Nitrogen Mineralization and Assimilation at Millimeter Scales

C H A P T E R

F O U R

Nitrogen Mineralization and Assimilation at Millimeter Scales David D. Myrold,* Jennifer Pett-Ridge,† and Peter J. Bottomley*,‡ Contents 92 92 93 93 94 94 95 96 101 109 109

1. Introduction 2. Microbial Habitats in Soil 2.1. Rhizosphere 2.2. Plant detritus 2.3. Soil aggregates 3. Methodological Approaches 3.1. General isotope pool dilution principles and procedures 3.2. Applications of IRMS analysis to soil microhabitats 3.3. Applications of SIMS analysis to soil microhabitats 4. Conclusions References

Abstract The assimilation (uptake or immobilization) of inorganic nitrogen (N) and the production of ammonium (NH4þ) from organic N compounds are universal functions of microorganisms, and the balance between these two processes is tightly regulated by the relative demands of microbes for N and carbon (C). In a heterogeneous environment, such as soils, bulk measurements of N mineralization or immobilization do not reflect the variation of these two processes in different microhabitats (1 mm–1 mm). Our purpose is to review the approaches that can be applied to measure N mineralization and immobilization within soil microhabitats, at scales of millimeter (using adaptations of 15N isotope pool dilution and IRMS—isotope ratio mass spectrometry) to micrometer (using SIMS—secondary ion mass spectrometry).

* Department of Crop and Soil Science, Oregon State University, Corvallis, Oregon, USA Chemical Sciences Division, Lawrence Livermore National Laboratory, California, USA Department of Microbiology, Oregon State University, Corvallis, Oregon, USA

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Methods in Enzymology, Volume 496 ISSN 0076-6879, DOI: 10.1016/B978-0-12-386489-5.00004-X

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2011 Elsevier Inc. All rights reserved.

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1. Introduction Microorganisms need nitrogen (N) to carry out cellular functions and to grow. Ammonium (NH4þ) is generally acknowledged as their preferred source of inorganic N; however, microorganisms may also use organic N compounds, such as amino acids, or nitrate (NO3). When microorganisms encounter organic N in excess of the growth needs for N, they engage in a combination of enzymatic processes that depolymerize and deaminate organic forms of N into NH4þ. This process is commonly termed N mineralization or ammonification. Through nitrification, NH4þ can be oxidized to NO3. The opposing, anabolic process is the transformation of NH4þ or NO3 into organic N compounds for assimilation into cellular constituents, a process also known as N immobilization. In soil microbiology, it is conventional to think of mineralization of organic N occurring under carbon (C)-limited conditions and assimilation of inorganic N occurring under C-sufficient (i.e., N-limited) conditions. In the environment, N mineralization and immobilization can occur simultaneously, but at a given time the two processes are likely to be spatially partitioned into different microhabitats (Chen and Stark, 2000; Myrold and Bottomley, 2008; Schimel and Bennett, 2004). To gain a more sophisticated understanding of the factors that control the balance between N mineralizing and immobilizing activities, there is a need to move beyond bulk measurements that average across microhabitats to measuring N mineralization and assimilation at scales relevant to microorganisms. In this chapter, we review methods that can be used to measure N mineralization and assimilation at several spatial scales. In doing so, we will focus primarily on soils because of their variability over a wide range of spatial scales.

2. Microbial Habitats in Soil Soil is a complex, spatially and temporally heterogeneous, threedimensional habitat in which microorganisms function to process C, N, and other nutrients. Consequently, soil can be considered a mosaic of niches, or microhabitats, with unique characteristics that structure their associated microbial communities and their functions (Dechesne et al., 2007; Jastrow and Miller, 1998; Nunan et al., 2007). In soil science, these microhabitats have commonly been classified and named based on their sphere of influence (Beare et al., 1995; Fig. 4.1). The rhizosphere, decaying plant material, and soil aggregates are soil microhabitats that have been examined for sub-centimeter scale measurements of N mineralization and immobilization.

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Mycorrhizal hyphae

Clay microstructures

Plant root

Pore space Microbial debris

Macroaggregates

Microaggregate

Detritus with saprotrophic fungi

Figure 4.1 Examples of microhabitats found in soil. Nitrogen mineralization and immobilization have been investigated in soil associated with roots and mycorrhizal hyphae (rhizosphere), plant detritus, and aggregates of various sizes. Adapted from Jastrow and Miller (1998).

2.1. Rhizosphere Plants alter the physical and chemical environment around their roots, generating the microhabitat known as the rhizosphere (e.g., Dessaux et al., 2010), thereby influencing the microorganisms living there and their function (Hawkes et al., 2007; Philippot et al., 2009). Most directly, this is through symbiotic relationships of plant roots with mycorrhizal fungi or with root-nodulating, N2-fixing bacteria. Indeed, the ubiquity and influence of mycorrhizae has led to finer microhabitat distinctions (e.g., “mycorrhizosphere” or “hyphosphere”). More generally plants put substantial amounts of C into the soil through root exudation ( Jones et al., 2009), alter soil water and gas relationships (Philippot et al., 2009), and compete with rhizosphere microorganisms for nutrients (Inselsbacher et al., 2010; Kaye and Hart, 1997; Ma˚nsson et al., 2009). Although N mineralization and immobilization are elevated in rhizosphere compared to bulk soil (Breland and Bakken, 1991; Herman et al., 2006; Norton and Firestone, 1996), within the rhizosphere there is also likely to be significant heterogeneity and the development of smaller microhabitats (Philippot et al., 2009).

2.2. Plant detritus Dead plant parts are diverse, ranging from succulent, fresh leaves or fine roots to highly lignified, coarse woody materials. Whether incorporated into soil through agricultural activities or entering through natural litter fall

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or root turnover, plant detritus represents a major input of C, N, and other nutrients into soil systems and is a hot spot for microbial activity. In general, the tipping point between N mineralization and immobilization is a function of the quality of the residue (e.g., its C:N ratio, lignin content) and the composition and physiology of the microbial community (Myrold and Bottomley, 2008). Microbial communities directly associated with decaying residue are known to be different than bulk soil (McMahon et al., 2005) and vary with residue characteristics (Baumann et al., 2009; Rousk and Ba˚a˚th, 2007; Williams et al., 2007). As decomposition proceeds, the chemical composition of the residue changes (e.g., C:N ratio narrows, percentage of lignin increases); these changes are accompanied by shifts in the relative magnitudes of N immobilization and mineralization (Gaillard et al., 1999; Magid et al., 2006) and sometimes by concomitant shifts in the microbial community (Baumann et al., 2009; Williams et al., 2007). It is not clear if this is a cause or an effect of the latter.

2.3. Soil aggregates The structure of the soil—soil aggregation—imparts many of the key properties to soil in terms of the transport of water, solutes, and gases, and it shapes the habitats available to soil microorganisms (Or et al., 2007). Soil aggregates vary in size and are dynamic in terms of their formation and disintegration; these characteristics are partly a function of microbial activities, such as the production of extracellular polymeric materials that help stabilize aggregates (Six et al., 1999; Tisdall and Oades, 1982). Consequently, microbial communities and their activities can vary among different sizes of soil aggregates (Mendes et al., 1999; Muruganandam et al., 2009). For example, microbial N mineralization and immobilization were greatest in intermediate to larger water-stable soil aggregates (Angers et al., 1997; Muruganandam et al., 2010). Variation in microbial processes can also occur within individual soil aggregates. For example, the interplay between oxygen diffusion and microbial respiration results in a gradient of oxygen concentrations within a soil aggregate, which in turn influence denitrification (Sexstone et al., 1985). Gradients of nutrients and C are also likely to exist within aggregates, and thereby have the potential to influence the balance between N mineralization and immobilization processes.

3. Methodological Approaches Measurements of N mineralization and immobilization in soils are typically made on bulk samples, such as undisturbed cores ( 10–1000 cm3) or sieved soils (10 g–1 kg), and most often changes in the pool sizes of NH4þ

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and/or NO3 are measured at two or more times to determine a net rate of N mineralization (or immobilization if a decrease in inorganic N is observed). In order to separate N mineralization from N immobilization, it is most common to use compounds labeled with the stable isotope 15N as part of the isotope pool dilution technique (Hart and Myrold, 1996; Hart et al., 1994; Murphy et al., 2003). Assimilation of N can also be measured by the incorporation of an 15 N label directly into the microbial biomass (Hatch et al., 2000; Ledgard et al., 1998; Myrold and Tiedje, 1986) or by determination of residual 15N in soils after removal of the added tracer (Andersen and Jensen, 2001; Mary et al., 1998; Recous et al., 1999). Because the processes occur simultaneously, the use of 15N is necessary when measuring N mineralization or immobilization at small spatial scales, regardless of the approach used.

3.1. General isotope pool dilution principles and procedures

NH4+ p

5

14N

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15N

Initial time

NH4+ c

p

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14N

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15N

Final time

c

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The conceptual model of isotope dilution and its associated mathematical calculations were developed by Kirkham and Bartholomew (1954). In brief, an 15N-labeled compound is added to a soil pool (15NH4þ in the case of gross N mineralization or immobilization) and as unlabeled organic N is mineralized to NH4þ, the 15N abundance of the NH4þ is diluted and decreases exponentially (Fig. 4.2). By measuring the size and 15N abundance of the NH4þ pool at two (or more) times, the rates of NH4þ production (gross N mineralization) and consumption (the sum of NH4þ assimilation and nitrification) can be calculated using the equations derived by Kirkham and Bartholomew (1954) or more recent modeling approaches (Mary et al., 1998; Mu¨ller et al., 2007; Myrold and Tiedje, 1986). The isotope dilution model has several assumptions, including: (i) no isotopic discrimination, (ii) uniform distribution of label, (iii) equilibrium

0.5 0.4 0.3 0.2 0.1 0.0 Initial

Final Time

Figure 4.2 The principle of 15N isotope dilution as applied to the production (p, gross N mineralization) and consumption (c) of NH4þ. 15N-labeled NH4þ is added to a soil (in this case, in equal amounts to the unlabeled, native soil NH4þ) and measured shortly thereafter (initial time). The sample is incubated (often for 1–2 days) and measured again (final time). At the right is the expected change in the 15N abundance of the NH4þ pool through time as it is diluted with unlabeled NH4þ produced from organic N through mineralization.

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between added label and indigenous, unlabeled pools, and (iv) no remineralization of the label, although this can be taken into account (Kirkham and Bartholomew, 1955; Mary et al., 1998; Mu¨ller et al., 2007; Myrold and Tiedje, 1986). The assumptions of homogeneity of labeling and equilibrium are influenced by spatial heterogeneity of indigenous soil inorganic N, as well as the spatial distribution of the soil microbial community, and can result in inaccurate calculations of gross rates of N mineralization and immobilization (Davidson et al., 1991; Manzoni et al., 2008). Consequently, there has been interest in scaling down the 15N isotope dilution approach to study N mineralization and immobilization in soil microhabitats. In principle, 15N isotope dilution can be applied to soil microhabitats by specifically labeling particular microhabitats (often experimentally isolated with physical barriers), by labeling the whole soil and later separating the desired fraction, or with a combination of these two approaches. The most significant practical challenge when working with microhabitats is whether the sample is large enough so that the concentration and 15N abundance of the pool of interest (e.g., NH4þ) can be measured with existing analytical instruments. For example, it is difficult to accurately measure the 15N abundance of a sample with < 10 mg of N using modern isotope ratio mass spectrometers (IRMS; Barrie and Prosser, 1996). To use isotope dilution at the scale of a single soil aggregate, an aggregate with a 1 cm3 volume would need to have an NH4þ concentration of 10 mg N kg 1 soil, which is several-fold higher than typical soil NH4þ concentrations (Fig. 4.3). The volume of soil can be reduced when highly enriched 15N solutions are added if a “spike” of NH4þ of known mass and 15N abundance is added; however, this reduces the sensitivity and precision of the measurement. In general, sensitivity declines in proportion to the amount of spike added relative to amount of N from the sample. Thus, if the size of the spike was 100-fold, the sensitivity would decline by a factor of 100.

3.2. Applications of IRMS analysis to soil microhabitats Applying 15N-labeling methods to soil microhabitats requires samples large enough (>10 mg or >10 mm3; Fig. 4.3) to be analyzed by IRMS techniques. In general, the methods can be placed into two categories based on the order of isolating the microhabitat of interest and adding the label. 3.2.1. Physical separation followed by labeling The primary requisite for isolating a microhabitat is that doing so will not compromise its ability to function in its natural state. This is unlikely to be the case for rhizosphere soil because by definition it is dependent upon the functions of living roots, and this dependency is disrupted once the roots are removed. Physical fractionation methods are more appropriate to isolating detritusphere (e.g., particulate organic matter, light fraction) or water-stable

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NanoSIMS ToF-SIMS MALDI-ToF 15

N isotope dilution + spike 15

N isotope dilution 10–12 10–11 10–10 10–9 10–8 10–7 10–6 10–5 10–4 10–3 10–2 10–1 100 101

Mass (g) 0.001

0.010 0.100 1.000 Linear dimension (mm)

10.000

Figure 4.3 Recommended method for measuring nitrogen (N) assimilation (gray bar) as a function of sample size. Linear dimensions based on cubic geometry and a soil bulk density of 1.25 g cm 3. Nitrogen assimilation assumes a microbial biomass of 40 mg N kg 1 soil. Isotope dilution measurements of N mineralization (white bar) require samples  10 times larger, and are based on a pool size of 2 mg N kg 1 soil following label addition. Note that there is an intermediate range in which N assimilation cannot be conveniently measured by existing methods. SIMS—secondary ion mass spectrometry; ToF—time-of-flight; MALDI—matrix-assisted laser desorption/ionization.

aggregates, although the separation methods used have the potential to alter subsequent microbial activity. An example of this approach is the study of gross N-cycling rates in soil aggregates of different sizes by Muruganandam et al. (2010). They chose three size classes (2–4, 0.5–1.0, and <0.25 mm diameter) of water-stable soil aggregates that were isolated from a soil that had been subjected to three different tillage regimes for 22 years. Special features of the experimental design included: Soil was air dried at 4  C for 4–5 days to achieve 10% gravimetric water content. The air-dried soil was separated into aggregate size classes by sieving through screens of different mesh sizes. The choice of aggregate sizes used for experimentation was based upon the fact they possessed different biological and chemical properties (Muruganandam et al., 2009).  15N-labeled NH4þ or NO3 was added in combination with the respective unlabeled ionic partner, for example, 15NH4þ 14NO3 or 14 NH4þ 15NO3 at 30 atom% 15N.  Inorganic N was added at concentrations of 2 mg NH4þ–N and 8 mg NO3–N g 1 soil because the background soil NO3–N level was 2.5fold greater than that of NH4þ–N. Replicate samples (10 g) of each aggregate size class were incubated for a week with periodic destructive sampling at 0, 2, 4, and 7 days. This amount of soil allowed them to use standard IRMS methods (e.g., Hart et al., 1994). 

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Label was added in a prescribed amount of water sufficient to raise the soil water content to 60% of water holding capacity.

It should be remembered that relatively large shifts in the water content of soil during label addition might change conditions sufficient to influence the gross rates (Herron et al., 2009; Murphy et al., 1997). Each replicate sample provided enough mass for standard extraction, diffusion, and IRMS analysis procedures (Stark and Hart, 1996). Muruganandam et al. (2010) used the FLUAZ model (Mary et al., 1998) to calculate gross rates of N mineralization, N immobilization, and nitrification. In general, gross rates of all processes increased with decreasing tillage intensity and were positively correlated with soil C and microbial biomass. No effect of aggregate size on any of the gross rates was observed in the most intensively tilled soil; however, differences in gross rates across aggregate sizes were more pronounced as tillage intensity decreased, often peaking in the 0.5–1.0 mm size class. For example, gross N mineralization varied from 0.9 to 1.1 mg N kg 1 aggregates d 1 across the three size classes for soils subjected to moldboard plowing, whereas the rate for the no-till soil were 1.9 (< 0.25 mm), 3.8 (0.5–1.0 mm), and 2.6 (2.0–4.0 mm) mg N kg 1 aggregates d 1. It should be noted, however, that all aggregates were crushed and mixed prior to label addition to enhance uniformity of labeling, which may have had the unintended effect of stimulating activity in the presumably more stable, larger aggregates found in less disturbed soils (Elliot, 1986). Further, it is possible that crushing and mixing might upset the spatial separation essential for maintaining the balance between mineralization and immobilization of N. 3.2.2. Labeling followed by physical dissection More commonly, soil systems are labeled with 15N-containing substrates, incubated for a period of time, and then the desired fractions are isolated. This approach has been used to study the rhizosphere, detritusphere, and soil aggregates. Studies of N cycling in the rhizosphere often use microcosms in which roots are physically constrained by membrane barriers with a mesh size that prevents root penetration (Luster et al., 2009). This results in distinct compartments of rhizosphere and bulk soil that can be easily separated for analysis. When the root compartment becomes highly colonized, a gradient of rhizosphere influence can become established in the adjacent bulk soil compartment. This rhizosphere gradient can then be subsampled to examine the finer-scale spatial influence of plant roots on microbial activity. An example of this is the study of Schenk zu Schweinsberg-Mickan et al. (2010), where 15N-labeled rhizodeposits were traced into microbial biomass at five distances between 1.0 and 4.2 mm from the root surface. They collected 10 g of soil from each distance, and performed chloroform

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fumigation–extraction (a method to measure microbial biomass; Brookes et al., 1985) to obtain fractions for IRMS analysis. As expected, the 15N assimilated into microbial biomass decreased exponentially with distance from the root surface, but was still above unlabeled control levels at 4.2 mm away from the roots. The 15N isotope dilution approach has also been applied to study the influence of the rhizosphere on microbial N cycling. Herman et al. (2006) grew Avena barbata plants in microcosms designed so that individual roots could be isolated in a thin layer of soil (Fig. 4.4A). This set-up facilitated the addition of 15NH4þ or 15NO3 as well as fine-scale sampling of rhizosphere soil associated with different longitudinal regions of the roots and of bulk soil. Special features of this experimental design included: 

Addition of high concentrations of NH4þ–N (14 mg N kg 1 soil) and harvesting sufficient rhizosphere soil (3 g) for analyses by standard IRMS methods.

A Divider Main chamber Slot

20mm C

D

et

rit

us

B

Soil

Soil 10 mm

2 mm 2 mm

Figure 4.4 Examples of using physical separation or dissection of soil microhabitats: (A) Rhizobox design that allows isolation of roots for labeling with 15N-labeled solutions (adapted from Herman et al., 2006; photo by Dr. Jennifer Pett-Ridge); (B) a detritus sandwich, adapted from Wang and Bakken (1997); (C) dissecting a soil aggregate, adapted from Dechesne et al. (2003).

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A rather nontraditional, short labeling incubation time of 2–3 h. A preliminary experiment had shown that label distribution in rhizosphere soil became heterogeneous after only 7 h presumably due to differential rates of N assimilation along the root length.  Further, the experiment performed with 15NO3 was done over a different time interval (6 h), and larger root sections (8 cm) were harvested, presumably because of different behavior of NO3 in the rhizosphere and to get sufficient NO3 for IRMS analysis. Herman et al. (2006) found that gross N mineralization was lowest in the bulk soil and increased 7- to 13-fold in the rhizosphere, suggesting that while the microbial population was being stimulated by rhizosphere C availability, it was accessing soil N by increasing N mineralization rates. In addition, nitrification was found to change along the root away from the root tip. The gross rate of nitrification was identical to that of gross NH4þ consumption in the zone nearest the root tip (0–8 cm), whereas in the 8–16 cm zone, a much higher rate of NH4þ consumption far exceeded that of gross nitrification and probably represented enhanced root uptake of NH4þ in this zone rather than microbial assimilation, because the rate was more than 10-fold greater than the size of the pool of microbial biomass N. In an analogous fashion, the influence of decomposing plant materials on microbial activity has been explored by constructing microcosms with defined layers of plant residue sandwiched between layers of soil (Gaillard et al., 1999; Wang and Bakken, 1997). To date, this approach has most often been used to determine the effect of heterogeneous distribution of plant N uptake, so N mineralization has been assessed only indirectly (Magid et al., 2006; Wang and Bakken, 1997). Gaillard et al. (1999) did use the “detritus sandwich” approach (Fig. 4.4B) to follow the transfer and incorporation of 13 C- and 15N-labeled wheat straw into the detritusphere. Similar to rhizosphere studies, the label reached about 5 mm into the soil from the detritus– soil interface, probably reflecting similar diffusional constraints on the movement of soluble organic compounds. The fate of plant C and N into soil aggregates has also been traced by incubating 13C- and 15N-labeled wheat straw, and subsequently separating out aggregate size fractions (Angers et al., 1997). Although assimilation of N into microbial biomass was not measured directly, their data showed that greater proportions of N (and C) were found in larger aggregates (0.24–1.0 and >1.0 mm diameter) than in smaller aggregates, at least during the first 200 days of incubation. The greater N immobilization activity is consistent with gross N immobilization rates measured by 15N isotope dilution (Muruganandam et al., 2010). All the physical dissection methods described so far depend upon collecting enough soil to use IRMS approaches without the addition of a “spike” of N (Fig. 4.3). It is tempting to think that one could physically

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separate smaller samples, for example, by sampling a transect through a soil aggregate (Fig. 4.4C), as has been done for ammonia- and nitrite-oxidizing bacteria or the mineralization of a 14C-labeled herbicide (Gonod et al., 2006; Grundmann and Debouzie, 2000). Calculations suggest that, with current technology, this could be scaled down to a sample of 2 mm in linear dimension (Fig. 4.3). Other methods, such as secondary ion mass spectrometry (SIMS), are necessary to examine finer-scale resolution of N mineralization or assimilation.

3.3. Applications of SIMS analysis to soil microhabitats SIMS has the potential to provide quantitative measures of N assimilation at the single-cell scale; however, relatively few SIMS studies have been carried out in microbiological systems, with only a handful of applications in soil (Blair et al., 2006; Clode et al., 2009; Cliff et al., 2002, 2007; DeRito et al., 2005; Herrmann et al., 2007a,b; Pumphrey et al., 2009). In SIMS imaging, a highly charged ion beam is used to sputter a sample surface, causing secondary ions that are derived from the sample’s upper layers to be emitted (Fig. 4.5). When these ions are separated by their mass/charge ratio and detected, a quantitative ion map of the sputtered area is created. There are two broad classes of SIMS instruments used to study N dynamics in soils: time-of-flight (ToF) and dynamic (magnetic sector) SIMS. In ToF-SIMS, a primary ion beam is pulsed and resulting secondary ions are detected based on their mass-to-charge ratio and the time an ion takes to reach the detector. Although ToF-SIMS has the capacity to measure the full mass spectrum and detect molecular species, its design can require the user to compromise between high spatial resolution and mass resolving power (see reviews by Jacoby, 2006; Lockyer and Vickerman, 2004). With dynamic SIMS (e.g., the Cameca 3f, 5f, and NanoSIMS), N assimilation can be quantitatively measured with up to 50-nm resolution, typically after a cell culture or environmental sample has been exposed to a continuous or pulsechase 15N-labeling experiment. The highest spatial resolution is accomplished by visualizing 15N distribution with either the NanoSIMS 50 or 50 L ion microprobe (Cameca, Gennevilliers, France). Because N ionizes poorly alone, N must be detected as part of the cyanide (12C14N or 12C15N) polyatomic ion. In a ratio image of the 12C15N:12C14N ion maps, an 15N enrichment greater than the natural 15N abundance ratio of 0.37 atom% suggests that the cell, particle, or subcellular region assimilated “new” N during the labeling period. MALDI-ToF (matrix assisted laser desorption/ ionization ToF mass spectrometry) is one additional non-SIMS imaging technique that may also be useful for fine-scale imaging of N uptake. However, this type of analysis, where a laser is used to desorb surface molecules that are then detected by a ToF spectrometer, has so far been used primarily for biomolecule imaging in tissue and organs (reviewed by Burnum et al., 2008; McDonnell and Heeren, 2007) as opposed to soils.

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To mass spectrometer

Analysis beam sources (Cs+, O–)

– –

–

y ar nd o c

s ion

Sec – on da ry

io n

s

Se

–

Cs+

+ e–

–

e–

–

–

e– e– + – e– e–

e– –

Sample n

tio

e–

ec oll

M

d

12

C

19

F

-c lti

u

+

rs

to

c ete 31

P

32

S

35

Cl

Sample surface

50 nm beam diameter under ideal conditions

Figure 4.5 NanoSIMS instrument schematic. The left panel depicts the NanoSIMS sputtering process where primary ions (Csþ in this case) impact the sample surface, and secondary ions derived from the sample’s upper layers are extracted coaxial to the primary ion beam. The right panel shows an overview of the entire instrument, following the ion path from the primary ion source, to sample chamber, through the magnetic sector and ultimately secondary ion detection by a series of five electron multiplier detectors. Courtesy of Cameca (Gennevilliers, France), as modified by Dr. Peter Weber (Lawrence Livermore National Laboratory, USA).

ToF-SIMS and MALDI-ToF may be particularly useful for questions where the spatial scale of interest ranges between 100 mm and 1 cm (Fig. 4.4; e.g., in micro-and some macroaggregates), or where the molecular fate of assimilated 15N is of interest. For finer scale applications (e.g., single cells or colonies, bacteria–mineral interactions, <100 mm microaggregates), NanoSIMS imaging has a number of advantages: high sensitivity (1 in 20 N atoms are detected), ability to measure concurrent data for multiple (5–7) elements/isotopes, and high mass specificity (e.g., allowing the user to distinguish 12C15N from 13C14N at mass 27) while retaining high resolution (50 nm; Boxer et al., 2009; Lechene et al., 2006). Although NanoSIMS is still an emerging technology, it allows the investigator to quantitatively visualize such fine-scale differences in N uptake as those between bacteria in the endosphere, rhizosphere, or ectosphere of plant roots exposed to 15 NH4þ (Clode et al., 2009). These differences would never be discernable with bulk IRMS analysis. Access to these instruments is currently limited ( 20 exist worldwide, with 8 instruments focused on biological samples);

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however, multiple new instruments are being installed each year. As this approach has the potential to provide valuable insights into the interactions between microbial diversity and soil N cycling, we focus on it here. The rate of new N uptake may be quantitatively determined with NanoSIMS analysis following an 15N tracer experiment where samples were exposed to 15N2, 15NH4þ, or other 15N-labeled substrate. Exposure periods should be kept brief relative to best estimates of the doubling time of microbial populations being studied and subsamples should be harvested at multiple time points during the isotope incubation in order to measure and minimize recycling and leakage, which can approach 35% of newly fixed N (Ploug et al., 2010). As the NanoSIMS measures total N, and does not discriminate between N derived from NO3, NH4þ, or amino pools, measurements yield net N uptake only, not gross assimilation. The amount of N lost from a cell due to secondary metabolite production, denitrification, passive leakage, or sample preparation effects cannot be precisely measured with NanoSIMS analysis. Indeed, it is important to remember that the instrument measures total N ionized, without discerning between organic and inorganic sources. If we define N assimilation strictly as the uptake of N and its conversion into cellular organic N forms, NanoSIMS measurements will bulk all new 15N taken up regardless of whether the organism has utilized it for organic biosynthesis or not. By contrast, with ToF-SIMS analyses, enrichment of NO3, NH4þ, and amino pools can be measured independently; this allowed Cliff et al. (2007) to measure microspatial patterns in gross N assimilation and mineralization in a model soil system— following the Kirkham and Bartholomew model described in detail above. In some situations, such as a cell culture where one may collect multiple replicate samples under controlled conditions, net N assimilation may be nearly equal to gross N assimilation. Using 99.99 atom% NaH13CO3 and 15 N2 as cyanobacterial substrates, Popa et al. (2007) and Finzi-Hart et al. (2009) demonstrated that NanoSIMS can be used to isolate subcellular regions of high N2-fixation activity, as well as storage locations, mobilization, and assimilation rates of newly fixed N in cyanobacteria. To calculate atom% 15 N excess (APE), they measured the initial N isotopic ratios of the culture at T0 (Ri) and the isotopic ratio of the labeled cells (Rf): APE ¼ ½Rf =ðRf þ 1Þ  Ri =ðRi þ 1Þ  100%

ð4:1Þ

Net-fixation (Fxnet) or the percentage of N assimilation into the cells relative to their initial N content was calculated as Fxnet ¼ ðFs =Fi Þ  100%;

ð4:2Þ

where Fi is the fraction of N in the sampled cells derived from the initial cellular N content and Fs is the fraction of N in the sampled cells taken up

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from the spiked 15N pool. These and many other NanoSIMS studies (Clode et al., 2009; Halm et al., 2009; Herrmann et al., 2007a,b; Musat et al., 2008) document a high level of microheterogeneity in N assimilation at the singlecell level, which, while not surprising, was heretofore unknown. In a rhizosphere exposed briefly to 15NH4þ, Clode et al. (2009) found individual cells varied in N uptake by up to 110% relative to each other (more than 5s). The vagaries of microedaphic and genetic factors that underlie this phenomenon may be scientifically interesting—yet this cell–cell variability is also a potential problem for NanoSIMS isotopic imaging that must be overcome by adequate replication of analysis locations. With pure cultures, 5–20 individual cells/time point may be adequate to characterize the N uptake rates for the entire population (Finzi-Hart et al., 2009; Peteranderl and Lechene, 2004; Popa et al., 2007). Quantitative measurements of net N assimilation can be more difficult to achieve at small spatial scales in mixed, natural systems such as soils and sediments. In such settings, where it is not possible to know the starting total N pool that is being enriched or that an isotope tracer is homogeneously distributed, 15N tracer experiments can still provide qualitative or “potential” estimates of N immobilization for individual taxa (Musat et al., 2008; Ploug et al., 2010), can distinguish treatment effects or spatial gradients (Cliff et al., 2007; Orphan et al., 2009), and can provide evidence of symbiotic interactions. The arena of trophic and symbiotic relationships may be one of the more fruitful avenues for future NanoSIMS research on N assimilation. For example, Lechene et al. (2007) demonstrated that in some shipworms, symbiotic bacteria fix N2 that is then used by their eukaryal host cell for metabolism. In another example, Orphan et al. (2009) showed that in marine methane-oxidizing aggregates, the methanotrophic archaea member of the consortia assimilated far more N than its symbiotic sulfate reducing partner. Finally, in a study of arbuscular mycorrhizal transport of N and C to plant roots from 15N/13C enriched soil organic matter, Herman et al. (in review) were able to quantify hyphal 15N assimilation and transport to host roots at both the macro- (IRMS) and microscale (Fig. 4.6). Silicates, clays, and Fe/Al oxide minerals make it additionally challenging to apply similar experiments in soil matrices because they make it difficult to embed and thin-section soil samples (Fig. 4.7), and also cause electrical charging effects (Cliff et al., 2002). To date, a small number of proof-of-concept studies have showed that 15N isotope additions can be imaged by NanoSIMS within a natural or synthetic soil matrix. Herrmann et al. (2007a,b) used NanoSIMS to locate previously 15N-labeled Pseudomonas fluorescens cells within a sterilized sand matrix and found significant variability in N isotopic enrichment from cell to cell. In a rhizosphere system incubated with added 15NH4þ, Clode et al. (2009) also found variability as different bacterial cells took up the 15N label to differing degrees. In those that did incorporate the 15NH4þ, up to 50% of the cell

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Figure 4.6 NanoSIMS images from the surface of a Plantago root infected with Glomus hoi arbuscular mycorrhizal fungi. Fungi had access to 15N and 13C enriched soil organic matter (root did not). From left to right, total ion counts for 14N displayed in grayscale (white ¼ highest counts); NanoSIMS secondary electron image; ratio of 12 15 C N:12C14N images indicating areas of isotopic enrichment. Values superimposed on ratio image indicate 15N enrichment for subregions labeled on 14N image. The regions circled with white outlines represent the background—or main root surface. Courtesy of coauthor Pett-Ridge (Lawrence Livermore National Laboratory, USA) and Dr. Angela Hodge (University of York, UK).

N was newly assimilated. One of the few studies to have moved beyond these proof-of-principle tests used ToF-SIMS to study small-scale differences in N assimilation as a function of C versus N limitation (Fig. 4.8; Cliff et al., 2002). They qualitatively followed 15N and 13C incorporation into soil microorganisms, using an analysis regime balancing spatial resolution with high mass specificity. When they compared SIMS values with bulk-measured microbial biomass N assimilation, they found substantial spatial heterogeneity in 15N distribution that was not apparent through bulk analysis (Cliff et al., 2007). The same concept could certainly be applied with 15N-labeled plant materials—to track microbial and aggregate immobilization of plant-derived N in soil. 3.3.1. Combining N assimilation with microbial identification Many studies of microbial function in the environment aim to link phylogenetic identity and metabolic activity of individual cells. Indeed, the first significant microbiological SIMS study (Orphan et al., 2001) showed SIMS could be used to measure C assimilation, the source of C, and the taxa involved using FISH (fluorescent in situ hybridization). This can be accomplished in situ with a technique combining NanoSIMS imaging and rRNAbased in situ hybridization, called “El-FISH” or “FISH-SIMS” (Behrens et al., 2008; Li et al., 2008; Musat et al., 2008). In this approach, fluorine or bromine atoms are introduced into cells via 16S rRNA-targeted probes or in situ hybridization with halogen-labeled tyramides, enabling phylogenetic identification of individual cells by NanoSIMS imaging. This novel approach could potentially facilitate studies of the ecophysiology of known

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Figure 4.7 Soil aggregate from a sandy soil amended with 13C and 15N-labeled Pinus ponderosa fine roots and needles. (A) Montage of multiple transmission electron microscopy images (FEI Tecnai 12 120 KV Transmission Electron Microscope) of a single soil aggregate, embedded in sulfur, and microtomed to 200 nm; (B) higher resolution TEM, (C) 12C15N NanoSIMS image of putative fungal hyphae (16 mm field of view; area is indicated in (A)). Its relatively low phosphorus (P) content (data not shown) suggests that this feature may be a ‘ghost hyphae’, that is, the shell marking where live tissue once existed. (D–F) Higher resolution TEM images of likely organic particle and bacterial cells; areas are indicated relative to image in (A). Reproduced from Herrmann et al. (2007a,b).

and uncultured microorganisms in soil; however, it will need to overcome several methodological barriers, including background autofluorescence. 3.3.2. Sample preparation for SIMS SIMS experiments must be custom designed based on the hypotheses being tested, the sample matrix, and the amount of analysis time available. Analysis is performed under ultrahigh vacuum; therefore, samples must be dry, relatively flat, and vacuum stable. Sample preparation methods that preserve both the quantitative and spatial distribution of N within cells are essential. When N assimilation has resulted in the accumulation of NO3, NH4þ, or amino acids in a cell, but not yet proceeded to biosynthesis, there is a risk that these diffusible ions can be lost during sample preparation. Chemical fixation appears to attenuate this effect by cross-linking proteins, purines, and pyrimidines, and retaining at least as much newly fixed N in a cell as freeze drying (Peteranderl and Lechene, 2004). Still, the techniques used in

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Figure 4.8 Secondary electron image (A) and light micrograph (B) of an Si contact slide that was in contact with a model soil system. The system consisted of a straw–manure interface on kaolinite to which 15NO3was added. The area in panel A is bracketed in yellow in panel B. Dark, electron-poor sputtered areas in panel A are represented by white boxes in panel B. The values adjacent to the analysis areas are the atom% 15N of the region of interest of the fungal hyphae (shaded red). The dashed line represents the straw–manure interface. Note the greater 15N assimilation by the hyphae growing on the C-rich, N-poor straw compared to the N-rich manure. Bar ¼ 100 mm. Reproduced from Cliff et al. (2002).

electron microscopy (such as fast freezing followed by low temperature dehydration) would appear to be the most prudent approach. Other standard electron microscopy techniques, such as chemical fixation (e.g., 2% glutaraldehyde to stabilize biological membranes), cell filtering, resin embedding (LR White, epoxy resin Araldite 502, or sulfur) combined with ultramicrotomy, or simple air drying may suffice for stable samples (see Herrmann et al., 2007a,b for detailed embedding methods). If intact soils need to be sectioned, a diamond knife or diamond saw is necessary to cut through particles with heterogeneous density. For pure cultures or biofilms, samples should be repeatedly washed with Milli-Q H2O and transferred onto a silica chip (or other conductive smooth surface), and dried and coated with a thin conductive layer (5–20 nm) of Au, Ir, or C prior to analysis. Regardless of the sample preparation, evaluation of sample quality, topography, and morphology with high-resolution light microscopy, SEM, or TEM is critical prior to SIMS analysis. 3.3.3. NanoSIMS instrument use For analyses, an 1–5 pA Csþ primary beam should be focused to a spot size of 50–150 nm and stepped over the sample in a 128  128 pixel raster (for 1–10 mm2) or 256  256 pixel raster (for 10–30 mm2) to generate secondary ions for quantification. Dwell time is typically 1 ms per pixel and,

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although the typical raster size ranges from 5 to 50 mm2, mapping of larger areas is possible by digitally stitching multiple individual rasters together (e.g., Clode et al., 2009; Lechene et al., 2007). The SIMS instrument must be tuned for 6800 mass resolving power to resolve isobaric interferences at mass 27. Data may be collected for up to seven (with the NanoSIMS 50 L) secondary ions (e.g., 12C, 13C, 16O, 12C14N, 12C15N, 28Si, 31P) in simultaneous collection mode. Enough serial secondary ion images (i.e., layers) should be collected to achieve consistent ion yields and isotope ratios with sputtering depth. The depth of a typical analysis ranges between 50 and 200 nm and is controlled by the energy of the primary beam and the length of the analysis time (see Ghosal et al., 2008 for depth of analysis calculations). For reference, the sample should also be imaged simultaneously by secondary electrons detected by a photomultiplier. To achieve sputtering equilibrium, samples should be presputtered to a depth of  100 nm. Measurements should be repeated on multiple cells or regions of the sample to ensure accuracy and capture natural variations in N uptake. Data can be processed as quantitative isotopic ratio images using image processing software such as Cameca’s proprietary WinImage, or the MIMS plugin for ImageJ freeware (http://www.nrims.hms.harvard.edu/NRIMS_ImageJ. php), and corrected for detector dead-time and image shifts from layer to layer. Individual bacterial cells or other particles of interest may be defined as “regions of interest” (ROI), and the isotopic composition for each ROI can be calculated by averaging over all the replicate layers. Reference materials should be used as calibration standards for isotopic measurements; options include samples from microcosms where no 13C or 15N was applied, well-characterized preparations of homogeneous bioparticles (e.g., Behrens et al., 2008), or pulverized bovine liver sample (NIST SRM 1577b). Precision of 2s should be determined for individual measurements; typically measurement precision for cell cultures is 0.4–1.4% (2s) for individual 15N/14N measurements, and analytical precision of standard materials is 2.1% (2s) for an individual measurement (Popa et al., 2007). Precision for replicate analyses should be calculated by appropriate error propagation techniques. As with any technique, the user should be aware of potential issues that can compromise the quality of NanoSIMS data. Charging is the most common artifact affecting SIMS analyses of soil samples, which frequently comprise insulating materials. Although the organic constituents of soil may act as semiconductors, most mineral particles are electrically insulating and will require (at least) a 5–20 nm coating of Au, Ir, C, or other high-purity conductive material, and (commonly) the use of the electron flood gun to provide charge compensation at the sample surface. During exploratory analyses on a new sample type, the user should also sputter at high-beam currents between repeat measurements to determine if isotopic composition changes with depth.

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4. Conclusions Measurements of N mineralization and assimilation require the use of N, employed either by isotope dilution or as a tracer. In soil microhabitats, such as the rhizosphere, detritusphere, and soil aggregates, the method of 15 N isotope dilution can be scaled down to measure N mineralization in samples as small as 100 mg; N assimilation can be measured by IRMS in 10-mg samples of soil. This corresponds to microhabitats with linear dimensions of >2 mm. At smaller spatial scales, it is necessary to use SIMS, which can measure the uptake and assimilation of 15N into microorganisms and allow visualization of cell–cell interactions, but cannot measure N mineralization. Clearly, there are trade-offs between the use of the 15N isotope pool dilution approach (which yields bulk-scale gross N immobilization, but little insight into microscale controlling factors) and 15N stable isotope probing with SIMS (which can measure gross N assimilation at high spatial resolution, though at a significant cost). Given the right experimental design, this method may provide new insights into the primary factors controlling N assimilation at the microscale (e.g., moisture content and temperature), as well as biotic factors ranging from spatial distribution of active microorganisms, association of microorganisms with particular minerals, roles of filamentous fungi in mediating transport of N and other elements, and distribution/impact of N2-fixing soil microbes. To date, studies have demonstrated that N mineralization and assimilation can vary at small scales and that the balance between these opposing processes can be influenced by C inputs from roots or decaying plant materials. It is also likely that synergistic or competitive interactions among microorganisms (e.g., bacteria growing in association with fungal hyphae) affect the balance between N mineralization and assimilation, but demonstration of this possibility awaits future applications of SIMS imaging methods coupled with well-designed 15N labeling experiments. 15

REFERENCES Andersen, M. K., and Jensen, L. S. (2001). Low soil temperature effects on short-term gross N mineralisation-immobilisation turnover after incorporation of a green manure. Soil Biol. Biochem. 33, 11–521. Angers, D. A., Recous, S., and Aita, C. (1997). Fate of carbon and nitrogen in water-stable aggregates during decomposition of 13C15N-labelled wheat straw in situ. Eur. J. Soil Sci. 48, 295–300. Barrie, A., and Prosser, S. J. (1996). Automated analysis of light-element stable isotopes by isotope ratio mass spectrometry. In “Mass Spectrometry of Soils,” (T. W. Boutton and S. I. Yamsaki, eds.), pp. 1–46. Marcel Dekker, Inc., New York, NY.

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Baumann, K., Marschner, P., Smernik, R. J., and Baldock, J. A. (2009). Residue chemistry and microbial community structure during decomposition of eucalypt, wheat and vetch residues. Soil Biol. Biochem. 41, 1966–1975. Beare, M. H., Coleman, D. C., Crossley, D. A., Hendrix, P. F., and Odum, E. P. (1995). A hierarchical approach to evaluating the significance of soil biodiversity to biogeochemical cycling. Plant Soil 170, 5–22. Behrens, S., Losekann, T., Pett-Ridge, J., Weber, P. K., Ng, W. O., Stevenson, B. S., Hutcheon, I. D., Relman, D. A., and Spormann, A. M. (2008). Linking microbial phylogeny to metabolic activity at the single-cell level by using enhanced element labeling-catalyzed reporter deposition fluorescence in situ hybridization (EL-FISH) and NanoSIMS. Appl. Environ. Microbiol. 74, 3143–3150. Blair, N., Prince, K. E., Faulkner, R. D., and Till, A. R. (2006). Using the scanning electron microprobe and secondary ion mass spectrometry to locate 14C- and 13C-labelled plant residues within soil aggregates. Scanning 28, 259–266. Boxer, S. G., Kraft, M. L., and Weber, P. K. (2009). Advances in imaging secondary ion mass spectrometry for biological samples. Annu. Rev. Biophys 38, 53–74. Breland, T. A., and Bakken, L. R. (1991). Microbial growth and nitrogen immobilization in the root zone of barley (Hordeum vulgare L.), Italian ryegrass (Lolium multiflorum Lam.), and white clover (Trifolium repens L.). Biol. Fertil. Soils 12, 154–160. Brookes, P. C., Landman, A., Pruden, G., and Jenkinson, D. S. (1985). Chloroform fumigation and the release of soil nitrogen: A rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842. Burnum, K. E., Frappier, S. L., and Caprioli, R. M. (2008). Matrix-assisted laser desorption/ ionization imaging mass spectrometry for the investigation of proteins and peptides. Annu. Rev. Anal. Chem. 1, 689–705. Chen, J., and Stark, J. M. (2000). Plant species effects and carbon and nitrogen cycling in a sagebrush-crested wheatgrass soil. Soil Biol. Biochem. 32, 47–57. Cliff, J. B., Gaspar, D. J., Bottomley, P. J., and Myrold, D. D. (2002). Exploration of inorganic C and N assimilation by soil microbes with time-of-flight secondary ion mass spectrometry. Appl. Environ. Microbiol. 68, 4067–4073. Cliff, J. B., Bottomley, P. J., Gaspar, D. J., and Myrold, D. D. (2007). Nitrogen mineralization and assimilation at millimeter scales. Soil Biol. Biochem. 39, 823–826. Clode, P. L., Kliburn, M. R., Jones, D. L., Stockdale, E. A., Cliff, J. B., III, Herrmann, A. M., and Murphy, D. V. (2009). In situ mapping of nutrient uptake in the rhizosphere using nanoscale secondary ion mass spectrometry. Plant Physiol. 151, 1751–1757. Davidson, E. A., Hart, S. C., Shanks, C. A., and Firestone, M. K. (1991). Measuring gross nitrogen mineralization, immobilization, and nitrification by N-15 isotopic pool dilution in intact soil cores. J. Soil Sci. 42, 335–349. Dechesne, A., Pallud, C., Debouzie, D., Flandrois, J. P., Vogel, T. M., Gaudet, J. P., and Grundmann, G. L. (2003). A novel method for characterizing the microscale 3D spatial distribution of bacteria in soil. Soil Biol. Biochem. 35, 1537–1546. Dechesne, A., Pallud, C., and Grundmann, G. L. (2007). Spatial distribution of bacteria at the microscale in soil. In “The Spatial Distribution of Microbes in the Environment,” (R. B. Franklin and A. L. Mills, eds.), pp. 88–107. Springer, Dordrecht, The Netherlands. DeRito, C. M., Pumphrey, G. M., and Madsen, E. L. (2005). Use of field-based stable isotope probing to identify adapted populations and track carbon flow through a phenol degrading soil microbial community. Appl. Environ. Microbiol. 78, 58–65. Dessaux, Y., Hinsinger, P., and Lemanceau, P. (2010). Rhizosphere: Achievements and Challenges. Springer, Dordrecht, The Netherlands, 538 pp. Elliot, E. T. (1986). Aggregate structure and carbon, nitrogen, and phosphorus in native and cultivated soils. Soil Sci. Soc. Am. J. 50, 627–633.

Nitrogen Cycling at Millimeter Scales

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Finzi-Hart, J. A., Pett-Ridge, J., Weber, P. K., Popa, R., Fallon, S. J., Gunderson, T., Hutcheon, I. D., Nealson, K. H., and Capone, D. G. (2009). Fixation and fate of C and N in the cyanobacterium Trichiodesmium using nanometer-scale secondary ion mass spectrometry. Proc. Natl. Acad. Sci. USA 106, 6345–6350. Gaillard, B., Chenu, C., Recous, S., and Richard, G. (1999). Carbon, nitrogen and microbial gradients induced by plant residues decomposing in soil. Eur. J. Soil Sci. 50, 567–578. Ghosal, S., Fallon, S. J., Leighton, T., Wheeler, K. E., Hutcheon, I. D., and Weber, P. K. (2008). Imaging and 3D elemental characterization of intact bacterial spores with highresolution secondary ion mass spectrometry (NanoSIMS) depth profile analysis. Anal. Chem. 80, 5986–5992. Gonod, L. V., Chadoeug, J., and Chenu, C. (2006). Spatial distribution of microbial 2, 4-dichlorophenoxy acetic acid mineralization from field to microhabitat scales. Soil Sci. Soc. Am. J. 70, 64–71. Grundmann, G. L., and Debouzie, D. (2000). Geostatistical analysis of the distribution of NH4þ and NO2–-oxidizing bacteria and serotypes at the millimeter scale along a soil transect. FEMS Microbiol. Ecol. 34, 57–62. Halm, H., Musat, N., Lam, P., Langlois, R., Musat, F., Peduzzi, S., Lavik, G., Schubert, C., Singha, B., LaRoche, J., and Kuypers, M. (2009). Co-occurence of denitrification and nitrogen fixation in a meromictic lake, Lake Cadagno (Switzerland). Environ. Microbiol. 11, 1945–1958. Hart, S. C., and Myrold, D. D. (1996). 15N tracer studies of soil nitrogen transformations. In “Mass Spectrometry of Soils,” (T. W. Boutton and S. I. Yamsaki, eds.), pp. 225–245. Marcel Dekker, Inc., New York, NY. Hart, S. C., Stark, J. M., Davidson, E. A., and Firestone, M. K. (1994). Nitrogen mineralization, immobilization, and nitrification. In “Methods of Soil Analysis, Part 2. Microbiological and Biochemical Properties,” (R. W. Weaver, S. Angle, P. Bottomley, D. Bezdicek, S. Smith, A. Tabatabai, and A. Wollum, eds.), pp. 985–1018. Soil Science Society of America, Madison, WI. Hatch, D. J., Jarvis, S. C., Parkinson, R. J., and Lovell, R. D. (2000). Combining field incubation with nitrogen-15 labelling to examine nitrogen transformations in low to high intensity grassland management systems. Biol. Fertil. Soils 30, 492–499. Hawkes, C. V., DeAngelis, K. M., and Firestone, M. K. (2007). Root interactions with soil microbial communities and processes. In “The Rhizosphere: An Ecological Perspective,” (Z. G. Cardon and J. L. Whitbeck, eds.), pp. 1–29. Academic Press, New York, NY. Herman, D. J., Johnson, K. K., Jaeger, C. H., III, Schwartz, E., and Firestone, M. K. (2006). Root influence on nitrogen mineralization and nitrifications in Avena barbata rhizosphere soil. Soil Sci. Soc. Am. J. 70, 1504–1511. Herman, D. J., Firestone, M. K., Pett-Ridge, J., Nuccio, E., and Hodge, A. (in review). Microbial community utilization of carbon and nitrogen from decomposing root Litter: Effects of an arbuscular mycorrhizal fungus. FEMS Microbiol. Ecol. Herrmann, A. M., Clode, P. L., Fletcher, I. R., Nunan, N., Stockdale, E. A., O’Donnel, A. G., and Murphy, D. V. (2007a). A novel method for the study of the biophysical interface in soils using nano-scale secondary ion mass spectrometry. Rapid Commun. Mass Spectrom. 21, 29–34. Herrmann, A. M., Ritz, K., Nunan, N., Clode, P. L., Pett-Ridge, J., Kilburn, M. R., Murphy, D. V., O’Donnell, A. G., and Stockdale, E. A. (2007b). Nano-scale secondary ion mass spectrometry—A new analytical tool in biogeochemistry and soil ecology: A review article. Soil Biol. Biochem. 39, 1835–1850. Herron, P. M., Stark, J. M., Holt, C., Hooker, T., and Cardon, Z. G. (2009). Microbial growth efficiencies across a soil moisture gradient assessed using 13C-acetic acid vapor and 15 N-ammonia gas. Soil Biol. Biochem. 41, 1262–1269.

112

David D. Myrold et al.

Inselsbacher, E., Umana, N. H. N., Stange, F. C., Gorfer, M., Schu¨ller, E., Ripka, K., Zechmeister-Boltenstern, S., Hood-Novotny, R., Strauss, J., and Wanek, W. (2010). Short-term competition between crop plants and soil microbes for inorganic N fertilizer. Soil Biol. Biochem. 42, 360–372. Jacoby, M. (2006). Bioimaging with mass spectrometry. Chem. Eng. News 84, 55–56. Jastrow, J. D., and Miller, R. M. (1998). Soil aggregate stabilization and carbon sequestration: Feedbacks through organomineral associations. In “Soil Processes and the Carbon Cycle,” (R. Lal, J. M. Kimble, R. F. Follett, and B. A. Stewart, eds.), pp. 207–223. CRC Press LLC, Boca Raton, FL. Jones, D. L., Nguyen, C., and Finlay, R. D. (2009). Carbon flow in the rhizosphere: Carbon trading at the soil-root interface. Plant Soil 321, 5–33. Kaye, J. P., and Hart, S. C. (1997). Competition for nitrogen between plants and soil microorganisms. Trends Ecol. Evol. 12, 139–143. Kirkham, D., and Bartholomew, W. V. (1954). Equations for following nutrient transformations in soil, utilizing tracer data. Soil Sci. Soc. Am. Proc. 18, 33–34. Kirkham, D., and Bartholomew, W. V. (1955). Equations for following nutrient transformations in soil, utilizing tracer data: II. Soil Sci. Soc. Am. Proc. 19, 189–192. Lechene, C., Hillion, F., McMahon, G., Benson, D., Kleinfeld, A. M., Kampf, J. P., Distel, D., Luyten, Y., Bonventre, J., Hentschel, D., Park, K. M., Ito, S., et al. (2006). High-resolution quantitative imaging of mammalian and bacterial cells using stable isotope mass spectrometry. J. Biol. 5, 20. Lechene, C. P., Luyten, Y., McMahon, G., and Distel, D. L. (2007). Quantitative imaging of nitrogen fixation within animal cells. Science 317, 1563–1566. Ledgard, S. F., Jarvis, S. C., and Hatch, D. J. (1998). Short-term nitrogen fluxes in grassland soils under different long-term management regimes. Soil Biol. Biochem. 30, 1233–1241. Li, T., Wu, T. D., Mazeas, L., Toffin, L., Guerquin-Kern, J. L., Leblon, G., and Bouchez, T. (2008). Simultaneous analysis of microbial identity and function using NanoSIMS. Environ. Microbiol. 10, 580–588. Lockyer, N. P., and Vickerman, J. C. (2004). Progress in cellular analysis using ToF-SIMS. Appl. Surf. Sci. 212–232, 377–384. Luster, J., Go¨ttlein, A., Nowack, B., and Sarret, G. (2009). Sampling, defining, characterising and modeling the rhizosphere-the soil science tool box. Plant Soil 321, 457–482. Magid, J., De Neergaard, A., and Brandt, M. (2006). Heterogeneous distribution may substantially decrease initial decomposition, long-term microbial growth and N-immobilization from high C-to-N ratio resources. Eur. J. Soil Sci. 57, 517–529. Ma˚nsson, K., Bengtson, P., Falkengren-Grerup, U., and Bengtsson, G. (2009). Plant-microbial competition for nitrogen uncoupled from soil C:N ratios. Oikos 118, 1908–1916. Manzoni, S., Porporato, A., and Schimel, J. P. (2008). Soil heterogeneity in lumped mineralization-immobilization models. Soil Biol. Biochem. 40, 1137–1148. Mary, B., Recous, S., and Robin, D. (1998). A model for calculating nitrogen fluxes in soil using 15N tracing. Soil Biol. Biochem. 30, 1963–1979. McDonnell, L. A., and Heeren, R. M. A. (2007). Imaging mass spectrometry. Mass Spectrom. Rev. 26, 606–643. McMahon, S. K., Williams, M. A., Bottomley, P. J., and Myrold, D. D. (2005). Dynamics of microbial communities during decomposition of carbon-13 labeled ryegrass fractions in soil. Soil Sci. Soc. Am. J. 69, 1238–1247. Mendes, I. C., Bandick, A. K., Dick, R. P., and Bottomley, P. J. (1999). Microbial biomass and activities in soil aggregates affected by winter cover crops. Soil Sci. Soc. Am. J. 63, 873–881. Mu¨ller, C., Ru¨tting, T., Kattge, J., Laughlin, R. J., and Stevens, R. J. (2007). Estimation of parameters in complex 15N tracing models by Monte Carlo sampling. Soil Biol. Biochem. 39, 715–726.

Nitrogen Cycling at Millimeter Scales

113

Murphy, D. V., Fillery, I. R. P., and Sparling, G. P. (1997). Method to label soil cores with 15 NH3 gas as a prerequisite for 15N isotopic dilution and measurement of gross N mineralization. Soil Biol. Biochem. 29, 1731–1741. Murphy, D. V., Recous, S., Stockdale, E. A., Fillery, I. R. P., Jensen, L. S., Hatch, D. J., and Goulding, K. W. T. (2003). Gross nitrogen fluxes in soil: Theory, measurements and application of 15N pool dilution techniques. Adv. Agron. 79, 69–118. Muruganandam, S., Israel, D. W., and Robarge, W. P. (2009). Activities of nitrogenmineralization enzymes associated with soil aggregate size fractions of three tillage systems. Soil Sci. Soc. Am. J. 73, 751–759. Muruganandam, S., Israel, D. W., and Robarge, W. P. (2010). Nitrogen transformations and microbial communities in soil aggregates from three tillage systems. Soil Sci. Soc. Am. J. 74, 120–129. Musat, N., Halm, H., Winterholler, B., Hoppe, P., Peduzzi, S., Hillion, F., Horreard, F., Amann, R., Jorgensen, B. B., and Kuypers, M. M. M. (2008). A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc. Natl. Acad. Sci. USA 105, 17861–17866. Myrold, D. D., and Bottomley, P. J. (2008). Nitrogen mineralization and immobilization. In “Nitrogen in Agricultural Soils,” (W. Raun and J. S. Schepers, eds.), pp. 157–172. American Society of Agronomy, Madison, WI. Myrold, D. D., and Tiedje, J. M. (1986). Simultaneous estimation of several nitrogen cycle rates using 15N: Theory and application. Soil Biol. Biochem. 18, 559–568. Norton, J. M., and Firestone, M. K. (1996). N dynamics in the rhizosphere of Ponderosa pine seedlings. Soil Biol. Biochem. 28, 351–362. Nunan, N., Young, I. M., Crawford, J. W., and Ritz, K. (2007). Bacterial interactions at the microscale—linking habitat to function in soil. In “The Spatial Distribution of Microbes in the Environment,” (R. B. Franklin and A. L. Mills, eds.), pp. 61–85. Springer, Dordrecht, The Netherlands. Or, D., Smets, B. F., Wraith, J. M., Dechesne, A., and Friedman, S. P. (2007). Physical constraints affecting bacterial habitats and activity in unsaturated porous media—A review. Adv. Water Resour. 30, 1505–1527. Orphan, V. J., House, C. H., Hinrichs, K.-U., McKeegan, K. D., and DeLong, E. F. (2001). Methane-consuming Archaea revealed by directly coupled isotopic and phylogenetic analysis. Science 293, 484–487. Orphan, V. J., Turk, K. A., Green, A., and House, C. H. (2009). Patterns of 15N assimilation and growth of methanotrophic ANME-2 archaea and sulfate-reducing bacteria within structured syntrophic consortia revealed by FISH-SIMS. Environ. Microbiol. 11, 1777–1791. Peteranderl, R., and Lechene, C. P. (2004). Measure of carbon and nitrogen stable isotope ratios in cultured cells. J. Am. Soc. Mass Spectrom. 15, 478–485. Philippot, L., Hallin, S., Bo¨rjesson, G., and Baggs, E. M. (2009). Biochemical cycling in the rhizosphere having an impact on global change. Plant Soil 321, 61–81. Ploug, H., Musat, N., Adam, B., Moraru, C. L., Lavik, G., Vagner, T., Bergman, B., and Kuypers, M. M. (2010). Carbon and nitrogen fluxes associated with the cyanobacterium Aphanizomenon sp. in the Baltic Sea. ISME J. 4, 1–9. Popa, R., Weber, P. K., Pett-Ridge, J., Finzi, J. A., Fallon, S. J., Hutcheon, I. D., Nealson, K. H., and Capone, D. G. (2007). Carbon and nitrogen fixation and metabolite exchange in and between individual cells of Anabaena oscillarioides. ISME J. 1, 354–360. Pumphrey, G. M., Hanson, B. T., Chandra, S., and Madsen, E. L. (2009). Dynamic secondary ion mass spectrometry imaging of microbial populations utilizing C-13labelled substrates in pure culture and in soil. Environ. Microbiol. 11, 220–229. Recous, S., Aita, C., and Mary, B. (1999). In situ changes in gross N transformations in bare soil after addition of straw. Soil Biol. Biochem. 31, 119–133.

114

David D. Myrold et al.

Rousk, J., and Ba˚a˚th, E. (2007). Fungal and bacterial growth in soil with plant materials of different C/N ratios. FEMS Microbiol. Ecol. 62, 258–267. Schenk zu Schweinsberg-Mickan, M., Joergensen, R. G., and Mu¨ller, T. (2010). Fate of 13 C- and 15N-labelled rhizodeposition of Lolium perenne as a function of the distance to the root surface. Soil Biol. Biochem. 42, 910–918. Schimel, J. P., and Bennett, J. (2004). Nitrogen mineralization: Challenges of a changing paradigm. Ecology 85, 591–602. Sexstone, A. J., Revsbech, N. P., Parkin, T. B., and Tiedje, J. M. (1985). Direct measurement of oxygen profiles and denitrification rates in soil aggregates. Soil Sci. Soc. Am. J. 49, 645–651. Six, J., Elliott, E. T., and Paustian, K. (1999). Aggregate and soil organic matter dynamics under conventional and no-tillage agriculture. Soil Sci. Soc. Am. J. 63, 1350–1358. Stark, J. M., and Hart, S. C. (1996). Diffusion technique for preparing salt solutions, Kjeldahl digests, and persulfate digests for nitrogen-15 analysis. Soil Sci. Soc. Am. J. 60, 1846–1855. Tisdall, J. M., and Oades, J. M. (1982). Organic matter and water-stable aggregates in soils. J. Soil Sci. 33, 141–163. Wang, J. G., and Bakken, L. R. (1997). Competition for nitrogen during mineralization of plant residues in soil: Microbial response to C and N availability. Soil Biol. Biochem. 29, 163–170. Williams, M. A., Myrold, D. D., and Bottomley, P. J. (2007). Carbon flow from 13C-labeled clover and ryegrass residues into a residue-associated microbial community under field conditions. Soil Biol. Biochem. 39, 819–822.