MINIREVIEW
Growth of saprotrophic fungi and bacteria in soil
Johannes Rousk1,2 & Erland Bååth1
1
Microbial Ecology, Department of Biology, Ecology Building, Lund University, Lund, Sweden; and 2Environment Centre Wales,
Bangor University, Gwynedd, UK
Correspondence: Johannes Rousk,
Environment Centre Wales, Bangor
University, 2nd floor, Bangor, Gwynedd LL57
2UW, UK. Tel.: 144 756 390 68 29;
fax: 144 1248 354997;
e-mail: [email protected]
Received 15 January 2011; revised 31 March
2011; accepted 1 April 2011.
Final version published online 28 April 2011.
DOI:10.1111/j.1574-6941.2011.01106.x
MICROBIOLOGY ECOLOGY
Editor: Ian Head
Keywords
fungal growth; bacterial growth; leucine/
thymidine incorporation; acetate in ergosterol
incorporation; turnover time;biomass
production.
Abstract
Bacterial and fungal growth rate measurements are sensitive variables to detect
changes in environmental conditions. However, while considerable progress has
been made in methods to assess the species composition and biomass of fungi and
bacteria, information about growth rates remains surprisingly rudimentary. We
review the recent history of approaches to assess bacterial and fungal growth rates,
leading up to current methods, especially focusing on leucine/thymidine incorporation to estimate bacterial growth and acetate incorporation into ergosterol to
estimate fungal growth. We present the underlying assumptions for these methods,
compare estimates of turnover times for fungi and bacteria based on them, and
discuss issues, including for example elusive conversion factors. We review what
the application of fungal and bacterial growth rate methods has revealed regarding
the influence of the environmental factors of temperature, moisture (including
drying/rewetting), pH, as well as the influence of substrate additions, the presence
of plants and toxins. We highlight experiments exploring the competitive and
facilitative interaction between bacteria and fungi enabled using growth rate
methods. Finally, we predict that growth methods will be an important complement to molecular approaches to elucidate fungal and bacterial ecology, and we
identify methodological concerns and how they should be addressed.
Introduction
Species composition, biomass, and growth rate (production) are important characteristics for any community,
including soil fungi and bacteria. Of these variables, the
growth rate will be most sensitive to changes in environmental conditions, thus being the prime choice to enable the
detection of rapid and subtle changes in microbial communities. Bearing this in mind, the rudimentary state of our
knowledge on microbial growth and production in soil is
striking. Different studies that have attempted to estimate
growth have yielded very different and often conflicting
results, and, more importantly, there are remarkably few
studies that report actual growth or turnover rates of the soil
microbial community at all. This is in contrast to the state of
the knowledge on aquatic environments, where thousands
of bacterial growth rate measurements can be compiled
(Cole et al., 1988; Fouilland & Mostajir, 2010) and where
several independent methods have been used to estimate
growth rates, yielding corroborative results, including for
FEMS Microbiol Ecol 78 (2011) 17–30
example thymidine (Fuhrman & Azam, 1980; Moriarty &
Pollard, 1982) and leucine incorporation (Kirchman et al.,
1985), frequency of dividing cells (Hagström et al., 1979),
and biomass increase after filtering out predators or diluting
with bacteria-free water (Fuhrman & Azam, 1980). One
reason for the different states of knowledge on microbial
growth in aquatic and soil systems is, of course, that in soil,
we have two major groups of decomposers, bacteria and
fungi, where the latter group also comprises both saprotrophs and mycorrhizal fungi with different feeding strategies. Moreover, the soil matrix is a complex structure
interfering with the measurements. For example, while
aquatic microorganisms can be easily separated from their
predators without seriously compromising the system using
the dilution and filtration technique, there is no easy way of
separating soil microorganisms from their predators without disturbing the system. Under normal soil conditions, the
growth of the microorganisms will be balanced by predation
or other types of cell death, thus resulting in a quasi-steadystate system, where biomass production will not always
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translate into a net increase in biomass, as indicated by the
usually small variations in biomass over time (Joergensen
et al., 2011). Another example of the difficulties in assessing
microorganisms in a soil system is the use of the frequency
of dividing cells approach. This approach appears to overestimate the bacterial growth rates in soil (Bloem et al.,
1992), probably because in soil, the presence of surfaces will
result in cells being close together long after a division,
unlike the situation in water, where dividing cells will
eventually split in two.
However, progress has been made by applying methods
originally used for estimating the growth rates of bacteria
and fungi in aquatic environments, namely the thymidine
(TdR) and leucine (Leu) incorporation techniques to estimate bacterial growth and production and acetate incorporation into ergosterol (Ac-in-erg) to estimate fungal
growth. In this review, we will compare estimates of bacterial
and fungal growth and turnover of biomass with earlier
estimates. We will also review how different environmental
factors, including both abiotic and biotic ones, affect
bacterial and fungal growth in soil. Finally, we will address
some of the main problems in determining fungal and
bacterial growth in soil and identify measures to resolve
them, and discuss the future role of growth rate measurements in environmental microbiology.
Methodology
Earlier studies
Some of the first attempts to determine the turnover rates of
soil microorganisms involved modeling using microbial
biomass and annual substrate input from plants as the input
parameters. This initially resulted in estimates of turnover
rates of the soil microbial biomass varying on the order of
days to years (Hunt, 1977; Jenkinson & Ladd, 1981; Chapman & Gray, 1986). With the inclusion of recycling and
maintenance in the models, even larger variations in calculated turnover times of the soil microorganisms were
obtained (Chapman & Gray, 1986). Bearing in mind that
both maintenance and the extent of recycling, which depend
on growth yields, are virtually unknown in soil, these
calculations are not very precise. Furthermore, the estimates
are dependent on input data on long time scales (annual),
and thus, short-term effects cannot be addressed.
Another classical way of studying the growth rates in soil
is by following increases in the biomass of fungi or bacteria,
usually during a situation of rapid growth after adding a
substrate, increasing the water content, or during recolonization by microorganisms of partially sterilized soil. For
example, frequently repeated counting of bacterial cells in
forest humus (summing periods of increasing biomass as
growth) resulted in an estimated annual turnover of 12
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J. Rousk & E. Bååth
times, that is, a bacterial turnover time of 30 days (Clarholm
& Rosswall, 1980). A problem with the rationale for this
approach is that bacteria are certainly also growing under
conditions of no net biomass increase, when growth is
balanced by predator consumption and death due to other
causes. Both increasing (Clarholm, 1981; Christensen et al.,
1992b, 1995) and decreasing (Christensen et al., 2007)
bacterial growth has been shown to result in increased and
decreased bacterial predator biomass, respectively, emphasizing that bacterial growth may not always be resolved from
the measurement of net biomass change. Consequently, the
estimates of growth rates using changes in biomass must be
considered minimum values. We can easily study a biomass
increase after adding a substrate (e.g. Nannipieri et al.,
1983), but it is often unclear how this situation can be
translated to normal soil conditions with low substrate
availability. Furthermore, even after adding a substrate,
predators will eventually start to grow, corrupting the
information provided by a biomass increase regarding the
growth rates during longer experiments.
The problems listed above can be largely circumvented
using techniques based on the addition of tracer amounts of
radioactively labeled precursors of macromolecules synthesized during growth and measurement of tracer incorporation over short time periods. During the brief incubation
periods, the potentially altered growth conditions following
the tracer additions do not affect the initial growth rates.
The estimated macromolecular synthesis can then be used as
a relative estimate of in situ microbial growth, because
macromolecular synthesis will be approximately proportional to increased biomass. Alternatively, conversion factors
can be used to calculate actual growth in terms of for
example number of cells produced or the production of
microbial carbon (C), or by dividing the concentration of
biomass by the rate of biomass production to estimate the
turnover time.
Bacterial growth rates measured using TdR and
Leu incorporation
Although several radioactively labeled precursors have been
used, especially in aquatic environments, TdR, incorporated
into DNA, and Leu, incorporated into proteins, are most
commonly used. Although the former approach was applied
very early in soil (Thomas et al., 1974), it only came into
common use following application in aquatic environments
around the 1980s (Fuhrman & Azam, 1980; Moriarty &
Pollard, 1982). TdR incorporation rapidly became the
standard technique to measure heterotrophic bacterial
growth in aquatic habitats. Because the ability to incorporate extracellular TdR into DNA is not a completely ubiquitous trait, while the ability to incorporate extracellular Leu
protein is more widespread (Pérez et al., 2009), TdR
FEMS Microbiol Ecol 78 (2011) 17–30
19
Growth of saprotrophic fungi and bacteria in soil
incorporation was later partly replaced by the Leu incorporation technique (Kirchman et al., 1985). Furthermore,
because proteins are more abundant than DNA in a bacterial
cell, Leu incorporation is also potentially more sensitive
than the TdR incorporation technique. However, several
comparisons in soil and water have shown that they yield
comparable relative results (e.g. Olsson et al., 1996a; Mahmood et al., 2003; Medina et al., 2003; Rousk et al., 2009b),
although Leu incorporation usually becomes relatively
higher under situations of high bacterial growth (Servais
& Garnier, 1993; Vinten et al., 2002; Rousk & Bååth,
2007a; Meidute et al., 2008) or at higher temperatures
(Dı́az-Raviña et al., 1994; Tibbles, 1996; Ranneklev & Bååth,
2001).
Initially, TdR and Leu incorporation in soil were estimated using protocols similar to those used for sediments in
aquatic habitats. The precursor was added in trace amounts
to a slurry, incubated briefly, after which the bacteria were
killed. This was followed by the extraction of radioactively
labeled macromolecules from the soil slurry using different
acid/base extraction steps and finally quantification using
liquid scintillation to measure the amount of precursor
incorporated into the macromolecules (Christensen et al.,
1989; Bååth, 1990; Michel & Bloem, 1993; Uhlı́řová &
Šantrùčková, 2003; Amalfitano et al., 2008).
A problem with measuring bacterial growth in a soil
slurry is the requirement for a high concentration of
precursor during incubation, as well as a large and variable
background noise derived from, for example, the precursor
binding to soil particles. To overcome this, Bååth (1992)
combined the TdR incorporation technique (and later the
Leu incorporation technique, Bååth, 1994a, b) with a method to extract bacteria from soil using homogenization,
followed by low-speed centrifugation (Bakken, 1985). The
tracer is then added to the suspension of cells recovered
from the soil. Although the homogenization/centrifugation
technique introduced yet another step in the procedure, the
addition of the precursor and subsequent washing steps
were less laborious than using the slurry technique. Also,
these steps could be performed exactly as in the application
of Leu and TdR incorporation techniques in aquatic samples. In the modified method, tracer amounts of the
precursor are added to the extracted bacterial suspension.
After a short incubation period (usually between 0.5 and 4 h
at room temperature), the bacteria are killed, followed by
several washing steps using filtration to remove nonincorporated precursor molecules. Later, the filtration step was
replaced by centrifugation using microcentrifuge vials
(Smith & Azam, 1992; Bååth et al., 2001), which made the
method even more rapid. By counting bacteria in the
extracted bacterial suspension, bacterial turnover rates
could also be estimated. Perhaps more importantly, this
simplified technique made it possible to process hundreds of
FEMS Microbiol Ecol 78 (2011) 17–30
samples in a day, allowing for high-resolution studies of
environmental effects, including temperature, moisture, pH,
toxic substances, substrate additions, etc. It is important to
consider that the homogenization/centrifugation step can
affect the results by the selective recovery of some cell types;
thus, the cells in the suspension may not fully represent the
community present originally in the soil (Uhlı́řová &
Šantrùčková, 2003). However, the effect on the measured
growth rates appeared to be minor (Bååth, 1996), as
indicated by the lack of difference between bacterial growth
estimates from soil slurries and samples processed by the
homogenization/centrifugation method.
Two critical prerequisites for the Leu and TdR incorporation methods to measure bacterial growth are specificity
(incorporation only into bacteria and not fungi) and to
what extent the growth rate in the slurry or the extracted
bacterial suspension reflects the original conditions in the
soil. The first will be especially problematic in the slurry
system. However, it has been suggested that the low concentrations of the added tracer molecules select for organisms with a maximal surface area to volume ratio, which
should benefit bacterial uptake (Bloem & Bolhuis, 2006).
Specificity is less problematic when extracting bacteria by
homogenization/centrifugation, because very few hyphae
will be present in the bacterial suspension, and thus this
step selects for bacteria. In agreement with these predictions,
in soils manipulated to be bacterial and fungal free using soil
sterilization and inoculation, Bååth (1990) showed that TdR
incorporation only occurred in soils with bacteria, even
when using the soil slurry technique. It has also been shown
that antibacterial antibiotics decreased bacterial growth (Leu
incorporation), but increased fungal growth (as Ac-in-erg
incorporation) (Rousk et al., 2008), also suggesting that the
Leu and TdR incorporation specifically reflects soil bacterial
growth.
Both the slurry and the homogenization/centrifugation
technique will alter the nutrient status and other conditions
for the bacteria due to the addition of the potential
substrates TdR and Leu and by releasing substrate from the
soil matrix into the aqueous phase, with the potential to
affect the growth rates. However, there are several lines of
evidence that indicate that the altered growth conditions
will not affect bacterial growth rates during several hours at
normal laboratory temperatures. Both TdR and Leu incorporation rates were stable up to at least 1 h after preparing
the slurry (Bååth, 1990) and over a period of 4 h for
the homogenization/centrifugation method (Bååth, 1992,
1994b) at room temperature, with measurements made
already 15 min after tracer addition. Later studies have
shown that this incubation period with stable incorporation
rates can be extended, especially at low temperatures. For
example, at 5 1C, constant incorporation rates (linear
increase in cumulative Leu incorporation) were found for a
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J. Rousk & E. Bååth
Ac-in-erg incorporation (DPM)
Leucine incorporation (DPM)
1.2×105
S1
S2
M1
M2
1×105
8×104
6×104
4×104
2×104
400
300
200
100
0
0
0
5
10
15
Time (h)
20
25
Fig. 1. Bacterial growth estimated as Leu incorporated into bacterial
suspensions (DPM) extracted from soil using homogenization/centrifugation. The bacterial suspensions were incubated at 5 1C for different times
after adding 3H-Leu. S and M indicate two different agricultural soils,
with 1 and 2 being replicate suspensions (H. Koponen & E. Bååth,
unpublished data).
period of at least 24 h (Fig. 1). Also, addition of more
substrates such as glucose does not alter the bacterial growth
rate for a period of up to 10 h (Bååth, 1990; Iovieno & Bååth,
2008; Rousk et al., 2009a; S. Reischke, J. Rousk, & E. Bååth,
unpublished data), showing that altered nutrient conditions
do not result in immediate changes in bacterial growth rates.
This is consistent with the substrate-induced-respiration
response after adding glucose that remains at a stable level
usually for up to 10 h or more, indicating no altered
microbial growth during that time (Anderson & Domsch,
1985, as also discussed by Bååth, 1990).
Fungal growth rates measured using Ac-in-erg
incorporation
The method is based on the incorporation of radioactively
labeled acetate into the fungal-specific lipid ergosterol. The
method was originally used on plant litter in aquatic
habitats (Newell & Fallon, 1991), but was later adapted to
soil (Pennanen et al., 1998; Bååth, 2001). Briefly, 14C-acetate
is added to a soil slurry and incubated to allow the fungi to
incorporate the substrate into newly synthesized ergosterol,
where the rate of ergosterol produced will be proportional to
fungal growth. Originally, an incubation time of 16 h was
used (Bååth, 2001), but this has lately been reduced to 4–5 h
at 22 1C (Bapiri et al., 2010; Rousk et al., 2010) and even
down to only 2 h (S. Reischke, unpublished data). Ergosterol
is then extracted and separated using HPLC using a UV
detector and a fraction collector. The ergosterol peak is
collected and the amount of acetate incorporated is determined using liquid scintillation.
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500
0
2
4
6
8
10
12
14
Time (h)
Fig. 2. Fungal growth estimated as acetate incorporated into ergosterol
(Ac-in-erg) (DPM) in a grassland soil. A soil slurry was incubated at 22 1C
for different times after adding 14C-Ac (J. Rousk & E. Bååth, unpublished
data).
In the same way as for the TdR and Leu incorporation
technique, the lack of specificity and altered substrate
concentrations during the incubation of the soil slurry
might confound the results. The former problem is, however, less problematic because ergosterol is specific to fungi.
Additionally, the lack of Ac-in-erg incorporation into fungal-free soil (Bååth, 2001), and the lack of negative effects of
antibacterial antibiotics (Bååth, 2001), which can totally
inhibit bacterial growth (Rousk et al., 2008), represent
corroborative evidence for the specificity of the method.
Bååth (2001) also found a constant incorporation rate up to
18 h after adding acetate to the soil slurry, and we have later
verified this up to around 12 h (Fig. 2). This suggests that the
present use of a 2–4-h incubation time would not alter the
fungal growth rate to any large extent compared with the
original growth before adding the acetate, and that the
method can therefore be used to estimate in situ fungal
growth. It should be noted, however, that although only
fungi will incorporate Ac into ergosterol, making the
method specific, bacteria are also able to use the labeled Ac,
affecting the supply to fungi, which could potentially
influence the result. A short incubation period should also
minimize this problem, however.
Growth rates in soil
Most studies on bacterial growth rates using either the TdR
or the Leu incorporation method suggest that the turnover
times of the soil bacterial community are in the order of days
to weeks at a temperature of around 20 1C (Table 1),
irrespective of whether the slurry or the centrifugation/
homogenization method is used. However, some earlier
FEMS Microbiol Ecol 78 (2011) 17–30
21
Growth of saprotrophic fungi and bacteria in soil
Table 1. Estimated bacterial turnover times in soil
Habitat
Method
Turnover time (days)
Incubation temperature ( 1C)
Reference
Agricultural and humus soil
Agricultural and humus soil
Arable sol
Agricultural soil
Agricultural soil
Agricultural soil
Agricultural soil
Nunatak soils, Antarctica
19 different soils
19 different soils
Meadow and forest soil
Meadow and forest soil
TdR, slurry
TdR, susp
FDC
Leu, susp
TdR, susp
TdR, susp
TdR, slurry
TdR, slurry
TdR, susp
Leu, susp
TdR Leu, slurry
TdR Leu, susp
2–4.7
3.5–4.8
0.5–1
4.3
5.9
3.8
107–160
11–215
2.3–33 (mean 9.3)
2.1–13.1 (mean 5.9)
1–7
1.1–53.7
23
22
NA
22
22
22
25
10
20
20
20
20
Bååth (1990)
Bååth (1992)
Bloem et al. (1992)
Bååth (1994a)
Bååth (1994a)
Bååth (1994b)
Harris & Paul (1994)
Tibbles & Harris (1996)
Bååth (1998)
Bååth (1998)
Uhlı́řová & Šantrùčková (2003)
Uhlı́řová & Šantrùčková (2003)
TdR, thymidine incorporation; Leu, leucine incorporation; slurry, incubation using a soil slurry; susp., incubation in a bacterial suspension extracted from
soil using homogenization/centrifugation; FDC, frequency of dividing cells; NA, not applicable.
Table 2. Estimated fungal turnover times in soil and on decomposing leaf litter in water using the Ac-in-erg incorporation method
Habitat
Growth conditions
Turnover time (days)
Incubation temperature ( 1C)
Reference
Water
Water
Water
Soil
Water
Soil
Soil
Water
Water
Leaf litter
Leaf litter
Leaf litter
Glucose-amended
Leaf litter
Unamended
Straw or alfalfa amended
Leaf litter
Wood
200
53–203
68
170
28–32
130–150
20–40
46–99
300–580
25
Field, 5–10
Field, 7–25
15
Field, 7–23
22
22
Field, 5–18
Field, 5–18
Newell & Fallon (1991)
Komı́nková et al. (2000)
Kuehn et al. (2000)
Bååth (2001)
Carter & Suberkropp (2004)
Rousk & Bååth (2007b)
Rousk & Bååth (2007b)
Gulis et al. (2008)
Gulis et al. (2008)
Field indicates the range of in situ temperatures during field measurements.
studies have suggested much longer turnover times using
TdR incorporation, with values varying between 107 and
160 days at 25 1C (Harris & Paul, 1994). As discussed by the
authors, differences in the methods used could be the reason
for this large discrepancy. Longer turnover times were also
found by Tibbles & Harris (1996) for soils from Antarctica.
However, these soil samples were incubated at 10 1C. The
incubation temperature will of course be of utmost importance in determining growth rates. Assuming a Q10 for
bacterial growth between 10 and 20 1C of 2.5 (Rinnan et al.,
2009), the estimates by Tibbles & Harris (1996) can be
recalculated to estimate growth rates at 20 1C. This recalculation results in estimates of 4.4–86 days at 20 1C, which
overlap with the range found in the other studies (Table 1).
Bacterial growth in the rhizosphere represents a special
situation. The rhizosphere will be a place of rapid proliferation of bacteria compared with the surrounding soil due to
the input of root exudates into the soil. This will result in an
initial increase in microbial biomass, making it possible to
estimate growth rates by repeated counting of bacterial cells.
This has resulted in estimates of bacterial turnover times of
12–19 h (Olsson et al., 1987), with doubling times of 24 h on
FEMS Microbiol Ecol 78 (2011) 17–30
young roots increasing to over 100 h on old roots (Barber &
Lynch, 1977), and sometimes with generation times as short
as 7.5–9.1 h (Bowen & Rovira, 1976). Although some early
attempts to use the TdR method to compare the growth
rates in the rhizosphere and in the bulk soil could not detect
differences (Christensen et al., 1992a; Christensen, 1993;
Christensen & Christensen, 1994), several studies have later
indicated that the bacterial growth rates in the rhizosphere
are higher than bulk soil, with the actual growth rates
similar to those estimated by repeated counting. Turnover
times of 9–60 h for 6-day-old roots were found by Bååth &
Johansson (1990) and around 2–3 days by Söderberg &
Bååth (1998), and the growth rate measured in rhizosphere
soil was consistently higher than that in bulk soil estimated
by both the TdR and the Leu incorporation techniques
(Christensen et al., 1995; Olsson et al., 1996a; Söderberg &
Bååth, 1998, 2004; Söderberg et al., 2002).
Fewer attempts have been made to determine fungal
growth rates in soil (Table 2), and all of these suggest longer
turnover times of the fungal community compared with the
bacterial community, with turnover times in the range of
tens of days to several hundred days (Table 2). Because
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measurements are scarce in soil, we have also included
estimates obtained from aquatic studies of fungi growing
on leaf litter in our comparison (Table 2). Although this will
be a situation of no moisture limitations and initially a
surplus of fresh substrate, turnover rates comparable to
those reported for soil fungi were found (Table 2). Thus, it
appears that the turnover times of soil fungi are up to one
order of magnitude greater than those of soil bacteria. This
pattern is consistent with assessments in aquatic systems,
with longer turnover times for the fungal compared with the
bacterial community (Buesing & Gessner, 2006).
There are several problems and uncertainties in the calculation of growth rates using the incorporation of radioactive
precursors. These include the extent of isotope dilution, the
extent of incorporation into nontarget macromolecules, and
the choice of conversion factors used to calculate the actual
production of biomass from the amount of TdR incorporated
into DNA and Leu incorporated into proteins for bacteria,
and Ac incorporated into ergosterol for fungi. The extent of
isotope dilution, that is, the extent to which the labeled
precursor added is diluted by exogenous substrate already
present in soil or de novo synthesized during incubation, can
be determined using the isotope dilution approach (see Bååth
(1998) for examples from soil), while the degree of nonspecific
labeling of other macromolecules can be estimated using a
combination of acid–base extraction steps (Riemann &
Söndergaard, 1984). Isotope dilution was more varied for
TdR than for Leu incorporation, but could be avoided by
adding large amounts of TdR (Bååth, 1998).
Obtaining appropriate conversion factors to use for
converting incorporation of TdR and Leu for soil bacteria
and Ac-in-erg for fungi to the actual production of biomass
is more uncertain. In aquatic habitats, conversion factors for
bacterial growth can be estimated by comparing different
methods used for estimating microbial growth. However, in
soil, no such comparisons for bacteria have been made,
although growth in an extracted bacterial suspension from
soil over 24 h suggested that a similar conversion factor
for TdR incorporation as commonly used in water,
2 1018 cells produced mol 1 TdR incorporated, is valid for
soil (Bååth, 1992). Conversion factors for Ac-in-erg to
fungal biomass C can been established in soil by comparing
the uptake of radiotracer to the increase in ergosterol
concentrations during periods of fungal biomass accumulation (Rousk & Bååth, 2007b). These conversion factors rely
on subsequent conversion from the estimated ergosterol
concentration to fungal biomass, which can only be determined easily in pure cultures grown under conditions rather
different from those in the natural soil habitat for fungi, and
it is likely that these conversion factors overestimate fungal
biomass (as discussed in Rousk & Bååth, 2007b).
Another uncertainty is to what extent a single conversion
factor can be used for soils under different environmental
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J. Rousk & E. Bååth
conditions, i.e. how does the conversion factor vary depending on the growth conditions of the microorganisms? In a
recent study of coastal bacterioplankton (Franco-Vidal &
Morán, 2011), the conversion factor for both Leu and TdR
incorporation varied by a factor of around 10 over the
course of the year, although the mean values were close to
the theoretical ones: 3.1 kg C mol 1 Leu incorporated and
2 1018 cells mol 1 TdR incorporated. This suggests that
although a rough estimate of growth rate can be obtained
using a common conversion factor, more data are needed,
not only on conversion factors for soil organism per se but
also on the extent of variation in different soils and under
different growth conditions. Furthermore, it may be necessary to establish specific conversion factors for each soil to
enable correct estimates of absolute growth.
No less important than the calculation of growth
and production of the microorganisms is actual biomass
determination. The biomass concentration is used in the
numerator of the calculation of turnover rates (biomass :
microbial production). Estimating bacterial and fungal
biomass in soil is not trivial, and different methods can yield
very different results. This was extensively discussed by
Rousk & Bååth (2007b) in connection with fungal growth
rate determinations.
To avoid the biomass problem, one can calculate the
actual biomass production from the incorporation data,
although the problems pertaining to the conversion factor
used will remain. Such estimates are scarce in soil, but using
TdR incorporation, bacterial production between 30 and
60 g C m 2 year 1 was estimated in a forest humus, which
can be compared with an estimated C input from plants of
200 g C m 2 year 1 (Bååth, 1990). Using Leu incorporation,
a bacterial production of 7–14 10 5 g C h 1 g 1 soil C at
room temperature was estimated in an agricultural soil
(Bååth, 1994a), which was comparable to soil respiration
rates. A lower fungal production rate of around
5–6 10 6 g C h 1 g 1 soil C was estimated for a garden soil
(Rousk & Bååth, 2007b).
Environmental effects on fungal and
bacterial growth in soil
Temperature
Temperature is one of the most important factors determining microbial growth in soil. Temperature relationships can
be determined rapidly by incubating soil slurries or bacterial
communities extracted from soil in a suspension at different
temperatures while measuring the growth rates (Dı́azRaviña et al., 1994; Tibbles & Harris, 1996; Bååth, 2001;
Pietikäinen et al., 2005; Bárcenas-Moreno et al., 2009;
Rinnan et al., 2009). Both fungal and bacterial growth had
an optimum (Topt) around 25–30 1C in temperate soils
FEMS Microbiol Ecol 78 (2011) 17–30
23
Growth of saprotrophic fungi and bacteria in soil
(Pietikäinen et al., 2005; Bárcenas-Moreno et al., 2009), with
the maximum temperature for growth (Tmax) usually being
around 10 1C higher (Rinnan et al., 2011). Below the
optimum temperature, both fungal and bacterial growth
follows a quadratic relationship (the square root or the
Ratkowsky equation; Dı́az-Raviña et al., 1994; Pietikäinen
et al., 2005), where the square root of microbial growth
decreases linearly with a lower temperature, with an estimated minimum temperature (Tmin) for growth often below
0 1C. The square root relationship implies that Q10 for
growth is not constant, but increases at a lower temperature.
Thus, Q10 between 0 and 10 1C was around 6, while between
10 and 20 1C it was 2.5 for bacteria from a temperate soil
(Rinnan et al., 2009). Thus, increasing the temperature from
0 to 20 1C would increase bacterial growth around 15 times.
The optimum temperature for growth usually is much
higher than the mean annual temperature. For instance, in
Antarctic soils, the Topt can be above 20 1C (Rinnan et al.,
2009). At first glance, it may seem counter-intuitive that the
temperature for the optimum growth rate for most of the
year will be at a temperature far above the in situ temperature. However, it is the highest temperature during the year
that is probably the most important in determining Topt. If
the temperature is higher than Topt, even for a short period,
this will result in the death of the community, being replaced
with one having a higher Topt (Bárcenas-Moreno et al.,
2009). This process, death of strains that cannot tolerate
high temperatures and growth of more high-temperatureadapted strains, is rapid and will rapidly alter the microbial
community’s temperature relations. When the temperature
decreases, this will not kill the new community, because low
temperatures only slow growth. The recovery of the initial
community with lower Topt will consequently be a slow
process, especially at very low temperatures when the
growth and turnover of the soil community, even of better
adapted strains, is very slow (Ranneklev & Bååth, 2001).
That Tmin for bacterial growth, around 4 to 8 1C in
temperate soils, is substantially below 0 1C may seem
unrealistic, because there should be no growth in frozen soil
where there will not be any free water. Thus, Tmin is often
stated as an apparent minimum temperature for growth.
However, for normal soil bacteria, with a Topt around
25–30 1C in a pure culture, estimates of Tmin are also lower
than 0 1C (Rosso et al., 1993). Thus, the growth of bacteria
in soil will be possible even below 0 1C if free water is
present. Indeed, microbial biomass synthesis in soil at
4 1C was demonstrated recently (Harrysson Drotz et al.,
2010).
Pietikäinen et al. (2005) reported that fungal growth was
less negatively affected by low temperatures compared with
bacteria, as indicated by a lower Tmin for fungal growth than
for bacteria. However, subsequent studies (Bárcenas-Moreno et al., 2009) did not find this difference. A more
FEMS Microbiol Ecol 78 (2011) 17–30
systematic comparison between the temperature sensitivities
of fungal and bacterial growth still remains before general
conclusions can be established.
Soil moisture and drying/rewetting
Moisture is also a very important regulating factor for
microbial activity in soil. The influence of soil moisture on
the overall microbial activity in soil, as indicated by C
mineralization, is well understood. In accordance with C
mineralization, bacterial growth also increases with a higher
moisture content of the soil (Iovieno & Bååth, 2008), a
relationship that has also been corroborated for bacterial
communities in drying Mediterranean river beds (Amalfitano et al., 2008). The relationship between fungal growth and
soil moisture has not been studied directly, although it is
reasonable to expect that low moisture inhibits and higher
moisture is also conducive for fungal growth in soil. To what
extent soil moisture affects the balance of fungal and
bacterial growth remains to be investigated systematically.
A special situation with regard to moisture is the sudden
increase in the water content during a rewetting event.
Although the effects of these perturbations on microbial
biomass, biomass composition, and fluxes of nutrients and
greenhouse gases have been rather extensively studied (see
discussion in Bapiri et al., 2010), the effects on direct
measurements of microbial growth are more scarce. Following the addition of water to a dry soil, there is an abrupt
(o 1 h) increase in respiration to a rate that considerably
supersedes the basal respiration rate of the moist soil. The
pulse quickly passes and the respiration rate asymptotically
converges with that of a continually moist soil within days.
Bacterial growth does not follow this pattern (Iovieno &
Bååth, 2008). Instead, the bacterial growth rate initially is
very low, but an immediate and steady increase results in a
recovery of bacterial growth that converges with that of the
moist control soil after around 10 h. This indicates that the
bacterial growth response cannot be inferred from respiration measurements. Furthermore, the bacterial response is
very different from that after adding a substrate like glucose.
A glucose addition initially does not alter the growth rate,
but after a lag phase, results in an exponential increase in the
growth rate. Thus, although altering the nutrient conditions
during incubation with a radioactive precursor in a slurry or
a bacterial suspension does not appear to alter the initial
growth rate for several hours, precaution should be exercised when working with soil that is much drier than the
optimum moisture conditions. In such situations, the
duration of the incubation times should be minimized to
avoid the potentially confounding influence of the altered
growth conditions used in the method. For example, Iovieno & Bååth (2008) used 15 min as their shortest incubation
time.
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c
24
Bapiri et al. (2010) compared bacterial and fungal growth
responses, using Leu and Ac-in-erg incorporation, following
repeated drying/rewetting events of soil in a microcosm
system. Drying–rewetting decreased bacterial growth while
fungal growth remained unaffected, resulting in an elevated
fungal : bacterial growth ratio. This effect was found irrespective of the initial fungal : bacterial biomass ratio (three
soils of various fungal : bacterial ratios were investigated).
Many drying–rewetting cycles did not, however, affect the
fungal : bacterial growth ratio compared with a few cycles. In
contrast, Williams (2007) found that microbial growth,
determined as 13C-glucose incorporation into phospholipid
fatty acid (PLFA) markers, was unaffected by the drying–rewetting treatment, suggesting no difference between the
fungal and the bacterial growth responses. Williams (2007)
measured microbial growth 0–6 and 0–24 h following rewetting (with identical results), while Bapiri et al. (2010)
measured the microbial growth responses 3 days after
rewetting. It remains to be seen whether the discrepancy
between the results from Bapiri et al. (2010) and Williams
(2007) was due to the different techniques used or due to the
differences in the timing of measurements after rewetting.
J. Rousk & E. Bååth
tury-old continuous soil pH gradient: Hoosfield acid strip,
Rothamsted Research, UK (Rousk et al., 2009b). This
experiment provides a uniform pH gradient, ranging from
pH 8.3 to 4.0, within 180 m in a silty-loam soil on which
barley has been continuously grown for more than 100
years. Growth-based measurements revealed a fivefold
decrease in bacterial growth, and a fivefold increase in fungal
growth, with a lower pH. This resulted in a c. 30-fold
increase in the fungal : bacterial growth ratio, from pH 8.3
to pH 4.5. The different relationships with soil pH for fungi
and bacteria in this soil, when variations in other factors
were minimized, have since been verified (Rousk et al.,
2010). Using soils from the 150-year-old Park Grass experimental grassland experiment at Rothamsted Research,
Rousk et al. (2011) also found that bacterial growth
decreased with lower pH, while fungal growth increased,
resulting in a 50-fold increase in the fungal : bacterial growth
ratio between pH 7.5 and 3.3. A similar pattern was also
found in a set of Iberian Vineyard soils, varying between pH
4 and 7 (D. Fernández-Calviño & E. Bååth, unpublished
data). We conclude that 30–50-fold increases in the fungal : bacterial growth ratio can be expected between soils of
neutral pH and soils of pH 4–5.
Soil pH
An association between fungal dominance in acid soils, and
bacterial dominance in neutral or slightly alkaline soils, is
well known (Brady & Weil, 2008). However, clear evidence
for the differential growth of fungi and bacteria in soils with
different pH has been lacking until recently. Bååth &
Arnebrant (1995) studied the effects of lime- and ashtreated forest soils on bacterial growth. The treatments
resulted in a range of pH values from about pH 4 to 7,
which resulted in an approximately fivefold increase in the
bacterial growth rate, as measured by TdR incorporation.
Higher TdR incorporation in ash-treated soils was also
found by Fritze et al. (2000) and Perkiömöki & Fritze
(2002). Similarly, in a study including 19 different soils
under various land uses, spanning pH 4–8, there was a
positive correlation between bacterial growth and higher pH
as measured with Leu incorporation (Bååth, 1998). Bacterial
growth increased fourfold between pH 4 and 8. The influence of soil pH on both fungal and bacterial growth in soils
with a more restricted pH range (pH 3.6–4.1) in forest
humus (Pennanen et al., 1998) and the acute effects of
artificially increasing pH using 13C-Ac incorporation into
PLFAs (Arao, 1999) have also been determined. Both studies
found increased bacterial and lower fungal growth at higher
pH, and vice versa. However, in all these cases, other factors
also covaried with pH, possibly confounding the pH effect,
making causality difficult to assign.
A study where the confounding influences by factors
other than pH were minimized was conducted on a cen2011 Federation of European Microbiological Societies
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Substrate effects
It is commonly thought that fungi are more important for
the degradation of complex substrates such as wood, composed mainly of macromolecules like cellulose and lignin,
while bacteria are considered more competitive in degrading
easily available substrates. Specialized fungal groups, such as
white- and brown-rot fungi, are mainly involved in the
former. A study on the bacterial and fungal growth
responses to pure substrate additions corroborated this.
Meidute et al. (2008) found that bacterial growth responded
relatively more than fungal growth following the addition of
simple C compounds (glucose and gelatin), while there was
a relatively higher fungal response following the addition of
a more complex C substrate (cellulose) to soil.
More complex substrates from plant material have also
been shown to have a differential effect on fungal and
bacterial growth. Adding alfalfa (C/N = 15) or straw (C/
N = 75) to soil in a time-series laboratory microcosm
experiment resulted in the alfalfa addition increasing bacterial growth more than fungal growth, and the reverse was
observed following straw amendment (Rousk & Bååth,
2007a). A possible explanation could be that bacteria
benefitted from conditions of higher N availability compared with fungi and that the results were simply due to the
stoichiometric difference in the C : N ratio between the plant
materials. This was, however, not the case. When mineral N
was added to compensate for the difference between the
C : N ratios, the same differences in growth responses from
FEMS Microbiol Ecol 78 (2011) 17–30
25
Growth of saprotrophic fungi and bacteria in soil
the two plant material were still obtained. Moreover, bacterial
growth was unaffected by extra mineral N addition, while
fungal growth increased between days 4 and 7 when mineral
N was added to the straw. This suggests that the difference
between the plant materials was derived from the quality of
the C compounds, rather than the elemental composition.
Similar results were found by Meidute et al. (2008), where
adding extra N enhanced fungal growth on cellulose even
more, while adding N with glucose resulted in increased
bacterial growth.
It is not only the quality and type of substrate that affects
the balance of bacterial and fungal growth in soil. The
concentration of substrate is also of importance. Griffiths
et al. (1999) added different concentrations of a mixture of
easily available carbon substrate (sugars, amino acids, organic acids) and found increasing fungal compared with
bacterial growth with increasing loading rates of substrate
(measured as increase in PLFAs indicative of the two
groups). This was also found with the addition of different
concentrations of glucose (S. Reischke, J. Rousk, & E. Bååth,
unpublished data) using Leu and Ac-in-erg incorporation.
At low concentrations (o 1 mg glucose-C), only bacterial
growth increased significantly, while at high concentrations
(4 4 mg glucose-C), increased fungal growth was also
detected. At very high concentrations (4 16 mg glucose-C),
bacterial growth was inhibited, while fungi proliferated
extensively.
Plant effects
The increased substrate flow in the rhizosphere due to root
exudation has been shown to increase bacterial growth rates
significantly (see references above). However, it has also
been shown that there is a plant species effect on bacterial
growth in the rhizosphere (Söderberg et al., 2002), presumably due to different exudation rates. Even different genotypes of the same plant can result in different bacterial
growth rates (Velasco et al., 2009; Aira et al., 2010).
The biotic component in the rhizosphere can also be of
importance, both directly affecting bacterial growth, but
also via its effect on plant growth. In a series of studies on
the effect of adding different species of plant growthpromoting rhizobacteria (PGPR), the growth rate of the
total bacterial community in the rhizosphere was altered
depending on which PGPR was added to the rhizosphere
(Medina et al., 2003; Garcı́a et al., 2004), although the effect
was not always seen (Rincón et al., 2006). The presence of
mycorrhizae is also of importance. Although the presence of
arbuscular mycorrhizae appeared to have little influence on
bacterial growth compared with the rhizosphere effect
(Olsson et al., 1996a; Söderberg et al., 2002), the presence
of ectomycorrhizal mycelium has been shown both to
decrease (Olsson et al., 1996b; Olsson & Wallander, 1998;
FEMS Microbiol Ecol 78 (2011) 17–30
Wallander, 2002) and to increase (Olsson & Wallander, 1998;
Wallander, 2002) bacterial growth.
Toxicity effects
Both TdR/Leu incorporation and Ac-in-erg incorporation
have been used to study toxic effects on bacterial and fungal
growth in soil. The former especially has provided a sensitive
method to detect the toxic effects of for example heavy
metals (Dı́az-Raviña & Bååth, 1996; Rajapaksha et al., 2004;
Nolsø Aaen et al., 2011), phenols (Aldén Demoling & Bååth,
2008), antibiotics (Rousk et al., 2008), and salt (Bååth et al.,
2001). It is worth noting that Leu incorporation could be
used to detect direct effects even using bacteriostatic antibiotics, including sulfa compounds (Aldén Demoling et al.,
2009; Brandt et al., 2009), which was only achievable using
biomass-based methods after an initial triggering of increased growth by adding a substrate (Thiele-Bruhn & Beck,
2005). Less work has been carried out on fungal growth,
although it has been observed that antifungal antibiotics
(e.g. cycloheximide) affect Ac-in-erg incorporation negatively (J. Lind Birgander, E. Bååth, & J. Rousk, unpublished
data).
Interaction between bacteria and fungi
Measurement of growth rates is ideal for studying the
interactions between fungi and bacteria not only because
the methods are sensitive to subtle changes but also because
it is equally easy to rapidly detect both increases and
decreases in growth rates, which is not the case when using
biomass measurements to infer interactions. There have
been indications of a pronounced interaction between fungi
and bacteria from soil systems. For instance, studies by
Thiele-Bruhn & Beck (2005) and Feeney et al. (2006)
obtained results suggesting bacterial inhibition of fungal
growth (without reciprocity), while Meidute et al. (2008)
found indications of synergistic interactions, where the
initial fungal degradation of cellulose seemed to promote
bacterial growth. Observations from studies of fungal and
bacterial biomass production during the decomposition of
litter in soil and water also indicated pronounced interactions between fungi and bacteria, including reports of
reciprocal negative interactions (Mille-Lindblom & Tranvik,
2003), antagonistic interactions (Møller et al., 1999; MilleLindblom et al., 2006), and synergistic interactions (Bengtsson, 1992; Romani et al., 2006).
Using an approach different from the addition-type
experiments previously conducted on litter (above), Rousk
et al. (2008) utilized a removal-type experiment to investigate the interaction between bacteria and fungi. Using a
range of soils with various fungal : bacterial growth ratios,
the application of three different bacterial inhibitors resulted
in bacterial growth being reduced to virtually zero. In
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26
response to the bacterial growth inhibition, fungal growth
increased. Consequently, the study demonstrated that bacteria exerted an important competitive pressure on fungi,
and that competition was alleviated when the influence by
bacteria was terminated. Negative interactions between
fungal and bacterial growth responses have been suggested
repeatedly, for instance in response to substrate (Rousk &
Bååth, 2007a), heavy metal (Rajapaksha et al., 2004) and salt
addition (Tobor-Kapłon et al., 2005), and following landuse change (Lopez-Sangil et al., 2011) or during the recolonization after a fire event (Bárcenas-Moreno et al., 2011).
One of the clearest examples of a reproducible and very
pronounced negative correlation between bacterial and
fungal growth is along pH gradients (Rousk et al., 2009b),
suggesting that the interaction between the groups could be
influential in shaping pH relationships of the decomposer
groups. The interaction between fungi and bacteria was
further studied in an arable soil pH gradient (Rousk et al.,
2010). In the absence of a bacterial inhibitor, the pH
relationships for bacterial and fungal growth corroborated
those documented previously (Rousk et al., 2009b). When a
bacterial inhibitor was added, the bacterial growth was
suppressed across the entire pH gradient, and the strong pH
dependence of fungal growth, starting low at a high pH and
increasing toward a lower pH, was offset; fungal production
was high across the entire pH gradient. This result indicated
that the pH dependence of fungal growth was, at least partly,
mediated by competitive interaction with bacteria.
Concluding remarks
In the light of modern molecular method, which presently
allows us to investigate the vast microbial diversity in soil at
a high resolution, the use of methods that integrate measurements across large groups like bacteria and fungi might
be considered obsolete. The use of stable isotope probing
both in connection with PLFA (Boschker & Middelburg,
2002; Bengtson et al., 2009) and DNA (Dumont & Murrell,
2005; Buckley et al., 2007) may also be an alternative way of
estimating microbial growth rates in soil, at a higher
taxonomic resolution. However, the ease, accuracy, and
speed with which bacterial and fungal growth can be
estimated using the incorporation of radiolabeled tracers
means that they will continue to be invaluable in soil
ecological studies, both as a reference to compare with other
methods and as a way of comparing environmental effects
on these broadly defined important decomposer groups.
Keeping in mind that bacteria and fungi drive different food
webs in soil, differentiating between the growth of these two
groups will also be important for understanding the ecosystems in which they exist. Last, but not least, the use of the
same methods in both soil and aquatic habitats enables
proper cross-ecosystem comparisons.
2011 Federation of European Microbiological Societies
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c
J. Rousk & E. Bååth
There are still several points of uncertainty in using TdR
and Leu incorporation and Ac-in-erg incorporation to
estimate bacterial and fungal growth in soil, respectively,
that need to be addressed in the future. Several of these have
been touched upon in this review. For example, conversion
factors to calculate bacterial and fungal growth from incorporation data need to be better constrained. This will not
only enable the estimation of actual production of bacteria
and fungi in soil – which will ultimately be transferred into
higher trophic levels – but, together with data on substrate
loss or respiration, will allow us to determine the growth
efficiencies of soil microorganisms. We also need to develop
methods allowing for a higher resolution in time (shorter
incubation periods) and space (allowing for measurements
on milligrams of soil). The taxonomic resolution of the
tracer incorporation methods should also be increased in
the future. We need, for example, to be able to differentiate
between the growth of saprotrophic and mycorrhizal fungi
in soil. However, there are possibilities for even higher
taxonomic resolution, for example by combining immunomagnetic separation of specific bacteria with the Leu incorporation method (Sengeløv et al., 2000). Finally, the
growth rates of archaea in soil still remain to be determined
and related to those of bacteria and fungi. It was shown that
both archaea and bacteria incorporate Leu in sea water
(Herndl et al., 2005). The combination of Leu incorporation
with specific bacterial inhibitors has also suggested that the
contribution by archaea to the overall heterotrophic activity
was low in marine systems (Ionescu et al., 2009). Similar
studies in soil are, however, lacking.
Acknowledgements
This review was written with financial aid from the Swedish
Research Council to E.B. (Project No. 2009-4503) and J.R.
(Project No. 623-2009-7343).
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