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Applied and Environmental Microbiology, August 1999, p. 3690-3696, Vol. 65, No. 8
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Microscale Distribution of Populations and Activities of
Nitrosospira and Nitrospira spp. along a
Macroscale Gradient in a Nitrifying Bioreactor: Quantification by In
Situ Hybridization and the Use of Microsensors
Andreas
Schramm,1,*
Dirk
de Beer,1
Johan C.
van den Heuvel,2
Simon
Ottengraf,2 and
Rudolf
Amann1
Max Planck Institute for Marine Microbiology,
D-28359 Bremen, Germany,1 and Department
of Chemical Engineering, University of Amsterdam, NL-1018WV Amsterdam,
The Netherlands2
Received 29 January 1999/Accepted 24 May 1999
 |
ABSTRACT |
The change of activity and abundance of Nitrosospira
and Nitrospira spp. along a bulk water gradient in a
nitrifying fluidized bed reactor was analyzed by a combination of
microsensor measurements and fluorescence in situ hybridization.
Nitrifying bacteria were immobilized in bacterial aggregates that
remained in fixed positions within the reactor column due to the flow
regimen. Nitrification occurred in a narrow zone of 100 to 150 µm on
the surface of these aggregates, the same layer that contained an
extremely dense community of nitrifying bacteria. The central part of
the aggregates was inactive, and significantly fewer nitrifiers were
found there. Under conditions prevailing in the reactor, i.e., when
ammonium was limiting, ammonium was completely oxidized to nitrate
within the active layer of the aggregates, the rates decreasing with increasing reactor height. To analyze the nitrification potential, profiles were also recorded in aggregates subjected to a short-term incubation under elevated substrate concentrations. This led to a shift
in activity from ammonium to nitrite oxidation along the reactor and
correlated well with the distribution of the nitrifying population.
Along the whole reactor, the numbers of ammonia-oxidizing bacteria
decreased, while the numbers of nitrite-oxidizing bacteria increased.
Finally, volumetric reaction rates were calculated from microprofiles
and related to cell numbers of nitrifying bacteria in the active shell.
Therefore, it was possible for the first time to estimate the
cell-specific activity of Nitrosospira spp. and
hitherto-uncultured Nitrospira-like bacteria in situ.
| |
INTRODUCTION |
Immobilized microorganisms are used
for the purification of a variety of wastewaters in fixed-film
treatment plants with systems such as trickling filters, rotating
biological contactors, or fluidized beds (7). In all these
systems, the organisms responsible for treatment are present in a
microbial biofilm. Unlike in well-mixed activated sludge basins,
sequential transformation of the sewage compounds may occur while the
wastewater passes through the filter, and pronounced gradients of,
e.g., oxygen, dissolved organic carbon, or ammonium can be measured in
the bulk water along such a reactor (7). In comparison,
changes of the underlying microbial communities and activities within
the biofilm are more difficult to assess. However, these data are
needed for the improvement of mathematical models used to design and
dimension fixed-filter reactors.
Fluorescence in situ hybridization (FISH) with rRNA-targeted
oligonucleotide probes is a reliable tool for the direct identification and quantification of bacteria in their natural environment (1, 3). Microsensors have been developed for various compounds for
the determination of substrate and product gradients and activities on
a micrometer scale (22, 30). The combination of both methods (2) has been shown to have great potential for direct
observations of structure and function of sulfate-reducing
(28) and nitrifying biofilms (32, 34). In this
study, a lab-scale fluidized bed reactor (12) was used as a
model system for the in situ analysis of structure and function of a
whole biofilm reactor. The nitrifying community of this reactor was
recently identified as Nitrosospira and
Nitrospira spp. by the rRNA approach (32). Here,
we present data on the changes of abundance and activity of these
nitrifying populations with the bulk water gradient along the reactor.
In a more ecological context, this can be regarded as an example of how
environmental parameters structure microbial communities.
In an additional experiment, the microsensor measurements were repeated
under an excess of substrate (ammonium or nitrite) to test the
nitrification potential of the system and to evaluate the maximum
specific activities of its components. This again is important for
process engineers to model the system and also to estimate the
competitiveness of yet-uncultured species, such as
Nitrospira spp., in the environment.
(A preliminary account of part of this work appeared in the Proceedings
of the 2nd International Conference on Microorganisms in Activated
Sludge and Biofilms, International Association on Water Quality,
Berkeley, Calif., 1997.)
| |
MATERIALS AND METHODS |
Reactor operation.
The conical 360-ml continuous-upflow
reactor used as a model system has been described in detail by de Beer
et al. (12). For this study, the reactor was fed with
mineral medium containing 72 µM NH4+
(influent concentration), and the liquid phase was recirculated at a
rate of 1.8 ml s
1 (32). The temperature was
kept at 30°C. The chemical gradients that developed along the reactor
are displayed in Table 1. The conical
shape of the vertical reactor column creates a flow velocity gradient
that stabilizes aggregates of different diameter and density at
different heights in the column according to their settling velocity.
Aggregate samples were taken from three different points of the
reactor, labeled A1 through A3 (Table 1).
Microsensor measurements.
Clark-type O2
microsensors (29) and liquid ion-exchanging membrane (LIX)
microsensors for NH4+,
NO2, and NO3
(11) were prepared and calibrated as described previously. Tip diameters were <10 µm for O2, 5 µm for
NH4+ and NO3, and 15 µm for NO2 microsensors.
Aggregates were placed in a flow cell and perfused with medium, and
microprofiles were recorded at steps of 25 µm from the
bulk liquid
into the aggregate as described by de Beer et al.
(
12) and
Schramm et al. (
32). Measurements were performed
under in
situ conditions, i.e., when [O
2],
[NH
4+], [NO
2],
and pH in the medium were adjusted to the values at the respective
sampling points (referred to as in situ conditions [Table
1])
and in
air-saturated mineral medium containing 300 µM
NH
4+ (referred to as incubation conditions).
Profiles of aggregate
samples from point A3 were also recorded in
air-saturated mineral
medium containing 300 µM
NO
2 (labeled A3
nitrite).
[NO
3] was always 100 µM.
Chemical analysis.
[NH4+],
[NO2], and
[NO3] in the reactor bulk liquid were
determined colorimetrically (Spectroquant; Merck). [O2]
and pH were measured by an O2 microsensor and a pH
electrode (Radiometer, Copenhagen, Denmark) which were lowered in the
reactor down to the sampling points.
Calculations.
Oxygen uptake and the rates of ammonium and
nitrite oxidation were determined from the O2,
NH4+, and NO3
profiles as the fluxes, J, through the diffusive boundary
layer (DBL). Net fluxes for O2,
NH4+, NO2, and
NO3 were calculated by using Fick's first
law as follows:
|
(1)
|
where
DW is the molecular diffusion
coefficient in water,
C
is the bulk liquid
phase concentration,
C0 is the concentration
at
the aggregate surface, and
eff is the
effective DBL
thickness. The latter is defined by extrapolating the
concentration
gradient at the aggregate-water interface to the bulk
water phase
concentration. Determination of the exact thickness of
eff was done by a simple diffusion reaction
model as described in
detail by Ploug et al. (
26). Diffusion
coefficients of O
2, NH
4+,
NO
2, and NO
3 at
30°C were taken as 2.75 · 10
5, 2.25 · 10
5, 2.17 · 10
5, and 2.16 · 10
5 cm
2 s
1, respectively
(
8,
23).
Volumetric conversion rates were calculated from the volume of the
active shell and the net fluxes into whole aggregates as
follows:
|
(2)
|
where 4
r2 and
4/3
r3 are the surface and the volume of the
aggregate, respectively,
ra is the thickness of
the active shell
as determined by microsensor measurements, and
4/3
(
r 
ra)
3 is the volume
of the inactive central part of the
aggregate.
Oligonucleotide probes.
Previously described oligonucleotide
probes specific for certain ammonia-oxidizing (25) and
nitrite-oxidizing (32) bacteria were used. Their sequences
and target sites are presented in Table 2. Probes were synthesized and
fluorescently labeled with the hydrophilic sulfoindocyanine dyes CY3 or
CY5 at the 5' end by Interactiva Biotechnologie GmbH (Ulm, Germany).
Sample preparation and in situ hybridization.
Aggregates
were fixed in paraformaldehyde and cut on a cryomicrotome, and the
individual cross-sections (thickness, 14 µm) were immobilized on
microscopic slides. This whole procedure has been described in detail
by Schramm et al. (32). In situ hybridization of fixed and
dehydrated aggregate sections was carried out at 46°C in an
isotonically equilibrated humidity chamber according to the protocol of
Amann et al. (4). Stringent hybridization conditions for the
different oligonucleotide probes were adjusted by using the formamide
and sodium chloride concentrations listed in Table 2 in the
hybridization and washing buffers, respectively (24). Double
hybridizations with two probes that require different stringencies
(e.g., NSR826 plus NSR1156) were done as subsequent hybridizations,
starting with the probe of higher thermal stability.
Confocal microscopy and image analysis.
Digital images of
aggregates after hybridization were taken by confocal laser scanning
microscopy (CLSM) on a model LSM510 (Carl Zeiss, Jena, Germany)
equipped with two HeNe lasers (543 and 633 nm). We applied optical
sections 1.5 and 0.7 µm thick for Nitrosospira and
Nitrospira spp., respectively. As these are approximately
the mean cell diameters of the two populations, the optical sections
were assumed to contain single-cell layers. For each probe, cell
numbers per unit of volume were derived from randomly chosen optical
sections by using the area function of the standard software delivered
with the instrument. A threshold value was set manually to exclude
empty spaces and background fluorescence from the record, and the
remaining cell area was quantified relative to the total aggregate
area. Threshold levels were calibrated separately for each probe and
sample by determining mean values for the area of at least 300 single
cells, counting cells within a defined area, and adjusting the
threshold value to match the calculated total cell area. The same
calibrations were used to calculate cell numbers from the cell area
values. On the assumption that there was only one layer of cells in an optical section, these numbers were regarded as cell numbers per unit
of volume, where the volume was the total measured area multiplied by
the thickness of the optical section. Nitrifying bacteria in the active
shell were enumerated separately from those in the central part of the aggregates.
Statistical evaluation.
Cell numbers of ammonia- and
nitrite-oxidizing bacteria in the active shell as well as fluxes of
oxygen, ammonium, and nitrate were subjected to statistical analysis
with the software package STATISTICA 4.5 (Stat-Soft Inc., Tulsa,
Okla.). Data were tested for even distribution by applying
Shapiro-Wilk's W test. Because this test showed uneven distribution of
all data, nonparametric statistics were used for further evaluation. We
tested for differences in mean values of cell numbers and fluxes from
all three samples (A1, A2, and A3) by applying a Kruskal-Wallis
analysis of variance. Finally, the data were tested for differences in
mean values between individual groups (A1 and A2, A1 and A3, and A2 and
A3) by using the Kolmogorov-Smirnov test and the Mann-Whitney U test.
| |
RESULTS |
Microgradients.
For practical reasons, three to seven profiles
(Table 3) of O2,
NH4+, NO2, and
NO3 were measured, each in a separate
aggregate, under in situ conditions and incubation conditions for all
three sampling sites. Examples of these profiles are shown in Fig.
1. The effective DBL ranged from 70 to
225 µm, depending on aggregate size, surface structure, and solute
type (data not shown). Oxygen consumption and ammonium and nitrite
oxidation were always restricted to a shell consisting of the outer 75 to 200 µm of the aggregate, while the central part of the aggregates
appeared to be inactive. The mean thickness of the nitrifying zone as
defined by ammonium, nitrite, and nitrate profiles decreased with
increasing distance of the aggregate sampling site from the inlet, from
about 150 µm (sample A1) to 125 µm (A2), to 100 µm (A3).
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FIG. 1.
Microprofiles of oxygen ( ), ammonium ( ), nitrite
( ), and nitrate ( ) in nitrifying aggregates from different
sampling points in the fluidized bed reactor near inlet A1 (a, b),
middle A2 (c, d), and near outlet A3 (e to g). (a, c, e) Measurements
under in situ conditions (Table 1); (b, d, f) profiles in 300 µM
ammonium (pH 8.0) at air saturation; (g) profiles in 300 µM nitrite
(pH 8.0) at air saturation.
|
|
Under in situ conditions, oxygen was only partially consumed within the
nitrifying zone. In contrast, ammonium and nitrite
present in the bulk
water phase were almost completely converted
to nitrate within the
aggregate, since less than 10 µM ammonium
was found in the central
part of A1 and A2 aggregates (Fig.
1a,
c, and
e).
Because nitrification was obviously substrate limited under reactor
conditions, we also measured microprofiles while aggregates
were
incubated in 300 µM ammonium, sufficient to saturate ammonia
oxidation, under air saturation to obtain some information about
the
nitrification potential (Fig.
1b, d, and f). In A1 and A2
aggregates,
oxygen was now depleted within the nitrifying zone,
while ammonium was
consumed to concentrations down to 100 to 150
µM within the
aggregate. Nitrite accumulated to significant concentrations
(~100
µM) in A1 aggregates but only to negligible levels in A2.
Almost no
change in the concentration of oxygen, ammonium, or
nitrate was
detected in A3 aggregates, showing very low ammonium
oxidation
potential. Therefore, a third set of microprofiles was
measured in
these aggregates, supplying 300 µM nitrite under air
saturation (Fig.
1g). Oxygen and nitrite were consumed but not
depleted within the
active shell, resulting in the enhanced production
of
nitrate.
Rate calculations.
Net fluxes of oxygen, ammonium, nitrite,
and nitrate through the aggregate-bulk liquid interface were calculated
from the microprofiles and are summarized in Table 3. In general, the fluxes measured under incubation conditions exceeded the in situ fluxes. The fluxes of oxygen and ammonium and those of nitrate under in
situ conditions were significantly higher for samples A1 than for
samples A3 (P < 0.001). In contrast, no significant difference of fluxes was found between samples A1 and A2 or between all
nitrate fluxes under incubation conditions. The ratio of the fluxes for
NH4+-O2-NO3
was close to 1:2:1 for all samples when all species were present. When
ammonium was absent (i.e., in samples A3in situ and
A3nitrite), the ratios of the fluxes of
NO2-O2-NO3
were 1:1.9:2.7 and 1:0.7:0.92, respectively.
Volumetric conversion rates of oxygen and ammonium were calculated from
the net fluxes into the active layer of the aggregates,
whereas the
rates of nitrite oxidation were calculated from the
net fluxes out of
this active layer (Table
4). Again, the
rates
were higher under incubation conditions than in situ, and no
significant
difference was found in conversion rates between A1 and A2
aggregates.
However, volumetric rates were significantly higher in
samples
A1 than in samples A3 (
P < 0.002), with one
exception; nitrite
oxidation was higher in A3
nitrite than
in A1 under incubation
conditions, indicating high nitrite oxidation
potential at the
top of the reactor.
In situ detection, quantification, and specific reaction rates of
nitrifying bacteria.
The principal composition of the nitrifying
community of the reactor had been resolved previously as
Nitrosospira and Nitrospira spp. by the rRNA
approach (32). Here, the stratification of these populations
within the aggregates as well as along the reactor column is reported
(Table 5 and Fig.
2). The relative close
match of cell numbers for probes NSO1225 and NSV443, targeting all
ammonia-oxidizing 
-Proteobacteria and all known members
of the genus Nitrosospira, respectively, confirmed our
observation that Nitrosospira spp. represent the vast
majority, if not all, of the ammonia-oxidizing bacteria in the system.
The numbers of ammonia oxidizers were significantly higher at the
bottom (A1 [Fig. 2a]) than at the top (A3 [Fig. 2c]) of the reactor
(P < 0.001), whereas no significant difference was
evident between A1 and A2 or between A2 and A3. Many fewer cells were
detected in the center of all aggregates than in the outer shell.
Moreover, ammonia oxidizers formed substantially larger cell clusters
in the nitrifying zone than in the inner part of the aggregate (Fig.
2). Concerning the stratification within a single aggregate, the same
observation is also true for nitrite-oxidizing bacteria of the genus
Nitrospira as detected by a combination of probes NSR826 and
NSR1156. The combination of these probes targets all known
Nitrospira-like sequences from freshwater habitats. In
contrast, the cell volume of Nitrospira spp. was
significantly higher at the top of the reactor than at the bottom
(P > 0.0001) and equaled in aggregate A2 the cell
volume of Nitrospira spp. (cf. Fig. 2). However, due to
their much smaller cell size, numbers of nitrite-oxidizing bacteria
exceeded those of ammonia-oxidizing bacteria by more than 1 order of
magnitude. Interestingly, a distinct, less-abundant population of
Nitrospira spp., as detected by probe NSR447, was restricted
almost exclusively to the active shell of the aggregates.
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FIG. 2.
CLSM images of part of aggregate cross-sections
after FISH with CY5-labelled probe NSV443, specific for
Nitrosospira spp. (in red), and with CY3-labelled probes
NSR826 plus NSR1156, specific for Nitrospira spp. (in
yellow). For each picture, two confocal images and the respective
phase-contrast image were combined. Aggregates from A1 (a), A2 (b), and
A3 (c) are shown. The aggregate surface is indicated by arrows.
Bar = 100 µm.
|
|
Cell numbers were used to calculate specific oxidation rates of
ammonium and nitrite per cell from the volumetric ammonium
and nitrite
oxidation rates (Table
6). Generally, the
specific
reaction rates of
Nitrosospira spp. were 1 order of
magnitude
higher than those of
Nitrospira spp., and rates
were higher under
incubation conditions than in situ. However, no
significant change
in the specific rates per cell was observed along
the reactor
column. The only exception was the ammonium oxidation rate
of
Nitrosospira spp. for aggregate A3, which was
considerably lower
than the rates for aggregates A1 and A2 when
incubated with 300
µM ammonium.
| |
DISCUSSION |
Accuracy of the calculations.
The nitrifying aggregates
investigated in this study were rather heterogeneous regarding their
irregular surface structures and the patchy distribution of nitrifying
bacteria within the active shell (Fig. 2). Consequently, the measured
profiles showed some variability, and the standard deviations of both
calculated conversion rates and FISH quantification were rather high.
The ratio of the fluxes for
NH4+-O2-NO3,
however, was close to the expected stoichiometric ratio of 1:2:1, thus
lending support to the mean values obtained. In contrast, the flux
ratio in sample A3 (in situ conditions) clearly indicates that not
enough profiles have been measured to reliably calculate average fluxes
of nitrite and/or nitrate. A small source of uncertainty, again due to
the irregular shape of the aggregates, was the determination of the
radius required to calculate volumetric conversion rates. However, the
error introduced by a deviation of ±100 µm amounted to only about
2% and therefore can be disregarded.
For the FISH-based quantification of nitrifying populations, the
threshold set point for the area measurement was critical.
Thus,
special effort was taken in its calibration, and occasionally
the
results from image analysis were compared with conventional
counts of
hybridized cells in defined areas of an optical slice.
Since the
results from both procedures never differed more than
10%, we
concluded that enumeration of nitrifying bacteria by our
image analysis
procedure was accurate enough for our purposes.
However, this was
possible only because of the morphological homogeneity
of the
respective nitrifying populations. Another source of uncertainty
was
the extrapolation of these values to cell numbers per unit
of volume.
Biofilm samples have been reported to shrink, especially
in the
z direction during immobilization on microscopic slides
and
during dehydration (
33). This would lead to underestimation
of the total aggregate volume and hence to the overestimation
of cell
numbers per unit of volume. A comparison of the thickness
of sections
after hybridization with the cryosection thickness
revealed a shrinkage
of about 15% for all samples. Therefore,
the numbers of nitrifiers per
unit of volume might have been overestimated
by 15%, while the
specific rates per cell might have been underestimated
by 15%, but
both parameters were overestimated and underestimated
to the same
extent for all samples. For all the reasons discussed
above, we are
aware that the absolute numbers reported in this
study might be only
best estimates, especially those for the specific
conversion rates per
cell. Nevertheless, we are convinced that
our data reliably describe
the trends in the investigated system
and are within the correct order
of
magnitude.
Analysis under in situ conditions.
The decrease of ammonium in
the bulk liquid phase with reactor height (Table 1) most likely leads
to decreasing numbers of ammonia-oxidizing bacteria in the active shell
of the aggregates from A1 to A3 (Table 5 and Fig. 2) and to a
decreasing thickness of this shell (Fig. 1a, c, and e). However, no
significant change in cell numbers, volumetric ammonium oxidation rate
and, consequently, the specific ammonium oxidation rate per cell of
Nitrosospira spp. was detectable from A1 to A2 (Tables 4 to
6). The estimated value of approximately 0.25 fmol · cell1 · h1 is comparable to the
specific rates reported by Wagner et al. for Nitrosococcus
mobilis in activated sludge (20, 35) but is 1 to 2 orders of magnitude below the rates reported for
Nitrosospira spp. and other ammonia oxidizers from
pure-culture studies (6, 27). This was probably due to the
apparent ammonium limitation under in situ conditions. In aggregates
from the top of the reactor (A3) and in the central parts of all
aggregates, ammonium was virtually absent or probably below
Km as discussed previously (32), and
no ammonium oxidation activity was detected (Fig. 1). Nevertheless,
ammonia-oxidizing bacteria were detectable by FISH, although in
significantly lower numbers than in the active zones (Fig. 2 and Table
5). This again demonstrates the capacity of ammonia-oxidizing bacteria
to maintain their ribosomes, even under conditions not conducive to
activity and growth (34, 35).
Nitrite oxidation was almost completely coupled to nitrite production
by ammonia oxidizers. Consequently, nitrite oxidation
rates decreased
from A1 to A3 (Table
4), despite an increase
in the number of
Nitrospira spp. found in the active shell from
A1 to A3
(Fig.
2 and Table
5). Specific nitrite oxidation rates
per cell were
always extremely low (maximum, 0.02 fmol · cell
1 · h
1). Pure culture data are
currently not available for
Nitrospira spp., but the values
reported for
Nitrobacter spp. are about 200
to 2,000 times
higher (
27). Again, this difference might result
from
unfavorable in situ conditions and/or from the differing
physiological
properties of these distantly related (
13) nitrite
oxidizers.
Nitrification activity under elevated substrate
concentrations.
To test the nitrifying capacity of the system,
additional measurements were performed under air saturation in medium
containing 300 µM ammonium (A1, A2, and A3) or 300 µM nitrite (A3).
The volumetric respiration rates in A1 and A2 are high (~100
nmol · mm3 · h1) compared to
the values of 2 to 40 nmol · mm3 · h1 reported from sediments (31),
activated-sludge flocs (34a), and heterotrophic aggregates
(26) or biofilms (21). They are similar, however,
to rates determined earlier under the same conditions in the same
system (12), in a nitrifying trickling filter biofilm (34), or in a hypersaline microbial mat (19). It
should be noted that such high rates are possible only if bacteria, and hence their activities, are extremely concentrated, as is shown for the
nitrifying shell in this study (Fig. 2).
The specific ammonium oxidation rates per cell under incubation
conditions (Table
6) are approximately the same in A1 and
A2, and both
are higher than the rates under in situ conditions.
Although oxygen
limited, we assume these values to be close to
the maximum specific
activity, since higher oxygen levels previously
have been shown to
inhibit nitrification in the same system (
12).
Still, the
specific activity is well below the rates reported
for pure cultures
(see above). Interestingly, ammonia oxidizers
in A3, i.e., the
population subjected to starvation in situ, developed
significantly
less activity, even when supplied with enough substrate
(Tables
4 and
6, A3
ammonium). This finding leads to the hypothesis
that
Nitrosospira spp. adapt to starvation by entering a dormant
or inactive state that is not coupled to the reduction of the
cellular
ribosome level, as proven by FISH. Whether this is due
to decreased
activity or concentration of ammonia monooxygenase
or to some other
unknown mechanisms might be addressed by the
application of
mRNA-targeted probes or ammonia monooxygenase-targeted
antibodies in
the
future.
Cell-specific nitrite oxidation rates increased for all sampling points
when aggregates were released from nitrite limitation
(Table
6).
However, whether the maximum nitrite oxidation activity
was reached
during incubation is questionable. Ammonia oxidizers
are thought to
possess lower
Km values for oxygen than nitrite
oxidizers (
14,
27). Therefore, the nitrite accumulation
detected
in A1 and A2 (Fig.
1b and d) might indicate that ammonia
oxidizers
have out-competed nitrite oxidizers for oxygen. On the other
hand,
Km values are available only for
Nitrosomonas spp. and
Nitrobacter spp., and
nitrite accumulation was less pronounced in A2, although
the oxygen
concentration within the active layer was even lower
than in A1.
Furthermore, in A3, when neither oxygen nor nitrite
was limiting, the
specific nitrite oxidation rates were not significantly
higher. For
these reasons, we assume that the specific rates were
at least close to
the maximum activity. As mentioned for the ammonia
oxidizers, these
activities are much lower (100 to 900 times)
than those described for
Nitrobacter. The recent detection of
Nitrospira-like sequences and cells in various environments
(
10,
13,
16,
20) and the absence of
Nitrobacter
spp. in similar
habitats (
15,
33,
36) might therefore
indicate other competitive
advantages of
Nitrospira spp.,
e.g., higher substrate affinity
for oxygen and/or nitrite, better
adaptation to starvation, or
better resistance to toxic
shocks.
In principle, substrate affinities (expressed as
Km values) can be estimated from ammonium and
nitrite microprofiles and cell
numbers by Michaelis-Menten kinetics.
For this approach, cell-specific
conversion rates were calculated for
each data point by using
the second derivative of the profiles.
Relating these values to
the respective substrate concentration in a
Lineweaver-Burk plot,
Km values as low as 40 µM ammonium (pH 7.8) and 10 µM nitrite
were obtained for
Nitrosospira and
Nitrospira spp., respectively.
This is 1 to 2 orders of magnitude lower than the
Km values for
Nitrosomonas europaea
and most other
Nitrosomonas strains (
18,
27) and
most
Nitrobacter spp. (
17,
27) found in the
literature.
In an ecological context,
Nitrosospira and
Nitrospira spp. thus
could indeed be regarded as typical
K strategists, with high substrate
affinities and low
maximum activity (or growth rate), compared
to the
r
strategists
N. europaea and
Nitrobacter spp.
(
5,
32).
However, again it must be emphasized that these
data are subject
to many uncertainties. First, the sample was highly
heterogeneous,
as discussed above; second, whether maximum reaction
rates could
be reached under the conditions applied is not sure, and
third,
the oligonucleotide probes used in this study are not specific
at the species level, leaving open the possibility of phylogenetic
and
physiological diversity in
Nitrospira spp., as discussed
below.
Therefore, the present data should be considered best-possible
estimates, correct to within an order of
magnitude.
It is tempting to speculate about the small fraction of
Nitrospira spp. that was detected exclusively in the active
shell
of the aggregates by probe NSR447. Are they physiologically
different
from the main population? This which, as long as it has not
been
proven on pure cultures, certainly cannot be decided on the basis
of this study. There are currently two dozen
Nitrospira-like
sequences
available, probably representing at least five distinct
species,
should not be presumed to have identical
physiologies.
In conclusion, the combination of microsensor measurements and FISH
allowed a detailed analysis of the in situ structure and
function of
the nitrifying bioreactor on a microscale. Measurements
under elevated
substrate concentrations were used to extract valuable
information
about the in situ activity of hitherto-uncultured
nitrifying
bacteria.
| |
ACKNOWLEDGMENTS |
We thank G. Eickert, A. Eggers, and V. Hübner for
constructing oxygen microsensors. Michael Wagner, Jens Harder, and
Arzhang Khalili are acknowledged for fruitful discussions. The help of Jakob Pernthaler with statistical analysis is appreciated.
This work was supported by a grant of the Körber Foundation to
R.A. and by the Max Planck Society.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Max Planck
Institute for Marine Microbiology, Celsiusstraße 1, D-28359 Bremen,
Germany. Phone: 49 421 2028 834. Fax: 49 421 2028 580. E-mail:
aschramm{at}mpi-bremen.de.
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Copyright © 1999, American Society for Microbiology. All rights reserved.
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Abstract
Introduction
