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Department of Environmental Science and Policy, George Mason University, Fairfax, Virginia 22030
Masoumeh Sikaroodi
Department of Environmental Science and Policy, George Mason University, Manassas, Virginia 20110
David Chalkley
American Type Culture Collection, 10801 University Boulevard, Manassas, Virginia 20110-2209
Patrick M. Gillevet
Department of Environmental Science and Policy, George Mason University, Manassas, Virginia 20110
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ABSTRACT |
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Fungal decomposers are important contributors to the detritus-based food webs of salt marsh ecosystems. Knowing the composition of salt marsh fungal communities is essential in understanding how detritus processing is affected by changes in community dynamics. Automated ribosomal intergenic spacer analysis (ARISA) was used to examine the composition of fungal communities associated with four temperate salt marsh plants, Spartina alterniflora (short and tall forms), Juncus roemerianus, Distichlis spicata and Sarcocornia perennis. Plant tissues were homogenized and subjected to a particle-filtration protocol that yielded 106 µm particulate fractions, which were used as a source of fungal isolates and fungal DNA. Genera identified from sporulating cultures demonstrated that the 106 µm particles from each host plant were reliable sources of fungal DNA for ARISA. Analysis of ARISA data by principal component analysis (PCA), principal coordinate analysis (PCO) and species diversity comparisons indicated that the fungal communities from the two grasses, S. alterniflora and D. spicata were more similar to each other than they were to the distinct communities associated with J. roemerianus and S. perennis. Principal component analysis also showed no consistent, seasonal pattern in the composition of these fungal communities. Comparisons of ARISA fingerprints from the different fungal communities and those from pure cultures of selected Spartina ascomycetes supported the host/substrate specificity observed for the fungal communities.
Key words: automated ribosomal intergenic spacer analysis, Distichlis, fungal community fingerprinting, Juncus, salt marsh fungi, Sarcocornia, Spartina
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). However, only 5–10% of this production is used by herbivores because more than 80% of living Spartina biomass is refractory lignocellulose (Benner et al 1984), which is indigestible for all but a few metazoans. Extensive research has implicated microbial decomposers, both the fungi and bacteria, in the conversion of lignocellulose to microbial biomass, thereby enhancing the nutritional value of the detritus that then can serve as a source of food for salt marsh fauna (Newell and Porter 2000).
Because the stems and leaves of salt marsh grasses are not deciduous, a significant amount of decomposition occurs in dead, standing plants. Fungi are well suited for degrading such solid, lignocellulosic substrates because of their penetrating, mycelial mode of growth, their lignocellulose-degrading activity and their ability to withstand periodic wetting and drying (Torzilli and Andrykovitch 1986, Newell 1996, Newell and Porter 2000). In contrast maximized surface area and high substrate affinities make bacteria more competitive for dissolved as opposed to solid substrates. Consistent with this are data showing fungi to be the predominant microbial decomposers on dead, standing Spartina alterniflora with a ratio of living-fungal to total-bacterial standing crop of 165:1 even in the presence of grazing Littorinid snails, which consume 55% of the fungal biomass (Newell 1993). It has been estimated that 75–100% of the total nitrogen content of dead, standing Spartina is fungal (Newell 1993). As decomposition progresses the dead shoots eventually fall onto the marsh sediment where they break down into smaller fragments. This increase in substrate surface area is accompanied by an increase in bacterial biomass and activity that is associated with sediment detritus.
As the importance of fungi in salt marsh detritus processing has become apparent numerous studies have focused on describing the fungal communities associated with this activity. Two general approaches, direct and indirect, have been used to isolate and identify fungi. The direct approach, most commonly used for taxonomic studies, involves the microscopic examination of the natural substratum for identifiable reproductive structures. Because reproductive structures might not be present at the time of examination this method might underestimate the diversity of the fungal community. With indirect approaches, such as soil dilution plating, mycelium is cultured from environmental samples and cultures that sporulate are identified. This method might uncover greater fungal diversity but also suffers the drawbacks that many fungi either will not grow or not sporulate in the culture medium employed, thereby precluding identification (Bills and Polishook 1994). Furthermore the culture-dependent method favors fast-growing mitosporic species that might cover a plate before slower-growing species can be detected. Also inactive spores on the surface of the substratum might germinate in culture, resulting in inaccurate assessments of the active fungal community. Therefore particle filtration and serial-washing techniques have been developed to remove inactive spores before culturing, favoring the isolation of fungi growing from within the substratum (Bills and Polishook 1994).
More recently culture-independent techniques employing DNA analysis have been developed to characterize complex microbial communities. These include DNA fingerprinting techniques, such as terminal restriction fragment length polymorphisms (T-RFLP), length heterogenicity PCR (LH-PCR), automated ribosomal intergenic spacer analysis (ARISA), denaturing gradient gel electrophoresis (DGGE), as well as cloning and sequencing. The T-RFLP method, which is used frequently, involves PCR amplification of the target gene (e.g. small ribosomal subunit gene or internal transcribed spacer [ITS] region) with specific primers, one of which is fluorescently labeled. This is followed by restriction enzyme digestion, generating labeled terminal restriction fragments that are separated by electrophoresis. In a comparison of the T-RFLP method with that of LH-PCR Mills et al (2003) found that results with the T-RFLP method were less consistent due to partial digests. This necessitated the use of multiple restriction enzyme digests to produce three replicate samples that were similar enough for further analysis. The problem might be due to the blocking of restriction sites by inhibitors or the complexity of mixed templates in the PCR products (Osborn et al 2000). In any event the additional steps required to rectify this technical difficulty increased the time and expense of the method.
To avoid the problems inherent with the T-RFLP method, we used ARISA to characterize salt marsh fungal communities. Like LH-PCR, ARISA does not require restriction digests and discriminates between the different members of a microbial community on the basis of the inherent variation in length of a specific amplified sequence of DNA, in this case the ITS region of the ribosomal gene. Although rapid fingerprinting techniques such as ARISA might exhibit shortcomings (Crosby and Criddle 2003) they nonetheless represent a rapid, if not taxonomically specific, survey technique for profiling microbial communities, with individual peaks or bands designated as operational taxonomic units (OTU). This enables one to follow microbial community dynamics more readily compared to time-consuming, culture-dependent methods. To evaluate the performance of ARISA we included in our analyses the fungal communities from two salt marsh plants with well described mycofloras, Spartina alterniflora and Juncus roemerianus, for which there is also T-RFLP data (Blum et al 2004), and the fungal communities from two species, Distichlis spicata and Sarcocornia perennis (formerly Salicornia perennis [Kartesz 1994]), which have mycofloras that have been studied less intensively and for which there is no molecular data. Taxonomic descriptions of fungi from S. alterniflora and J. roemerianus as well as T-RFLP data suggest that different plant substrates harbor distinct fungal communities (Newell and Porter 2000, Blum et al 2004). In this report we provide ARISA data that supports the hypothesis that substrate is an important factor in determining fungal community composition using S. alterniflora and J. roemerianus as a basis of comparison with the T-RFLP method while extending the analysis to include D. spicata and S. perennis. Furthermore ARISA data collected during the summer, late fall and late winter over a 2 y period also suggest that fungal community composition does not vary seasonally in a predictable manner.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Sample processing.— –
Shoots of host plants were collected over a 2 y period during the late fall (6 Nov 2000 and 12 Dec 2001), late winter (20 Mar 2000 and 8 Feb 2001) and summer (6 Jul 2001 and 17 Jul 2002) for a total of six samplings for each host. Because a comprehensive survey of shoot-associated fungi was the objective, a mixture of shoot tissues from several individuals was processed at each collection time for each host plant. For Spartina this mixture consisted of leaf blades, leaf sheaths and true stems; for Distichlis stems and leaves; for Sarcocornia stems, leaves and stolens; for Juncus stems and leaves. Summer collections comprised exclusively living, green tissues. Late fall and late winter collections consisted of dead/standing, brown tissues with the exception of Juncus collected in late fall, which often was a mixture of green and brown stems. The collections were stored on ice until transported to the laboratory where they were air dried at room temperature before being subjected to a particle-filtration protocol based on that of (Bills and Polishook 1994). Dried shoots were cut into small pieces. Five g aliquots of cut tissue were aseptically blended in 100 mL of 17.5% (half-strength) artificial seawater (ASW; Instant Ocean, Carolina Biological Supply Co., Burlington, North Carolina) in 15 s bursts for a total of 2 min. The homogenates were filtered through a series of sieves with decreasing mesh sizes of 2 mm, 500 µm, 210 µm and 106 µm. Tissue particles collected on the 106 µm sieve have been shown to yield the ideal ‘‘one colony per particle’’ in plating experiments (Bills and Polishook 1994) and were used as a source of fungi for culturing and molecular analysis. They also lend themselves more readily, than do larger pieces of tissue, to washing procedures aimed at removing extraneous spores. The 106 µm particle fraction was washed with sterile ASW and resuspended in 40 mL of ASW in sterile 50 mL centrifuge tubes. The tubes were centrifuged to pellet the particles, the supernatants discarded, 40 mL of ASW added and the tubes shaken vigorously to resuspend the pellets. This washing procedure was repeated for a total of 10 times. After the final wash the pellets were diluted ~1/20 and 0.1 mL aliquots spread onto either DRBC (peptone, 5 g; dextrose, 10 g; KH2PO4, 1 g; MgSO4 · 7H2O, 0.5 g; dichloran, 0.002 g; rose bengal, 0.025 g; chloramphenicol, 0.01 g; agar, 15 g; ASW, 17.5 g per L of distilled H2O) or MYE (malt extract 10 g, yeast extract 2 g, chloramphenicol 0.01 g, dichloran 0.002 g, rose bengal 0.025 g, agar 20 g, ASW 17.5 g per L of distilled H2O) for culture isolations. Chlorotetracyclin and streptomycin were added at 50 mg L–1 to both media after autoclaving. The remainder of each particulate fraction was frozen at –80 C until subsequent DNA extraction. Plates were sealed in plastic wrap and incubated at 18 C under fluorescent light with a 12 h photoperiod. Over a period of several weeks the plates were examined regularly under a dissecting microscope and particles with emergent hyphae were transferred to culture tubes containing potato-dextrose agar (PDA; Difco Laboratories, Sparks, Maryland), half-strength ASW, and a sterile shoot segment from the corresponding host to help induce sporulation. Sporulating cultures were identified to genus with light microscopy.
DNA extraction.— – Frozen particulate fractions from each collection were thawed on ice and three 300 µL aliquots of particles from each sample were individually extracted with the Fast DNA Spin Kit for fungi following the procedure provided by the manufacturer (BIO 101; Vista, California). Each extraction tube was agitated three times with a Fast Prep FP120 instrument (BIO 101; Vista, California) at a speed setting of 5 for 30 s. Tubes were cooled on ice between agitations.
PCR.— –
The full ITS region (ITS1, 5.8S, and ITS2) from DNA extracts was amplified with fluorescently labeled forward primer 1F (5'-[6FAM] CTT GGT CAT TTA GAG GAA GTA A-3') and unlabeled reverse primer ITS4A (5'-CGC CGT TAC TGG GGC AAT CCC TG-3'). These primers exhibit enhanced specificity for ascomycetes (Larena et al 1999) or their corresponding anamorphs, which are the predominate fungi associated with salt marsh plants (Crabtree and Gessner 1982, Petrini and Fisher 1986, Kohlmeyer and Volkmann-Kohylmeyer 2001, Buchan, et al 2002). The reactions were carried out in 20 µL (final volume) reaction mixtures consisting of 1x PCR buffer, 0.01% bovine serum albumin to bind PCR inhibitors, 2.5 mM MgCl2, each deoxynucleoside triphosphate at a concentration of 0.25 mM, each primer at a concentration of 0.5 µM, 2 µL of a 1/5 diluted DNA extract, and 0.5 U of TAQ Gold DNA polymerase. Initial denaturation at 94 C for 11 min was followed by 35 cycles consisting of denaturation for 1 min at 94 C, annealing at 48 C for 1 min, and extension at 72 C for 2 min. Following the 35 cycles there was a final extension time of 45 min to minimize peak shoulders during electrophoresis due to TAQ polymerase-induced artifacts.
ARISA.— – The PCR products from each of the three replicate extractions for a given plant tissue sample were separated on the SCE 9610 capillary DNA sequencer (Spectrumedix LLC, State College, Pennsylvania) with GenoSpectrum software to convert fluorescent output into electropherograms. Electropherogram peaks represented amplicons of different lengths from the fungal communities being examined. Relative peak abundance was calculated by dividing individual peak heights by the total peak heights in an electropherogram with a custom PERL script (P.M. Gillevet personal communication). Interleaved, normalized abundances were compared with Excel (Microsoft Office). A mean normalized abundance for each amplicon was calculated from the three replicates of each tissue sample, excluding means less than 1%. To generate a composite picture of all fungal amplicons observed for a given plant species, normalized means from the six biennial sample collections were summed graphically to give a cumulative normalized abundance profile of the fungal community. The six community profiles for each host also were subjected to principal components analysis (PCA) and principal coordinates analysis (PCO) using the MultiVariate Statistical Package (Kovach Computing Services, Pentraeth, Wales, UK). Fungal community diversity was measured by calculating the Shannon index for the community profiles also using the Multi-Variate Statistical Package.
Fungal cultures.— – Pure cultures of Spartina fungi also were subjected to ARISA. These cultures of ascomycetes, isolated directly from decaying leaves of S. alterniflora by S.Y. Newell, were obtained from the American Type Culture Collection (Manassas, Virginia): Phaeosphaeria spartinicola, SAP132, MYA-2374 (MYA number = ATCC accession number); P. spartinicola, SAP135, MYA-2375; Mycosphaerella sp. 2 Group A, SAP153, MYA-2376; Mycosphaerella sp. 2 Group B, SAP154, MYA-2377; P. halima, SAP134, MYA-2378; Hydropisphaera erubescens, SAP145, MYA-2379; ‘4clt’, SAP162, MYA-2380. Also used were pure cultures of the Spartina ascomycetes Buergenerula spartinae and Pleospora vagens var. vagans from our own collection.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). Many were mitosporic fungi (including potential ascomycete anamorphs) along with several common salt marsh ascomycete genera. Most of the fungi we identified from Spartina, Juncus and Sarcocornia have been described previously (Gessner and Goos 1973a, b, Gessner 1977, Crabtree and Gessner 1982, Petrini and Fisher 1986, Farr et al 1989, Kohlmeyer and Volkmann-Kohlmeyer 2001, 2002). Exceptions were Acremonium, Aposphaeria and Septoriella from Spartina and Asteromella from Juncus. In the case of the less well studied Distichlis only Ascochyta, Fusarium, Phoma and Septoriella have been reported previously (Farr et al 1989).
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) with a representative example from Spartina, short form. Peak heights from triplicate electropherograms were interleaved, normalized, averaged and then graphed as illustrated (FIG. 2) which shows the fungal amplicon distributions generated from all four salt marsh plants over a 2 y period. Here one can see that the amplicons from the individual hosts tended to cluster in different size ranges. Amplicons from Spartina (short and tall forms combined) were predominant in ranges of 632–643 bps, 651–654 bps and 662–713 bps. Amplicons from Juncus were dominant in the 611–631 bps range with prominent peaks also at 655 and 658 bps. In the case of Sarcocornia there was a large, unique amplicon peak at 644 bps, a cluster of peaks at 659–664 bps and smaller peaks at either end of the amplicon size range. Amplicons from Distichlis were predominant at 645–650 bps and showed a noticeable overlap with many Spartina amplicons. The clustering of amplicons on the basis of host as observed (FIG. 2) was demonstrated also by PCA of the same amplicon size and abundance data (FIG. 3). Here the community profiles for Juncus and Sarcocornia are distinct from each other and from those of Spartina and Distichlis, which cluster close together. The close clustering of the community profiles from the latter two hosts is consistent with the sharing of amplicons between these hosts (FIG. 2). When subjected to PCO the data showed the same cluster pattern (not shown) as produced by the PCA.
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show correspondences between the amplicons of the individual pure cultures and those of the different fungal communities.) A good match can be seen between the amplicons from the Spartina pure-culture isolates and those from the fungal community of Spartina tissue. Out of nine pure cultures, only one isolate, B. spartinae, at 636 bps did not coincide with an amplicon from Spartina tissue. It also was not detected by (Buchan et al 2002) among ITS amplicons from their samples of Spartina. This was ascribed to either poor DNA extraction from highly melanized areas or possibly to competition with other fungi resulting in the early decline of the species. The B. spartinae amplicon did match up with a minor peak from Juncus tissue, which might be just coincidental because it has not been recorded from Juncus and because more than one species may share the same amplicon size (see below). In contrast the Spartina ascomycete amplicons showed a poor match with amplicons from the other host plants, particularly Juncus and Sarcocornia, and only to the extent that these host amplicons overlapped with those from Spartina (FIG. 2). The more frequent association of the pure culture amplicons with those from Distichlis reflects the greater coincidence of amplicons from Distichlis and Spartina (FIG. 2).
It should be noted that the ITS amplicon from SAP132 (P. spartinicola) was the same size (653 bps) as that from SAP134 (P. halima), indicating that a given amplicon size may represent more than one species, something that has been observed in studies of bacterial communities (Crosby and Criddle 2003) and which might be the case above where the amplicon from B. spartinae coincided with one from Juncus. The two Mycosphaerella strains, SAP153 and 154, had different amplicon sizes (645 and 638 bps, respectively). Buchan et al (2002) using T-RFLP also detected differences in their fingerprints of these two strains. The two S. spartinicola strains (SAP132 and 135), which represent two subgroups (77.2% similarity) based on ITS sequence (Buchan et al 2002), differed by one base pair (652 vs. 653).
The diversity of fungal amplicons from all four plants was measured with the Shannon index (TABLE II). Both the tall and short forms of Spartina yielded the highest number of fungal amplicons (richness) and highest diversity indices, followed by Distichlis and then by Juncus and Sarcocornia. Spartina and Distichlis appeared more similar to each other than to Juncus and Sarcocornia in terms of the diversity of fungi they harbor.
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). The data showed a mixture of amplicons, those unique for a given season (usually of lower abundance) and those appearing during more than one season (usually higher abundance). Although the most abundant fungal amplicons were present during more than one season, the relative abundance of these amplicons varied depending on the season (e.g. amplicons of 643, 652 and 672 bps). When the data were subjected to PCA, the amplicons did not show a consistent seasonal pattern (data not shown). The lack of a consistent seasonal pattern also was observed for the tall form of Spartina and for the other three plant species (data not shown).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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ARISA has been shown to be a rapid, reproducible and highly sensitive survey technique for assessing microbial community structure globally. Nevertheless estimates of microbial abundance must be interpreted with caution due to biases introduced during the amplification of mixed templates from whole community DNA extracts (Farrelly et al 1995, Suzuki and Giovannoni 1996, Polz and Cavanaugh 1998, Suzuki et al 1998). Yannarell and Triplett (2005) explored some of the technical issues associated with estimating natural bacterial abundances by studying the effects of amplicon detection level (sensitivity) and various transformations of ARISA data on the outcome of their experiments. They showed that quantitative and semiquantitative transformations of ARISA data were not influenced by sensitivity level (minimum peak height requirement for analysis) whereas a binary transformation (i.e. presence or absence) was. Although different transformations resulted in different outcomes in some cases, overall they thought that the application of ARISA was informative. By using a semiquantitative transformation of our ARISA data (individual peak heights/total of peak heights from the entire community), we were able to distinguish among the fungal communities associated with four different salt marsh plants, two of which (D. spicata and S. perennis) had not been examined previously with molecular techniques. Different methods for analyzing the ARISA results (amplicon size distributions, PCA and PCO case scores, and diversity indices) all indicated that the fungal communities associated with the grasses Spartina and Distichlis, although different, were more similar to each other than they were to the distinct communities from Juncus and Sarcocornia. The association of specific fungal communities with particular plant substrates was supported further by a good match of Spartina fungal amplicons (from pure cultures) with community profiles from Spartina but not with profiles from non-Spartina hosts. The fact that the PCA plot showed the two overlapping forms of Spartina clustering close to Distichlis, also a grass, but far from the two disparate taxa, Juncus ( Juncaceae) and Sarcocornia (Chenopodiaceae), lends further credence to the ARISA results. Furthermore Blum et al (2004) also showed that Spartina and Juncus supported distinct mycofloras with T-RFLP analysis. However not having to contend with the time, expense and potential artifacts associated with restriction enzyme digestions (Mills et al 2003) makes ARISA a more convenient alternative for analyzing fungal community composition. The differences in fungal community composition observed here might be attributed to taxon-specific characteristics of the host plants including anatomy, physiology, cell wall chemistry and/or secondary chemistry.
When the ARISA data for fungal communities collected during different seasons were compared with PCA no distinct pattern was observed. One might have expected to see community differences associated with dead-standing tissues (late fall and late winter collections) vs. living tissues (summer collections), but this was not the case. Likewise (Buchan et al 2003) could not correlate microbial community changes with changing substrate composition. Our data suggest that the type of plant tissue is more important in structuring fungal communities than is the time of year/state of decay, at least at the OTU level of resolution. Although they did not survey living plants, Blum et al (2004) also concluded that plant type, not geographic location, was the primary factor responsible for the composition of microbial communities on the dead-standing plants that they examined.
Whether the differences in fungal community composition observed here have an impact on detritus processing and whether these communities respond differently to environmental perturbations are questions yet to be answered. As indicated earlier the amplicon profiles generated by ARISA do not provide for the specific taxonomic identification of individual OTU. Furthermore a discrete amplicon size (OTU) may harbor more than one fungal species as demonstrated here for some of the pure cultures. To resolve these issues we currently are using ARISA community profiles to identify major OTU of interest for targeted cloning and sequencing. More efficient than shotgun sequencing of clones, this will help identify the specific fungi contributing to the diversity observed with ARISA, including species that might share the same amplicon size. The increased resolution provided by sequence data also might reveal seasonal patterns in community species composition not detected by ARISA. This type of information can serve as a basis for investigations into how different fungal communities respond to various environmental perturbations and ultimately provide insights into the ecological relevance of specific taxa to community structure and function.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 Corresponding author: E-mail: atorzill{at}gmu.edu
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LITERATURE CITED |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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