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Applied and Environmental Microbiology, August 1999, p. 3407-3412, Vol. 65, No. 8
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Determination of Abundance and Biovolume of
Bacteria in Sediments by Dual Staining with
4',6-Diamidino-2-Phenylindole and Acridine Orange: Relationship to
Dispersion Treatment and Sediment Characteristics
Tomohiro
Kuwae* and
Yasushi
Hosokawa
Marine Environment Division, Port and Harbour
Research Institute, 3-1-1, Nagase, Yokosuka 239-0826, Japan
Received 18 March 1999/Accepted 18 May 1999
 |
ABSTRACT |
We measured the abundance and biovolume of bacteria in intertidal
sediments from Tokyo Bay, Japan, by using a dual-staining technique
(4',6-diamidino-2-phenylindole and acridine orange) and several
dispersion techniques (ultrasonic cleaner, ultrasonic sonicator, and
tissue homogenizer). Dual staining reduced serious background
fluorescence, particularly when used for silt-, clay-, and
detritus-rich sediments, and allowed us to distinguish bacteria from
other objects during both counting and sizing. Within the studied
samples, the number of bacterial cells ranged from 0.20 × 109 to 3.54 × 109 g of wet
sediment
1. With the cleaner and sonicator treatments, the
bacterial numbers for all of the sites initially increased with
dispersion time and then became constant. For the homogenizer
treatments, the highest bacterial numbers were observed with the
shortest (0.5- to 2-min) treatments, and the counts then declined
steeply as the homogenization time increased, indicating that cell
destruction occurred. The cleaner treatment had the possibility of
insufficient dispersion of bacteria for fine-grain sediments. Within
the studied samples, the bacterial biovolume ranged from 0.07 to 0.22 µm3. With the cleaner and sonicator treatments, the
biovolume peaked during the shorter dispersion time. This pattern was
caused not by cell destruction but by the incremental portion of
dispersed small cells. We concluded that with the cleaner and sonicator treatments, the longer dispersion time reflected the real size spectrum
and was preferable for accurate estimation of mean bacterial biovolumes.
| |
INTRODUCTION |
The importance of bacteria in marine
and estuarine sediments as a food source and major contributor to
biogeochemical processes in benthic ecosystems has been widely
recognized (1, 4, 13, 16). The quantification of bacterial
roles requires precise measurements of their parameters. A standard
procedure used to determine bacterial abundance and biovolume is the
microscopic examination of fluorescently stained cells with either
4',6-diamidino-2-phenylindole (DAPI) or acridine orange (AO). Most
benthic bacteria are attached to sediment particles with extracellular
polymeric substances (EPS), in contrast to free-living bacteria in
water columns. Thus, a direct measurement of the abundance and
biovolume of benthic bacteria by epifluorescence microscopy is possible
only when bacteria can be detached or segregated from aggregates which
include mineral particles and detritus.
Factors affecting the accuracy of the microscopic examination have been
reported for the sample dilution and staining procedure (18)
and for the efficiency of the bacterial dispersion, including the
specification of equipment, treatment time, and dispersing intensity
(9). DAPI specifically binds with nucleic acids and emits a
brilliant blue light under UV excitation, enabling bacteria to be
segregated more easily than with AO, which dyes the protein. In the
case of low sample dilution, however, the problems of background fluorescence still remain even with DAPI staining. Several instruments are available to disperse bacterial cells from aggregates. Ultrasonic cleaners and ultrasonicators (9, 18, 21) disperse bacteria by the vibration of individual particles, while tissue homogenizers (1, 7, 12) mechanically break sediments into smaller
particles. The dispersing time as well as the dispersing intensity
strongly affects cell counts (9) and size distribution.
Longer and more intense treatments tend to decrease the aggregate
masking effect. This leads to an increase in the bacterial cell counts;
however, with the longer and more intense dispersion, the tendency for cell destruction is higher. Moreover, the efficiency of the bacterial dispersion is affected by sediment characteristics, including viscosity
and grain size distribution (7).
In this paper, we report a new dual-staining technique using both DAPI
and AO for estimating the abundance and biovolume of benthic bacteria.
We also explain the effect of dispersion procedures and sediment
characteristics on bacterial enumeration and sizing. Intertidal
sediments from Tokyo Bay, Japan, were used in the present study.
| |
MATERIALS AND METHODS |
Sampling.
Samples were obtained in May 1998 from three sites
on the coast of Tokyo Bay, Japan: a sandy beach (35°10.6'N,
139°39.5'E), an intertidal sand flat (35°24.2'N, 139°54.2'E), and
a mud flat (35°8.5'N, 139°39.9'E). Core samples were taken to a
depth of 5 cm with acrylic core tubes (8.6-cm internal diameter). Each sample was thoroughly mixed and immediately brought back to the laboratory. Sediments for the dispersion procedures were obtained by
subsampling from these samples. Subsamples (0.3 g) were mixed with 5 ml
of filter-sterilized seawater (particle-free water) in 10 ml of
acid-washed polycarbonate tubes and stored at 4°C. The particle-free
water was obtained by two filtrations of 10% formalin-seawater
solution buffered with sodium tetraborate (final concentration,
3.5 g liter1) (1) by using Millipore
filters (0.22-µm pore size).
Dispersion procedures and bacterial counting.
Prior to
dispersion, the samples were incubated for at least 15 min with Tween
80 (final concentration, 1 mg liter1). This surfactant
facilitates even bacterial distribution on the membrane filter
(9). Three different devices were used for the bacterial
dispersion from the sediments: an ultrasonic cleaner (B-2200; Branson)
(60-W output), an ultrasonicator (GE-100; Biomic) (100-W output)
equipped with a 3-mm tapered microtip and with the amplitude set at
40% of the maximum, and a homogenizer (PT-2000; Kinematica) set at
20,000 rpm. The dispersion time for samples in the tubes was 5 to 60 min for the cleaner and 0.5 to 8 min for the others. To prevent
possible denaturation of nucleic acids caused by overheating, the tubes
were placed in ice water during the dispersion treatments
(9).
After dispersion, the samples were diluted 50 to 250 times (final
dilution, 830 to 4,160) with particle-free seawater. Diluted samples
were dual stained with a combination of DAPI to a final concentration
of 5 µg ml1 (18) and AO to a final
concentration of 1 mg ml1 for counterstaining. After more
than 30 min of staining, 0.5 to 2 ml of the samples was filtered
through polycarbonate black filters (0.2-µm pore size) and then
rinsed with particle-free seawater. The filters were immersed in
nonfluorescent oil on microscope slides and covered with coverslips.
Bacteria retained on the filters were examined within 24 h after
dispersion under an Olympus BX-FLA-3 epifluorescence microscope (UV
excitation) equipped with a 100× oil immersion objective. On each
filter, no fewer than 200 clear-edged cells in 20 microscopic fields
were counted.
Measurement of cell volumes.
After dispersion, the samples
were centrifuged (100 × g) for 5 min in order to
exclude nonbacterial particles as much as possible. Supernatants were
dual stained and filtered as described above. A camera (TM-10AK;
Olympus) mounted on the microscope was used to take microphotographs on
color slide films. Images on the films were scanned with a film scanner
(QuickScan 35; Minolta) connected to a computer and digitized, and
thresholds were determined by using image analysis software (Image
1.59; NIH). Thresholds were manually adjusted by comparing original
color images in each image. Bacterial cell-shaped objects were
subsequently segregated from other objects, such as detritus particles
and artifacts. Objects having an area of less than 6 pixels were
automatically excluded as noise. Dividing cells, which have two
well-defined local intensity maxima, were also removed. The pixel size
for the resulting image was 0.17 by 0.17 µm. The project area of an
object (A), cell length, and cell width (w) were
automatically measured by the image analysis software. To compute the
cell volume (V), we considered the rod-shaped cells to be
cylinders with a hemispherical cap based on the microscopic observations: V = 
wA/4 +w3/6 
2w3/16. At least 500 bacterial
cell-shaped images per sample were analyzed.
Sediment characteristics.
At each study site, water content,
sediment granulometry, and EPS were measured for triplicate samples.
The water content was determined by the weight loss when wet sediments
were dried at 90°C for 24 h. The grain size was measured by
sieving the sediment, and the silt and clay components were determined
with a Coulter Multisizer. EPS was examined with the phenol-sulfuric
acid assay described by Underwood et al. (20) as a parameter
of viscosity between the bacterial cells and other objects. The amount
of EPS was expressed as micrograms of C per gram (dry weight) of
sediment, with glucose as a standard.
Statistical analysis.
Statistical differences in bacterial
counts and sizes among dispersing times in each disperser in each
sediment were tested by using a one-way analysis of variance. Each
analysis of variance was followed by a Student-Newman-Keuls (SNK)
multiple-comparison test of means. Data sets were tested for
homogeneity of variances (Levene test), and the log-transformed values
were used if needed for a normal distribution.
| |
RESULTS |
Characteristics of sediments.
The characteristics of the three
intertidal sediments are summarized in Table
1. There was a consistent relationship
between sediment granulometry and other sediment characteristics. The mud flat sediment exhibited high water and silt contents, with a mean
grain size of 92 µm. The mean grain size in the sand flat was almost
the same as that in the sand beach (170 µm); however, the proportion
of silt was six times higher in the former. The concentration of EPS
was higher in the fine sediment.
Bacterial counts.
Figure 1 shows
the number of dispersed bacteria versus dispersion time for the
cleaner, sonicator, and homogenizer techniques for sediments from each
site. With both the cleaner and sonicator treatments, the bacterial
numbers at all of the sites initially increased with treatment time and
then leveled off, resulting in the highest number of bacteria at 15 to
45 min with the cleaner and at 3 to 8 min with the sonicator. However,
for the homogenizer treatments, the pattern was totally different from
that for the cleaner and sonicator treatments at all of the sites. The
highest bacterial numbers were observed for the shortest (0.5- to
2-min) treatments. The bacterial counts then declined steeply as the homogenization time increased, especially in the sand flat and mud flat
sediments, where the counts were less than those observed for
nondispersed sediments.
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FIG. 1.
Comparisons of the numbers of dispersed bacteria with
cleaner ( ), sonicator ( ), and homogenizer ( ) treatments in
sandy beach (a), sand flat (b), and mud flat (c) sediments. Bars
indicate standard errors (n = 3).
|
|
We used the SNK test to examine a statistically homogenous subset
including the maximum mean bacterial count in each case
of the
dispersing time series. Table
2
summarizes the average
bacterial count in each homogenous subset for
each sediment and
disperser treatment. The average value was considered
the maximum
value in each case. For both the cleaner and sonicator
treatments,
the SNK test revealed that the bacterial counts were
homogenous
(
P > 0.05) among the dispersion times
except for several shorter
dispersion times. For the sand beach
sediment, no statistical
differences in the maximum numbers were found
among the three
dispersion techniques. In the sand flat sediment, the
maximum
number for the cleaner treatment was significantly lower than
that for the sonicator treatment (0.01 <
P < 0.05). In the mud
flat sediment, the maximum number for the
cleaner treatment was
significantly lower than those for the sonicator
and homogenizer
treatments (0.01 <
P < 0.05).
The more dispersed bacteria were observed in the finer-grain sediments.
The maximum number for the sonicator treatment ranged
from 0.20 × 10
9 to 0.94 × 10
9 cells g
1
in the sand beach, 0.69 × 10
9 to 1.02 × 10
9 cells g
1 in the sand flat, and 1.67 × 10
9 to 3.54 × 10
9 cells
g
1 in the mud flat on a wet-sediment basis (Table
2),
which corresponded
to 0.25 × 10
9 to 1.18 × 10
9 cells g
1, 0.93 × 10
9 to
1.37 × 10
9 cells g
1, and 3.05 × 10
9 to 6.46 × 10
9 cells g
1
on a dry-sediment basis, respectively. The bacterial numbers
in the
sand flat and mud flat sediments were approximately two-
and fivefold
higher, respectively, than those in the sand beach
sediment. This
tendency was more distinct in the nondispersed
samples, for which the
counts in the sand and mud flats were more
than 1 order of magnitude
higher than those in the sand beach
sediment.
Bacterial cell volume.
Figure 2
shows the mean bacterial volume of dispersed bacteria versus dispersion
time for sediments from each site. In all of the treatments, the
biovolumes peaked at shorter times. The biovolumes then dropped as the
dispersion time increased.
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FIG. 2.
Comparisons of dispersed bacterial volumes with cleaner
(), sonicator (), and homogenizer () treatments in sandy beach
(a), sand flat (b), and mud flat (c) sediments. Bars indicate standard
errors.
|
|
To investigate these fluctuation patterns more thoroughly, we size
fractionated the numbers of dispersed bacteria for the
cleaner and
sonicator treatments. The histogram for each data
set showed a
Guassian-shaped profile (not shown). When the counted
bacterial cells
were fractionated into four size classes (Fig.
3), the bacterial cells in the smaller
fractions (<0.10 µm
3) required a longer dispersion time
to become constant than those
in the larger fractions (>0.10
µm
3) in each data set. No apparent decline was found for
either the
cleaner or sonicator treatment. These results indicate that
the
decrease in the mean cell volume with longer dispersion times
(Fig.
2) was caused not by cell destruction but by the increased
proportion
of smaller cells. Consequently, it was concluded that
the longer
treatment time reflected the real size spectrum and
was preferable for
the accurate estimation of mean bacterial biovolumes.
For the
homogenizer treatment, in which only the mud flat sediment
was
fractionated, all of the bacterial cell fractions dropped
steeply after
2 min (not shown). The fraction of 0.03 to 0.1 µm
3
dominated in both the sand beach and sand flat sediments, while
the
fraction of 0.1 to 0.3 µm
3 dominated in the mud flat. In
the sand flat sediment, the cell
counts in the 0.03- to
0.1-µm
3 fraction were lower with the cleaner treatment
than with the
sonicator treatment, which caused the statistical
difference in
the mean volume between them. In the other sediments, the
cell
counts of the entire fraction exhibited nearly similar values.
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FIG. 3.
Comparison of the numbers of size-fractionated bacteria
with cleaner and sonicator treatments at three sites.
|
|
The mean bacterial biovolume, equivalent spherical diameter, and cell
length/width ratio for the three sediment types and
dispersion
treatments are summarized in Table
3. The
range of
bacterial biovolumes was consistent with those previously
reported
(
12,
14,
16,
17). The largest bacterial biovolumes
were
observed in the finer-grain sediments. Biovolumes ranged from
0.07 to 0.10 µm
3 (0.49- to 0.52-µm equivalent spherical
diameter) in the sand
beach, from 0.10 to 0.13 µm
3 (0.53 to 0.56 µm) in the sand flat, and from 0.17 to 0.22 µm
3
(0.62 to 0.66 µm) in the mud flat. This tendency was also true
for
the nondispersed samples. The cell length/width ratios, which
ranged
from 1.6 to 2.1, were not significantly different among
dispersion
techniques or sediment types (
P > 0.05).
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|
TABLE 3.
Biovolume, equivalent spherical diameter, and cell
length/width ratio of dispersed bacteria at three sites
|
|
| |
DISCUSSION |
Dual staining with DAPI and AO.
The dual-staining technique
utilized in this study can contribute to a better understanding of the
bacterial abundance and size distribution in sediments. Until now,
either AO or DAPI alone has been used as a dye for benthic bacteria by
other workers. If only AO is used for bacterial staining, all of the
aggregate components are stained in similar colors, resulting in the
contrast between the bacteria and nonbacterial substances being too low to distinguish between them. Compared with AO staining, DAPI staining provides higher image contrast and is more specific for bacterial staining (12). However, the problems of background
fluorescence also occurred when staining with DAPI. In clay- and
silt-rich sediments, which are rich in detritus and EPS, the background fluorescence by aggregates containing detritus and minerals as well as
bacteria is more intense. When AO and DAPI are used together, under UV
light only the bacteria are vividly seen as blue, and the nonbacterial
substances are orange. For a counterstaining dye, Epstein and Rossel
(9) proposed the use of Evans blue. However, based on our
observations, AO is superior to Evans blue in providing contrast to
bacteria illuminated blue by DAPI. When the sample is not diluted
enough and aggregates accumulate on the filter at a depth greater than
that for proper focus, only part of the cells are in constant focus. In
this context, some bacteria will be masked by both the nonbacterial
substances and background, leading to an underestimation
(18). If this occurs, dual staining can reduce the masking
effect, as image contrast is improved and background is reduced
compared to those with single-staining techniques. Consequently, dual
staining simultaneously overcomes the problems of low contrast in the
AO technique and background in the DAPI technique.
Moreover, dual staining is also useful for the measurement of cell
images. High-color-contrast images allow us to segregate
bacteria more
easily from nonbacterial substances, which are incorrectly
recognized
by a computer. Recent progress in the measurement of
bacterial size has
included automatic threshold determination
systems (
2,
3),
which are faster than the manual threshold
determination method used
here. The high contrast is also helpful
for the problem of dim cells,
which have weak fluorescence and
are difficult (or almost impossible
with the automatic threshold
determination system) to distinguish from
the background by using
only AO or
DAPI.
Effect of dispersion and sediment characteristics.
As already
mentioned, although the bacterial cell counts increase when the masking
effect due to aggregates is decreased by making the treatment time
longer, the longer dispersion time can cause cell destruction. This
cell destruction can result in an unclear cell edge due to the leaking
of protoplasm and lead to the inaccurate measurement of biovolume as
well as abundance. In the present study, cell destruction, which was
indicated by a decline in the bacterial numbers, was observed with the
homogenization treatment but not with the cleaner or sonicator
treatment (Fig. 1). The homogenizer mechanically breaks down sediment
particles into finer ones, resulting in an increased background. Hence, the counting and sizing for a homogenized sample are relatively time-consuming and somewhat subjective compared to those for the other
two treatments. For sonication treatment, no cell destruction has been
reported (5, 9, 10). Epstein et al. (10) showed no cell destruction in the samples with optimal dispersing time based
on the thorough examination of labeled bacteria with radioisotopes. For
cleaner treatment, Ellery and Schleyer (8) reported that cell destruction occurred with a 100- to 200-W output cleaner but not
with our 60-W output cleaner. The main reason for this discrepancy is
probably the difference in the specifications or intensities of the
cleaners. Therefore, there is possible cell destruction in the case of
too-long or too-intense dispersion with the sonicator as well as with
the cleaner.
For the beach sand sediment, the maximum number of dispersed bacteria
was not significantly different among the three dispersion
techniques
(Table
2). However, for the sand flat and mud flat
sediments, the
cleaner was inferior to the other dispersers (Table
2). This indicates
that for the silt- and clay-rich sediments,
where the viscosity (EPS)
was also higher (Table
1), the cleaner
did not efficiently separate the
cells, at least with our low-output
equipment. Nonetheless, differences
in the maximum yield of bacteria
among the dispersion techniques were
not as high as those previously
reported (
9).
For the homogenizer, bacterial counts peaked for the short dispersion
time in all of the sediments, while for the cleaner
and sonicator, the
counts increased as the dispersion time increased
and then leveled off
(Table
2). The pattern of cell counts during
homogenization was similar
to those previously reported (
7,
9) and somewhat different
from the observations of Ellery and
Schleyer (
8) and
Montagna (
15), which were similar to those
for the cleaner
and sonicator. These differences were presumably
due to the advantage
of dual staining. Direct observation of samples
after 0.5 to 2 min of
homogenization revealed that there were
significant numbers of bacteria
in the aggregates. This bacterial
retention in the aggregates was also
observed by Ellery and Schleyer
(
8).
The more dispersed bacteria were observed in the finer-grain sediments.
This tendency has been found by many workers in relation
to sediment
grain surface area (
5,
19), protected habitat
(
22), organic content (
6), grazer regulation
(
11), and
porosity (
19) and need not be discussed
further.
In summary, dual staining has advantages over conventional staining
techniques, especially for silt-, clay-, and detritus-rich
sediments,
by reducing serious background fluorescence. With dual
staining,
bacteria stand out from other objects and can be more
easily counted
and sized. Cleaner and sonicator treatments are
recommended for
dispersing bacteria from aggregates, while homogenization
treatment has
the possibility of cell destruction in the case
of dispersion
treatments that are too long. The cleaner treatment,
however, has the
possibility of insufficient dispersion for silt-
and clay-rich
sediments. Small bacteria (<0.10 µm
3) require a longer
dispersion time to become constant than large
bacteria (>0.10
µm
3). It is concluded that studies of bacterial sizing
need a sufficient
treatment time to disperse small bacteria and to
obtain the real
size
distribution.
| |
ACKNOWLEDGMENTS |
The work was supported in part by a grant from the Environment
Agency of Japan.
We thank E. Miyoshi, E. Kibe, and Y. Hagimoto for their kind assistance
with the physical and chemical analysis; K. Furukawa and M. A. Elzeir for valuable comments, and M. T. Waters for correcting the
English text and helpful comments on the manuscript.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Port and Harbour
Research Institute, 3-1-1, Nagase, Yokosuka 239-0826, Japan. Phone: 81 468 44 5019. Fax: 81 468 44 6243. E-mail:
kuwae{at}cc.phri.go.jp.
| |
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Applied and Environmental Microbiology, August 1999, p. 3407-3412, Vol. 65, No. 8
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
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Uribe, P., Espejo, R. T.
(2003). Effect of Associated Bacteria on the Growth and Toxicity of Alexandrium catenella. Appl. Environ. Microbiol.
69: 659-662
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Abstract
Introduction
