A significant but often overlooked focus of diazotrophy in salt marshes is dead aboveground Spartina biomass, particularly standing dead biomass (19, 33). There are quite large amounts of standing dead biomass at all times of the year, with ratios of dead to live aboveground biomass exceeding 1:1 during the winter and spring months (7, 31). Standing dead biomass is partially mineralized and frequently very dry (17) but supports substantial microbial activity (17–19), which is greatly stimulated when the material becomes wet through tidal action or precipitation (17). Rates of diazotrophy in moist standing dead Spartina are among the highest reported for decomposing plant materials (see Table 4 in reference 19).

Relatively little attention has been given to the microorganisms involved in decomposition of and diazotrophy in dead aboveground Spartina biomass. Much of the microbial biomass in standing dead materials consists of fungal hyphae (18). Cyanobacteria are present but occur chiefly in clay-rich surface films (18), while diazotrophy occurs primarily on and within the decaying biomass itself (19). It seems that the predominant diazotrophs in this material are heterotrophic bacteria, but the types of organisms present have not been determined.

Recent applications of molecular biological methods have greatly facilitated the study of natural bacterial communities and functionally significant taxa within them (9, 34, 39, 42). In particular, PCR amplification has been used to recover segments of nifH, the structural gene encoding the nitrogenase iron protein, from various types of environmental samples, including marine and freshwater plankton (1, 3, 44), termite hindguts (11, 20), microbial mats and aggregates (21, 22, 43), terrestrial soils (28, 29, 32, 41), the rhizoplanes of rice (Oryza sativa) (36) and of shoal grass (Halodule wrightii) (10), and the rhizosphere of Spartina (14). PCR amplification of nifH sequences followed by their separation through denaturing gradient gel electrophoresis (DGGE) has been used to examine the complexity and stability of the diazotroph assemblage found in the Spartina rhizosphere (25–27), and sequence analysis of the DGGE bands has been used to determine phylogenetic relationships of the diazotrophic organisms represented (14). While such methods have certain inherent limitations and biases (25, 42), they provide an efficient means to profile the diazotrophs associated with dead aboveground Spartina biomass and to determine the phylogenetic affiliations of these organisms.

In this study we determined the types of diazotrophic heterotrophic bacteria present in standing dead and loose, recently deposited (wrack) Spartina biomass, as defined by recoverable partial nifH sequences resolved by DGGE. Our primary objectives were to assess the diversity of these assemblages and to identify the major phylogenetic groups of organisms that are capable of contributing to N₂ fixation in dead aboveground Spartina biomass.

Sampling sites. Samples of standing dead Spartina stalks and Spartina wrack were collected from the short-form Spartina zones in two different salt marsh systems. The Crab Haul Creek Basin site in the North Inlet estuary, near Georgetown, S.C. (79°12′W, 33°20′N), was located in the intertidal zone approximately 50 m from the nearest tidal creek and was sampled on 31 August 2000. The Doboy Sound site on Sapelo Island, Ga. (31°23′N, 81°17′W), was located in the intertidal zone near Doboy Sound (Georgia Coastal Ecosystems Long Term Ecological Research Site 6) and was sampled on 1 August 2000. The upper, approximately 10-cm lengths of dry standing dead stalks were collected. Dry wrack, which consisted of loose stalks (litter) recently deposited on the sediment surface, was collected from deposits lying near the sampling locations for standing dead stalks. Standing dead stalks and wrack were transferred to sterile Whirl-Pak bags and stored at −70°C pending DNA extraction.

DNA extraction. Standing dead and wrack stalks were broken up into 2-cm fragments. DNA was extracted from the samples using a direct lysis procedure described previously (13, 25). DNA extracts were further purified and concentrated using the Wizard DNA clean-up system following the manufacturer's instructions (Promega, Madison, Wis.). DNA quality and quantity were assessed by agarose gel electrophoresis and fluorometry, respectively.

PCR amplification of nifH. PCR was performed using Taq DNA polymerase (Qiagen, Valencia, Calif.) in a reaction mixture containing (25-μl reaction volume) 25 ng of template DNA, 1.5 mM MgCl₂, 2 μM deoxynucleoside triphosphate (dNTP) mixture, 0.5 pmol of each primer, and 10 μg of bovine serum albumin. The nifH primers used were those of Piceno et al. (25) and are specific for heterotrophic diazotrophs. These primers were designed to have low degeneracy, which is needed for DGGE applications, and are not expected to amplify nifH sequences from cyanobacteria, Frankia spp., and methanogens. Primer design and testing have been described previously (25). Amplification was initiated by a denaturation step at 94°C for 2 min and proceeded in two phases: (i) a 20-cycle touchdown program (94°C for 45 s, 58°C for 30 s, decreasing 0.5°C/cycle, and 70°C for 30 s), and (ii) 20 cycles of a standard amplification program at a 48°C annealing temperature for 30 s. A final extension step at 70°C for 2 min was used. Multiple individual reactions were performed for each sample. PCR products were pooled (200-μl final volume per sample) and stored as alcohol precipitates at −20°C. Prior to DGGE, amplimers were recovered by centrifugation and dissolved in 15 μl of TE (10 mM Tris-HCl [pH 8.0], 1 mM EDTA).

DGGE. nifH amplimers were electrophoresed on denaturing gradient gels (1-mm thick, 6.5% polyacrylamide, 78 to 89% denaturant, where 100% denaturant contains 7 M urea and 40% formamide) at 48°C for 1,900 V·h using the Bio-Rad (Hercules, Calif.) DCode universal mutation detection system. Gels were stained for 30 min in TE with SYBR Gold (Molecular Probes, Eugene, Oreg.) and documented using the Alpha Imager 2000 (Alpha Innotech Corp., San Leandro, Calif.). Gel plugs were collected from all well-resolved bands in the profiles using wide-bore micropipette tips and stored in 50 μl of distilled water at −20°C. Gel bands were designated homoduplexes or heteroduplexes following previously described methods (25).

Amplimer cloning and identification of different cloned amplimer sequences. Amplimers from DGGE gel plugs were recovered by reamplification and cloned as described previously (14). Recombinant colonies were maintained on Luria-Bertani agar plates containing 100 μg of ampicillin ml⁻¹. Clones were screened for appropriately sized insert by amplification using primers specific for the SP6 and T7 RNA polymerase binding sites (14). Restriction fragment length polymorphism analysis was employed to assess gel band amplimer composition (i.e., homogeneous or heterogeneous) and to identify different clones for sequencing (14).

DNA sequencing and analysis. Recombinant plasmids were purified from selected clones by using the Qiagen Plasmid Mini Kit. Plasmid concentrations were determined fluorometrically. Sequencing reactions used T7 and Sp6 primers and ABI (Applied Biosystems, Foster City, Calif.) BigDye version 2.0 chemistry. Sequences were determined using an ABI 3100 genetic analyzer. For phylogenetic reconstructions, nifH sequences from numerous different known diazotrophs and from various environmental sources were selected using the Blast search feature of the NCBI GenBank database (2). Nucleotide sequences were translated, and the inferred amino acid sequences were aligned (5) and checked by hand for proper alignment of conserved marker residues (14). Neighbor-joining phylogenies (30) were constructed in MEGA version 2.0 (12) using percent dissimilarity distances and pairwise deletion of gaps and missing data. The use of alternative amino acid distance measures (e.g., Poisson and gamma correction for multiple substitutions) or tree construction methods (neighbor joining or Unweighted Pair Group Method Using Arithmetic Averages) had no significant effect on the resulting dendrogram topology (data not shown). NifH amino acid sequences from Methanobacterium thermoautotrophicum (accession no. AE00916) and Methanosarcina barkeri (X56072) were used as outgroup taxa. Bootstrapping (6) was used to estimate the reliability of phylogenetic reconstructions (500 replicates).

All dead aboveground Spartina biomass samples yielded strong amplification products, although the North Inlet samples produced substantially stronger amplification than the Sapelo Island samples (Fig. 1). DGGE yielded 16 well-resolved nifH amplimer bands from North Inlet standing dead biomass and 9 bands from wrack. Due to somewhat lower yields of amplification products from the Sapelo Island samples, only five robust bands were recovered from the standing dead material and four bands from wrack. All of these bands were successfully sampled, and the amplimers were cloned and screened for unique sequences. An artifact band, which was described previously (25), was also observed in each sample lane. A total of 54 different partial nifH sequences were recovered from standing dead Spartina and 24 from Spartina wrack collected at North Inlet. Twenty-one different sequences were recovered from the standing dead material and 20 from the wrack from Sapelo Island.

FIG. 1 Denaturing gradient gel images showing nifH amplimers from dead aboveground Spartina biomass. PCR and DGGE conditions are described in Materials and Methods. Lanes: A, North Inlet standing dead Spartina; B, North Inlet Spartina wrack; C, Sapelo Island (more ...)

The partial nifH sequences were initially translated and examined for key, highly conserved amino acid residues that are important in nitrogenase iron protein structure and function (4, 24). Within the segments analyzed, 11 amino acids, including (Klebsiella pneumoniae [J01740] numbering) Lys15 and Ser16 (within the MgATP binding domain), Arg100 (the ADP-ribosylation site), Asp125 (possibly involved in protein conformation changes), Asp129 (involved in ATP hydrolysis), Arg140 and Lys143 (contribute to salt bridge formation), and four conserved Cys residues (numbers 38, 85, 97, and 132, two of which coordinate the Fe₄S₄ cluster), were used as markers for determining sequence accuracy. Four sequences had one substitution each: NIS2-1 and SIW2-6, Cys85 replaced by Arg85; NIS3-2, Ser16 replaced by Trp16; and NIW8-1, Cys97 replaced by Arg97. All sequences were used in subsequent analyses.

The sequences from dead aboveground Spartina biomass and their closest affiliations with known diazotrophs on the basis of sequence similarity are listed in Table 1. As has been reported in numerous previous studies of environmental nifH sequences (1, 3, 14, 29, 36, 41, 43, 44), these sequences fell into three major clusters. The overwhelming majority of dead Spartina nifH sequences were affiliated with a cluster defined by sequences from α-Proteobacteria and well supported by bootstrapping (Fig. 2). Forty-six of 54 sequences (85%) from the North Inlet standing dead sample, all 24 of the sequences from North Inlet wrack (100%), 19 of 21 sequences (90%) from the Sapelo Island standing dead sample, and 17 of 20 sequences (85%) from Sapelo Island wrack were from presumptive α-Proteobacteria. These sequences were further subdivided into a number of smaller clusters, some of which contained nifH sequences from known diazotrophs.

Dead Spartina sequence(s)	Organism(s) with most similar sequence(s)	% Similarity
Presumptive α-Proteobacteria
NIS2-1	Gluconacetobacter diazotrophicus	95.2
NIS2-2, NIS2-3, NIS4-2, NIS4-4, NIS5-1, NIS5-2, NIS6-1, NIS6-2, NIS7-1, NIS8-1, NIS9-2, NIS10-2, NIS12-3, NIS13-1, NIS13-2, NIW4-1, NIW6-2	Rhodobacter sphaeroides	94.4
NIS3-1, NIS6-2, NIS7-3	Azospirillum brasilense	94.4
NIS3-2, NIS9-1, NIS10-3, NIS14-1, NIS15-2, NIS15-4, NIS16-3	Bradyrhizobium japonicum	97.6
NIS4-1	Azospirillum brasilense, Gluconacetobacter diazotrophicus	92.8
NIS4-3	Rhodobacter sphaeroides	95.2
NIS7-2, NIW2-3, NIW4-2, NIW5-1, NIW8-2, NIW8-3, NIW9-4	Rhizobium sp.	94.4
NIS8-2	Rhodobacter sphaeroides	92.8
NIS8-3, NIW3-1	Rhodobacter sphaeroides	96.0
NIS10-1, NIS13-3	Rhodobacter sphaeroides	96.8
NIS10-4	Azospirillum brasilense	88.0
NIS11-1	Rhodobacter capsulatus, Rhodobacter sphaeroides	97.6
NIS11-2	Azospirillum brasilense	92.0
NIS11-3	Rhodobacter sphaeroides	98.4
NIS12-1	Bradyrhizobium japonicum, Rhizobium leguminosarum biovar phaseoli	95.2
NIS12-2	Rhodobacter sphaeroides	93.6
NIS13-4	Herbaspirillum seropedicae, Rhizobium sp.	92.0
NIS14-3, NIS14-4, NIS15-3, NIS16-4	Rhodobacter sphaeroides	97.6
NIS15-1	Azospirillum brasilense	91.2
NIS16-2, NIW8-1, NIW9-1	Rhizobium sp.	92.8
NIW2-2, NIW6-3, SIS5-1	Herbaspirillum seropedicae, Rhizobium sp.	92.8
NIW2-4	Azospirillum brasilense, Gluconacetobacter diazotrophicus	96.8
NIW3-2, NIW6-1	Herbaspirillum seropedicae, Rhizobium sp.	92.0
NIW3-3, NIW4-3, NIW5-2, NIW6-3, NIW7-1, NIW9-2, NIW9-3	Rhizobium sp.	93.6
NIW4-4	Azospirillum brasilense	98.4
NIW5-3	Azospirillum brasilense, Gluconacetobacter diazotrophicus	91.2
SIS1-1, SIS4-4	Azospirillum brasilense, Gluconacetobacter diazotrophicus	94.4
SIS2-1, SIS4-2	Azospirillum brasilense	100.0
SIS2-2, SIW1-2	Gluconacetobacter diazotrophicus	94.4
SIS2-3	Gluconacetobacter diazotrophicus	92.8
SIS2-5	Azospirillum brasilense	92.8
SIS2-6	Gluconacetobacter diazotrophicus	86.4
SIS3-1	Azospirillum brasilense	95.2
SIS3-2, SIW1-7	Gluconacetobacter diazotrophicus	97.6
SIS3-3, SIS3-6	Azospirillum brasilense	93.6
SIS3-4	Azospirillum brasilense, Bradyrhizobium japonicum, Gluconacetobacter diazotrophicus, Rhodobacter sphaeroides	93.6
SIS3-5	Gluconacetobacter diazotrophicus, Rhizobium sp.	83.2
SIS3-7	Azospirillum brasilense, Gluconacetobacter diazotrophicus	92.0
SIS3-8, SIW2-3, SIW2-5	Gluconacetobacter diazotrophicus	93.6
SIS4-1, SIW2-6	Herbaspirillum seropedicae, Rhizobium sp.	93.6
SIS4-3	Azospirillum brasilense	99.2
SIW1-5	Azospirillum brasilense, Bradyrhizobium japonicum, Gluconacetobacter diazotrophicus, Rhizobium leguminosarum biovar phaseoli	94.4
SIW1-6	Azospirillum brasilense, Gluconacetobacter diazotrophicus	93.6
SIW2-1	Rhodobacter sphaeroides	96.0
SIW2-2	Azospirillum brasilense	96.0
SIW2-4, SIW4-2	Herbaspirillum seropedicae	92.8
SIW3-1	Gluconacetobacter diazotrophicus	96.0
SIW4-1	Gluconacetobacter diazotrophicus	91.2
SIW4-3	Rhizobium sp.	89.6
SW4-4	Azospirillum brasilense	99.2
SW4-5	Azospirillum brasilense	97.6
Presumptive γ-Proteobacteria
NIS1-2	Azomonas agilis, Azotobacter chroococcum	95.2
NIS1-3	Azomonas agilis, Azotobacter chroococcum	99.2
NIS1-4	Pseudomonas stutzeri	98.2
NIS11-4	Azotobacter chroococcum, Azotobacter vinelandii	84.9
SIS2-4	Vibrio diazotrophicus	86.1
SIS2-7	Vibrio diazotrophicus	84.2
SIW1-4	Azomonas agilis	96.8
Presumptive anaerobes
NIS1-1	Desulfovibrio salexigens	84.2
NIS3-3	Desulfonema limicola	84.8
NIS14-2	Desulfonema limicola	82.8
NIS16-1	Desulfovibrio salexigens	88.1
SIW1-1	Desulfovibrio salexigens	85.1

FIG. 2 Phylogenetic analysis of dead aboveground Spartina biomass NifH amino acid sequences from presumptive α-Proteobacteria, from various known α-Proteobacteria, and from selected unknown, presumptive α-Proteobacteria from other sources. (more ...)

Several sequences from North Inlet standing dead Spartina biomass were closely affiliated with purple nonsulfur bacteria, and seven had substantial similarity (≥96%) to the Rhodobacter sphaeroides NifH sequence (Table 1). Several sequences from all sample types were over 95% similar to the Gluconacetobacter diazotrophicus sequence. Another group of eight sequences from North Inlet samples were substantially similar (≥95%) to NifH sequences from rhizobia. Seven of these were over 97% similar to a Bradyrhizobium japonicum sequence. Another substantial sequence grouping, predominantly from the Sapelo Island standing dead sample, was strongly affiliated with the NifH sequence from Azospirillum brasilense. Four of these had 99% or greater similarity to the A. brasilense sequence, and two were identical to it. The NifH sequences of A. brasilense and Azospirillum lipoferum are 99.3% similar, so at least four of the dead Spartina biomass NifH sequences were very likely from Azospirillum species and two seemingly from a strain of A. brasilense. This finding confirms the prediction of Newell et al. (19) that Azospirillum-like organisms may be involved in degradation of standing dead Spartina biomass. There were also many sequences that were not closely affiliated with any known diazotrophs among the α-Proteobacteria. Blast searches of the NCBI GenBank database revealed only a few sequences from other types of environmental samples that had meaningful similarity to any sequences from dead aboveground Spartina biomass. Among these were four sequences recovered from the Spartina rhizosphere (14).

The second major cluster containing sequences from dead aboveground Spartina biomass was characterized by sequences from γ-Proteobacteria (Fig. 3). This cluster contained three sequences from standing dead Spartina whose positions were ambiguous. When these three sequences were omitted and the tree was reconstructed, the γ-Proteobacteria cluster was strongly supported by bootstrap analysis (60% for the cluster as a whole, 96 and 91% for the two major subclusters). Omitting these sequences also raised the bootstrap score for the α-Proteobacteria cluster from 76 to 99%. One of the remaining seven presumptive γ-Proteobacteria sequences was very strongly affiliated with the Azotobacteriaceae, with over 99% similarity to the NifH sequences of Azomonas agilis and Azotobacter chroococcum (Table 1). For comparison, the NifH sequences of A. chroococcum and Azotobacter vinelandii are 99.3% similar. Two other sequences also had substantial similarity (≥95%) to sequences from azotobacteria. The only other sequence with strong similarity to a sequence from a known organism was a North Inlet standing dead sequence that was >98% similar to the sequence from Pseudomonas stutzeri. As was the case for sequences from presumptive α-Proteobacteria, few environmental sequences were substantially similar to those from dead aboveground Spartina biomass, and these were from the Spartina rhizosphere.

FIG. 3 Phylogenetic analysis of dead aboveground Spartina biomass NifH amino acid sequences from presumptive γ-Proteobacteria, from various known γ-Proteobacteria, and from selected unknown, presumptive γ-Proteobacteria from other sources. (more ...)

Only five sequences recovered from dead aboveground Spartina biomass were affiliated with the remaining major NifH sequence cluster, the anaerobes (Fig. 4). While the closest affiliations of these sequences to any from known organisms were all with sulfate-reducing bacteria, none of the dead Spartina NifH sequences were sufficiently similar to any sequence from a known diazotroph to permit even presumptive identification. Two sequences from the North Inlet standing dead sample were similar to sequences from Spartina rhizosphere, but since the rhizosphere core samples contained both roots and sediments, and the dead aboveground biomass samples all carried a small amount of sediment, these sequences may be from sediment diazotrophs rather than species closely affiliated with the decomposing plant materials.

FIG. 4 Phylogenetic analysis of dead aboveground Spartina biomass NifH amino acid sequences from unknown, presumptive anaerobic bacterial sequences, from various known anaerobic bacteria, and from selected unknown, presumptive anaerobic bacteria from other sources. (more ...)

NifH sequences recovered from dead Spartina biomass reflected a diazotroph assemblage of very limited diversity, consisting almost exclusively of α-Proteobacteria. Some of these organisms are apparently related to known diazotrophs, including Azospirillum brasilense, Bradyrhizobium japonicum, Gluconacetobacter diazotrophicus, and Rhodobacter sphaeroides. Very few sequences from dead Spartina biomass were affiliated with the other major NifH sequence groups. However, it is noteworthy that among the few sequences recovered from presumptive γ-Proteobacteria, several were quite similar to those from known diazotrophs, including Azomonas agilis, Azotobacter chroococcum, and Pseudomonas stutzeri. While it is certainly possible that some sequences were lost due to PCR biases or other artifacts (25, 42), identical methods have yielded much more diverse sequence collections from other sample types (14; Lovell et al., unpublished data). It appears that while the relatively harsh (partially mineralized and frequently dry) microenvironments represented by dead aboveground Spartina biomass can support impressive rates of diazotrophy (19) when wet, they pose a substantial challenge for many diazotrophic biota and consequently harbor a very restricted range of organisms.

Nucleotide sequence accession numbers. The nifH sequences determined in this study are available in the GenBank database under accession numbers AF389702 to AF389823.

We acknowledge Steven Newell for assistance with Sapelo Island sampling site identification and the Belle W. Baruch Institute for Marine and Coastal Research for access to North Inlet sampling sites.

This research was supported by NSF award DEB-9903623 to C.R.L.