Molecular Ecology (2014) 23, 4406–4417
Contrasting soil fungal community responses to experimental nitrogen addition using the large subunit rRNA taxonomic marker and cellobiohydrolase I functional marker R E B E C C A C . M U E L L E R , M O N I C A M . B A L A S C H and C H E R Y L R . K U S K E Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Abstract Human activities have resulted in increased nitrogen inputs into terrestrial ecosystems, but the impact of nitrogen on ecosystem function, such as nutrient cycling, will depend at least in part on the response of soil fungal communities. We examined the response of soil fungi to experimental nitrogen addition in a loblolly pine forest (North Carolina, USA) using a taxonomic marker (large subunit rDNA, LSU) and a functional marker involved in a critical step of cellulose degradation (cellobiohydrolase, cbhI) at five time points that spanned fourteen months. Sampling date had no impact on fungal community richness or composition for either gene. Based on the LSU, nitrogen addition led to increased fungal community richness, reduced relative abundance of fungi in the phylum Basidiomycota and altered community composition; however, similar shifts were not observed with cbhI. Fungal community dissimilarity of the LSU and cbhI genes was significantly correlated in the ambient plots, but not in nitrogen-amended plots, suggesting either functional redundancy of fungi with the cbhI gene or shifts in other functional groups in response to nitrogen addition. To determine whether sequence similarity of cbhI could be predicted based on taxonomic relatedness of fungi, we conducted a phylogenetic analysis of publically available cbhI sequences from known isolates and found that for a subset of isolates, similar cbhI genes were found within distantly related fungal taxa. Together, these findings suggest that taxonomic shifts in the total fungal community do not necessarily result in changes in the functional diversity of fungi. Keywords: cellulose decomposition, fungi, nitrogen deposition, pine forest Received 4 September 2013; revision received 30 June 2014; accepted 9 July 2014
Introduction Nitrogen deposition has increased threefold to fivefold over the last century due to human activities (Vitousek et al. 1997), and inputs from anthropogenic sources now exceed those from natural inputs (Gruber & Galloway 2008). Changes in nitrogen concentration could have large-scale impacts on ecosystems by altering biogeochemical cycles. In particular, increased nitrogen has been shown to have large effects on carbon cycling, Correspondence: Cheryl R. Kuske, Fax: 505-667-3024; E-mail: [email protected]
often resulting in increased carbon accumulation in ecosystems (Magnani et al. 2007; Fornara & Tilman 2012). Increased carbon storage in terrestrial systems can be attributed to both above- and belowground responses, from higher levels of aboveground net primary productivity (LeBauer & Treseder 2008) and decreased rates of soil respiration (Janssens et al. 2010), respectively. These changes are likely linked to shifts in soil fungal and bacterial communities, the primary drivers of plant matter decomposition in terrestrial ecosystems (van der Heijden et al. 2008). Previous studies have shown that changes in soil carbon cycling belowground were correlated with shifts in microbial biomass
Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
S O I L F U N G A L C O M M U N I T Y R E S P O N S E T O N I T R O G E N 4407 (Treseder 2008) and enzyme activities (Carreiro et al. 2000). Studies examining shifts in microbial communities commonly employ molecular surveys, often by targeting phylogenetically informative genes, such as ribosomal (rRNA) genes. While these markers can provide insights into how biodiversity and composition will respond to environmental change, they may not accurately reflect functional shifts that underlie changes in ecosystem functions, such as decomposition. An alternate approach is to target genes that encode enzymes involved in decomposition (functional markers) that may be more directly linked to ecosystem processes (e.g., Philippot et al. 2013). In soils, multiple enzyme systems are involved in decomposition (Carreiro et al. 2000), but cellulose comprises up to 75% of plant material, and the activity of cellulose-degrading enzymes has been shown to respond to nitrogen addition (Frey et al. 2004; Sinsabaugh et al. 2005; Keeler et al. 2008). The rate-limiting step in cellulose degradation, the depolymerization of cellulose to cellobiose, is controlled by the cellobiohydrolase I enzyme (CBH), which is encoded by the cbhI gene (Baldrian & Valaskov a 2008; Edwards et al. 2008). The diversity of cbhI genes has been shown to correlate with shifts in CBH activity (Fan et al. 2012), which in turn has been linked to altered rates of decomposition in soil (Allison & Vitousek 2004). As a result, targeted analysis of cbhI could provide insights into interactions between nitrogen deposition and carbon cycling driven by fungi. We investigated the impact of 9–10 years of experimental nitrogen amendment on soil fungal community richness and composition at the Duke Forest free air CO2 enrichment (FACE) site (North Carolina, USA), located within a loblolly pine forest. We used targeted sequencing of the large subunit ribosomal RNA gene (LSU) as a taxonomic marker and the cbhI gene as a functional marker. A previous study at this site found no significant effect of nitrogen on the CBH enzyme, but seasonal shifts in enzyme activities have been shown in other systems (Vorıskova et al. 2014). The study was conducted using soils collected over five time points spanning 14 months. Although many studies have been conducted using single time points, fungal communities have been shown to shift over seasons (e.g. Osono 2007), and microbial response to experimental climate changes can vary depending on sampling time (e.g. Kelley et al. 2011). As one of the goals of many community surveys is to predict functional shifts resulting from changes in biodiversity, we also conducted a phylogenetic analysis of the cbhI gene using publically available sequence data from identified isolates to determine whether this gene is phylogenetically conserved among fungal lineages. Given that nitrogen
deposition from anthropogenic sources is predicted to increase with human population growth (Galloway et al. 2004), understanding how these inputs will alter the composition and functions of soil fungal communities is critical to accurately predict terrestrial ecosystem responses and to identify approaches for amelioration of negative effects.
Materials and methods Field site description and soil sample collection This study was conducted at the U.S. Department of Energy FACE experiment in the Blackwood Division of the Duke Forest (North Carolina, USA) established in 1996 to determine the ecosystem impacts of increased carbon dioxide. The plots are located in a loblolly pine (Pinus taeda) plantation that was established in 1983. Soils at this site are moderately low fertility, acidic clay loam of the Enon series (McCarthy et al. 2009). The FACE experiment consisted of six 30-m rings, half of which received increased CO2. As we were interested primarily in the effects of nitrogen deposition, only the ambient CO2 plots were included in this study, a total of three rings. In 2005, the experimental plots were divided into quarters, and nitrogen was added to two of the quadrants at a rate of 11.2 g N/m2/year (112 kg/ha/year) in the form of pellet ammonium nitrate (NH4-NO3). Additional site details can be found in Ellsworth et al. (1995, 2012). In May 2009, November 2009, April 2010, July 2010 and September 2010, mineral soil was sampled to 15-cm depth from three random locations within each of the three ambient CO2 rings (ambient nitrogen and nitrogen-amended). Immediately following collection, each soil core was placed in a ziptop bag and manually homogenized. A single subsample was then collected in a 50-mL Falcon tube and immediately flash-frozen in liquid nitrogen, for six soil samples from each ring and a total of 18 samples per time point. Samples were transported back to the laboratory on dry ice and stored at 70 to 80 °C until processing.
Soil DNA extraction DNA was extracted from 0.5 g of soil from each soil core using the FastDNA SPIN Kit (MP Biomedicals, Solon, OH) according to the manufacturer’s protocol. DNA concentrations were determined for each extract using PicoGreen fluorescence. Extracts from the same fertilization treatment within each of the rings were pooled in equimolar quantities. This resulted in six pooled DNA extracts (three soil cores from two subplots) for each of the five sampling points.
Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
4408 R . C . M U E L L E R , M . M . B A L A S C H and C . R . K U S K E
Amplification and sequencing processing of LSU Fungal LSU gene fragments were PCR-amplified in triplicate from each pooled DNA extraction using the primers LR0R (ACCCGCTGAACTTAAGC) and LR3 (CCGTGTTTCAAGACGGG), which target the D1-D2 hypervariable region of the LSU (http://www.biology. duke.edu/fungi/mycolab/primers.htm). Each 50-lL reaction contained the following: 19 PCR buffer (Applied Biosystems, Foster City, CA), 0.8 mM dNTPs, 6 lg Bovine Serum Albumin and 1.5 U AmpliTaq Polymerase LD (Applied Biosystems). Reactions were performed in an Eppendorf Mastercycler Pro thermal cycler using the following thermal cycling programme: initial denaturation at 95 °C for 3 min, followed by 30 cycles of 95 °C for 1 min, 55 °C for 1 min, 72 °C for 1 min and a final extension at 72 °C for 10 min. PCR products from each sample were purified using the QIAquick PCR Purification Kit (Qiagen, Germantown, MD), pooled and visualized by gel electrophoresis on a 1% TBE agarose gel stained with ethidium bromide. PCR products were ligated into the pCR 4-TOPO Vector and cloned using the TOPO TA cloning Kit (Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions, and 394 colonies were randomly selected and sequenced bidirectionally on an ABI 3730 Genetic Analyzer from the M13 vector primers. Forward and reverse sequences were assembled using Fincon (unpublished software, courtesy of Cliff Han, Los Alamos National Laboratory, NM). Quality filtering to remove any sequence that contained an ambiguous base or that was