28 G.T. Hill et al. Applied Soil Ecology 15 2000 25–36
Table 1 Common fatty acid signatures
Common bacterial signatures i15:0, a15:0, 15:0, 16:0, 16:1v5, 16:1v9, i17:0, a17:0, 17:0, 18:1v7t, 18:1v5, i19:0, a19:0
Aerobes 16:1v7, 16:1v7t, 18:1v7t
Anaerobes cy17:0, cy19:0
Sulfate-reducing bacteria 10Me16:0, i17:1v7, 17:1v6
Methane-oxidizing bacteria 16:1v8c, 16:1v8t, 16:1v5c, 18:1v8c, 18:1v8t, 18:1v6c
Barophilicpsychrophilic bacteria 20:5, 22:6
Cyanobacteria 18:2v6
Protozoa 20:3v6, 20:4v6
Fungi 18:1v9, 18:2v6, 18:3v6, 18:3v3
Actinobacteria 10Me18:0
Microalgae 16:3v3
Flavobacterium balustinum i17:1v7, Br 2OH-15:0
Bacillus spp.
Various branched chain fatty acids
3. Culture-independent methods of community analysis
Because of the inherent limitations of culture-based methods, soil microbial ecologists are turning increas-
ingly to culture-independent methods of community analysis. Using culture-independent methods, the
composition of communities can be inferred based on 1 the extraction, quantification, and identifi-
cation of molecules from soil that are specific to certain microorganisms or microbial groups; or 2
advanced fluorescence microscopic techniques. Use- ful molecules for such studies include phospholipid
fatty acids and nucleic acids Morgan and Winstanley, 1997 whereas the microscopic techniques involve
either the hybridization of fluorescent-labeled nucleic acid probes with total RNA extracted from soils or
hybridizations with cells in situ.
3.1. Phospholipid fatty acid analysis Phospholipid fatty acid PLFA analysis has been
used as a culture-independent method of assessing the structure of soil microbial communities and determin-
ing gross changes that accompany soil disturbances such as cropping practices Zelles et al., 1992, 1995,
pollution Frostegard et al., 1993, fumigation Macal- ady et al., 1998, and changes in soil quality Bardgett
et al., 1996; Reichardt et al., 1997; Bossio et al., 1998; Petersen et al., 1998. Phospholipid fatty acids
are potentially useful signature molecules due to their presence in all living cells. In microorganisms, phos-
pholipids are found exclusively in cell membranes and not in other parts of the cell as storage products.
This is important because cell membranes are rapidly degraded and the component phospholipid fatty acids
are rapidly metabolized following cell death. Con- sequently, phospholipids can serve as important in-
dicators of active microbial biomass as opposed to non-living microbial biomass.
An essential consideration in the use of these molecules to describe microbial communities is that
unique fatty acids are indicative of specific groups of organisms Table 1. Our knowledge of such signature
molecules comes from the use of fatty acid analysis for bacterial taxonomy, in which specific fatty acid
methyl esters FAMEs have been used as an accepted taxonomic discriminator for species identification.
Furthermore, phospholipid fatty acids are easily ex- tracted from microbial cells in soil Tunlid and White,
1992; Zelles and Bai, 1993 allowing access to a greater proportion of the microbial community resi-
dent in soil than would otherwise be accessed during culture-dependent methods of analysis.
The presence and abundance of these signature fatty acids in soil reveals the presence and abundance of
particular organisms or groups of organisms in which those signatures can be found. For example, Tunlid
et al. 1989 were able to use PLFA analysis to demon- strate differences in microbial communities associated
with Rhizoctonia damping-off. They were further able to monitor the presence of the biological control or-
ganism Flavobacterium balustinum strain 299 on cu- cumber roots. In other studies, PLFA profiles were
generated from soils exposed to different farming sys- tems Bossio et al., 1998. Organically-managed soils
G.T. Hill et al. Applied Soil Ecology 15 2000 25–36 29
i.e. those receiving no synthetic fertilizers and pes- ticides gave rise to PLFA profiles that were signifi-
cantly different from those from conventionally man- aged soils i.e. those receiving synthetic fertilizers and
pesticides. Profiles from organically-managed soils were enriched with i14:0, a15:0, 16:1v7c, 16:1v5c,
14:0, and 18:2v6c fatty acids indicating a greater di- versity of aerobic bacteria as well as populations of
cyanobacteria and methane-oxidizing bacteria. These studies clearly demonstrate the utility of this method
in determining gross community changes associated with soil management practices.
Despite the usefulness of this method, there are some important limitations Haack et al., 1994. First,
appropriate signature molecules are not known for all organisms in a soil sample and, in a number of cases,
a specific fatty acid present in a soil sample cannot be linked with a specific microorganisms or group of mi-
croorganisms. In general, the method cannot be used to characterize microorganisms to species. Second, since
the method relies heavily on signature fatty acids to determine gross community structure, any variation in
these signatures would give rise to false community estimates created by artifacts in the methods. Third,
bacteria and fungi produce widely different amounts of PLFA and the types of fatty acids vary with growth
conditions and environmental stresses. Although sig- nature PLFAs can be correlated with the presence of
some groups of organisms, they may not necessarily be unique to only those groups under all conditions.
Consequently, this could give rise to false community signatures.
3.2. Nucleic acid techniques Of all the cell component molecules tested to date,
nucleic acids have been the most useful in providing a new understanding of the structure of microbial com-
munities. For example, in recent studies of soil micro- bial diversity, Torsvik and colleagues Torsvik et al.,
1990a,b, 1996; Ovreas and Torsvik, 1998 compared the re-association kinetics of DNA isolated from soil
with that of pure cultures of microorganisms. They reasoned that the greater the sequence diversity of the
DNA and hence the microbial diversity, the greater the DNA reannealing time. Based on these studies,
they estimated that the genetic diversity of soil was 200 times greater than the diversity among bacteria
cultured from the same soil. This indicates that soil microbial communities are much more complex than
we currently recognize and that the analysis of DNA sequences may provide a greater understanding of the
microbial diversity that exists in soil than could be gained from culture-dependent methods.
Of the various nucleic acid techniques used to esti- mate microbial community composition and diversity
in complex habitats, the most useful is the determina- tion of the sequences of 16S ribosomal RNA rRNA
genes i.e. encoded by rDNA in prokaryotes and 5S or 18S rRNA genes in eukaryotes Ward et al., 1992.
These small subunit SSU rDNA molecules are par- ticularly suited for such studies for a number of rea-
sons. First, they are found universally in all three forms of life: the domains Bacteria, Archaea, and Eucarya
Woese et al., 1990. Second, these molecules are com- posed both of highly conserved regions and also of
regions with considerable sequence variation Woese, 1987. Because of these differential rates of sequence
evolution, phylogenetic relationships at several hier- archical levels can be measured from comparative se-
quence analyses. Third, the phylogenetic information held in the SSU rDNA molecule is further enhanced by
its relatively large size e.g. ∼1.5 kb for the 16S rDNA molecule and the presence of many secondary struc-
tural domains. Consequently, evolutionary changes in one domain do not affect the rate of change in other
domains. Finally, SSU rDNA can be easily amplified using polymerase chain reaction PCR and rapidly
sequenced.
Perhaps the greatest advantage of the analysis of SSU rDNA is that is that microorganisms from natu-
ral habitats can be studied and characterized without culturing. Various studies have shown that rDNA from
over 90 of the microorganisms that can be observed microscopically in situ can be extracted and analyzed
Steffan and Atlas, 1988; Steffan et al., 1988; Tsai and Olsen, 1992; More et al., 1994; Zhou et al., 1996;
Porteous et al., 1997 as compared with less than 0.1 of the microorganisms observed in soil that can be
recovered on culture media.
Numerous studies have applied these techniques to the study of soil microbial communities e.g. Stacke-
brandt et al., 1993; Lee et al., 1996; Stephen et al., 1996; Ueda et al., 1995; Borneman et al., 1996;
Rheims et al., 1996; Bintrim et al., 1997; Borne- man and Triplett, 1997; Felske et al., 1997, 1998a,b;
30 G.T. Hill et al. Applied Soil Ecology 15 2000 25–36
Heuer and Smalla, 1997; Kuske et al., 1997; Smith et al., 1997; Duineveld et al., 1998; Grosskopf et al.,
1998. In nearly all of these studies, novel microbial lineages have been discovered, confirming our lack
of understanding of the microbial species that inhabit soils and their potentially important roles in ecosys-
tem function. For example, studies have shown that agricultural soils contain a diversity of Archaea, or-
ganisms previously thought to exist only in extreme environments Ueda et al., 1995; Bintrim et al., 1997;
Buckley et al., 1998. Other studies have shown that some soil microbes, which have previously not been
cultured and described, are global in their distribution and may play important roles in soils worldwide Lie-
sack and Stackenbrandt, 1992; Felske et al., 1997; Kuske et al., 1997.
All DNA extraction techniques are based on meth- ods developed over the past 20 years. Once the micro-
bial community rDNA is amplified from soil samples using PCR, individual amplicons must be separated
prior to sequence analysis. Methods used most com- monly for the separation of individual amplicons have
been standard cloning procedures using a variety of Escherichia coli
vectors. Recently, as a complement to cloning procedures,
the use of denaturing gradient and temperature gra- dient gel electrophoresis DGGETGGE for separat-
ing individual amplicons has been described Muyzer et al., 1993; Ferris and Ward, 1997; Heuer et al., 1997;
Muyzer and Smalla, 1998. This technique allows one to separate mixtures of PCR products that are of the
same length but differ only in sequence. The sepa- ration power of this technique rests with the melting
behavior of the double stranded DNA molecule. As DNA molecules are electrophoresed in an increasing
gradient of denaturant or in an increasing temperature gradient, it remains double-stranded until it reaches
the denaturant concentration or temperature that melts the double-stranded molecule. As the DNA melts, it
branches, thus reducing the mobility in the gel. Since the melting behavior is largely dictated by the nu-
cleotide sequence, the separation will resolve individ- ual bands, each corresponding to a unique sequence.
Theoretically, any SSU rRNA gene found in the mixed template DNA extracted from soils could be specifi-
cally amplified and resolved on a DGGE gel.
Once rDNA amplicons have been cloned or sepa- rated by DGGE or TGGE, they can be sequenced and
analyzed for similarity to other known sequences in public-domain databases e.g. the NCBI GeneBank
database [http:www.ncbi.nlm.nih.gov], the Riboso- mal Database Project [http:www.cme.msu.eduRDP]
Maidak et al., 1997 and the Antwerp SSU rRNA database [http:rrna.uia.ac.be] Van de Peer et al.,
1997. By estimating phylogenetic relatedness to other sequences in the databases, the identity of the
microorganism from which the SSU rRNA gene was derived can be determined. It is hoped that
the potentially close phylogenetic relationships of non-culturable microorganisms with known species
can be utilized to devise culturing techniques for many of these microorganisms.
In recent years, a number of analyses have focused on the characterization of soil microbial communities
based on rRNA as opposed to rRNA genes encoded by rDNA e.g. Felske and Akkermans, 1998b; Hahn
et al., 1990; Moran et al., 1993; Felske et al., 1996; Purdy et al., 1996; Duarte et al., 1998. Like rDNA,
rRNA has both conserved and highly variable regions that permit the discrimination of taxa at multiple tax-
onomic levels. In addition, use of rRNA offers three principle advantages over rDNA techniques:
1. Because ribosomes are the sites of protein synthe-
sis, cellular ribosome content and thus rRNA con- tent are directly correlated with metabolic activ-
ity and growth rate Wagner, 1994. Therefore, a high proportion of the rRNA sequences detected
in soil samples should correspond to metabolically active and growing microorganisms Felske et al.,
1996. Results with rRNA can be readily compared with those for simultaneously-extracted DNA e.g.
Felske et al., 1996 to estimate both the dormant and metabolically-active community.
2. Because rRNA sequences are typically present in cells in higher copy number than rDNA sequences,
they should be easier to detect Moran et al., 1993. 3. When ribosomes are extracted directly from soil
samples, free nucleic acids and many dormant mi- croorganisms are excluded and only rRNA from
active cells is detected Felske et al., 1997; Felske and Akkermans, 1998a.
When rRNA amplicons are separated on a DGGE or TGGE gel, the banding pattern serves as a fingerprint
of the soil microbial community. Assuming no ampli- fication bias, the intensity of a given band indicates
the abundance of the corresponding rRNA sequence
G.T. Hill et al. Applied Soil Ecology 15 2000 25–36 31
in the soil community Felske et al., 1998b. A com- plicating factor is that the number of rRNA operons
is known to vary among taxonomic groups Rosado et al., 1997, so that rRNA sequence heterogeneity can
and does occur within cells of the same species. Con- sequently, each amplification product on a gel cannot
be assumed to correspond to a different organism, and a single organism may be represented by several am-
plification products.
A taxon may contribute rRNA to a soil community in two ways: 1 by being represented by many active
cells; and 2 by being represented by cells containing many ribosomes Felske et al., 1997. These scenarios
are only reliably distinguishable by in situ hybridiza- tion e.g. Binder and Liu, 1998. However, a compar-
ison of probe signal intensity for rRNA and rDNA in DGGE or TGGE gels can provide evidence for which
of the scenarios is more likely. For example, simi- lar signal intensities for rRNA and for rDNA suggest
that activity is due to cell abundance rather than high ribosome copy number per cell Felske et al., 1997.
Despite the usefulness of these nucleic acid tech- niques for characterizing soil microbial communities,
there are a number of limitations. As with most tech- niques that measure metabolic activity, storage of
samples prior to processing can bias results. Shifts in active functional groups of prokaryotes have been
observed when samples are stored aerobically or left at room temperature reviewed in van Winzingerode
et al., 1997. However, presumably this bias could be removed easily by immediate processing or freezing.
Another limitation is that comparisons of activity among organisms or soil samples may be confounded
by several factors. Extraction efficiency differs among soils and microorganisms, so that apparent differences
in activity of particular organisms across soil samples can be an artifact of the extraction procedure Moran
et al., 1993. Some prokaryotic cells are more easily lysed than others, so that incomplete lysis of some
species could result in underestimates of activity van Winzingerode et al., 1997. Sequence amplification
and detection are only as good as the probes used; or- ganisms with different affinities for the probes used
will differ in their apparent activities Zheng et al., 1996. Amplification bias has also been shown to oc-
cur for templates that differ substantially in abundance, with preferential amplification of more abundant se-
quences Suzuki and Giovannoni, 1996. However, Felske and Akkermans 1998a found no evidence of
amplification bias for the universal bacterial primers they have used to amplify 16S rDNA. For a detailed
review of possible sources of amplification bias, see van Winzingerode et al. 1997.
Another important limitation to this approach is that it has been applied largely to investigations of prokary-
otes. Theoretically, detection of rRNA could be used to determine active eukaryotes, as well as prokary-
otes, in soils. However, eukaryote ribosomes have not been well studied and their encoding genes and reg-
ulation are far more complex. Furthermore, sequence representation in public databases is not as extensive,
making identifications of known eukaryotes from soil samples problematic.
3.3. Phylogenetic analysis The success of any of the preceding methods for
community characterization relies on a suitable phy- logenetic analysis because many of the organisms that
are likely to be described from soil communities have not been studied previously. A number of phylogenetic
methods have been utilized in studies of microbial ecology Woese, 1987. While rDNA and rRNA are
commonly used as characters in phylogenetic analysis, the list of characters is extensive and can range from
molecular to morphological traits Olsen and Woese, 1993. For microorganisms, molecular data often pro-
vide the greatest wealth of information because mi- croorganisms such as bacteria simply do not have the
diversity of form to make morphological characteris- tics useful in establishing phylogenies.
Aside from the derivation of taxonomies, phyloge- netic analyses are important in identifying similarities
between organisms, leading to the ability to understand the physiology and ecology of as yet non-culturable
species. Unfortunately for taxonomists, phylogenetic analyses have at least one major drawback. The fact
that an analysis based on a single type of molecule re- sults in a close relationship between taxa does not nec-
essarily mean that another, equally suitable molecule will support these results, although this often occurs
Olsen and Woese, 1993. When based on a limited set of taxonomic criteria, it is difficult to say with
certainty whether or not those criteria can resolve an unknown microorganism from other known microor-
ganisms. Therefore, microbial phylogenies should be
32 G.T. Hill et al. Applied Soil Ecology 15 2000 25–36
interpreted with caution when used in soil microbial community analyses.
3.4. Fluorescent in situ hybridization FISH Fluorescent in situ hybridization FISH has been
used primarily with prokaryotic communities and allows the direct identification and quantification of
specific andor general taxonomic groups of microor- ganisms within their natural microhabitat Amann
et al., 1995; Assmus et al., 1995; MacNaughton et al., 1996; Kenzaka et al., 1998. In FISH, whole cells
are fixed, their 16S or 23S rRNA is hybridized with fluorescently-labeled taxon-specific oligonucleotide
probes, and then the labeled cells are viewed by scan- ning confocal laser microscopy SCLM. Because
whole cells are hybridized, artifacts arising from biases in DNA extraction, PCR amplification, and
cloning are avoided Ludwig et al., 1997; Wallner et al., 1997; Felske et al., 1998a. FISH has two ad-
vantages over immunofluorescence techniques. First, FISH can detect microorganisms across all phyloge-
netic levels, whereas immunofluorescence techniques are limited to the species and sub-species levels.
Second, FISH is more sensitive than immunofluores- cence because non-specific binding to soil particles
does not typically occur Amann et al., 1995. FISH probes can be generated without prior isolation of the
microorganism, whereas pure cultures are needed in immunofluorescence studies for generating specific
antibodies Hahn et al., 1992. Scanning confocal laser microscopy SCLM surpasses epifluorescence
microscopy in sensitivity and has the ability to view the distribution of several taxonomic groups simulta-
neously as a three-dimensional image Assmus et al., 1995; Kirchhof et al., 1997. Use of distinctive flu-
orescent dyes and corresponding filter sets allows the observer to differentiate fluorescing microbes
from autofluorescent soil particles and plant debris Assmus et al., 1995; MacNaughton et al., 1996.
FISH provides a more accurate quantification of cells as compared to the rough estimates obtained from
dot-blot assays Amann et al., 1995 in which micro- bial DNA is blotted onto a membrane than probed
with the fluorescent oligonucleotide probe.
The sensitivity of FISH has been greatly improved to afford the detection of single cells within com-
plex environments such as rhizosphere and bulk soils Christensen and Poulsen, 1994; Fischer et al., 1995;
MacNaughton et al., 1996; Zarda et al., 1997; Felske et al., 1998a. Strongly fluorescing dyes can be used
or multiple probes can be designed to target different regions of the same 16S or 23S rRNA molecule, thus
increasing the strength of the signal Amann et al., 1995; Ludwig et al., 1997. Probes for kingdoms Eu-
bacteria, Archaea, Eucarya, families, genera, species, or sub-species can be differentially labeled and used
in combination to view the occurrence and distribution of several taxonomic groups simultaneously within a
single soil sample Manz et al., 1992; Amann et al., 1995; Zarda et al., 1997. To be detected, soil mi-
crobes must be metabolically active and possess cell walls sufficiently permeable to allow penetration of the
probe Christensen and Poulsen, 1994; Amann et al., 1995. Penetration of cells with such probes is a prob-
lem in nutrient-poor soils and in soils where microor- ganisms are dormant or quiescent Hahn et al., 1992;
Fischer et al., 1995 because cells are generally smaller and cell walls relatively thicker under these condi-
tions. However, progress is being made to overcome these problems with groups such as actinobacteria and
Bacillus
spores MacNaughton et al., 1994; Fischer et al., 1995. To address the problem of low metabolic
activity in soil, some researchers have added nutri- ents to stimulate microbial activity Hahn et al., 1992.
However, so as not to bias the community profile, the amendments should equally stimulate all members of
the community.
FISH can be used to visualize soil microorgan- isms that have not yet been cultured, and is useful
in studying the ecological distribution of microorgan- isms throughout diverse habitats Ludwig et al., 1997;
Zarda et al., 1997; Wullings et al., 1998. When using FISH to examine all members within a given taxon,
one must keep in mind that the probe being used is only as good as the representative members that
were used to generate it Amann et al., 1995. Other, non-cultured organisms may not be detected with this
probe or cross-hybridization to related organisms may occur Hahn et al., 1992; MacNaughton et al., 1996;
Felske et al., 1998a.
FISH can be combined with cultivation techniques, immunofluorescence, nucleotide probes targeting
structural genes or mRNAs, reporter genes, microsen- sors, or flow cytometry to gain information regarding
the structure and function of microorganisms within
G.T. Hill et al. Applied Soil Ecology 15 2000 25–36 33
a complex microbial community Amann and Kuhl, 1998. FISH is a powerful tool that can be used not
only for studying individuals within a population, but also has potential uses for studying population
dynamics, tracking microorganisms released into the environment e.g. for biological control or biore-
mediation, epidemiology, and microbial ecology of economically important plant pathogens in agricul-
tural soils Hahn et al., 1992; Kirchhof et al., 1997; Wullings et al., 1998.
4. Summary
