ROOT INTERACTIONS WITH SOIL MICROBIAL COMMUNITIES
AND PROCESSES
Christine V. Hawkes, Kristen DeAngelis, and Mary K. Firestone
I.
INTRODUCTION
A common definition of soil is “the surface layer of earth, supporting plant life.” (Webster’s). In
fact, most of the volume of the upper weathering layer of the earth’s crust has been influenced by
plant roots at one time or another and hence by standard definition, most of soil would be or
would have been at some time considered rhizosphere soil. Here we will focus on soil that is in
active, current communion with living plant roots. However, the fact that a large proportion of
surface soil was directly impacted by plant roots last year, ten years ago, or 100 years ago
provides a potentially valuable context for discussion of soil microbial communities and
processes generally.
Rhizosphere soil effectively forms a boundary layer between roots and the surrounding soil
Because roots and soil act as both sources and sinks for a diverse range of compounds, this
boundary layer of soil mediates large fluxes of solution and gas-phase nutrient (and non-nutrient)
compounds (Belnap et al. 2003). From the microbial perspective then, rhizosphere soil is both a
crossroads and a marketplace. The physical extent of the active rhizosphere zone is not easily
defined, but at any time is expected to extend only a few millimeters from the root surface and to
differ based on the process or characteristic of interest. Empirical measurements have found the
rhizosphere zone to have an outer boundary at 2 mm for protease and aminase activity
(Badalucco et al. 1996), or to occur as a steep gradient across 10 mm (Merbach et al. 1999),.
Bacteria and fungi in soil are infamous for their numbers and their diversity. Plant roots grow
into and through an extraordinary array of “indigenous” soil microorganisms. The composition
and characteristics of the community that develops in concert with the plant root is thus framed
by the background, bulk soil community. In a sense, the indigenous soil microbial community is
a keyboard on which plant root play their characteristic chords as they move into and inhabit soil
(Figure 1). This is an exciting time in rhizosphere microbial ecology. The development of new
methods for studying the intact rhizosphere is opening up yet another black box. In this chapter,
we discuss recent advances in rhizosphere microbial ecology, the role of rhizosphere microbial
communities in nitrogen cycling, and the importance of rhizosphere processes at larger scales.
II. CHARACTERISTICS OF THE ROOT ENVIRONMENT FROM A MICROBIAL
PERSPECTIVE
The physical-chemical environment of rhizosphere soil can differ substantially from that of nearby bulk soils. The differences in rhizosphere and bulk soil encompass environmental
characteristics that are most critical to soil microbial activity and survival: water, oxygen, and
carbon availability.
A. Carbon and Other Exudates
Plant roots exude a large amount and a complex assortment of organic compounds into the
nearby soil (Kennedy 1998). Between 1 and 70% (most often 10 - 30%) of photosynthetically
fixed carbon is released into the rhizosphere (Whipps 1990, Kuzyakov and Domanski 2000). The
quantity and quality of this exudate varies with plant species, age, physiological status, root
morphology, and the presence of the solid soil matrix, soil organisms, and water availability
(Curl and Truelove 1986, Yeates and Darrah 1991, Neumann and Römheld 2001, de Neergard et
al. 2002). The variety of carbon compound also changes with location along the root (Jaeger et
al. 1999). Root cap cells and mucilages (carbohydrates) comprise the bulk of carbon input near
the root tip. Near the zone of root extension, exudates, secretions, and lysates generally reflect
the composition of root-cell contents. In rhizosphere soil near older sections of roots, carbon
inputs commonly reflect their origin from root cell turnover and include both structural
components of roots as well as lysate materials. The quality of the carbon, as a substrate and as a
chemically active input to the soil environment, frames the composition of the community that
results from the root interaction with the extant soil community.
B. Water, Nutrients, and Oxygen
Microbes in the rhizosphere are subject to an environment in which the supply of water, oxygen,
and nutrients is strongly influenced by plant activity. An actively transpiring plant removes huge
quantities of water from the soil solution. Depending in part on the rate of water supply from the
surrounding soil to the rhizosphere, the water potential in rhizosphere soil can be much lower
and more variable than in the surrounding soil (Papendick and Campbell 1975). During the
daytime, rhizosphere soil is commonly measurably drier than the surrounding bulk soil.
In some terrestrial ecosystems, rhizosphere soil can exhibit a higher water content than that of
the surrounding soil at night as a result of “hydraulic redistribution” (Caldwell and Richards
1989). Water from deeper in the soil profile is accessed by deep roots, transported to roots in
surface soil, and can ultimately move out into dry surface soil at night when the
evapotranspiration demand by the plant is reduced.
Both of these preceding phenomenon can result in large diurnal water potential fluctuations in
the soil adjacent to roots. The daily water potential fluctuations characteristic of rhizosphere soil
must be a critical environmental characteristic selecting rhizosphere microbial communities and
impacting the rates of nitrogen-cycling occurring in this zone.
Transpiration-driven movement of water also carries nutrient and non-nutrient salts dissolved in
the water from bulk soil through the rhizosphere soil. This flux of soluble salts into the
rhizosphere can result in salt concentrations many times that of bulk soil. Conversely, nutrient
ion uptake by roots drives diffusional movement and creates zones of nutrient depletion (e.g.,
NH4, NO3, and PO4) in rhizosphere soil.
Rates of O2 consumption are elevated in the rhizosphere zone due both to root and microbial
respiration (Sorensen 1997). Increased rates of respiration can create zones of lowered O2
concentrations and even anaerobic conditions depending on the diffusional resupply of O2 into
the rhizosphere from surrounding soil pores. Because diffusion of O2 is highly dependent on soil
water content, reduced water content in soil pores in the rhizosphere due to plant
evapotranspiration can result in enhancement of O2 diffusion. Thus, depending on the water
content of soil, the availability of O2 in the rhizosphere soil atmosphere can be either greater or
less than that of the surrounding soil.
Plant roots are well known to change the pH of the rhizosphere by extruding protons via H+ATPase in epidermal cells (Hinsinger et al. 2003). This can occur in response to iron starvation
(Schmidt, 2003), since a change in pH affected by the plant can also cause the release of
inorganic metals. Low molecular weight organic acids secreted by the plant can also act to lower
the pH of the surrounding soil.
The rhizosphere is thus a spatially and temporally patchy environment with rapid (commonly
diurnal) fluctuations between potentially extreme conditions, including cycles of water stress and
anaerobiosis, that microbes must respond to in order to survive and thrive.
III. THE COMPOSITON OF RHIZOSPHERE MICROBIAL COMMUNITIES
A. Microbial Populations and Communities in the Rhizosphere
Studying organisms in the rhizosphere, and more generally in soil, is not a straightforward task.
A complex community of bacteria may exist at the scale of a soil aggregate, a biofilm, or a
section of root surface where boundaries can be difficult to delineate (Belnap et al. 2003).
Physically removing microbes from soil is also non-trivial, particularly from intact rhizosphere
soil. The recent development and popularity of molecular techniques to identify soil organisms
has allowed us to move beyond the small subset of culturable soil organisms and begin defining
populations and communities of microbes belowground. Using these methods, we have begun to
understand how population and community ecology concepts apply to rhizosphere microbes.
Most population studies have focused on organisms that can be manipulated in agricultural
settings either for biocontrol or for increased plant growth, including species of symbiotic
nitrogen fixers (Carelli et al. 2000), plant growth promoting rhizobacteria (Bevivino et al. 1998),
deleterious rhizosphere bacteria (Nehl et al. 1996), pathogens (Khan and Khan 2002), and
bacteriophage (Ashelford 2000, 2003). Population-level studies are also common for rhizosphere
bacteria useful for bioremediation (Dutta et al. 2003). For example, Dalmastri et al. (2003)
recently reported high genotypic and phenotypic diversity of a Burkholderia cepacia complex
population in maize rhizosphere, potentially important in explaining the diverse ecological roles
of these bacteria in biocontrol, bioremediation, and human illness.
Because the effects of microbes in the rhizosphere are often synergistic, understanding them at
the community level is perhaps most ecologically meaningful. Microbial community
characterization is often limited to a subset of the rhizosphere community, such as plant growth
promoting bacteria (Dalmastri et al. 1999), pseudomonads (Misko and Germida 2002), nitrifiers
(Priha et al. 1999), or mycorrhizal fungi (Daniell et al 2001). Alternatively, entire communities
can be described. Microbial community characterizations have taken place most often in
economically important agricultural species, particularly corn (Chiarini et al. 1998, Dalmastri et
al. 1999, Chelius and Triplett 2001, Daniell et al. 2001, Baudoin et al. 2002, Buyer et al. 2002,
Kandeler et al. 2002), but also species such as alfalfa (Miethling et al. 2000, Wieland et al.
2001), avocado (Yang et al. 2001), barley (Normander and Prosser 2000, Yang and Crowley
2000, Daniell et al. 2001), beet (Schmalenberger and Tebbe 2003a), canola (Kaiser et al. 2001,
Smalla et al. 2001, Misko and Germida 2002), lettuce (Maloney et al. 1997), pea (Daniell et al.
2001), potato (Smalla et al. 2001, Krechel et al. 2002), rye (Miethling et al. 2000), soybean
(Buyer et al. 2002),.tomato (Maloney et al. 1997), and wheat (Daniell et al. 2001, Germida and
Siciliano 2001). In a small number of cases the focus is on plants in natural communities (Clapp
et al. 1995, Westover et al. 1997, Priha et al. 1999, Kuske et al. 2002).
In past studies researchers using culture-based methods have generally reported dominance of
Gram-negative bacteria and up to 70% similarity in rhizosphere microbial communities across
plant species (Sturz et al. 1998). Results from molecular-based characterizations are however
more variable (Table 1). Rhizosphere microbial communities were dominated by Proteobacteria
in 16 of 19 studies with 14 different species in 13 genera (Table 1). Within the Proteobacteria,
patterns were variable but most often members of the γ-Proteobacteria were dominant. Grampositive bacteria and the Cytophaga-Flavobacterium-Bacteroides group followed the
Proteobacteria in abundance.
In an analysis of published bacterial and archaeal isolates from rhizospheres of these 14 plant
species, we discovered that the distribution of prokaryotic isolates from rhizosphere soil in fact
spans the entire tree of life (Table 2; Figure 2). This analysis was based on the published results
of isolates found in rhizosphere soils from 14 (there are 18 records, but only 14 different plant
species – several are duplicates or varieties) plant species, consisting of 9 herbaceous dicots, 2
woody dicots and 3 monocots. Based on prior results from culture-experiments, we expected to
find the Proteobacteria and Actinobacteria well-represented, which was indeed the case. Most of
the -Proteobacteria were unclassified at the level of order, which suggests that there is
potentially more sequence and functional diversity in the rhizosphere than was revealed in this
analysis. Nitrospira were virtually unreported in these studies, perhaps as a result of sampling
bias or other methodological constraints. A few unexpected bacteria were found including
thermophiles and deinococcus; it is not clear whether these were indigenous soil bacteria or
whether these sequences were miscategorized or erroneously sequenced.
Across plant species, there was a great deal of overlap in rhizosphere community composition.
Differences were only observed when comparing the herbs to the two trees in the analysis,
Persea americana (avocado) and Pinus contorta (lodgepole pine). The trees had fewer
organisms from the Cytophaga-Flavobacterium-Bacteroides group, actinobacteria, and bacilli
and more acidobacteria and rhodospirillales. The tree rhizospheres also had several unique
aspects, containing the two representatives from termite groups and seven archaea; archaea were
not found in the rhizosphere of any other plant species.
While this is far from a complete picture of the diversity of the rhizosphere, it is the first
demonstration that the rhizosphere is potentially capable of hosting an array of microbes far
more diverse than what has been reported with other methods. It also suggests that, at coarse
taxonomic scales, there is some degree of specificity in the selection of rhizosphere microbial
communities. As more DNA-based characterizations of rhizosphere microbial communities
become available, we can continue to increase our understanding of rhizosphere microbial
communities and their controllers
Community characterization is not always genotypic in nature, but may occur at different scales
ranging from functional diversity to broader taxons to simple abundance. Functional diversity is
a common measure of microbial community composition and may be more biologically relevant
than taxonomic diversity (Øvreås 2000). Indicators of functional diversity are those that measure
the type, abundance, activity, and rate of microbial substrate use. The most common method is
the sole-carbon-source utilization profile (Campbell et al. 1997, Preston-Mafham et al. 2002).
Functional diversity can also be estimated by measuring functional genes that play a role in
ecosystem processes (Prosser 2002). This is commonly used for those processes in which a
limited number of genes are involved, such as nitrification and denitrification.
More broadly-based groups, such as Gram-positive bacteria, Gram-negative bacteria,
actinomycetes, methanotrophs, and fungi, can be identified with methods such as phospholipid
fatty acid analysis, or PLFA. This technique measures the phospholipid fatty acid composition of
membranes and the lipid composition of cell walls to give estimates of relative abundance
(Zelles 1999). PLFA can be a sensitive measure of change in microbial communities at very
broad taxonomic scales, but is not generally useful for identifying finer taxonomic or functional
changes.
B. Factors Affecting Rhizosphere Microbial Populations and Communities
Plant Species and Root Exudates
Plant species can be an important factor affecting the structure of rhizosphere bacterial and
fungal communities (e.g., Westover et al. 1997, Miethling et al. 2000, Stephan et al. 2000), with
both positive and negative effects on different microbial groups. Within plant species, microbial
communities differ based on plant genotype (Smith et al. 1999) or specific conditions such as
plant nutrient status (Yang and Crowley 2000), pathogen infection (Yang et al. 2001) and
mycorrhizal infection (Andrade et al. 1997, 1998b; Söderberg et al. 2002). Mycorrhizal
infection, for example, can augment specific bacterial species (Mansfeld-Giese 2002) or change
bacterial community composition (Marschner et al. 2001a) in the rhizosphere. There is, however,
no clear, consistent response by the microbial communities to mycorrhizal infection.
Within root systems, microbial communities can differ among root zones (Jaeger et al. 1999,
Semenov et al. 1999, Yang and Crowley 2000, Thirup et al. 2003) and at different distances from
the root surface as rhizosphere soil grades into bulk soil (Marilley and Aragno 1999). The largest
numbers of bacteria in the rhizosphere have been reported to occur in the zone of root elongation
(Jaeger et al. 1999).
A variety of biotic factors (mycorrhizal and pathogen interactions) and abiotic factors (water
stress) can impact the composition of the microbial community in the rhizosphere The
mechanism by which each of these factors can influence patterns of microbial communities in
the rhizosphere is thought to be the same: they cause variation in the quantity or quality of root
exudation. Thus a critical determinant of rhizosphere microbial communities is thought to be
variation in root exudates (Badalucco and Kuikman 2001, Brimecombe et al. 2001). Exudates
can attract beneficial (Bansal and Mukerji 1994) and pathogenic organisms (Nehl et al. 1996),
and ultimately affect the diversity of bacteria in the rhizosphere (Badalucco and Kuikman 2001).
Plant species have measurable differences in the composition (Merbach et al. 1999, Hütsch et al.
2002) and magnitude (Biondini et al. 1988, Merbach et al. 1999, Kuzyakov and Domanski 2000)
of root exudation, which can be affected by plant genotype (REF), developmental stage (Curl
and Truelove 1986) and nutrient status (Van der Krift et al. 2001). Even within root systems
exudation is not constant, but changes both spatially and temporally as roots grow through soil
(Jaeger et al. 1999, Semenov et al. 1999).
When roots are infected with mycorrhizae, the established paradigm assumes rhizosphere
microbes are affected by changes in carbon exudation brought about because the fungus is a
large sink for plant carbon and may therefore impact both the quantity and quality of carbon
leaving the root (Hodge 2000). The same should be true for any pathogenic fungus that changes
root carbon flow. The limited evidence that exists is equivocal however. Arbuscular mycorrhizal
fungi have been shown to increase, decrease, and have no effect on carbon exudation by plant
roots, with changing patterns for different combinations of plant and fungal species (Snellgrove
et al. 1982, Schwab et al. 1984, Bansal and Mukerji 1994, Marschner et al. 1997). Effects are
likely to be species- and host-specific in nature.
Specificity of Root-Microbial Interaction
Root-microbial interactions encompass a range of specificity from “highly-evolved” symbioses
(legume-rhizobium) to less-specific associations (AM mycorrhizae). The degree of specificity
and co-evolution of rhizosphere heterotrophs is however quite unclear. As discussed above, host
plant genotype can effect the composition of the rhizosphere microbial community and this
community has the potential to affect plant growth and survival (Nehl et al. 1996). Thus the
potential for coevolution exists. Furthermore, colonization of the rhizosphere environment may
involve a complex array of microbial behaviors that require the development of some host
specificity. A model biological control organism, Pseudomonas fluorescens, was put through the
promoter-trapping technique IVET (in vivo expression technology) to determine what genes it
needs in order to colonize the sugar beet rhizosphere. Twenty genes were identified as having a
significant increase in transcription, one quarter of which were involved in nutrient acquisition
(organic acid metabolism and xylanase), three related to oxidative stress, one copper-inducible
regulator and one component of the type-III secretion system (Rainey 1999).
Apparent symbioses are the most likely to develop host-specificity. Specificity in legumerhizobia relationships, for example, is determined by plasmids which contain the genes
responsible for both nodulation and nitrogen-fixation, and can be exchanged among strains
(Hedges and Messens 1990). Some legume-rhizobia associations are clearly defined, with a
single rhizobium species limited to a single plant genus or small group of genera (Hedges and
Messens 1990, González-Andrés and Ortiz 1999), though individual plants may host several
genetic strains of the same microbial species (Carelli et al. 2000) and some rhizobium species are
promiscuous (Squartini 2001). Thrall et al. (2000) posit that rare rhizobia species may be more
host-specific than widespread ones.
Mycorrhizae exhibit some specificity to plant hosts, with orchidaceous and ericoid mycorrhizae
the most specialized, followed by ectomycorrhiza (REF). Arbuscular mycorrhizae, originally
thought to be extremely promiscuous with regard to plant host (REF), have been found to exhibit
ecological rather than absolute specificity, where some combinations of host plant and fungus are
more beneficial than others (McGonigle and Fitter 1990, Sanders and Fitter 1992, Bever et al.
1996, Eom et al. 2000). Host-specific feedbacks have also been demonstrated (see below).
Non-symbiotic associations may also be specific to plant species. Antagonists of the soilborne
pathogen, Verticillum dahliae, varied significantly among four host plants (Berg 2002). Using
hybrid tomato plants, Smith et al. (1999) demonstrated that genotype accounted for 38% of the
variability in the plant growth promoting rhizosphere bacteria, Bacillus cereus, mediating
resistance to the pathogen, Pythium torulosum.
Soil Environment
The composition of the rhizosphere microbial community is of course, strongly affected by the
soil environment (Groffman et al. 1996, Grayston et al. 1998, Miethling et al. 2000, Marschner et
al. 2001b). Conditions in soil may influence microbes directly through changes to water, oxygen,
nutrient availability, pore size, and aggregate stability or indirectly through effects on root
exudation (Brimecombe et al. 2001). The soil environment and the plant must act in concert to
frame the composition and activity of the rhizosphere community. While the indigenous soil
community provides the species “keyboard” for the plant, it is not clear how the components of
the rhizosphere community of a given plant will differ from that of the same plant in a different
soil in terms of microbial functional or physiological characteristics.
Biotic Interactions
When a root passes through soil and activates the indigenous microbial community there,
competition among microbes for resources or space will partially determine the resulting
rhizosphere community (Curl and Truelove 1986, Brimecombe et al. 2001). During this process,
bacteria may interact with each other through the release and detection of chemicals. In one class
of chemical interactions, bacteria perceive a threshold concentration of chemical signal, i.e.,
sense a quorum, inducing a change in gene expression and thus behavior (Whiteley 1999). The
nature of the chemical signal is specific to the organism, with more closely related microbial
species generally sharing more similar signals (Schauder and Bassler 2001, Loh 2002). For Gram
negative bacteria these are commonly acyl homoserine lactones, for Gram positive bacteria,
modified polypeptides have been found. Most known soil bacteria have at least one receptor that
senses signal and a synthase that makes signal; some rhizosphere bacteria are known to make a
number of signal compounds (Cha et al. 1998). Because of the commonality of synthase and
receptor genes in bacteria, quorum sensing via small diffusible molecules and cross-talk between
species is thought to be common (REF).
Chemical signaling allows individual bacterial cells to act in coordination with an entire bacterial
population or community in response to the presence of new resources or environments such as
the rhizosphere provides. Coordination can result in either cooperative (Crespi 2001) or
competitive ecologically relevant behaviors in the rhizosphere that would have a lower chance of
success if undertaken alone. For example, chitinase production in the Gram-negative bacterium
Chromobacterium violaceum is turned on by the presence of chitin and high signal
concentration, which together indicate a high probability of return on the extracellular enzyme
investment (Chernin 1998). Other examples of biotic interactions that involve chemical signals
and-induced behaviors are pathogenesis, antibiotic production, biofilm formation, symbiosis
initiation, and motility (Miller and Bassler 2001).
Direct interactions between the root and the bacterial community may also occur, particularly
when quorum sensing behavior is triggered by the root or other bacteria. Plants have the ability
to affect density-dependent behaviors of rhizosphere bacteria by secreting quorum sensing mimic
compounds. Exudates from pea (Pisum sativum), for example, contained several compounds that
repressed violacein synthesis, extracellular protease activity, and chitinase activity in
Chromobacterium violaceum and induced swarming in another Gram-negative bacterium,
Serratia liquefaciens (Teplitski 2000). In response to exposure of roots to specific signaling
compounds, plants may either produce compounds that mimic the chemical structure of signal
molecules (Mathesius 2003) or excrete interference compounds (Mae et al. 2001), thereby
changing the concentration of quorum sensing molecules in the rhizosphere that bacteria
experience. Moreover, the accumulation of signal-specific proteins in roots indicates that plants
can detect and respond to individual signaling molecules and, therefore, to different bacterial
populations (Mathesius 2003).
Of course, bacteria are not simply the victims of plant interference. The microbial community
has an elaborate and varied repertoire of signaling interference mechanisms as well. Plants
introduce numerous phytohormones into the rhizosphere to regulate root growth, tropisms, and
new root production. These hormones are most commonly flavinoids such as auxins. Bacteria
can sense and respond to these chemicals and the results for the plant may be either positive, as
in the case of plant growth promoting bacteria, or negative, as with pathogenic bacteria (Barazani
and Friedman 2001). Bacteria also commonly release hormones or active hormone analogues
that can affect plant growth and behavior (REF).
Roots and their associated bacterial communities also attract predators, including protozoa,
nematodes, enchytraeids, mites, and collembolans, that can directly impact the abundance and
composition of bacteria (Garbaye 1991). These complex and interesting rhizosphere food webs
are discussed in Chapters 5 and 12 of this book. Clearly, the composition of the rhizosphere
microbial community reflects selective grazing by mesofauna (Venette and Ferris 1998,
Bonkowski et al. 2000) in the short term and more complex biotic interactions over evolutionary
time (Klironomos and Ursic 1998, Gange 2000).
Mycorrhizal infection of roots may affect the rhizosphere bacteria community, though the
direction of the effect is variable. Some groups have reported no change in microbial activity,
number, or composition at coarse taxonomic scales (Olsson et al. 1996, Andrade et al. 1997,
Soderberg 2002), whereas others have shown that mycorrhizal infection can change the fine-
scale taxonomic composition of the rhizosphere bacterial community in a manner that is
dependent upon the plant-fungus species pair (Andrade et al. 1997, Marschner 2001, MansfeldGiese 2002). Some bacteria appear to require the presence of mycorrhizal hyphae (Andrade et al.
1998a). This is not a one-sided interaction – bacteria and pathogens in the rhizosphere can also
affect mycorrhizal colonization of roots (Garbaye and Bowen 1987, Germida and Wiley 1996,
Barea et al. 2002). Interactions between mycorrhizal fungi and bacteria have the potential to be
extensive, as bacterial endosymbionts of the genus Burkholderia, a commonly found Gramnegative soil bacterium, have been found closely associated with hyphae of the Gigasporaceae
(Bianciotto, 2000).
IV. MICROBIAL FUNCTION IN THE RHIZOSPHERE – NITROGEN CYCLING
Microbial nitrogen (N) processing in rhizosphere soil is of central importance in the availability
of N to plants because it is the soil microsite (or mesosite): 1) from which N is actually taken up
by plant roots; 2) in which root processes immediately impact and interact with microbes
actively transforming N; and 3) in which head to head competition for nitrogen might occur.
Rhizosphere microbial communities are known to differ from those in bulk soil in terms of
metabolic profiles, activity, and species composition (e.g., Sorenson 1997, Yang and Crowley
2000) suggesting that rhizosphere N-cycling may be substantially different that that in bulk soil.
A. Nitrogen Mineralization
The conversion of organic N to NH4+ generally occurs under three conditions in soil: when (i)
microbes are utilizing substrates with low available C/N ratios; substantially more than half of
the available organic C must be used for energy generation and the resulting excess N is released
as NH4+ (ii) fluctuations in water and temperature cause cell death and lysis; the subsequent
utilization of the low C/N necromass results in N mineralization; and (iii) microbes are
consumed by predators and mesofaunal release of excess NH4+ results.
The increased numbers of microorganisms in rhizosphere soil can represent a potentially labile
stock of organic N near plant roots. There are several ways that N contained in microbial
biomass can become available to plants. If the supply of labile C is high near young roots and
declines substantially in older root sections, then C-limited heterotrophs would mineralize NH4+
during catabolism of N-rich cell components. Such a spatial pattern of C-availability along roots
(high C availability near root tips and low C availability near mature roots) could in itself result
in N mineralization. Alternatively, root-carbon enhancement of microbial numbers and activity
may attract bacterivores, which upon consumption of low C/N microbial biomass, release N as
NH4 into the rhizosphere. Protozoa and other soil fauna excrete an estimated 30% of consumed
bacterial N into the rhizosphere (Griffiths et al. 1992), where it is available for plant uptake
(Elliott et al. 1984, Clarholm 1985a, b; Ferris et al. 1998, Kuikman et al. 1991). Alternatively,
rhizosphere bacteria could be infected by bacteriophage (Ashelford 2000, 2003); this would also
result in cell lysis and biomass N mineralization. Finally, rhizosphere soil is a zone of water
potential fluctuation as a result of evapotranspiration during the day followed by re-equilibration
with surrounding soil water during the night. Such relatively rapid fluctuations in soil water
potential could also result in N mineralization from the rhizosphere microbial biomass as N-rich
cellular materials are released during cell water potential equilibration (Kieft et al. 1987;
Halverson, et al. 2000)
The potential for N-mineralization in rhizosphere soil thus appears to be high. We have recently
measured average gross rates of N-mineralization in rhizosphere soil that were significantly
higher than in bulk soil (Herman and Firestone, unpublished). Average rates of N-mineralization
in soil adjacent to Avena barbata roots was 9.2 mg N kg-1d-1 compared to 1.0 mg N kg-1d-1 for
bulk soil. Plants may be able to affect rates of N-mineralization by a variety of mechanisms. A
number of these are discussed in the preceding paragraph. Another intriguing possibility is that
microbe-microbe and root-microbe communication can affect N cycling in the rhizosphere. .
It has traditionally been thought that plants get virtually all of their N from inorganic sources and
compete poorly with soil microbes for NH4+ and NO3-. This standard view of the N-cycle is
however undergoing major evolution. Schimel and Bennett (2004) have recently suggested that
depolymerization of N-containing macromolecular polymers by soil microbes drives N-cycling
in soil. Because the bulk of soil N is organic, primarily chitin, proteins, lignoprotiens, and
nucleotides, microbial production of extracellular enzymes that release N in more accessible
monomeric forms may at times be mediating the rate limiting steps in production of rootavailable N. Interactions between roots and soil heterotophs that result in increased activity of
enzymes involved in depolymerization of macromolecular organic is thus highly relevant to root
N-availability. Recent work in our lab (DeAngelis unpublished) has shown elevated activities of
N-Acetyl Glucosaminidase (chitinase) and protease in rhizosphere soil adjacent Avena barbarta
roots. The activities of these two key enzymes differed in soils adjacent to different root zones.
The production of some of these enzymes by Gram-negative bacteria, has been found to be under
the control of signaling molecules, acylated homoserine lactones (Worm 2000, Schauder and
Bassler 2001). This then raises the interesting possibility that chemical interactions among
bacteria and roots are playing a significant role in controlling plant N availability in rhizosphere
soil.
B. Nitrification
Autotrophic nitrification in soil is thought to be primarily limited by the availability of substrate
(NH3 /NH4+). The presence of plant roots can also depress rates of nitrification. Historically, this
has been thought to occur by three mechanisms. First, roots remove NH4+ from the soil solution.
If rates of root uptake exceed rates of resupply of NH4+ through diffusion and mass flow , zones
of NH4+ depletion occur in rhizosphere soil, thus limiting nitrification. Second, roots supply
carbon to the rhizosphere; any factor which increases carbon availability potentially enhances net
NH4+ immobilization into microbial bodies thus again reducing NH4+ availability to nitrifying
bacteria. Finally, based on the assumption that plants benefit from reduced nitrification, it has
long been hypothesized that plants (including roots) chemically inhibit nitrifiers. However,
unequivocal data demonstrating lower gross rates of nitrification in rhizosphere soil have been
lacking. We measured gross rates of nitrification in rhizosphere soil from Avena barbata, a
common annual grass in California (Firestone, unpublished data). Actual gross rates of
nitrification were zero in areas of active NH4+ uptake by the root (8-16cm from root tip).
However in rhizosphere soil from which little NH4+ uptake was occurring (0-8 cm from the tip),
rates of nitrification were indistinguishable from those of bulk soil (11 vs 12 ug N g-day -1).
Thus root competition for NH4+ can shut down nitrification in zones of active root uptake. In the
same rhizosphere soils, populations of nitrifiers paralleled rates of nitrification. with nitrification
potentials slightly higher in soil adjacent to the 0-8 cm zone compared to those in bulk soil, but
lower in soil from the 8-16 cm root zone.
C. Denitrification
Denitrification occurs when nitrate is used as an alternative terminal electron acceptor under
conditions of oxygen limitation. When root respiration depletes local concentrations of O2,
nitrate reduction in the rhizosphere increases. When root water uptake increases diffusional
resupply of O2 to the rhizosphere compartment, denitrification can be reduced. When root
uptake of NO3 reduces NO3 availability, denitrification can decrease (Firestone, 19xx). Thus
there is no simple, uniform response of denitrification to the presence of roots.
Denitrification may have another important role in rhizosphere processes due to the gaseous
intermediates formed during NO3 reduction to N2. These intermediates, especially NO, are
biologically active and may play a role in seed germination, root growth, and immune response
to plant pathogens (Stohr and Ulrich 2002). While NO is known to affect these aspects of plant
biology, the extent to which microbially generated NO plays a role in these processes is unclear.
D. Decomposition
Nitrogen mineralization occurs during decomposition processes in soil and rates of
decomposition have been shown to be increased and decreased by the presence of living roots.
Dormaar, in his 1990 review, analyzed the seemingly contradictory literature on the topic, and
found that plant effects on water and N availability explained many of the observed differences
in outcome. Dormaar (1990) concluded, however, that “the diversity of the microflora present at
all stages of interaction” comprise a critical unknown in the process. The primary decomposers
in soils are bacteria and fungi. Both have the ability to release extracellular enzymes that are
essential to the breakdown of complex soil organic matter into monomeric forms that can be
assimilated and immobilized. Enzymes important for decomposition include ligninases,
cellulases, phenol oxidases, proteases, pectinases and chitinases (Badalucco and Kuikman 2001).
V. IMPORTANCE OF RHIZOSPHERE MICROBIAL COMMUNITIES AT LARGER SCALES
A. Plant Populations
Microbial communities in the rhizosphere can directly impact plant productivity and
demographic parameters. Root pathogens are the obvious case, acting as a sink for plant carbon,
damaging root tissue, reducing root uptake, and directly reducing plant growth, reproduction, and
survival (Newsham et al. 1994, Weste and Ashton 1994, Packer and Clay 2003).
Microorganisms in the rhizosphere that are more mutualistic can also affect individual plant
performance. Arbuscular mycorrhizal (AM) fungi, for example, altered growth and flowering of
grasses and forbs in tallgrass prairie, with the direction of the effect dependent on the species
(Hartnett et al. 1994, Wilson and Hartnett 1997, Wilson et al. 2001). Free-living microbial
communities in the rhizosphere are more likely to have indirect effects on plants. Microbes are
well known competitors for scarce nutrients in the rhizosphere (Kaye and Hart 1997), but may
also increase availability of resources such as nitrogen to the plant (see above). By changing
resource availability to plants, microbes can alter plant fitness and ultimately population
dynamics.
B. Plant Communities
Microbes living in the rhizosphere can also affect aboveground plant community composition
and, potentially, successional trajectories (Reynolds et al. 2003). Simple feedbacks between soil
microbial communities and plant communities can alter plant community composition. Plants
that experience a net negative effect of soil rhizosphere microbes will ultimately be replaced,
whereas those that experience a net positive effect will continue to occupy the patch (Bever et al.
1997). Negative feedback can thereby maintain changing diversity through time whereas positive
feedback should support a static plant community composition. This model, which assumes that
plants develop a unique suite of rhizosphere microbes, fits particularly well for AM fungi, and
both positive and negative feedbacks of AM fungal communities on plants have since been
demonstrated (e.g., Bever 2002, Klironomos 2002). Soil pathogens can also drive shifts in the
dominance of grassland patches through negative feedback effects (Olff et al. 2000).
Furthermore, small-scale distance- and density-dependent mortality of conspecifics caused by
soil pathogens can be observed as predicted by Janzen (1970) and Connell (1971). This is the
case with black cherry (Prunus serotina) seedlings, which are subject to increasing mortality
from oomycete Pythium spp. closer to parent trees (Packer and Clay 2003). In these ways,
rhizosphere microbes can drive patch dynamics in plant communities.
Landscape level changes to plant community composition can also be caused by root-associated
microbes. Dramatic examples of this can be found with the invasion of root rot pathogens in the
genus Phytophthora into new habitats. Phytophthora cinnamoni invasion of Australian open
forests caused the death of >40% of the dominant eucalypts (Eucalyptus spp.) and the complete
destruction of the dominant sclerophyllous understory shrubs (Xanthorrhoea australis; Weste
1987). Thirty years after pathogen invasion, the aboveground community composition has not
recovered (Weste and Ashton 1994). In the northwestern United States, a congener, P. lateralis,
caused 46% mortality of Port Orford cedar (Chamaecyparis lawsoniana) populations and 10%
mortality in nearby Pacific yew shrubs (Taxus brevifolia) across Oregon and California (Murray
and Hansen 1997). Clearly, pathogens in the rhizosphere can have extremely widespread effects
on the composition of plant communities and their presence may in part define the distributional
limits of some species.
The distribution of species across the landscape can also be defined by the presence or absence
of required symbionts. For example, the ranges of two woody legumes (Genista spp.) in Spain
are effectively limited by the distributions of specific rhizobia, as they cannot establish in new
sites in their absence, but the bacteria are only found in soils where the shrubs already naturally
occur (Gonzalez-Andres and Ortiz 1999). In agroforestry, pine plantations had little success until
they were grown with the simultaneous introduction of associated ectomycorrhizal fungi (REF).
C. Ecosystems
Root-associated soil microbial communities are in many cases the ultimate drivers of ecosystem
processes and can alter process rates both directly and indirectly. These include numerous
ecosystem functions including nutrient and carbon cycling and storage (Brussard et al. 1997). By
changing plant productivity and plant community composition, for example, soil microbes can
indirectly affect litter inputs and decomposition rates. Rhizosphere microbes may be important
not only as initial decomposers of root debris, but also as a critical way-station for root C as it
becomes soil humus. The biochemistry of the soil microbial bodies responsible for decomposing
root debris may frame the process of humification as these bodies serve as nascent humic
substances.
Though we know that many ecosystem processes are under microbial control, simple models of
these processes, including nitrogen mineralization, work well without explicitly including soil
microbes. Nevertheless, microbial response data are crucial to the success of these models –
starting conditions, response functions, and parameter values are all developed from biological
data (Andrén et al. 1999). There are some conditions where inclusion of microbial mechanisms
behind ecosystem processes may be critical, particularly under scenarios where a change in the
microbial community could feedback to directly change ecosystem process rates.
Narrow ecosystem processes, i.e., those under the control of a limited group of microorganisms,
may be closely tied to the composition and functioning of rhizosphere microbial communities
(Schimel et al. 2004). Lignin decomposition, which requires fungi with lignolytic activity
(basidiomycete white rot fungi and a few ascomycete fungi) is dependent on microbial
community composition. Nitrification and denitrification rates have been shown to differ in
proportion to the abundance and composition of nitrifying and denitrifying communities in soil
(Schimel et al 2004).
Global changes in climate and plant communities may further alter microbial communities with
consequences for ecosystem process rates. Invasion of novel habitats by exotic plant species can
alter mycorrhizal communities as well as processes mediated by mycorrhizal fungi and other
rhizosphere microbes, including soil aggregation (Andrade et al. 1998b, Vogelsang and Bever
REF) and nitrification (Hawkes et al. unpublished). As atmospheric CO2 increases, microbial
communities may shift with consequences for microbial carbon storage and turnover (Treseder
and Allen 2000, Cornelissen et al. 2001).
VI. CLOSING OBSERVATIONS
Research over the past decade has underscored the fact that understanding and quantifying the
interactions among plants and soil microbes is essential to understanding both plant and soil
microbial community ecology and the roles that these communities play in ecosystem function.
Tremendous progress has recently been made in the area of plant-soil microbial interactions and
there now exist powerful new tools that show promise for rapid and continued expansion of our
understanding. That said, major challenges remain both in scientific questions and scientific
sociology. How and to what degree do plants impact bulk soil communities and rhizosphere
communities? How and to what degree do soil microbial communities impact plant
physiological, population, and community ecology? Exactly how do plant-microbial feedback
loops work? And how long do they take to become fully functional? How does the chemicalphysical environment of soil impact these biotic interactions? What are the roles of signaling
and cell-cell communication in mediating root-microbial interactions? Researchers equipped to
address these complex questions need expertise in a breath of areas ranging from pedology to
biometeorology to plant physiology to microbial genetics. Thus we expect that the most
substantial advances in this area will be made by research collaborations that encompass a range
of disciplinary expertise.
ACKNOWLEDGEMENTS
We thank XXX for providing comments on the manuscript. The work was supported by a CA
AES Project 6117-H. C. Hawkes was supported by an NSF Microbial Biology Fellowship and
K. DeAngelis by an EPA-STAR graduate fellowship.
Table 1. Characterizations of rhizosphere microbes based on 16S rDNA or 16S rRNA.
% of
Reference
Plant Species
Rhizosphere
clones or
Dominant Species
bands
Beta vulgaris
Brassica napus
cv. Licosmos
Brassica napus
cv. Westar
Dendranthema
grandiflora cv. Majoor
Bosshardt
Fragaria ananassa
Hordeum vulgare
cv. Pastoral
Lolium perenne cv.
Bastion
Medicago sativa – soil 1
Medicago sativa – soil 2
Medicago sativa
cv. Regen-SY
Persea americana
Phaseolus vulgaris
Pinus contorta
Solanum tuberosum
Proteobacteria
CFB group
Actinomycetes
Proteobacteria (α & γ)
Gram-positive bacteria (Bacillus
megaterium)
α-Proteobacteria (Bradyrhizobium)
CFB group
β-Proteobacteria
γ-Proteobacteria (Nevskia)
Gram-positive bacteria (Bacillus)
β-Proteobacteria (Comamonas,
Ralstonia, Variovarox)
γ-Proteobacteria (Pseudomonas)
α-Proteobacteria (Acetobacter,
Azosporillum)
High G+C Actinomycetes
α-Proteobacteria
γ-Proteobacteria (Acinetobacter,
Pantoea agglomerans,
Pseudomonas)
β-Proteobacteria (Burkholderia)
Gram-positive bacteria (Bacillus)
γ-Proteobacteria (Pseudomonas)
Gram-positive bacteria
Holophaga-Acidobacterium
α-Proteobacteria
α-Proteobacteria
γ- Proteobacteria
Bacteroidetes
50
32
30
20
10
Schmalenberger
& Tebbe 2003a
Smalla et al. 2001
52
30
9
6
23
17
Kaiser et al. 2001
Bacteroidetes
γ- Proteobacteria
Proteobacteria
CFB group
Gram-positive bacateria
Proteobacteria (Pseudomonas,
Polyangium)
γ-Proteobacteria
Bacteroidetes
α-Proteobacteria
β-Proteobacteria
Acidobacterium
γ- Proteobacteria
Proteobacteria (α & γ)
Gram-positive bacteria (Bacillus
50
38
35
30
11
30
Duineveld et al.
2001
17
10
50
10
30
13
13
53 (15)
15
15
9
44
22
22
60
40
24
19
19
9
22
11
Smalla et al. 2001
Normander &
Prosser 2000
Marilley &
Aragno 1999
Miethling et al.
2003
Tesfaye et al.
2003
Yang et al. 2001
Miethling et al.
2003
Chow et al. 2002
Smalla et al. 2001
Trifolium pratense
Trifolium repens
cv. Milkanova
Zea mays
Zea mays
transgenic KX8445
Zea mays
cv. Bosphore and
transgenic KX8445
megaterium)
γ-Proteobacteria
β-Proteobacteria
γ-Proteobacteria (Pseudomonas)
β-Proteobacteria
Gram-positive bacteria
α-Proteobacteria (Rhizobia)
β-Proteobacteria (Burkholderia)
γ-Proteobacteria
CFB group
CFB group
α-Proteobacteria
β-Proteobacteria
γ-, β/γ-Proteobacteria
β-Proteobacteria
γ-Proteobacteria
CFB group
β/γ- & δ-Proteobacteria
α-Proteobacteria
63
18
52 (18)
12
12
36
27
14
7
24
21
17
14
23
19
21
14
9
Miethling et al.
2003
Marilley &
Aragno 1999
Chelius &
Triplett 2001
Schmalenberger
& Tebbe 2002
Schmalenberger
& Tebbe 2003b
Table 2. Diversity of bacterial and archaeal isolates in rhizosphere soil of dicot herbs, dicot
trees, and monocots.
domain
Bacteria
phylum
Proteobacteria
class
Alphaproteobacteria
Betaproteobacteria
Gammaproteobacteria
order
Rhodospirillales
Sphingomonadales
Caulobacterales
Rhizobiales
Bradyrhizobiaceae
Acetobacteriaceae
unclassified
Burkholderiales
unclassified
Acidithiobacillales
Xanthomonadales
Legionellales
Pseudomonadales
Enterobacteriales
Shewanella
unclassified
Deltaproteobacteria
Epsilonproteobacteria
Gemmatimonadetes
Deferribacteres
Bacteroidetes
Nitrospira
Bacteroidetes
Flavobacteria
Sphingobacteria
Flexibacteria
Saprospiraceae
unclassified
Nitrospira
Leptospirillum
Thermodesulfodevibrio
Magnetobacterium
Verrucomicrobia
Chlamydiae
Planctomycetes
Acidobacteria
Deinococcus-Thermus Deinococci
Actinobacteria
Actinobacteria
Spirochaetes
Chlorobiales
Fibrobacteres
Thermales
Acidimicrobidae
Coriobacteridae
Pseudonocardiaceae
Micrococcaceae
Microbacteriaceae
Promicromonospora
Micromonospora
Propionibacterineae
Frankinaceae
Streptomycineae
dicot
0
4
6
26
8
2
50
52
5
2
24
0
27
8
0
4
8
3
0
.
3
15
3
3
32
2
1
.
.
.
0
1
6
1
4
4
0
8
11
1
0
2
1
6
.
2
.
dicot trees monocots
17
0
9
3
18
3
7
12
0
6
12
0
75
14
66
38
45
2
0
1
22
8
16
2
4
10
0
7
0
0
4
2
34
3
0
0
18
0
.
.
0
1
0
5
10
3
2
11
14
6
0
0
0
0
.
.
.
.
.
.
19
4
5
118
0
13
0
0
0
0
0
0
0
0
0
.
0
.
2
4
0
0
0
0
0
0
0
0
0
0
0
.
0
.
sum plants
17
16
27
45
14
14
139
156
52
3
54
18
41
15
0
10
45
3
18
0
4
20
16
16
52
2
1
0
0
0
23
0
8
128
1
17
4
0
8
11
1
0
2
1
6
0
0
0
Cyanobacteria
Chloroflexi
Sulfobacillus
Firmicutes
Archaea
Totals
termite group
TM7
Thermotogae
Thermodesulfobacteria
Aquificae
unclassified
Clostridia
Mollicutes
Bacilli
Lachnospiraceae
.
0
.
.
.
21
3
.
5
.
.
.
0
0
.
0
.
.
.
8
1
0
0
1
1
.
0
2
2
0
0
.
0
0
0
0
0
.
7
0
5
0
0
0
29
4
2
2
2
1
1
0
7
361
537
163
1061
This table was generated from ribosomal small-subunit DNA sequences from 13(?) publications
representing isolated rDNA sequences extracted from rhizosphere soils from 18 plant species (11
herbacious dicots, 2 dicot trees and 5 monocots). Numbers in each colum represent isolates
found in the rhizosphere of each plant type and reflect the diversity but not necessarily relative
abundance of each class or order of bacteria.
Figure 1. Root growing through soil. This image might be better on the cover of the book than in
this chapter…
Figure 2. Evolutionary distance dendrogram of the phyla Bacteria and Archaea based on 16S
rDNA isolates from rhizosphere soils.
TREE LEGEND
Dendrogram constructed using the programs ARB, and sequences were imported into the ARB
database using published GenBank accession numbers (Ludwig and Strunk, 1997). The initial
dataset consisted of 1360 ribosomal small-subunit DNA sequences from 13(?) publications
representing isolated rDNA sequences extracted from rhizosphere soils from 18 plant species (11
herbacious dicots, 2 dicot trees and 5 monocots). Some sequences had to be eliminated from the
analysis due to insufficient length or quality of sequence, bringing the final dataset down to 1227
sequences; in the final analysis, 90.2% of the initial sequences were aligned within Phil
Hugenholtz’s 16s rDNA alignment as per Bergey’s taxonomy of species (Garrity et al., 199x).
In the dendrogram, the horizontal length of each wedge corresponds to the diversity of the
phylum or class, while the vertical thickness reflects the abundance of different rDNA isolates
detected. This dataset does not reflect the relative abundances of organisms in the rhizosphere
soils, as the aim of each of the original experiments was to categorize the phylogenetic diversity
of bacteria and archaea in the rhizosphere soil.
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