activity and diversity of nitrogen-cycling microbial ...kearney.ucdavis.edu/new...

2006-2011 Mission Kearney Foundation of Soil Science: Understanding and Managing Soil-Ecosystem

Functions Across Spatial and Temporal Scales Final Report: 2006015, 1/1/2008-12/31/2008

1Department of Environmental Sciences, University of California, Riverside

For more information contact Dr. Lisa Stein ([email protected]).

Activity and Diversity of Nitrogen-Cycling Microbial Communities in Soil Sequences Around California

Lisa Y. Stein*1, Brian D. Lanoil1, Suk Kyun Han1

Objectives

The cycling of inorganic nitrogen in soils via nitrifying and denitrifying microbial

communities provides essential nutrients that support primary productivity and plant growth.

Nitrogen is often the limiting nutrient for primary productivity and is therefore a major regulator

of the carbon cycle. This project investigated the compositions and activities of nitrifying and

denitrifying microbial communities in California’s diverse wildland soils sampled across large

spatial scales. Our main questions were: 1) how does the diversity of N-cycling microorganisms

vary at different spatial scales and across wildland soil sequences, 2) can the structure and

activities of N-cycling microbial communities be predicted based on chemical or physical

features of the soil, and 3) does acetate-consuming denitrification drive a significant component

of carbon and nitrogen cycling in wildland soils? The data derived from this project are unique in

representing a large range of unperturbed wildland soils rather than the forest or managed soils

that are the common target of nitrogen cycle studies.

Approach and Procedures

We collected physicochemical, biochemical activity, and microbial diversity data across

four soil chronosequences and one climosequence located in different regions of California

(Table 1). Soils were sampled in May 2007. Five soil cores (0-10 cm) were collected in a

randomized sampling pattern from plant-free regions at previously described sites within each

soil sequence (following the sampling schemes outlined in references for each sequence). Air

and ambient soil temperatures were recorded on site. Soil samples were kept on ice for shipping

back to the lab. The five soil cores collected from each site were homogenized together by sieve

and air-dried to represent a composite sample. Major ions, pH, water content, and total organic

carbon content were determined for the composite samples (data reported in 2008 progress

report). Activity measurements were initiated within a week of sample collection. Potential

denitrification activity (PDA) of native and substrate-amended soils was determined by

incubating soils (5 g) in 50 mL sodium phosphate buffer (1 mM, pH 7.2) with potassium nitrate

(1 mM) with or without acetate or glucose additions (50 µmol C-source). The vials were sparged

with N2 to achieve anaerobicity, and acetylene (10% v/v) was added to block nitrous oxide

reductase activity. Vials were incubated with shaking at 28 ºC and N2O was measured via gas

chromatograph (TCD; Hayesep D column) periodically over 90 h. PDA was defined as the linear

increase in N2O production over time. To assess the active denitrifying community, 13

C-labeled

acetate or glucose was used as the sole C-source in replicate anaerobic incubations without

acetylene amendment for 3 or 7 days. This procedure is known as “stable isotope probing.”

Potential nitrification activity (PNA) was measured by incubating soils (5 g) with 50 mL of 1.5

mM NH4Cl in sodium phosphate buffer (pH 7.2) with or without acetylene (1% v/v). Acetylene

treatment inhibits only chemolithotrophic nitrifiers, but not heterotrophic nitrifiers. Thus, we

Activity and Diversity of Nitrogen-Cycling Microbial Communities in Soil Sequences Around California—Stein

were able to discriminate between heterotrophic and chemolithotrophic nitrification activities.

Vials were incubated with shaking at 28 ºC and nitrate accumulation was measured by

Technicon autosampler in the slurry over 90 h. Since nitrification causes acidification, the pH

was maintained by periodic addition of NaOH throughout the experiment. PNA was defined as

the linear increase in nitrate production over time. DNA was extracted from soils by bead-

beating following manufacturers’ protocols (MO Bio Laboratories, Carlsbad CA). DNA

extracted from soils incubated with 13

C-labeled substrates was separated on a Cs-TFA gradient

via ultracentrifugation as described elsewhere (Neufeld et al 2007). The 13

C-labeled band was

recovered from the tube using a needle, precipitated, and resuspended in TE buffer for analysis.

Diversity of the total bacterial and archaeal populations (16S rRNA genes), select denitrifying

(nirK and nirS nitrite reductase) and nitrifying (bacterial and archaeal ammonia monooxygenase,

amoA) genes, and active denitrifying bacterial populations (nirK and nirS genes from 13

C-labeled

DNA) were analyzed by denaturing gradient gel electrophoresis (DGGE) of PCR-amplified

products using DNA recovered from the soil samples (Muyzer et al 1993). Bands from DGGE

gels were extracted, cloned, and sequenced. Sequences were analyzed for similarity to their

nearest relatives as described elsewhere (Kulp et al 2006). PCR primers used in this study are

listed in Table 2.

Results

Question #1: How does the diversity of N-cycling microorganisms vary at different

spatial scales and across wildland soil sequences? We addressed this question by performing

multivariate statistical analysis on the diversity of functional genes in correlation with

physicochemical parameters measured across each soil sequence. The collection of

physicochemical parameters measured within each soil sequence was largely congruent with that

of prior observations (from references in Table 1), indicating long-term stability of soils at each

site. Exceptions included local soil pH, temperature, and water content, which varied

significantly between our collections from 2005 and 2007 (data in prior Kearney progress

reports). These differences were expected due to seasonal fluctuations and differences in weather

and annual precipitation patterns.

PCR amplification products were obtained from the majority of DNA extracted from the

soils, although two of the four sites in Los Osos did not yield amplifiable PCR products from the

native soils (Table 3). Dice similarity coefficients of DGGE banding patterns from PCR

amplification products from four functional genes (nirK, nirS, BamoA, AamoA) showed more

similarity of nitrifying and denitrifying microbial populations within the Mendocino, Sierra, and

Los Osos sequences, and more diversity within the Merced and Shasta soil sequences (Fig. 1).

However, principle components analysis, correlating all soil physicochemical parameters with

functional gene DGGE banding patterns showed clustering of soils within their own sequences

(Fig. 2). Thus, soils within a sequence were largely congruent (i.e. less diverse) and distinct from

other soil sequences. This result leads us to conclude that diversity of N-cycling microbial

populations increases with physical distance.

Significant correlations were found between Merced soil DGGE banding patterns with

potential nitrification activity (PNA) and nitrate (Fig. 2). All of the Merced soils except the one

lacking measurable PNA (Merced 4) had PCR-amplifiable amoA gene products from bacteria,

whereas Merced soils 2 and 4 did not have amplifiable amoA gene products from archaea (Fig.

3). Although we are still in the process of quantifying bacterial and archaeal amoA genes from


these soils, the lack of archaeal amoA in Merced 2 suggests that bacteria may be the more

significant ammonia-oxidizers in these soils. Similarly, in the Sierra climo-sequence, bacterial

amoA genes were detected in all soils across the sequence, but archaeal amoA genes were only

found in Sierra 1 and 3, suggesting that bacterial ammonia oxidizers play the more significant

role. No other concrete conclusions could be drawn regarding the presence or absence of amoA

genes in correlation with PNA or other soil factors in the absence of relative gene abundance

data.

Together, the data suggest that the diversity of N-cycling microbial communities is less

within a soil sequence than between soil sequences. The results suggest that physicochemical

parameters within a relatively restricted geographical area allows for adaptation and selection of

particular groups of nitrifiers and denitrifiers. However, as observed below, there is some

heterogeneity of microbial communities within soil sequences that can be correlated to specific

physicochemical parameters.

Question #2: Can the structure and activities of N-cycling microbial communities be

predicted based on chemical or physical features of the soil? We addressed this question by

correlating specific gene diversity with soil physicochemical parameters without specific regard

to site or soil sequence. Canonical correspondence analysis (CCA), a multivariate method

designed to indicate potential relationships between environmental parameters and DGGE bands,

was statistically verified by LOGIT (P


in our stable isotope probing experiments, denitrifiers containing nirK genes tend to out-compete

those with nirS genes in the majority of soils.

In conclusion, our data suggest that the presence and diversity of some microbes –

archaeal ammonia oxidizers and nirS-encoding denitrifiers – are more driven by specific

physicochemical variables than bacterial ammonia oxidizers and nirK-encoding denitrifiers.

Interestingly, only one taxonomic cluster of bacterial amoA genes was identified in all the

wildland soils, indicating very limited diversity. The presence of Nitrosospira cluster 3A amoA

genes across soils sequences exhibiting a range of PNA rates suggests that the organisms persist

in soils even in the absence of substrate and are not very sensitive to physicochemical variation.

For the denitrifying communities, the data indicate strong correlation of nirS, but not nirK, genes

with denitrifying activities, which was further explored in the remaining experiments.

Question #3: Does acetate-consuming denitrification drive a significant component

of carbon and nitrogen cycling in wildland soils? By providing 13

C-labeled acetate or glucose

to soil samples under denitrifying conditions, we labeled the biomass of the initial heterotrophic

consumers (3 day incubation) and organisms that are competent in utilization of these substrates

(7 day incubation). DGGE of nirK and nirS marker genes showed the diversity of particular

denitrifying functional guilds. The lack of amplification of amoA genes from the 13

C-labeled

DNA indicated that we accurately separated it from unlabeled 12

C-DNA as amoA-encoding

organisms are aerobic chemolithoautotrophs and are unable to assimilate organic carbon. Unlike

DNA extracted from non-enriched soils, 13

C-labeled DNA yielded nirK PCR product from

nearly all of the samples whereas only a few nirS PCR products were attained (Tables 3&5).

Although more analysis remains to be done, it appears that both non-enriched and 13

C-labeled

soils had the same distribution of nirS genes. Thus, the above observation that nirS-encoding

denitrifiers are active only in soils where denitrifying conditions are optimal will be further

verified by statistically comparing data between the non-amended and 13

C-labled soils. Although

some sites and soil sequences showed similar DGGE banding patterns regardless of carbon

source or incubation time, such patterns were not consistent across all sites or soil sequences

(Figs. 6-11). Note that while we report the identity of the nearest cultured relative where

available, functional genes are not necessarily indicative of phylogeny or organism identity, and

thus these identities should be taken as provisional and showing association with particular

clusters of nirK or nirS genes found in other environmental samples.

Merced chronosequence. The diversity of nirK and nirS was the highest in the Merced sites

of all the soil sequences examined. Within this soil sequence, the nirK DGGE patterns were

most similar within sampling sites regardless of carbon source or incubation time although more

band richness (i.e. numbers of bands) was seen with the longer incubation time (Fig. 6). Based

on sequence analysis, the majority of DGGE bands from all sites within this soil sequence were

affiliated with the same phylogenetic group, which shows a close relationship to genes from

denitrifying strains of Sinorhizobium spp. (Alphaproteobacteria) (Table 6). nirK DGGE bands

related to Paracoccus, Alcaligenes, and Rhizobium were found only at the Merced 1 site with

acetate as a substrate (Table 6). Thus, while detectable diversity was present in the DGGE

analysis, sequences were generally clustered together indicating limited diversity at a broader

level within the soil sequence. These data indicate that the parent material may be a major driver

of overall nirK diversity while microdiversity might be determined by site-specific

environmental factors such as carbon substrate utilization. DGGE band patterns of nirS genes

were very similar for the four Merced sites that gave nirS PCR product (Fig. 11). Most nirS


DGGE band sequences were related to the Alicycliphilus sp. R-24604 and Paracoccus sp. R-

26897 (Table 7). Therefore, nirK sequences were much more diverse than nirS sequences and

were found in soils with relatively high levels of PDA (Table 5) suggesting that nirK-encoding

denitrifiers are likely the dominant active microbes in these soils. Although there may be a

positive correlation between band richness and potential denitrification activity, this hypothesis

remains to be tested statistically.

Sierra climosequence. Most of the sites in this soil sequence had low nirK diversity, i.e.

few DGGE bands (Fig. 7). Most of the DGGE band sequences matched environmental clones

from agroecosystem soils and activated sludge, although a single band position was highly

similar to Bradyrhizobium sp. BTAi (99.3% similar, 426bp)(Table 6). nirS DGGE bands were

only detected after a 7 day incubation with glucose in the Sierra 3 and 5 samples (Figure 11 and

Table 7). Both Sierra and Shasta soil sequences had very few nirS DGGE bands, indicating that

denitrifiers using nirS were more limited in these two soil sequences relative to the others.

Shasta chronosequence. DGGE banding patterns of amplified nirK gene products showed

very low band richness with a total of ca. 17 bands from all samples and no sample having more

than 5 bands (Fig. 8). Acetate stimulated PDA much more than glucose (Table 5), and as a result

more nirK DGGE bands were detected from DNA isolated from the 13

C-acetate than the 13

C-

glucose enrichment (Fig. 8). Most DGGE band sequences were most closely related to

environmental clones from agroecosystem soils (Table 6). nirS gene products were only found

in two of the samples and diversity was quite low (Fig. 11). This again supports the idea that

NirK is the dominant gene product used by denitrifying microbes in these wildland soils, but that

NirS is active under optimal conditions. Furthermore, denitrification activity in the majority of

the wildland soils was largely stimulated by the presence of acetate, but not by glucose.

Mendocino chronosequence. The nirK DGGE banding patterns in this soil sequence

showed the second highest level of diversity next to Merced soils (Fig. 9). All DGGE band

sequences were related to Rhizobiales (Sinorhizobium and Bradyrhizobium;

Alphaproteobacteria). Similar to the Merced soil sequence, nirS amplification products were

found in most of the soil samples from Mendocino, but again, the community had very low

diversity (Fig. 11). Unlike the other soil sequences, glucose amendment either had no effect on

rates of PDA or reduced PDA below that of unamended soil at many of the sites (Table 5). In

contrast, acetate had a stimulatory effect on the majority of PDA measurements in these soils.

Thus, more in-depth analysis will be required to correlate the denitrifying community with

measurements of PDA in these soils and why these soils might be controlled by different factors

than other wildland soils.

Los Osos chronosequence. DGGE banding patterns of amplified nirK genes showed low

diversity and few changes with carbon enrichment (Fig. 10). Furthermore, DNA sequences of

DGGE bands from Los Osos were highly similar to those found in the Mendocino samples

(Table 6). This result corresponds to the analysis of non-enriched soil DGGE banding patterns

with physicochemical parameters in which the Mendocino and Los Osos samples grouped

together in our PCA plot (Fig. 2). Interestingly, we could not detect nirS gene products in any of

the Los Osos soil samples (Table 5). Thus, the active denitrifying community in soils at Los

Osos soils is likely a subset of the nirK-encoding community in Mendocino soils.


Discussion

The first part of this study examined the diversity of gene markers for nitrification and

denitrification across a series of different wildland soil sequences. Thus far, we have been able to

see that ammonia-oxidizing archaea and nirS-encoding denitrifiers correlate to specific

physicochemical variables more consistently than ammonia-oxidizing bacteria and nirK-

encoding denitrifiers. Nevertheless, the second part of the study utilizing 13

C-labeled substrates

to access the active component of the denitrifying consortium showed that the portion of the

denitrifying community utilizing acetate and sometimes glucose as a substrate is likely more

driven by nirK-encoding than nirS-encoding denitrifiers, although the latter organisms can

apparently compete well when denitrifying conditions are optimal. The first part of the study also

revealed that although each soil sequence has a range of physicochemical parameters (e.g.

organic carbon content with age, temperature/moisture with elevation, etc.), N-cycling microbial

communities at different sites within a soil sequence were very similar to one another. We also

found that some soil sequences (i.e. Mendocino and Los Osos) shared similar N-cycling

microbial communities even though they were relatively distant geographically. This similarity

could likely be due to the coastal proximity of both the Mendocino and Los Osos sites.

We are only beginning to analyze data obtained from stable isotope probing experiments in

context of the broader studies reported above. Nonetheless, we are beginning to see some

patterns. First, nirK is by far the dominant nitrite reductase gene encoded by denitrifiers in

wildland soils. Second, in most cases the carbon source and incubation time made little

difference in which organisms were detected, indicating that the denitrifiers are capable of

consuming new organic carbon relatively quickly (i.e. in less than 3 days), despite our prior

studies of the substrate utilization efficiency and substrate utilization velocity indicating that the

rate of organic carbon consumption varied significantly from soil to soil (see previous Kearney

reports for details). Also, denitrifiers appear to be site or soil sequence specific, are not uniformly

distributed throughout the California soils, and have variable responses to carbon addition (as

judged by PDA rates). Third, the sequence identities of DGGE bands were highly similar to

those from agricultural soils, sewage sludge, and other highly managed environments. Thus, the

denitrifiers in wildland soils may not be unique and may be similar to those found in managed

environments. Alternatively, we have such short sequences from the DGGE method that it may

be difficult in our final analysis to assign gene sequences to discrete taxonomic units.

The differences between SIP experiments and studies performed on non-enriched soils

are that the SIP experiments focus attention on the most active component of the anaerobic

denitrifying community. Furthermore, the SIP experiments were carried out under anaerobic,

denitrifying conditions while the non-enriched soils were aerobic. Thus, the two data sets are not

directly comparable. However, our final analysis will include comparison of the denitrifier

community as defined by SIP with that found in non-enriched soils. Already we have seen

similar properties of Mendocino and Los Osos soils including physicochemical, activity, and

community data. We intend to carry out more detailed analyses of denitrifier gene distribution

patterns from non-enriched soils to determine if any environmental factors are specifically

correlated with the patterns seen in the SIP data (e.g. PDA rates with nirK band richness).

Together, this data set represents the first in-depth assessment of nitrifying and

denitrifying microbial communities across a broad range of wildland soils. Nearly all other

published studies have been carried out in managed, grassland, or forest soils. In answer to our

original questions, we have found that: 1) diversity of N-cycling microbial communities is less


within a soil sequence than between soil sequence, although some soil sequences appear to be

quite similar to one another, 2) the structure of some N-cycling communities, particularly the

ammonia oxidizing archaea and the nirS-encoding denitrifiers, can be predicted by particular

physicochemical features, although this correlation may not be completely applicable to the

active component of the microbial community, and 3) acetate-consuming denitrifiers appear to

be more important in wildland soils than glucose-consuming denitrifiers. Furthermore, the active

denitrifiers in wildland soils tend to encode nirK nitrite reductase. The correlations found in this

study will establish a baseline of N-cycling microbial communities in wildland soils to compare

with the ecology and N-cycling in perturbed ecosystems. Perhaps the comparison between

wildland and perturbed or managed soils will allow us to understand how N-cycling microbial

communities adapt to environmental changes.

5. References

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of nitrite reductase genes (nirK and nirS) to detect denitrifying bacteria in environmental

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N variation

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bacteria. Appl. Environ. Microbiol. 65: 1652-7

Harden JW. 1988. Genetic interpretations of elemental and chemical differences in a soil

chronosequence, California. Geoderma 43: 179-93

Hornek R, Pommerening-Röser A, Koops H-P, Farnleitner AH, Kreuzinger N, et al. 2006.

Primers containing universal bases reduce multiple amoA gene specific DGGE band

patterns when analyzing the diversity of beta-ammonia oxidizers in the environment. J.

Microbiol. Methods 66: 147-55

Kulp TR, Hoeft SE, Miller LG, Saltikov C, Murphy JN, et al. 2006. Dissimilatory arsenate and

sulfate reduction in sediments of two hypersaline, arsenic-rich soda lakes: Mono and

Searles lakes, California. Appl. Environ. Microbiol. 72: 6514-26

Lilienfein J, Qualls RG, Uselman SM, Bridgham SD. 2003. Soil formation and organic matter

accretion in a young andesitic chronosequence at Mt. Shasta, California. Geoderma 116:

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Lilienfein J, Qualls RG, Uselman SM, Bridgham SD. 2004. Adsorption of dissolved organic and

inorganic phosphorous in soils of a weathering chronosequence. Soil Sci. Soc. Am. J. 68:

620-8

Merritts D, Chadwick O, Hendricks D. 1991. Rates and processes of soil evolution on uplifted

marine terraces, northern California. Geoderma 51: 241-75

Moody LE, Graham RC. 1995. Geomorphic and pedogenic evolution in coastal sediments,

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Muyzer G, De Waal EC, Uitterlinden AG. 1993. Profiling of complex populations by denaturing

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coding for 16S rRNA. Appl. Environ. Microbiol. 59: 695-700

Neufeld JD, Vohra J, Dumont MG, Lueders T, Manefield M, et al. 2007. DNA stable-isotope

probing. Nat. Prot. 2: 860-6

Øvreås L, Forney L, Daae FL, Torsvik V. 1997. Distribution of bacterioplankton in meromictic

Lake Saelenvannet, as determined by denaturing gradient gel electrophoresis of PCR-

amplified gene fragments coding for 16S rRNA. Appl. Environ. Microbiol. 63: 3367-73

Purkhold U, Wagner M, Timmermann G, Pommerening-Röser A, Koops H-P. 2003. 16S rRNA

and amoA-based phylogeny of 12 novel betaproteobacterial ammonia-oxidizing isolates:

extension of the dataset and proposal of a new lineage within the nitrosomonads. Int. J.

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Sollins P, Spycher G, Topik C. 1983. Processes of soil organic-matter accretion at a mudflow

chronosequence, Mt. Shasta, California. Ecology 64: 1273-82

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atmospheric carbon dioxide driven by temperature change. Science 272: 393-6

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Wuchter C, Abbas B, Coolen MJL, Herfort L, van Bleijswijk J, et al. 2006. Archaeal nitrification

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Table 1. Description of soil sequences

Location # of

sites

Sequence

Type

Ecological Unit Parent material/

geomorphology

Vegetation Refs.

Merced 5 Chrono Great Valley Dry

Steppe

Granitic alluvium Annual grasses (Brenner et al 2001, Harden 1988,

White et al 1996)

Central

Sierra

6 Climo Sierra Nevada Quartz diorite to

granodiorite

Ponderosa pine, mixed

conifers, true fir, lodgepole

pine, oaks, annual grasses

(Dahlgren et al 1997, Trumbore et

al 1996)

Mt. Shasta 4 Chrono Southern Cascades Andesitic mudflows Ponderosa pine (Dickson & Crocker 1953,

Lilienfein et al 2003, Lilienfein et

al 2004, Sollins et al 1983)

Jug Handle

Reserve,

Mendocino

9 Chrono Coastal Steppe Beach sands to

marine terraces

Annual grasses, redwood,

Douglas fir, bishop pine,

cypress

(Merritts et al 1991, Yu et al

2003)

Los Osos 4 Chrono Central Coast

Chaparral

Beach sands to

marine terraces

Shrubs, annual grasses (Moody & Graham 1995)


Table 2. Primer sequences used in this study

Target Gene Name Sequence (5’→3’) Ref.

Bacteria 16S rDNA 341F* CCTACGGGAGGCAGCAG 1

518R ATTACCGCGGCTGCTGG 1

Bacteria nirK F1aCu ATCATGGTSCTGCCGCG 2

R3Cu* TCGATCAGRTTGTGGTT 2

Bacteria nirS nirS1F* CCTAYTGGCCGCCRCART 3

nirS6R CGTTGAACTTRCCGGT 3

Bacteria amoA amoAf-i* GGGGITTITACTGGTGGT 4

amoAr-i CCCCTCIGIAAAICCTTCTTC 4

Archaea 16S rDNA pArch340F* TACGGGGYGCASCAG 5

pArch519R TTACCGCGGCKGCTG 5

Archaea amoA Arch-amoA forward CTGAYTGGGCYTGGACATC 6

Arch-amoA reverse* TTCTTCTTTGTTGCCCAGTA 6

“*” GC-Clamp added for DGGE-PCR.

References: 1. (Muyzer et al 1993), 2. (Hallin & Lindgren 1999), 3. (Braker et al 1998), 4.

(Hornek et al 2006), 5. (Øvreås et al 1997), 6. (Wuchter et al 2006)


Table 3. PCR amplification products from each soil.

Site Bacteria Archaea Bac-amoA Arch-amoA NirK NirS

Merced1 + + + + + +

Merced2 + + + + + +

Merced3 + + + + + +

Merced4 + + + +

Merced5 +

Sierra1 + + + + + +

Sierra2 + +

Sierra3 + + + + + +

Sierra4 + + + + +

Sierra5 + + + + +

Sierra6 + + + + +

Mt. Shasta1 + + + + +

Mt. Shasta2 + + + +

Mt. Shasta3 + +

Mt. Shasta4 + + + + +

Mendocino1 + + +

Mendocino2 + + + + +

Mendocino3 + + + + +

Mendocino4 + + +

Mendocino5 + + + + + +

Mendocino6 + + + +

Mendocino7 + + + +

Mendocino8 + + +

Mendocino9 + +

Los Osos1

Los Osos2 + + + +

Los Osos3 + + +

Los Osos4


Table 4. Presence of archaeal DGGE bands that correlating with specific physicochemical

parameters within soil sequences.

pH/salinity PNA/nitrate Ammonia/water Merced A21, A26, A28 A23, A24, A25, A28

Sierra A26 A23, A24, A25

Shasta A26 A25 A48

Mendocino A21, A26, A28, A33 A23, A24, A25, A27 A46, A47, A48

Los Osos A21, A26, A28, A33 A23, A24, A25, A27


Table 5. PCR amplification of nirK and nirS genes from soils incubated with different 13

C-substrates under denitrifying (anaerobic)

conditions. (+: PCR detected, blank: no amplification)

sample# site

nirK nirS PDA

acetate

3day

acetate

7day

glucose

3day

glucose

7day

acetate

3day

acetate

7day

glucose

3day

glucose

7day No C Acetate Glucose

1 merced1 + + + + + + + + 48.89 175.13 73.78

2 merced2 + + + + + + + + 28.47 165.77 178.32

3 merced3 + + + + + + + + 25.28 169.47 88.81

4 merced4 + + + + + + 10.21 124.71 60.49

5 merced5 + + + + + + 11.11 127.76 121.96

6 Sierra1 + + + + 27.10 113.54 155.16

7 Sierra2 + + + + 13.87 157.11 111.53

8 Sierra3 + + + + + 32.56 262.77 187.78

9 Sierra4 + + + + 30.99 57.04 70.36

10 Sierra5 + + + + + 36.17 239.37 231.51

11 Sierra6 + + + + 55.31 201.86 52.93

12 Shasta1 + + + + 13.42 169.52 63.79

13 Shasta2 + + + + 13.40 89.70 31.84

14 Shasta3 + + + + + 29.70 136.24 27.33 15 Shasta4 + + + + + 0.00 122.34 23.66

16 mendocino1 + + + + 11.16 135.30 131.50

17 mendocino2 + + + + + + 238.05 231.18 120.36

18 mendocino3 + + + + + + + + 148.27 182.18 95.94

19 mendocino4 + + + + + 80.33 223.46 95.45

20 mendocino5 + + + + 176.98 175.92 62.97

21 mendocino6 + + + 112.91 167.13 139.19

22 mendocino7 + + + + + + + + 48.92 270.35 120.30

23 mendocino8 + + + + + + + + 174.39 237.84 134.19

24 mendocino9 + + + + 118.65 163.62 87.96

25 Los Osos1 + + + + 11.60 85.05 52.28

26 Los Osos2 + + + + 115.33 357.23 138.09

27 Los Osos3 + + + + 29.17 327.93 140.91

28 Los Osos4 + + + + 14.39 164.65 149.14


Table 6. Nearest neighbor of nirK DGGE band DNA sequences in 13

C-acetate and glucose

assimilating bacterial populations in all soil sequences.

Site DGGE band Nearest neighbor Accession# Similarity

merced 1 K01A7D-1 Paracoccus denitrificans copper dependent nitrite reductase (nir)

gene AF114788

88.2

(380/431)

merced 1 K01A7D-2 Alcaligenes sp. STC1 nirK gene for dissimilatory nitrite

reductase, complete cds AB046603

89.6

(389/434)

merced 1 K01A7D-3 Paracoccus denitrificans copper dependent nitrite reductase (nir)

gene AF114788

88.9

(384/432)

merced 1 K01G3D-1 Clone Ag08-69 putative nitrite reductase (nirK) gene DQ304300 83.2

(326/392)

merced 1 K01G3D-2 Clone T8R2_0-7cm_061 NirK (nirK) gene DQ784011 84.4

(342/405)

merced 2 K02A3D-1 Partial nirK gene for copper containing nitrite reductase, clone

HlS3-226 AM235266

95.5

(386/404)


HlS3-226 AM235266

95.3

(385/404)

merced 2 K02G3D-1 Partial nirK gene for copper containing nitrite reductase, clone

HlS3-226 AM235266

95.3

(385/404)


HlS3-226 AM235266

95.5

(386/404)


HlS3-226 AM235266

87.3

(344/394)

merced 3 K03A7D-1 Partial nirK gene for copper-containing nitrite reductase, clone AgMA36

AJ487549 99.5 (410/412)

merced 3 K03A7D-2 Partial nirK gene for copper-containing nitrite reductase, clone

AgMA36 AJ487549

100.0

(412/412)

merced 3 K03A7D-3 Partial nirK gene for copper-containing nitrite reductase, clone AgMA36

AJ487549 99.5 (411/413)

merced 3 K03A7D-4 Partial nirK gene for copper-containing nitrite reductase, clone

AgMA36 AJ487549

99.3

(409/412)

merced 4 K04A7D-1 Clone T7R1_13-20cm_075 NirK (nirK) gene DQ783580 91.0 (375/412)

merced 4 K04A7D-2 Clone T7R1_13-20cm_075 NirK (nirK) gene DQ783580 90.8

(374/412)

merced 4 K04G3D-2 Clone DGGE band AK2B nitrite reductase (nirK) gene AY583382 89.0 (365/410)


HlS3-226 AM235266

88.3

(354/401)

merced 5 K05A7D-2 Partial nirK gene for copper containing nitrite reductase, clone HlS3-226

AM235266 88.3 (354/401)

merced 5 K05A7D-3 Sinorhizobium sp. R-25078 nirK gene for nitrite reductase AM230841 84.1

(344/409)

merced 5 K05G7D-1 Clone DGGE band AK2B nitrite reductase (nirK) gene AY583382 89.2 (370/415)

merced 5 K05G7D-2 Clone DGGE band AK2B nitrite reductase (nirK) gene AY583382 89.0

(365/410)

sierra 1 K06G7D-1 Clone T8R1_13-20cm_094 NirK (nirK) gene DQ783944 95.3 (324/340)

sierra 2 K07A3D-1 Clone KRF50 putative nitrite reductase (nirK) gene DQ182214 98.0 (50/51)

sierra 2 K07A7D-2 Clone T8R2_13-20cm_063 NirK (nirK) gene DQ784089 100.0 (49/49)

sierra 4 K09G3D-1 Clone T8R1_0-7cm_012 NirK (nirK) gene DQ783858 94.1 (48/51)

sierra 5 K10A7D-1 Clone T7R1_13-20cm_075 NirK (nirK) gene DQ783580 91.1 (378/415)

sierra 5 K10A7D-2 Clone T7R1_13-20cm_075 NirK (nirK) gene DQ783580 91.3

(387/424)

sierra 5 K10G3D-1 Clone KEP51 putative nitrite reductase (nirK) gene DQ182211 90.9 (60/66)

sierra 5 K10G7D-1 Clone DGGE band AK2B nitrite reductase (nirK) gene AY583382 89.5 (376/420)

sierra 6 K11A3D-1 Bradyrhizobium sp. BTAi1, complete genome CP000494 99.3

(426/429)

sierra 6 K11A3D-2 Bradyrhizobium sp. BTAi1, complete genome CP000494 99.3 (427/430)


mt.shasta 2 K13A7D-1 Clone T8R1_13-20cm_031 NirK (nirK) gene DQ783959 91.6 (391/427)

mt.shasta 2 K13G7D-1 Clone T8R2_0-7cm_017 NirK (nirK) gene DQ784006 95.5 (63/66)

mt.shasta 3 K14G7D-1 Clone T8R1_13-20cm_049 NirK (nirK) gene DQ783964 94.4

(404/428)

mt.shasta 4 K15A3D-1 Bradyrhizobium sp. BTAi1, complete genome CP000494 98.5 (66/67)

mt.shasta 4 K15A3D-2 Bradyrhizobium sp. BTAi1, complete genome CP000494 94.6

(368/389)

mt.shasta 4 K15G3D-1 Clone T1R1_0-7cm_045 NirK (nirK) gene DQ783227 90.3 (56/62)

mendocino 1 K16A3D-1 Bradyrhizobium sp. BTAi1, complete genome CP000494 99.3 (426/429)

mendocino 1 K16A3D-2 Bradyrhizobium sp. BTAi1, complete genome CP000494 100.0

(410/410)

mendocino 1 K16A7D-1 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 93.2 (400/429)

mendocino 1 K16A7D-2 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 97.0

(419/432)

mendocino 1 K16G3D-1 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 90.1 (393/436)

mendocino 1 K16G3D-2 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 92.1

(396/430)

mendocino 1 K16G3D-3 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 91.2 (393/431)

mendocino 1 K16G7D-1 Clone M9 nitrite reductase (nirK) gene AY121534 86.1

(348/404)

mendocino 1 K16G7D-2 Bradyrhizobium sp. BTAi1, complete genome CP000494 95.5 (399/418)

mendocino 2 K17G3D-1 Clone MW00049 nitrate reductase (nirK) gene AY249374 90.1

(391/434)

mendocino 2 K17G3D-2 Clone T7R1_0-7cm_043 NirK (nirK) gene DQ783512 91.0 (394/433)

mendocino 2 K17G3D-3 Clone MW00049 nitrate reductase (nirK) gene AY249374 91.7

(396/432)

mendocino 3 K18A3D-1 Clone U65 nitrite reductase (nirK) gene AY121516 95.2 (412/433)

mendocino 3 K18A7D-1 Clone K30O29 putative copper nitrite reductase (nirK) gene EF644998 94.7

(413/436)

mendocino 3 K18A7D-2 Clone T8R2_0-7cm_034 NirK (nirK) gene DQ783992 90.4 (368/407)

mendocino 5 K20G3D-2 Clone SJY-17 copper-containing dissimilatory nitrite reductase

(nirK) gene AY683863

97.7

(260/266)

mendocino 6 K21A7D-1 Bradyrhizobium sp. BTAi1, complete genome CP000494 99.1 (425/429)


(425/429)

mendocino 6 K21G3D-1 Clone SJY-17 copper-containing dissimilatory nitrite reductase (nirK) gene

AY683863 93.5 (286/306)

mendocino 7 K22A3D-1 Sinorhizobium sp. R-31759 partial nirK gene for copper-

containing nitrite reductase AM403563

96.9

(406/419)

mendocino 7 K22A3D-2 Sinorhizobium sp. R-31759 partial nirK gene for copper-containing nitrite reductase

AM403563 95.9 (401/418)

mendocino 7 K22A3D-3 Clone C1-15 putative nitrite reductase (nirK) gene DQ304147 96.0

(411/428)

mendocino 7 K22A7D-1 Clone N16 NirK (nirK) gene DQ996545 87.1

(296/340)


(345/405)


(411/430)


(422/432)

Los Osos 1 K25A3D-1 Clone KRF7 putative nitrite reductase (nirK) gene DQ182217 85.6

(267/312)

Los Osos 1 K25A3D-2 Clone T1R1_0-7cm_069 NirK (nirK) gene DQ783223 93.5

(402/430)


Los Osos 1 K25A3D-3 Clone T8R1_13-20cm_101 NirK (nirK) gene DQ783924 93.2 (398/427)


(405/431)

Los Osos 1 K25A7D-1 Clone T1D2_0-7cm_039 NirK (nirK) gene DQ783183 87.1 (373/428)

Los Osos 1 K25A7D-2 Clone T1D2_0-7cm_008 NirK (nirK) gene DQ783186 87.2

(353/405)

Los Osos 1 K25G3D-1 Clone T1R1_0-7cm_069 NirK (nirK) gene DQ783223 91.6 (393/429)

Los Osos 2 K26A7D-1 Clone N16 NirK (nirK) gene DQ996545 87.8

(266/303)

Los Osos 2 K26G3D-1 Sinorhizobium sp. R-31759 partial nirK gene for copper-containing nitrite reductase

AM403563 93.1 (392/421)


(380/420)

Los Osos 4 K28A7D-2 Clone T1R1_0-7cm_022 NirK (nirK) gene DQ783219 85.7 (361/421)

Los Osos 4 K28G3D-1 Clone SJY-27 copper-containing dissimilatory nitrite reductase

(nirK) gene AY683873 97.3 (71/73)

Los Osos 4 K28G7D-1 Bradyrhizobium sp. BTAi1, complete genome CP000494 99.1 (425/429)


Table 7. Nearest neighbor of nirS DGGE bands in 13

C-acetate and glucose assimilating

bacterial populations in California soils.

DGGE band Nearest neighbor Accession# Similarity

nirS-1 NirS gene for cytochrome cd1 nitrite reductase, clone: NS69 AB378618 88.6 (302/341)













Fig. 1. Prevalence and diversity of functional genes (bacterial amoA, archaeal amoA, nirK, nirS) among all sites as determined by denaturing gradient gel electrophoresis (DGGE). The similarities between samples are shown in a dendrogram of Dice similarity coefficients (unweighted pair group method with arithmetic mean). This method only takes band position, not intensity, into consideration. The scale bar indicates the level of similarity between sites.


Fig. 2. Principle Components Analysis (PCA) of functional gene composition and diversity with soil physicochemical parameters at each sampling site. 45% of the variability among the sites could be described by components in the two primary axes.


Fig. 3. Potential nitrification activity and presence of AOA and/or AOB at each site within the soil sequences. Direction of arrow denotes increase in parameter (age, elevation, or organic material). Presence of AOA or AOB determined by ability to amplify amoA genes with specific PCR primers (see Table 3).

0

1

2

3

4

5

μg N

O3

-·

mL

slu

rry -

1 d

ay

-1

- + - -

- - - -

+ - + - +

+ + + - +

+ - + - - -

+ + + + + +

+ - - +

- + + -

- + + - +

- + + - +

AOA

AOB

NA - + NA

NA - - NA

Merced Sierra Shasta

Mendicino

South Los OsosNorth

Age AgeOrganicsElev.

Age and Elevation

Heterotrophic

Combined

Chemolithotrophic


Fig. 4. Canonical correspondence analysis (CCA) of bacterial amoA DGGE bands with soil physicochemical parameters.

-1.0 1.0

-1.0

1.0

BamoA29BamoA30

BamoA34

BamoA36

BamoA37 BamoA38BamoA38

BamoA42 BamoA43

BamoA45

BamoA46

BamoA47BamoA48BamoA49

BamoA51

BamoA52

BamoA53

BamoA73

Chloride

NH4

Nitrate

K

pH

LOI

tempsoiltemp

PDA_NOC

PDA_ACET

PDA_GLUC

PNA_Acet

PNA


Fig. 5. CCA analysis of archaeal amoA DGGE bands with soil physicochemical parameters.

-0.6 1.0

-0.8

0.8

AamoA21

AamoA23AamoA24AamoA25

AamoA26

AamoA27

AamoA28

AamoA33

AamoA46

AamoA_47

AamoA_48

Chloride

Sulfate

Phosphou

NH4

Nitrate

Nitrite

Ca

K

Mg

NapH

water co

LOI

tempsoiltemp

PDA_NOC

PDA_ACET

PDA_GLUC

PNA_AcetPNA

conducti


Fig. 6. Band presence/absence (Dice) based cluster analysis of the nirK DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched Merced soil samples.


Fig. 7. Band presence/absence (Dice) based cluster analysis of the nirK DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched Sierra soil samples.


Fig. 8. Band presence/absence (Dice) based cluster analysis of the nirK DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched Mt. Shasta soil samples.


Fig. 9. Band presence/absence (Dice) based cluster analysis of the nirK DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched Mendocino soil samples.


Fig. 10. Band presence/absence (Dice) based cluster analysis of the nirK DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched Los Osos soil samples.


Fig. 11. Band presence/absence (Dice) based cluster analysis of the nirS DGGE band patterns of 13C-DNA extracted from 13C-acetate or -glucose enriched samples from all soil sequences.

This research was funded by the Kearney Foundation of Soil Science: Understanding and

Managing Soil-Ecosystem Functions Across Spatial and Temporal Scales, 2006-2011 Mission

(http://kearney.ucdavis.edu). The Kearney Foundation is an endowed research program created

to encourage and support research in the fields of soil, plant nutrition, and water science within

the Division of Agriculture and Natural Resources of the University of California.
http://kearney.ucdavis.edu/

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