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Applied and Environmental Microbiology, October 1999, p. 4419-4424, Vol. 65, No. 10
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
A Method of Profiling Microbial Communities Based
on a Most-Probable-Number Assay That Uses BIOLOG Plates and
Multiple Sole Carbon Sources
Masashi
Gamo* and
Tadashi
Shoji
National Institute for Resources and
Environment, Onogawa 16-3, Tsukuba, Ibaraki 305-8569, Japan
Received 2 April 1999/Accepted 9 August 1999
 |
ABSTRACT |
A new approach to the community-level BIOLOG assay was proposed.
This assay, which we call the BIOLOG-MPN assay, is a
most-probable-number (MPN) assay that uses BIOLOG plates and multiple
sole carbon sources, and the profiles obtained by this assay consist of
MPNs estimated for the substrates in the BIOLOG plates. In order to
demonstrate the performance of the BIOLOG-MPN assay, it was applied to
pure cultures, model bacterial communities that contain two strains in
different ratios, and microbial community samples. MPN estimation using
BIOLOG plates worked well for the substrates on which utilizers can
grow at a sufficiently high rate for color development under the
conditions of the assay procedure. Furthermore, the results obtained
using model communities showed that the MPNs obtained reflected the
mixing ratios of pure cultures in the model communities. The profiles
obtained using model communities and community samples were
differentiated properly by statistical analyses. The results suggest
that the BIOLOG-MPN assay is a promising procedure for obtaining a
quantitative picture of the community structure.
 |
INTRODUCTION |
The BIOLOG assay, which is a
sole-carbon-source test, was originally developed to identify microbial
isolates based on their substrate utilization profiles. Since the
proposal of the direct inoculation of environmental samples into BIOLOG
plates (3), the community-level BIOLOG assay has become
popular because of its rapidity and simplicity. Although the
community-level substrate utilization profiles seem to work well in
differentiating microbial community samples of various types, recent
studies and reviews have pointed out that the interpretation of the
results requires much care (2, 5, 6, 8, 10, 11). The major
caveats can be summarized as follows: (i) the inoculum density and
incubation time are arbitrary, and (ii) the substrate utilization
profiles obtained do not reflect the nature or structure of the
original microbial communities from which the samples were taken.
It is well-known that the inoculum density has a considerable effect on
the rate of color development. In order to reduce the effect of
arbitrariness in inoculum density, normalization procedures are often
applied. A straightforward way is the normalization of the inoculum
size. However, it has been argued that this type of normalization has
the disadvantage of being time-consuming; moreover, it is unclear which
cell enumeration method should be used (2). Another way is
the normalization of color development based on the average well color
development (AWCD). The simplest procedure for this type of
normalization is to divide the color development in each well by AWCD.
However, it has been pointed out that this type of normalization is
effective only when the initial cell density does not differ markedly
among the samples compared (6). It is often recommended that
the inoculum density be kept as high as possible because a low inoculum
density may increase the lag time in color development (5,
8). A prolonged lag time means that rare and/or slow-growing
populations cannot contribute to the resulting substrate utilization
profile. Another reason is that the low inoculum density may exclude
rare populations in the inoculum. The absence of rare populations in
highly diluted samples was discussed theoretically (8) and
was suggested based on the result obtained from a study using a
dilution series of inoculum (12). An improved procedure for
reducing the effect of differences in the rate of color development is
the comparison of samples among plate readings of equivalent AWCD
(2). In this procedure, the incubation time is not fixed but
dependent on the rate of color development.
Regarding the reduction of the effect of the arbitrariness of
incubation time, statistical analyses based on the parameters representing the kinetics of color development (11) and the area under the curve of color development (4, 9) were
proposed. Concerning experimental procedures, there are two conflicting general recommendations: one is that prolonged incubation time is
preferable because it can eliminate most of the effect of inoculum densities (12), and the other is that short incubation time with high inoculum density is preferable because it is effective for
reducing the enrichment effect (2).
Since the alteration of the community structure, i.e., the
enrichment effect, occurs during incubation of BIOLOG plates, it has been pointed out that the substrate utilization profile reflects the resulting community produced, not the original microbial
communities from which the samples were obtained (2, 5, 6, 8, 10,
11). Alteration of the community structure is inevitable because
samples need a certain incubation period to attain sufficient cell
density, i.e., approximately 108 cells/ml, for color
development. In particular, in the case of environmental samples, one
sample would contain populations with undetermined cell densities
exhibiting a variety of kinetic responses in BIOLOG plates. In other
words, we cannot know a priori which of the populations in a sample
contribute to the color development under a certain combination of
inoculum density and incubation time. Consequently, the color
development observed cannot be interpreted in terms of the number of
utilizers or the metabolic potential of the original microbial
community (5).
In this study, we investigated a new approach to the community-level
BIOLOG assay, where we introduced the concept of most probable number
(MPN). MPN is one of the most popular and conventional enumeration
procedures. By using a medium containing a sole carbon source for MPN
enumeration, the cell density of utilizers specific to the carbon
source can be estimated. Thus, our new approach, which we call
BIOLOG-MPN assay, is a MPN estimation method that uses
BIOLOG plates and multiple sole carbon sources. The profile obtained by
the BIOLOG-MPN assay consists of cell densities of utilizers of
substrates contained in BIOLOG plates.
 |
MATERIALS AND METHODS |
Sample preparation.
Three types of samples were prepared:
pure cultures, model communities, and community samples. As pure
cultures, Escherichia coli JM109 (Takara Shuzo Co., Ltd.,
Kyoto, Japan) and Pseudomonas aureofaciens IAM12353 (IAM
Culture Collection, Institute of Molecular and Cellular Biosciences,
The University of Tokyo) were used. The pure cultures were prepared as
follows: first, the cells were precultivated on nutrient broth (NB)
agar medium and then transferred onto tryptic soy broth (TSB) agar
medium and incubated at 30°C for 1 day. Then, colonies on the plates
were swabbed and resuspended in 50 mM phosphate buffer (pH 7) so that
the suspension would have a transmittance level of 20%. The cell
concentration of the suspension was confirmed to be approximately
1.1 × 109 cells/ml by the direct counting method with
acridine orange (7). Three model communities were prepared
by mixing two suspensions of the pure cultures described above at three
E. coli-to-P. aureofaciens ratios, namely,
1,000:1 (mixture A [MIX_A]), 1:1 (MIX_B), and 1:1,000 (MIX_C).
As microbial community samples, four samples of activated sludge taken
from a municipal wastewater treatment plant (WTP_1 to WTP_4) were
tested. They were taken from the same plant in four different seasons.
In addition, two samples of activated sludge fed by artificial
wastewater were also tested; one was fed with phenol (PHEN) as the
carbon source, and the other was fed with aniline (ANI) as the carbon
source. They were taken from the reactors in our laboratory. The feeds
contained PHEN or ANI at a concentration of 500 mg/liter. The reactors
were run in a semicontinuous process, that is, half of the volume of
the reactor was exchanged with fresh feed once a day. Activated sludges
were stored in a refrigerator for 3 or 4 days after they were
collected. A sample was prepared as follows: (i) the sample was washed
twice with 50 mM phosphate buffer by centrifugation at 8,000 × g for 15 min followed by removal of the resulting supernatant;
(ii) the sample concentration was adjusted to 100 mg of suspended
solids (SS) per liter using 50 mM phosphate buffer, and (iii) sonicated for 2 min at 40 W (Insonator 201 M; Kubota Ltd., Tokyo, Japan).
A dilution series was then prepared for each sample. The initial cell
density, which was prepared to be a transmittance level of 20% for
pure cultures and model communities and 100 mg of SS per liter for
activated sludge samples, was referred to as the dilution level (DL) of
zero. The dilution step was set at 10-fold. Thus, the cell density at
DL = 5, for example, is 10
5 of that at DL = 0. The dilution series for pure cultures and model communities had a range
of 11 orders of magnitude, and those for community samples had a range
of 5 to 7 orders of magnitude. Phosphate buffer of 50 mM was used for
preparing the dilution series.
Inoculation and incubation.
One BIOLOG ECO plate (BIOLOG
Inc., Hayward, Calif.), which was used in this study, has three
replicates of a set of 31 substrates and one blank well. Six replicates
were prepared, using two BIOLOG ECO plates for each DL. The inoculation
volume was 150 µl/well. The plates were incubated at 30°C for 2 weeks (pure cultures and model communities) or 1 week (community
samples). The optical density (OD) values were measured at a wavelength
of 595 nm with a plate reader (Microplate Reader model 3550; Bio-Rad,
Richmond, Calif.). The difference between the OD values at the
beginning and end of incubation was regarded as the increase in OD
values for the well. The average increase of the OD value in six blank wells was then subtracted from the increase in the OD value, with the
difference being the net increase.
MPN estimation and statistical analyses.
The net increase in
the OD value was translated into a positive or negative response with
the threshold OD value of 0.3. Since there are six replicates, each
substrate may yield zero to six positive responses at each DL. The MPNs
were estimated based on the maximum-likelihood estimation as follows.
When it is assumed that cells are randomly distributed in the
suspension of the sample, the probability that a certain number of
positive wells will be observed at a certain DL is calculated by the
following equations:
|
(1)
|
where d is the cell density (number of cells per
milliliter) at DL = 0, mi is the expected
number of cells in a well at DL = i,
Ni is the observed number of positive wells at
DL = i, and Li is the
probability that the number of positive wells is observed to be
mi at DL = i. For the MPN
estimation, four consecutive DLs (DLs = i,
i + 1, i + 2, i + 3, 0 < i < maximum DL
3) for which the
difference between mi and
mi + 3 may be maximized were selected. The MPN
was then determined as the value of d which maximizes the
likelihood function (equation 2). The calculation was executed by using
Microsoft Excel 5.0 for Macintosh.
|
(2)
|
Here, L is the likelihood function that represents
the probability that the numbers of positive wells for the four
consecutive DLs are exactly the same as in the observation when the
cell density at DL = 0 is d.
The set of logarithmically transformed MPNs for 31 substrates and one
blank was regarded as the profile representative of the sample. In the
case where no positive response was observed even at DL = 0, the
MPN was regarded to be 0.4 cell/ml. This cell density gives the
expected cell number introduced into a well of 0.06 cell/well, which
corresponds to no positive response in all six replicates at a
probability of 0.7. Statistical analyses, such as principal component
analysis or cluster analysis, were applied in order to examine the
similarity in profiles among the samples. Principal component analysis
was applied to pure cultures and model communities. The cluster
analysis was applied to community samples, where the distance between
profiles was measured as the Euclidean distance and the group average
method was applied as the linkage strategy. These statistical analyses
were executed with STATISTICA version 5 for MS Windows (StatSoft, Inc.,
Tulsa, Okla.).
Effectiveness of MPN estimation using BIOLOG plates.
Using
BIOLOG MT plates, 84 replicates for each DL were prepared. Three
combinations of substrate and inoculum were tested: xylose and the pure
culture of E. coli, L-asparagine and the
pure culture of E. coli, and D-xylose and an
activated-sludge sample obtained from a municipal wastewater treatment
plant. The concentration of substrate in each well was 0.3 mg/well. The
samples were prepared as described in "Sample preparation" above.
After 2 weeks of incubation, the number of positive wells at each DL
was counted with the threshold for positive response of OD = 0.3. Then, the observed number of positive responses at each DL was
estimated as follows. Assuming that cells are distributed randomly in
the sample suspensions and that the number of positive responses
follows a Poisson distribution, the expected number of positive wells
at each DL was estimated by the following equation:
|
(3)
|
where Ni is the expected number of
positive wells at DL = i and d is the cell
density (number of cells per milliliter) at DL = 0. The value of
d was determined so that the expected number of positive
wells at each DL can show the best agreement with the observation.
 |
RESULTS |
MPN estimations.
The result of analyzing the effectiveness of
MPN estimation using BIOLOG plates (Table
1) indicates that the numbers of positive wells expected based on the Poisson distribution showed good agreement with the observations. Furthermore, in the tests using the pure culture
of E. coli, the MPNs obtained were similar to the inoculum cell density of approximately 109 cells/ml confirmed by
direct counting using acridine orange.
Figure 1 shows the MPNs obtained for the
two pure cultures of E. coli and P. aureofaciens,
where the substrates are in the order of estimated MPNs. MPNs for some
substrates were estimated to be approximately 109 cells/ml,
which corresponds to the inoculum cell density confirmed by direct
counting with acridine orange. On the other hand, MPNs for other
substrates were estimated to be less than 103 cells/ml.

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FIG. 1.
MPNs obtained for pure cultures of E. coli
(ECOLI), and P. aureofaciens (PAU), using BIOLOG ECO plates.
Substrates are given in the order of the estimated MPNs.
|
|
The results for model communities are shown in Fig.
2, in which the substrates were
categorized into four categories based on the results shown in Fig. 1:
substrates for which MPNs can be estimated correctly for both bacteria
(category EP), those for E. coli only (category E), those
for P. aureofaciens only (category P), and those for neither
(category N). For all substrates included in category EP, the MPNs were
estimated to be approximately 109 cells/ml for the three
model communities. The MPNs for category E substrates were
estimated to be approximately 109 cells/ml for MIX_A
and MIX_B and 106 cells/ml for MIX_C (substrates A2
[
-methyl-D-glucoside] and H2
[DL-
-glycerol phosphate] were the exceptions).
Likewise, the MPNs for category P substrates were estimated to be
approximately 109 cells/ml for MIX_B and MIX_C and
approximately 106 cells/ml for MIX_A (substrate C4
[L-phenylalanine] was the exception). As for category N,
MPNs for all substrates except E4 (L-threonine) were
estimated to be less than 103 cells/ml. These observations
agree with the ratio of the two strains contained in the model
communities.

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FIG. 2.
MPNs obtained for the model communities. The substrates
are categorized into four categories based on the results shown in Fig.
1.
|
|
The MPNs for community samples were estimated to be in the range from
nearly 0 to 106 cells/ml, depending on the sample
inoculated and the substrate. Figure 3
shows the profiles of ANI and WTP_1 based on MPNs as examples.
Statistical analyses.
Figure 4
shows the results of the principal component analysis applied to the
profiles of pure cultures and model communities. The profile of MIX_A
was found to be between those of E. coli and MIX_B, while
the profile of MIX_C was found to be between those of P. aureofaciens and MIX_B. The first component accounted for 74.7%
of the variation in the data and the second component accounted for
20.6%.

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FIG. 4.
Principal component analysis of profiles based on MPNs
of pure cultures and model communities. Abbreviations: PC1 and PC2,
first and second components of principal component analysis,
respectively; ECOLI, E. coli; PAU, P. aureofaciens.
|
|
Profiles based on color development were also examined by principal
component analysis. The profile for each sample at each dilution level
was obtained by averaging the net increases in OD values from six
replicates measured after 2 weeks of incubation. Figure
5 shows 25 profiles that were obtained
from five samples at five DLs each. Figure 5 shows that the positions
of the profiles for the two pure cultures and MIX_B were stable and
independent of the DL and that their relative positions were similar to
those in Fig. 4. On the other hand, the positions of MIX_A profiles and
MIX_C profiles changed, depending on the DL. The profiles of both MIX_A
and MIX_C at lower DLs, DLs = 4 and 5, were located near that of
MIX_B. However, in the case of MIX_A, the profiles at higher DLs,
DLs = 7 and 8, were near those of E. coli. In the case
of MIX_C, the profiles at higher DLs, DLs = 6, 7, and 8, were
located near those of P. aureofaciens. The first component accounted for 71.6% of the variation in the data, and the second component accounted for 21.1%.

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FIG. 5.
Principal component analysis of profiles based on color
development obtained for pure cultures and model communities. The
profiles at DLs of 4 to 8 are included. For MIX_A and MIX_C, the number
of each DL is shown. Black and shaded circles represent the profiles of
MIX_A and MIX_C, respectively. Abbreviations: PC1 and PC2, first and
second components of principal component analysis, respectively; ECOLI,
E. coli; PAU, P. aureofaciens.
|
|
The results of cluster analysis applied to the profiles of community
samples (Fig. 6) show that the four
profiles of the activated sludge samples taken from a municipal
wastewater treatment plant (WTP_1 to WTP_4) clustered together, while
the profiles of activated sludges fed by artificial wastewater (PHEN
and ANI) and WTP_1 to WTP_4 were far apart.

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FIG. 6.
Cluster analysis of profiles based on MPNs of community
samples. The distance between profiles was measured as Euclidean
distance, and the group average method was applied as the linkage
strategy.
|
|
 |
DISCUSSION |
The community-level BIOLOG assay that directly inoculates
environmental samples is an attractive method of differentiating community samples. However, the procedures in current use are still
controversial and even conflict with each other. In addition, it has
been pointed out that interpretation of the substrate utilization profiles obtained by the assays requires much care. We propose here a
new approach to the community-level BIOLOG assay, which we call
BIOLOG-MPN since we introduce the concept of MPN to the BIOLOG assay.
In most of the current procedures, the responses are detected based on
color development (OD value) after a certain incubation period. The
extent of color development for a certain substrate can be affected by
three factors: initial density of the utilizers in the inoculum, growth
rates of the utilizers in the well of the BIOLOG plates, and incubation
period. These factors are related to each other, and we cannot separate
the effects of the three factors on the resulting color development
because we do not know a priori the initial densities of the utilizers
in the sample or their growth rates. In contrast, in the case of the
BIOLOG-MPN assay, the response to a substrate is more
definable. When we focus on each substrate, the
BIOLOG-MPN assay can be regarded as MPN enumeration using a
sole carbon source on the BIOLOG plate. Therefore, the MPN is defined
as the initial cell density of the utilizers that can grow sufficiently
under the conditions of the assay procedure.
The results shown in Table 1 suggest that MPN estimation using BIOLOG
plates works well when the utilizer of the substrate can grow at a
sufficiently high rate for color development under the assay procedure.
This is also supported by the results shown in Fig. 1, where the
estimated MPNs clearly fell into two groups, MPNs of approximately
109 and MPNs less than 103. However, there are
two types of substrates for which the MPNs were estimated to be less
than 103, that is, some substrates had no color development
even at the lowest DL and some had color development only at low DLs.
As for the latter substrate type, it is thought that the populations in
the samples can utilize the substrate but that the growth rates were
not high enough under the conditions of the assay procedure. Although
we think that a prolonged incubation period is preferable for accurate
MPN enumeration, particularly for slow-growing utilizers, we
arbitrarily used incubation periods of 1 or 2 weeks for practical reasons.
In the results for the model communities (Fig. 2), MPNs estimated for
most of the substrates reflect the mixing ratios of the two strains.
Although this suggests that the profile obtained by BIOLOG-MPN can
quantitatively reflect the microbial community structure that contains
strains at abundance levels of several orders of magnitude difference,
some exceptions were observed, that is, the MPNs for substrates C4
(L-phenylalanine), A2 (
-methyl-D-glucoside), and H2 (DL-
-glycerol phosphate) in MIX_C were lower than
those theoretically predicted based on the results found with pure
cultures, and the value for substrate E4 (L-threonine) in
MIX_A was higher than the theoretical prediction (Fig. 2). Although we
cannot definitively show the reason for these observations at present,
one possibility is that the discrepancies between predictions and
observations were due to the low color development that was observed
for these substrates. If a certain combination of strain and substrate
shows low color development, particularly if it is near the threshold OD value for positive response, even a subtle variation in the color
development would affect the detection of positive responses and the
resulting MPN estimation.
Figure 5 shows that the relative positions of the profiles of MIX_A and
MIX_C depended on the DL when the profiles were generated based on the
color development at a certain period of incubation. This observation
can be explained in terms of the composition of the model communities,
that is, E. coli in MIX_C and P. aureofaciens in MIX_A are excluded from the inocula at DL = 7 or higher. Likewise, according to the results of cluster analyses of
profiles of community samples using color development (data not shown),
the shape of the dendrogram can be affected by the DL. These results
suggest that profiles based on color development observed at a certain DL can be misleading, particularly in the case of environmental samples
that contain populations with much different densities. In contrast,
the profile obtained by the BIOLOG-MPN assay is independent of the DL
and unique for the sample. In addition, the BIOLOG-MPN assay works well
as a method for differentiating microbial community samples. According
to the results of principal component analysis using pure cultures and
model communities (Fig. 4), the relative positions of the profiles are
consistent with the structures of the model communities. The shape of
the dendrogram based on the result of the cluster analysis applied to
the profiles of activated sludges also appropriately reflects the
difference in the origins of the samples (Fig. 5).
The BIOLOG-MPN assay still has some limitations, some of which are
related to the specifications of the BIOLOG system. In order to
establish the BIOLOG-MPN assay as a MPN assay that uses multiple sole
carbon sources that can be used on environmental community samples, we
think that three improvements are necessary. First, the sensitivity for
the detection of positive response should be improved. Although the
current BIOLOG assay using a redox dye as an indicator for substrate
utilization is convenient, the sensitivity for the detection of
positive response seems insufficient for MPN enumeration. If the
detection of substrate utilization were more sensitive, the MPN
enumeration would be more accurate. Then, it would be expected that the
discrepancy between observed and expected MPNs in the results using
model communities (Fig. 2) would be reduced. Second, the incubation
conditions in the wells of the BIOLOG plate should be customized for
the target microbial community. In other words, the incubation
conditions in the wells of the BIOLOG plate can cause a bias toward a
certain group of microbial populations. For example, the substrate
concentration in the well of the BIOLOG plate is considered to be much
higher than that usually found in the environment. Other examples may be the salt content in the medium and the temperature during
incubation. When a researcher interprets the results of the BIOLOG-MPN
assay, these selection biases should be kept in mind. Third,
ecologically relevant substrates should be selected in a BIOLOG plate.
Campbell et al. (1) concluded that although the use of
ecologically relevant substrates is beneficial, these substrates would
be useful only if their use resulted in equal or better differentiation of samples. In the BIOLOG-MPN assay, if the dominant populations have a
wide range of substrate utilization, they can mask the existence of
rare populations. It is thought that a number of applications of the
BIOLOG-MPN assay to environmental samples are necessary in order to
determine the set of substrates appropriate for examining environmental samples.
Although the number and kind of examples tested in this study were
limited and the BIOLOG-MPN assay also suffers from the limitations
inherent to the BIOLOG assay, it can be concluded that the BIOLOG-MPN
assay provides a definable and quantitative picture of the community
structure of a sample. On the other hand, the disadvantage of the
BIOLOG-MPN assay is that it requires much time and resources. We
recommend that the current procedures be used to trace changes in a
microbial community and that the BIOLOG-MPN assay be used for defining
the community structure of concern. The combined use of current
procedures and the BIOLOG-MPN assay will improve our understanding of
the microbial community from the viewpoint of physiological substrate utilization.
 |
ACKNOWLEDGMENTS |
This work was supported by the Promotion System for Intellectual
Infrastructure of Research and Development of Science and Technology
Agency (STA) of Japan.
We gratefully acknowledge Gunze-Sangyo Inc. for technical advice on
BIOLOG ECO plates and K. Morikawa for technical advice on direct
counting with acridine orange. We also wish to give special thanks to
A. Shinotsuka who helped us with the BIOLOG assay.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: National
Institute for Resources and Environment, Onogawa 16-3, Tsukuba, Ibaraki
305-8569, Japan. Phone and fax: 81-298-58-8315. E-mail:
magamo{at}nire.go.jp.
 |
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Applied and Environmental Microbiology, October 1999, p. 4419-4424, Vol. 65, No. 10
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
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