ communities, but richness measures provide little insight into functional diversity.

In the studies reported here, isolate-specific quantitative PCR (qPCR) was used to examine fungal colonization success as a function of wood type. Physiochemical analyses of the resulting residues generated from decay were used to qualify fungus-specific outcomes and as a benchmark for confirming qPCR results, most notably using dilute alkali solubility (DAS). Three wood species were examined and at least one treatment per fungus (brown and white rot isolates) included a normal ‘host’ wood (a common natural association, for example, Gloeophyllum trabeum on pine).

Material and methods

Fungal isolates

The brown rot fungus, G. trabeum (Persoon: Fries) Karsten strain M617 (ATCC 11539), and the white rot fungus, Irpex lacteus (Fries: Fries) Fries strain M517 (ATCC 11245), were used in this study. Both fungi are native to, and commonly found in, Minnesota (USA). Irpex lacteus is often found fruiting on angiosperm woods, such as alder and birch, whereas G. trabeum can be isolated from angiosperm woods or conifers, such as spruce or pine, or on softwood lumber (Gilbertson & Ryvarden, 1988). Both fungi were isolated from a single forest plot in Cloquet, MN, during this experiment. Fungi were maintained in a culture collection at the University of Minnesota, using agar slants with pine or birch wafers for periodic culturing and maintenance of lignolytic activity. For this study, isolates were maintained in the dark at 25 °C on 20 mL of malt extract agar. Soil-block microcosms were inoculated with round agar plugs (38 mm2 with a diameter of 7 mm) of equal agar thicknesses, obtained from within the hyphal margin, from 14-day-old cultures.

Soil-block microcosms

Modified soil-block microcosms (ASTM D 1413, 2007) were used to study wood colonization and competitive interactions among fungal species (Fig. ). Soil-block jars (7 cm ID × 12 cm height) contained a 1 : 1 : 1 wetted mixture of peat (Conrad Fafard Inc., MA), vermiculite (Good Earth Horticulture Inc., NY), and fertilizer-free soil mix (Gertens, Inver Grove Heights, MN). Birch feeder strips (2 × 5 cm) were placed onto the surface of the soil mixture, autoclaved twice for 1 h with a 48 h interval, and inoculated with plugs of fungi; a single fungus species (two plugs per strip – four total plugs) or both fungal species in mixed-fungus competitive treatments (two plugs of a species on the same strip – two strips for two fungi). A 5-mm gap was left between parallel birch feeder strips, and a small trench (c. 5 mm deep) was excavated in the soil between the feeder strips. Fungi were grown for 7 days at 25 °C, in the dark, to the edge of the feeder strips without meeting each other in the soil trench. By later adding wooden dowels to span the trench, isolates colonized wood simultaneously on opposite sides of dowels before encountering each other.

Soil-block microcosm used for these experiments. a1 : 1 : 1 peat, vermiculite, fertilizer-free potting soil; bwooden dowels consisting of oak, pine, or birch; cGloeophyllum trabeum (brown rot fungus) and Irpex lacteus (white rot fungus). dCharacterization included mass loss, carbon fractions, alkali solubility, and pH; eergosterol content = fungal biomass.

Three matched wooden dowel sections (2 cm long × 1.5 cm dia) per wood species were added along the groove between the feeder strips. A space was left between each dowel section to allow fungal access to cross-sectional faces. Sapwood dowels of white birch (B. papyrifera), red oak (Quercus rubra), and pine (Pinus sp. southern yellow pine) were the substrate treatments. Oak and birch dowels were purchased locally, while pine dowels were shaped from strips using a bullnose router bit. Pine was selected because it is a natural ‘host’ wood for G. trabeum, while I. lacteus is rarely found on southern pine, but more commonly on hardwoods like birch and oak. Dowels were initially cut into 6-cm lengths and then into three matched 2-cm lengths to reduce wood chemistry variability among dowels within a jar. These sections were oven-dried (48 h, 100 °C), weighed, and autoclaved for 1 h prior to adding to jars.

Fungus treatments included feeder strips inoculated with pure cultures of each fungus alone or as mixed inocula containing both fungi. Each fungus treatment with each wood type was replicated 10 times, giving five replicates (n = 5) for each of two harvests at incubation times of 3 and 8 weeks postinoculation. Control microcosms, which lacked fungal inoculum treatments, provided baseline measurements used for wood characterization and as negative controls for PCR. Microcosms were incubated at 25 °C in the dark. At each harvest period, one dowel section from each replicate microcosm was ground fresh, without drying, to 40-mesh in a Wiley mill, and added to cold methanol (0.4 g wet weight wood per 5 mL) for ergosterol measurements. A second section was flash-frozen in liquid nitrogen, ground for 30 s into a fine powder using a Midas Rex bone mill (Medtronic, Inc, Minneapolis, MN), assessed for moisture content, and stored at −70 °C. The bone mill uses autoclavable teflon cups containing dual steel blades. Cups were modified by sharpening the blunt 90° leading edge of the lower blade to a 45° blade angle. Between each grinding, the teflon cup was washed with 95% ethanol and diluted with liquid Luminox (Alconox, Jersey City, NJ) to remove DNA residue without damaging milling cups. The third dowel section was oven-dried to calculate mass loss and to characterize residue chemistry.

Ergosterol measurements

Wood dowel material was extracted in methanol as described by Newell et al. (1988). Methanol-extracted samples (5 mL per 15 mL tube) were refluxed, saponified with 4% KOH in ethanol, and extracted into pentane for precipitation and dissolution back into MeOH. Samples were extracted and analyzed for ergosterol using high-performance liquid chromatography as described by Schilling & Jellison (2005).

DNA isolation

Fungal DNA was isolated from fresh mycelia and inoculated wood blocks (birch, oak, and pine) as previously described (Jasalavich et al., 2000), with slight modifications. Wood blocks colonized by fungi were ground to fine powder using the Midas Rex bone mill. Aliquots (150–550 mg) of the resulting wood powder were added to 50-mL conical tubes and resuspended in 6 mL of 1× CTAB buffer (Doyle & Doyle, 1987). The DNA was precipitated overnight at −20 °C with 0.6 volume of isopropanol, washed with 70% ethanol, dried in vacuo, and resuspended in 100 μL of nuclease-free water (Ambion, Austin, TX). DNA concentrations in samples were determined using a Qubit™ fluorometer (Invitrogen, Carlsbad, CA) and adjusted to final concentrations of 1.5 ng μL−1. DNA samples were stored at −20 °C until used.

Primer design for PCR

Primers for PCR were designed to specifically amplify a portion of the ITS region from G. trabeum and I. lacteus. The following published nucleotide sequences were aligned using MultAlin software (Corpet, 1988; http://multalin.toulouse.inra.fr/multalin/multalin.html): G. trabeum (accession AF423117), G. trabeum strain 900.73 (AY673077), G. trabeum strain BAM Ebw.109 (EF524032), G. trabeum isolate 259 (AJ420950), G. trabeum isolate 183 (AJ420949), I. lacteus isolate XSD-2 (EU273517), and I. lacteus isolate MAFF 420244 (AB079267). Potential forward and reverse primer pairs were manually chosen based on variations between the G. trabeum and I. lacteus nucleotide sequences within the ITS region. Primer pairs were examined for compatible melting temperatures and decreased secondary structures using Net Primer software (PREMIER Biosoft Internationl, Palo Alto, CA; http://www.premierbiosoft.com/netprimer/). Primers: GT94-F (5′-TCA GGC TGT CCT TCC TAT GTC-3′) and GT521-R (5′-GTC AAA TTG TCC GAA GAC G-3′) were developed to amplify a 427-bp DNA fragment from G. trabeum, whereas primers IL54-F (5′-ATC GAG TTT TGA ACG GGT TG-3′) and IL633-R (5′-AAA TGA TTG TCT CGG CAA GG-3′) were constructed to amplify a 579-bp DNA fragment from I. lacteus. The primers were synthesized by Integrated DNA Technologies (Coralville, IA).

Conventional PCR

Conventional PCR was used to detect cross-amplification between each fungal species. The amplification reaction (25 μL) contained 50 μM (each) dNTPs, 0.25 μM of each primer, 1× Taq buffer, and 1 U Choice-Taq DNA polymerase (Denville Scientific Inc., Metuchen, NJ). PCR was performed using a MyCycler thermocycler (Bio-Rad, Hercules, CA) using the following reaction conditions to detect G. trabeum: 95 °C for 5 min, and 35 cycles of 95 °C for 30 s, 58 °C for 30 s, and 72 °C for 1 min, and a final extension at 72 °C for 5 min. The same thermocycler program was used to detect I. lacteus, except the annealing temperature was increased to 60 °C. PCR products were separated by electrophoresis for 1 h at 100 V on 1% agarose gels in 0.5× TBE buffer containing 0.5 μg mL−1 ethidium bromide. A 1-kb Plus DNA Ladder (Invitrogen) was used to determine sizes of the PCR products.

Quantitative real-time PCR

Template DNAs for making standard curves were PCR products of the ITS region of G. trabeum and I. lacteus produced using primers GT94-F and GT521-R and primers IL54-F and IL633-R, respectively. The fungal ITS PCR fragments were cloned into the StrataClone PCR cloning vector, pSC-A-amp/kan, using the StrataClone PCR Cloning kit (Stratagene, La Jolla, CA), resulting in constructs, pSGT and pSIL for the cloned PCR fragment amplified from G. trabeum and I. lacteus, respectively. Plasmids were isolated using the QIAprep Spin Miniprep kit (Qiagen, Valencia, CA) according to the manufacturer's protocol, and each contained a single copy of the inserted DNA fragments as determined using conventional PCR with the amplification protocol described earlier. The concentration of plasmid DNAs was determined using a Qubit™ fluorometer.

Real-time, quantitative PCR amplification of the standard templates pSGT and pSIL and sample DNAs was performed using the ABI Prism™ 7000 sequence detection system (Applied Biosystems, Foster City, CA). Quantitative amplification of plasmid template DNAs (10-fold dilutions of 101–106 copies) or 4.5 ng of sample DNA was conducted in reaction wells containing a total volume of 40 μL. Triplicate measurements of each standard concentration were made. Reactions contained 400 nM of each forward and reverse primers, and 20 μL of 2× iTaq™ SYBR® Green Supermix with ROX (Bio-Rad). All reactions were performed in triplicate, and each run contained replicate nontemplate controls. The thermal cycling conditions for DNA amplification from I. lacteus were an initial denaturation at 95 °C for 10 min, followed by 40 cycles at 95 °C for 15 s, 60 °C for 30 s, and 72 °C for 1 min. A similar thermal cycling protocol was used for G. trabeum detection, except the annealing temperature was reduced to 58 °C. Dissociation curve analysis was performed postPCR on all plates. All raw data were analyzed using 7000 system sequence detection software (Applied Biosystems), version 1.2.3. The average slope for G. trabeum and I. lacteus standard curves was −3.32 (n = 6) and −3.25 (n = 4), respectively, with the r2 of all fits > 0.993. The PCR efficiencies of the plates ranged between 97–109% for I. lacteus and 90–105% for G. trabeum. The DNA quantity, or copy number, obtained from the quantitative cycle (Cq) from the real-time PCR assays was normalized to total DNAs and dry wood weight. Differences in fluorescence emission because of variability in DNA fragment length were insignificant in this study and did not require standardization of signal. Assessment of the potential for PCR inhibition in DNA extracts from colonized wood samples was performed in two random week 8 samples from each wood type cultured with either G. trabeum or I. lacteus. A 4.5 ng of sample DNAs was spiked with 105 copies of the standard DNA template of the same type of fungus (pSGT or pSIL). Triplicate qPCR runs for each fungus/wood combination demonstrated no significant effects on recovery of the DNA spike.

Extraction efficiency

As wood particles and liquid nitrogen may influence ergosterol determinations and yields of fungal DNA, the extraction efficiency of each fungus from pure culture and from inoculated fungus–wood combinations was assessed, as well as extracting from noninoculated control wood. Fungi were grown on basal salts medium (Highley, 1973), mixed with fresh wood to create samples with known fungal density, and samples were flash-frozen in liquid nitrogen and ground using the Midas Rex bone mill. Extracted DNA and ergosterol concentrations from these samples were compared with those obtained following extraction of pure cultures, and extraction efficiencies were calculated as the ratio of DNA and ergosterol concentrations from pure fungus to those obtained from fungus–wood sample (Table ). Although imperfect, mixing hyphae with wood as opposed to calculating extraction efficiency from colonized wood avoids assessments of ergosterol or chitin or measurements of mass change of colonized wood. These approaches either require their own extraction efficiency estimates, to infer biomass within an inoculated wood sample, or are complicated by mass loss in the wood along with fungal weight gain after colonization.

View this table:

DNA and ergosterol extraction efficiencies from different wood types

FungusWoodDNA (ng mg−1 dry fungus)Extraction efficiency of DNAErgosterol (μg mg−1 dry fungus)Extraction efficiency of ergosterol
G. trabeumn/a432.1n/a8.83n/a
I. lacteusn/a41.1n/a4.39n/a
  • From liquid-cultured fungus, frozen in liquid nitrogen and ground.

  • From liquid-cultured fungus, added fresh and extracted in MeOH.

  • From mixture of liquid-cultured fungus and wood, frozen and ground.

Wood characterization

Mass loss and change in wood specific gravity were calculated in single blocks by measuring oven dry weight lost during decay. Samples were ground to 60-mesh in the Wiley mill after determining postdecay weight and stored over CaSO4 desiccant. Carbon fractions (w/w) were determined for cellulose (glucan), for hemicellulose (arabinan, galactan, glucan, mannan, and xylan) carbohydrates, and for acid-soluble Klason lignin, as previously described (Schilling et al., 2009). The pH and DAS of decayed and nondecayed wood samples were determined following Shortle et al. (2010). The DAS is an indirect measure of decay extent and, at a similar mass loss, a proxy for decay type (DAS increases during brown rot, while staying similar to control wood during white rot) in both cases by gauging concentration of low-molecular-weight carbohydrates (hemicellulose and hydrolyzed cellulose). For DAS, wood powder was autoclaved in 0.2 M NaOH, filtered through a tared fritted glass crucible, and rinsed with distilled water and 0.1 M HNO3. The percent loss on extraction (LOE%) was calculated by weighing extracted materials. For pH determinations, wood powder was equilibrated in 5 mM CaCl2 at a ratio of 0.1 mg μL−1.

Statistical analyses

Data are expressed as means and standard error (SE). Analysis of variance (anova) (α = 0.05) was used for Tukey's means comparisons, using wood types as individual cases and after log-transforming data requiring normalization. Lignin, carbohydrate, ergosterol, and fungal biomass were normalized both as percent-of-original content and as weight-to-original volume using weight loss and wood density. The ratio of copy number between I. lacteus and G. trabeum in single and mixed treatments was calculated, as the comparison of absolute ITS copy numbers between two fungal species fails to provide a meaningful comparison. The variances of copy number ratio of single treatments were calculated based on delta method according to Cox (1990). The copy number ratios were tested for difference with two-sample t-tests (α = 0.05).

Results and discussion

Mass loss of wood degraded by the tested fungal isolates for 8 weeks was greater for the brown rot fungus G. trabeum than for the white rot fungus I. lacteus, and was greatest (nearly 50%) for G. trabeum grown on pine (Fig. a). Mass loss was statistically different between the fungi when colonizing birch and pine (P ≤ 0.05 for both wood types), but not when degrading oak (P = 0.420). Mass loss in wood colonized by both fungi (mixed), in degraded birch and pine, was similar to, and not statistically different from, mass loss in wood degraded by the single I. lacteus inoculum.

Characteristics of decay residues in three wood types after 8 weeks of decay by Gloeophyllum trabeum, Irpex lacteus, or a mixture of the two fungi. The data are means and SEs (n = 5). (a) Mass loss (as % of original dry weight) after 3 and 8 weeks. The mass loss after 3 weeks is shown inside the bars of week 8 samples. The result of multiple comparison of week 3 samples was not shown. (b) Lignin loss (as weight to original volume). (c) Carbohydrate loss (as weight to original volume). (d) Wood pH, error bars for pH are asymmetrical, calculated from [H+]. (e) DAS.

Similar to mass loss data, each of the wood residue characteristics measured from the mixed-fungus inoculations resembled I. lacteus values more than they resembled those measured in G. trabeum residues. This was true for lignin and carbohydrate contents (% original) (Table ), lignin removal in oak, carbohydrate removal in all wood types (per wood volume) (Fig. b and c), wood acidification, the alkali solubility of the residues (Fig. d and e), and wood moisture contents at the time of harvest. White rot residues, generated in all cases in the mixed-fungus treatments, are known to impart unique humic chemistries on the forest floor and different CO2 emission rates, relative to brown rot residues (Gilbertson, 1980; Harmon et al., 1986).

View this table:

Lignin and carbohydrates content of wood after 8 weeks (percentage of initial weight, %)

Wood typesFungus typesLigninCarbohydrates
GlucoseXyloseGalactoseArabinoseMannoseTotal carbohydrates
OakControl27.3 (0.2)b41.2 (0.2)a11.7 (0.2)a0.7 (0.1)e0.7 (0.1)bc4.7 (0.1)c59.1 (0.5)ab
G. trabeum27.0 (0.6)b22.6 (3.4)de2.3 (0.2)g3.2 (0.2)b0.2 (0.02)c1.0 (0.3)de29.3 (3.3)fg
I. lacteus21.6 (1.3)cd32.1 (1.6)bc4.7 (1.2)cdefg0.7 (0.1)e1.9 (0.3)a1.3 (0.2)de40.8 (2.1)de
Mixed19.9 (1.6)d27.3 (1.7)cd6.4 (1.6)bcde0.3 (0.1)e1.8 (0.3)a2.1 (0.2)d38.0 (3.2)ef
BirchControl32.9 (0.1)a45.0 (0.3)a9.3 (0.2)ab0.3 (0.02)e0.3 (0.04)c1.5 (0.1)de56.4 (0.5)abc
G. trabeum25.6 (0.6)bc18.7 (1.1)e3.5 (0.1)efg1.7 (0.2)d0.2 (0.1)c0.4 (0.1)e24.5 (1.1)g
I. lacteus24.7 (0.3)bc40.4 (2.2)a6.5 (0.6)bcd0.4 (0.1)e0.4 (0.1)c0.8 (0.2)e48.6 (3.0)cd
Mixed24.5 (0.3)bc38.8 (0.5)ab7.3 (0.2)bc0.5 (0.1)e0.4 (0.04)c1.3 (0.1)e48.4 (0.4)cd
PineControl33.0 (0.3)a41.1 (0.7)a5.5 (0.1)cdef5.0 (0.2)a1.1 (0.04)b8.9 (0.2)a61.6 (1.2)a
G. trabeum23.9 (0.6)bc17.3 (2.3)e2.9 (0.2)fg2.4 (0.2)c0.3 (0.02)c4.3 (0.3)c27.1 (2.5)g
I. lacteus22.9 (1.5)cd31.3 (1.6)bc3.4 (0.2)fg0.4 (0.1)e0.4 (0.04)c7.3 (0.2)b42.8 (2.0)de
Mixed24.6 (0.9)bc37.8 (1.1)ab3.7 (0.2)defg0.6 (0.05)e0.3 (0.03)c7.2 (0.6)b49.5 (1.6)bcd
  • Numbers in the parentheses are SEs of the means (n = 5). Letters indicate significant difference between two means (Tukey HSD, P ≤ 0.05) for each column.

The ergosterol contents of week 3 and 8 samples did not show an obvious pattern of biomass accumulation (Fig. ), after compensating for mass loss (per wood volume) and applying extraction coefficiency to degraded wood samples. Because ergosterol includes a large fraction of active biomass, this is not surprising at these decay stages when colonizing fungi are likely recycling their own biomass toward a unified decay front (Klein & Paschke, 2004). Ergosterol levels matched those of I. lacteus in each case with the exception of oak, where ergosterol levels of the mixed-fungus treatment matched G. trabeum levels and not those of I. lacteus. The ergosterol to biomass ratio also differed twofold in G. trabeum and I. lacteus (Table ), indicating that caution is needed when measuring ergosterol in samples with mixed-fungal species.

Ergosterol content (as weight to original volume) after 3 and 8 weeks of decay by Gloeophyllum trabeum, Irpex lacteus, or a mixture of the two fungi. The data are means and SEs (n = 5).

Quantitative PCR analyses of wood blocks inoculated with both fungi revealed that I. lacteus was the dominant fungus by week 3 on all wood types tested (Fig. ). Gloeophyllum trabeum, however, remained detectable throughout the incubation period. All of the I. lacteus-to-G. trabeum copy number ratios in mixed treatments were significantly greater (P ≤ 0.05) than their single-treatment counterparts, except for the week 8 oak sample. This was likely due to high variability among replicates, as the average ratio of mixed oak treatment was 300 times than that of the single treatment. However, the dominance of white rot in week 8 oak was confirmed by wood characterization analyses described earlier. This indicates that the wood characterization method provides complementary data for molecular analyses. The ITS copy number ratio method used in this study eliminated problems, because of difference in DNA extraction efficiency between wood types and ITS copy number variation in the genomes of the two fungal species. The copy number ratio method was previously used to compare the biomass of fungi and bacteria (Fierer et al., 2005; Graaff et al., 2010).

Irpex lacteus-to-Gloeophyllum trabeum ITS copy number ratio of single and mixed treatments after 3 and 8 weeks. The data are means and SEs (n = 5). *Significant differences (P ≤ 0.05) between the ratio of single and mixed treatments.

These results link the dominant biomass component of I. lacteus to certain outcomes of white rot in residues over a relatively large volume of wood. Typically, PCR-based approaches have been used to detect pest or pathogenic decay of fungi in wood, using subsampling with drill bits or pulverization of very small wood fragments (Kim et al., 1999; Jasalavich et al., 2000; Guglielmo et al., 2007, 2010). Minimizing destructive sampling is important when sampling lumber or living trees. In our case, however, we needed to assess the contribution of individual fungi in a mixed-species environment occupying a larger wood volume than a drill bit, and thus required whole-block milling of fresh samples and without DNA carryover issues and with a reliable extraction protocol. By thoroughly characterizing the relationships between DNA copy number, ergosterol, and mycelial biomass, along with extraction efficiencies from wood and residue characters that distinguish brown from white rot, one can begin to make a connection between wood residues and the fungi responsible for producing them. Importantly, despite inclusion of a range of wood species for each fungus, we were able to establish that there was only a small influence of wood type on fungal competitive success in the test microcosms inoculated with these two co-existing fungi.

Based on other studies and on-field guides, one can argue that associations between wood-degrading fungi and woody substrates are generally not rigid. Substrate specificity in a tropical sporophore study was weak among 32 wood-degrading fungi (only 9% with specificity) (Lindblad, 2000). Shaw (1973) created a host fungus index for specific tree types and found the number of different potential wood-rotting fungal species colonizing a given wood type ranged from 102 to 241. Similar examples can be seen in the Pacific Northwest Fungi Database (http://pnwfungi.wsu.edu).

One surprising result of this study was that I. lacteus so successfully colonized and degraded pine conifer wood in the mixed-fungus treatment, despite knowing that it would rarely be isolated from pine in the field (Gilbertson & Ryvarden, 1988). One explanation is that I. lacteus simply colonized more of each wood dowel than G. trabeum, growing faster in this particularly stable, moist environment. Assembly history can affect fungal community structure and decay rate in wood (Fukami et al., 2010), as can pre-colonization by pathogenic Trichoderma spp. (Bruce & Highley, 1991). Other explanations for the lack of competitive success of G. trabeum include use of bark-free wood blocks, temperature, moisture and heartwood content, and a simplified microbial community structure. While the influence of bark was negligible in a white rot and brown rot fungal spore trial by Tsuneda & Kennedy (1980), the presence of bark (causing hydrophobic encapsulation) along with naturally fluctuating temperature and moisture may affect competition among fungi with distinct moisture and temperature optima. Heartwood also contains phenolics and other water- or solvent-extractable fungitoxic compounds, and tolerance to these wood extractives has long been known to vary among decay fungi (Scheffer & Cowling, 1966). It seems more likely, however, that controlled-inoculum microcosms may not best reflect how competition, nor microbial succession, would proceed in a naturally diverse microbial community, collectively influenced by environment. Even if priority effect is a strong determinant of the rate of wood decomposition, it remains important to explain common fungus–wood associations and their consequence over longer time frames on both rate and character of decay. Therefore, scaling this approach to field decomposition studies, similar to the PCR-based competitive trial among ectomycorrhizal fungi (Kennedy et al., 2007, may lend important insight into long-term drivers of competition among fungi colonizing forest woody debris.


With a range of wood substrate options, the white rot fungus I. lacteus dominated each competition with the brown rot fungus G. trabeum and, consequently, dominated the character of humic residues generated. This demonstrates coupling qPCR with residue physiochemistry analyses, useful to track the influence of individual fungi within complex microbial consortia, and suggests that factors other than simple wood anatomy influence substrate-selectivity and competitive outcomes among wood-degrading fungi.


This research was made possible through the generous support of the Conservation and the Environment grants program of The Andrew W. Mellon Foundation (New York, NY). We also thank the University of Minnesota Graduate School for Grant-in-aid of Research, Artistry and Scholarship funding in the initial stages of method development.


  • Editor: Max Häggblom


View Abstract