Laboratory for Intensive Care Research and
Optical Spectroscopy, Erasmus University Rotterdam, and Department of
General Surgery 10M1 and Institute of
Medical Microbiology and Infectious Diseases,6
University Hospital Rotterdam "Dijkzigt," 3015 GD Rotterdam,
The Netherlands; Robert Koch Institute, Biophysical Structure
Analyses, 13353 Berlin, Germany2;
UdR INFM Milano-Bicocca, Dipartimento di Biotecnologie e
Bioscienze, 20126 Milan, Italy3; and
Unité MéDIAN, CNRS FRE 2141, IFR 53, UFR de
Pharmacie, Université de Reims Champagne-Ardenne, 51096 Reims
Cedex,4 and Service d'Hygiène
Hospitalière, Center Hospitalier de Versailles, 78157 Le
Chesnay Cedex,5 France
Fourier transform infrared and Raman microspectroscopy are
currently being developed as new methods for the rapid identification of clinically relevant microorganisms. These methods involve measuring spectra from microcolonies which have been cultured for as little as
6 h, followed by the nonsubjective identification of
microorganisms through the use of multivariate statistical analyses. To
examine the biological heterogeneity of microorganism growth which is reflected in the spectra, measurements were acquired from various positions within (micro)colonies cultured for 6, 12, and 24 h. The
studies reveal that there is little spectral variance in 6-h microcolonies. In contrast, the 12- and 24-h cultures exhibited a
significant amount of heterogeneity. Hierarchical cluster analysis of
the spectra from the various positions and depths reveals the presence
of different layers in the colonies. Further analysis indicates that
spectra acquired from the surface of the colonies exhibit higher levels
of glycogen than do the deeper layers of the colony. Additionally, the
spectra from the deeper layers present with higher RNA levels than the
surface layers. Therefore, the 6-h colonies with their limited
heterogeneity are more suitable for inclusion in a spectral database to
be used for classification purposes. These results also demonstrate
that vibrational spectroscopic techniques can be useful tools for
studying the nature of colony development and biofilm formation.
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INTRODUCTION |
In recent years, there
has been much effort invested into the development of new techniques
for the identification of microorganisms. Many of these methods are
aimed at providing the clinician with more rapid identification of the
microorganism responsible for infection in order to begin the
appropriate course of antimicrobial treatment (1, 9, 15, 21, 27,
31, 44, 51). The emergence of these novel methods reflects the
rise in drug-resistant microorganisms, which requires that
antimicrobial treatment be more effectively managed (2, 12, 28,
52). Among the new methods are those based on vibrational
spectroscopic techniques, namely Fourier transform infrared (FT-IR) and
Raman spectroscopies. Vibrational spectroscopic methods are reagentless
procedures in which there is no need to add dyes or labels for spectral
measurement. These nondestructive techniques are based on the
absorption (FT-IR) or scattering (Raman) of light directed onto a
sample. The amount of light absorbed or scattered depends on the
molecules found within the sample and the environment in which these
molecules are found. With these highly sensitive techniques, the
frequency of light in the resulting spectrum provides biochemical
information regarding the molecular composition and molecular structure
of and molecular interaction in cells and tissues (24,
55). Raman and infrared spectroscopies are complementary
techniques which together can provide a more complete impression of the
biochemical information within a sample. Furthermore, these two methods
differ such that each is capable of providing information not easily obtainable by the other. For instance, with FT-IR spectroscopy, hydrated samples are difficult to measure since water absorbs so
strongly that its signal masks other interesting peaks in the spectrum.
On the other hand, water is less problematic in Raman spectroscopy,
enabling measurement of hydrated samples. However, the signal-to-noise
ratio of the resulting Raman spectrum is overall poorer than that
obtained by FT-IR spectroscopy when spectra are measured for the same
amount of time. When these sensitive techniques are coupled to a
microscope, spectra can be acquired from microorganisms cultured for
short periods of time (~6 h) on or from solid culture media since
large biomasses are not required for spectral measurement.
The application of various spectroscopic techniques to identify and
characterize microorganisms has been explored previously (3, 9,
14-16, 20-23, 25-27, 29-35, 37, 42, 49, 54, 56). These
studies have shown that it is possible to discriminate among various
microorganisms at the genus, species, and strain level (14,
21-22, 25, 27, 29-32, 34, 49), and studies report the ability
to differentiate microorganisms from various serogroups (21-23,
37). Furthermore, the use of FT-IR spectroscopy to identify drug
resistance has also been investigated (3, 42). However, many of these previous studies are based on microorganisms cultured for
16 to 24 h or longer prior to spectral measurement. Our research is aimed at developing new rapid methods for the identification and
characterization of clinically relevant microorganisms through the use
of confocal Raman and FT-IR microspectroscopies. Current microbiological diagnostic methods require 2 to 3 days and involve culturing of microorganisms until a suitable biomass is obtained for
subsequent tests. Such methods are inherently slow, especially in
life-threatening situations such as cases of meningitis and sepsis and
for critically ill patients in the intensive-care units of hospitals
(52). With microspectroscopic methods, microorganisms can
be cultured for as little as 6 h prior to spectral measurement. It
is intended that these novel diagnostic methods quickly provide the
clinician with results within the same day that patient samples are obtained.
A critical aspect of these rapid identification methods based on
vibrational spectroscopy is the development of spectral reference databases against which clinical results can be compared in order to
arrive at nonsubjective identification and classification schemes. Not
only must the spectra contained within the database be derived from
rigidly standardized protocols regarding the culturing and measurement
conditions, the database needs to be comprehensive so that it reflects
any kind of intrinsic biological diversity and heterogeneity found
within microorganisms. Our interest in the development of microcolonies
is in regard to the need to understand the heterogeneity of
microorganism growth from the point of view of spectral variance. We
have previously described a Raman method of characterizing cultures
after 6 h of growth (27). In this paper, we present
the investigation of spatial colony heterogeneity and its biochemical
basis in 6-h and older cultures by Raman and FT-IR microspectroscopies.
The findings based on five well-characterized microorganisms after
growing on solid culture medium for various time periods are reported.
For comparison, similar studies were performed using a conventional
approach involving intrinsic fluorescence spectroscopy. From this
investigation, the nature of the variance of spectra derived from these
microorganisms provides insight on the development of microorganisms
grown on solid culture medium.
| |
MATERIALS AND METHODS |
Strains and sample preparation.
A group of five
well-characterized reference strains was obtained from the collection
of the Pasteur Institute (Paris, France) (Staphyloccocus
aureus CIP 4.83, S. aureus CIP 53.154, Escherichia coli CIP 53.126, E. coli CIP 54.8T)
and the American Type Culture Collection (Candida albicans
ATCC 90028). These strains were stored in brain-heart infusion broth
(Becton Dickinson, Paramus, N.J.) containing 10% glycerol at 
80°C
until ready for use. Sample preparation involved one overnight passage
on solid culture medium (to acclimatize the strain), followed by
reculturing of the strain for various incubation times, typically for
6, 12, and 24 h to yield (micro)colonies ranging in size from less
than 50 µm in the short incubation times to as large as 2,000 µm
after the longer culture times. Typical culture conditions for the
bacterial strains involved growing at 37°C on Mueller-Hinton medium
(Merck, Darmstadt, Germany). The yeast strain was cultured at 37°C on
Sabouraud-glucose 2% medium (Merck).
For the Raman studies, a biomass from the overnight passage was used to
streak out the strains in four segments. Following incubation, spectra
were typically acquired directly from microorganisms still growing on
the culture plate of well-isolated (micro)colonies found in the third
or fourth segment.
For the infrared studies, following incubation, microcolonies were
transferred from the agar plate to an infrared, transparent, zinc
selenide optical plate using a specially designed stamping device
(30-32). Imprints were allowed to air dry (approximately 15 min) prior to spectral measurement. Spectra were acquired from the
imprinted microcolonies on this substrate.
For the fluorescence studies, from the incubated plates, colony
imprints were done manually onto glass slides.
Spectral acquisition and data treatment. (i) Raman
spectroscopy.
Raman spectra were acquired using a Renishaw System
1000 Raman microspectrometer (Renishaw PLC, Gloucestershire, United
Kingdom) equipped with a 300-line/mm grating as described previously
(27). The accompanying Leica microscope was fitted with an
80× near-infrared objective (MIR Plan 80×/0.75; Olympus). Raman
signal was collected in the spectral interval from 250 to 2,150 cm
1, with a spectral resolution of 8 cm1. Measurements were performed using 830-nm
excitation from a titanium-sapphire laser (model 3900; Spectra Physics,
Mountain View, Calif.) pumped by an argon ion laser (series 2000;
Spectra Physics) delivering 100 mW of laser power on the sample.
The plates with cultures were taken from the incubator and were placed
directly under the microscope objective for measurements. Firstly, for
each (micro)colony, the diameter and depth were estimated. Thereafter,
various measurement positions were determined to give four equally
spaced lateral positions from the center to the edge of the colony. At
the thicker lateral positions, various depths within the colony were
also selected (Fig. 1). At each
measurement position, five spectra at 30 s were acquired and
averaged. At the very edge and at the bottom of the colony closest to
the culture medium, 10 spectra each at 30 s were acquired and
averaged in order to improve the spectral signal-to-noise ratio. The
depth spectra were acquired beginning from the surface and working
towards the bottom of the colony. Following the deepest measurement, a repeat measurement of the surface was taken as a duplicate check (labeled "rep" in Fig. 1). With the use of a computer-controlled xyz stage, it was possible to determine the lateral and
focusing positions reproducibly.
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FIG. 1.
Schematic representation of the various measuring
positions within a colony for spectra acquired by Raman
microspectroscopy. Letters refer to the lateral measuring positions,
while numbers refer to the depth measuring positions; "rep" refers
to a measurement of the surface position as described in Materials and
Methods.
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Following spectral acquisition, the constant background signal
contribution originating from optical elements in the laser light
delivery pathway was subtracted from all spectra. The reference spectrum of a tungsten-band lamp of known temperature was used to
correct for the wavelength-dependent signal detection efficiency of the
Raman setup (36, 55). Spectral treatment also involved taking the first derivative of the Raman spectra, scaling to standard normal variance (i.e., zero mean and unit variance) and using the
spectral region between 400 and 1,800 cm1 for
further analysis. Despite the use of a confocal arrangement in which
typical measuring volumes were approximately 1.5 µm in the lateral
direction and 7 to 8 µm along the optical axis, there exists the
possibility of sampling the underlying culture medium especially for
measurements toward the bottom of the colony. Therefore, it was
necessary to correct the acquired spectra for the variable underlying
signal of the culture medium using a vector correction approach.
(Details are provided in reference 27. As stated therein, it should be stressed once again that care must be taken in making biochemical interpretations of spectra that were treated with the
vector correction method.) Reduction of data was then performed through
principal-component analysis using the Matlab PLS Toolbox (Eigenvector
Research Inc., Manson, Wash.). The principal-component analysis scores
accounting for 99.9% of the total variance captured were used in a
hierarchical cluster analysis (SPSS, Chicago, Ill.) using Ward's
clustering method and squared Euclidean distance measure.
(ii) Infrared spectroscopy.
FT-IR spectra were recorded on
an FT-IR microscope, model IR Scope II, which was interfaced to an IFS
28/B spectrometer (Bruker Optics, Karlsruhe, Germany) and was equipped
with a motor-driven xy stage. For each spectrum, 256 interferrograms were coadded and averaged. Fourier transformation was
done using a Blackmann-Harris three-term apodization function and a
zero-filling factor of 4, resulting in a nominal resolution of 6 cm1. Spatial heterogeneity of the microcolonies
was examined by linearly mapping the microcolony in 10-µm steps in
the x and y directions and using an aperture size
of 30 µm. The first derivative spectra within the range of 820 to
1,780 cm1 were vector normalized as described
previously (4). Hierarchical cluster analysis was
performed using Pearson's product moment correlation coefficient and
Ward's algorithm.
The infrared measurements were done independently at two different
laboratories. Alternatively, FT-IR absorption spectra were collected
using a UMA 500 infrared microscope coupled to an FTS-40A spectrometer
(Bio-Rad Laboratories, Spectroscopy Division, Hemel-Hampstead, United
Kingdom) and equipped with a mercury-cadmium telluride narrow-band detector and a microscope diaphragm varying from 10 × 10 to 500 × 500 µm2. Measurements on
single microcolonies were performed by setting the microscope aperture
from 60 × 60 up to 100 × 100 µm2.
Absorption spectra were obtained in the microscope transmission mode
using the following parameters: 4-cm1
resolution, 5-kHz scan speed, 32- to 64-scan coaddition, triangular apodization, and spectral range of 800 to 4,000 cm1. No baseline correction or smoothing was
applied to the data. The data was first normalized using the z-score
function (i.e., zero mean and unit variance) in Matlab (The Math Works,
Inc., Natick, Mass.) and then subjected to cluster analysis using
Matlab's Statistics Toolbox employing Ward's algorithm and Euclidean
distance measure.
(iii) Intrinsic fluorescence.
Fluorescence emission signals
from (micro)colony imprints on glass slides were measured by excitation
in the UV wavelength (360 nm) with laser power of 1 µW, using an
argon ion laser (model 2065A; Spectra Physics). Spectra were recorded
using a UV confocal laser microspectrofluorometer (Dilor, Lille,
France). For the UV measurements, an Olympus BH2 microscope containing
a 100× objective was employed. Point-by-point analysis was done using
the spectral imaging acquisition mode, which consisted of scanning the
laser over the (micro)colony by moving the computer-controlled
xy stage. For each (micro)colony, 100 points were collected.
The data gave an emission spectral profile, which in turn produced a
spectral image that can be compared to the conventional optical image. All spectral manipulations were done with the LabSpec software (Dilor).
The spectral profiles obtained were used in a hierarchical cluster
analysis constructed with Ward's method and Euclidean distance measure
(Statistica; Statsoft, Tulsa, Okla.).
| |
RESULTS AND DISCUSSION |
In the development of new routine methods based on vibrational
spectroscopic techniques for the rapid identification of
microorganisms, spectra derived from rigidly standardized protocol are
used to establish a spectral database for the nonsubjective
classification and identification of clinically relevant
microorganisms. Thus, it is imperative that the database be
comprehensive so that the natural variance of the microorganism is
captured within the spectral database. A potential problem is that in
recent years, it is becoming more widely accepted that microorganisms
are not necessarily unicellular organisms but rather multicellular
organisms able to form complex communities with specific division of
tasks and population differentiation (39-41).
Furthermore, it is known that biofilms are elaborate structures composed of microcolonies attached to a surface and that within these
microcolonies, the bacteria are organized into communities with
functional heterogeneity (6). Given that colonies of
microorganisms are complex multicellular communities, it is necessary
to establish at what growth stage infrared and Raman spectra should be
acquired from such (micro)colonies. In so doing, any heterogeneity
which can interfere with the discrimination of microorganisms can be minimized. As the aim of these new methods is to provide the clinician with laboratory results on the same day that patient material is
acquired, the culture time should be kept short: for example, approximately 6 h of growth time. To gain an understanding of the
spectral heterogeneity, the development of (micro)colonies was
monitored over several culture times and at various positions within
the (micro)colonies.
In the discussion to follow, a large part of the analysis is based on
the results of subjecting the data to hierarchical clustering analysis.
This is a procedure that nonsubjectively groups the input cases (i.e.,
the spectra) based on similarities of their properties (the spectral
characteristics). When graphically displayed, the result of the
analysis forms a dendrogram; the relationship between the input cases
is represented by the distance at which they connect on a dissimilarity
scale (e.g., Fig. 2A). The more similar
the cases are, the smaller their connecting distance on the
dissimilarity scale. Dendrograms resemble the phylogenetic trees that
arise from taxonomic classification. Groups of similar members can be
readily visualized. Since the spectral information reflects the
biochemistry of the sample measured, the distance in the dendrograms
can be interpreted as a measure of how biochemically different the
various spectra are and, hence, the measurement positions within a
colony.
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FIG. 2.
(A) Dendrogram of hierarchical cluster analysis of UV
(360 nm)-excited intrinsic fluorescence spectra (derived from the
spectral image after filtering) of an E. coli CIP 54.8T
microcolony imprint. Spectra were acquired from various positions
within the peripheral, intermediate, and central regions of the
microcolony imprint. (B) Averaged intrinsic fluorescence spectra
corresponding to spectra acquired from the central ( ), intermediate
(- - - -), and peripheral (. . . . . .) regions of
the microcolony imprint. a.u., arbitrary units.
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Fluorescence of colony imprints.
As a starting point in the
investigation of (micro)colony heterogeneity, an approach involving
fluorescence microspectrometry was first employed. A series of
UV-excited intrinsic fluorescence spectra were acquired from a
microcolony imprint of E. coli CIP 54.8T cultured for 6 h. The spectra were normalized to account for possible differences in
intensity due to variation in the thickness of the microcolony imprint.
Subjecting the data to hierarchical cluster analysis revealed that the
intrinsic fluorescence was not homogeneously distributed over the
microcolony. As shown in the dendrogram in Fig. 2A, the spectral
profiles from the various positions within the imprint form their own
subclusters (central, intermediate, and peripheral). When the averaged
fluorescence spectrum from each subcluster is examined (Fig. 2B), the
various spectra are quite similar. The average spectrum from the center of the microcolony has an emission wavelength maximum of 442 nm. In
contrast, the spectra corresponding from the intermediate and peripheral regions have a broader spectral profile with a flatter maximum, possibly corresponding to the superposition of two maxima at
442 and 451 nm. Despite these differences, further information regarding the compositional heterogeneity of the various regions could
not be directly obtained from the intrinsic fluorescence data. Hence,
other methods were required.
Infrared spectra of (micro)colony imprints.
In order to gain a
further understanding of the biochemical heterogeneity of
(micro)colonies, vibrational spectroscopic techniques were employed.
Hierarchical cluster analysis of FT-IR spectra acquired from colonies
of E. coli CIP 54.8T which were 100 µm or larger in
diameter produced a dendrogram similar to that shown in Fig. 2A,
with the spectra tending to cluster into different groups depending
upon the measurement position within the colony (not shown for
brevity). By examining the individual infrared spectra and calculating
difference spectra, it is possible to gain a better understanding of
the source of the clustering scheme observed. In Fig.
3A, the FT-IR spectra acquired from the
center and edge of an E. coli CIP 54.8T colony are shown.
Although to the untrained eye these two spectra look remarkably
similar, any differences that exist can be highlighted by taking
difference spectra. The difference spectrum which results from
subtracting the spectrum of the edge from that of the center is shown
as well as the difference obtained from subtracting the
first-derivative spectra from the two measuring positions. Since
infrared bands tend to be quite broad, thereby potentially masking peak
differences, the differences are more apparent in the derivative
spectra. Comparison of the peak positions with those from empirical
studies in the literature (24) reveals differences in the
spectral region around 1,230 cm1 which can be
assigned to the phosphate double-bond asymmetric stretching vibration
of phosphodiester, free phosphate, and monoester phosphate functional
groups. Smaller alterations are also observed in the protein amide I
regions (approximately 1,620 to 1,670 cm1).
This band arises predominantly from the C==O stretching vibration of
the amide C==O groups of proteins. Furthermore, changes visible around
1,400 cm1 may be attributed to the symmetric
stretching vibrations of COO functional groups,
and very weak changes were observed in the carbohydrate region around
900 to 1,200 cm1. Similar changes were observed
for the other bacterial and yeast strains (35), although
the changes were more pronounced in the yeast strains (Fig. 3B).
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FIG. 3.
Original FT-IR spectra from a 100-µm-diameter
E. coli CIP 54.8T colony (A) and a 100-µm-diameter
C. albicans ATCC 90028 colony (B) measured at the center
(1) and edge (2) positions of the colony. The corresponding difference
spectrum (magnification, ×5) (3) between center and edge is shown, as
well as the difference spectrum (magnification, ×2) (4) obtained from
the first-derivative spectra. The difference spectra were obtained by
1-to-1 subtraction of vector-normalized spectra (normalization between
820 and 1,780 cm1). a.u., arbitrary units.
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Interestingly, in a separate study measuring FT-IR spectra from 12-h
colonies of the two E. coli strains (CIP 54.8T and 53.126), heterogeneity between spectra acquired from the center and edge of a
colony was large enough to influence the discrimination between the
different strains. As shown in Fig. 4A,
the spectra arising from the two strains formed mixed clusters.
However, when spectra acquired from younger colonies (approximately
7 h of culture time) were subjected to cluster analysis, two major
clusters were formed corresponding to the different strains (Fig. 4B).
These results suggest that with the older colonies, there is
significant heterogeneity in the spectra from various positions within
the colony. Similar studies performed with 50-µm-diameter
colonies or growth time of about 6 to 7 h revealed that there was
very little variance in the infrared spectra sampled from the center or
periphery of the colony. Therefore, it appears that until 6 to 7 h
of growth, there is very little heterogeneity observed in the
composition of microcolonies. However, beyond this time frame, marked
biochemical differences which vary from the center to the periphery of
the colony, such as changes in the protein amide I bands, phosphate moieties likely arising from nucleic acids, protein constitution, and
carbohydrate moieties, are noted. These differences likely influence
the classification results observed (Fig. 4A and B).
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FIG. 4.
Dendrogram from hierarchical clustering analysis of
FT-IR spectra of 12-h cultures (A) and 7-h cultures (B) of E.
coli CIP 54.8T (denoted by x) and E.
coli CIP 53.126 (denoted by o). a.u.,
arbitrary units.
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Raman spectra directly from (micro)colonies.
With infrared
microspectroscopy, spectra were acquired through the entire depth of
the colony at the central, intermediate, and peripheral regions.
However, with this approach, any heterogeneity arising from various
depths within the colony would not be readily revealed. Insight into
the heterogeneity of microcolonies can also be obtained from confocal
Raman microspectroscopy, in which spectra can be acquired from the
various lateral positions throughout the colony as well as at various
depths within the colony. The Raman spectra acquired in this manner
were subjected to hierarchical cluster analysis. In Fig.
5A, the results are shown for spectra acquired from 6-h cultures. Visual inspection of the dendrogram revealed no obvious groupings or clusters. This observation is in
accordance with the infrared findings for 6-h colonies, thereby suggesting that at this growth stage, the cultures are quite
homogeneous overall. Such observations were apparent irrespective of
the strain studied.
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FIG. 5.
Dendrograms from hierarchical cluster analysis of Raman
spectra from various measurement positions within a 6-h E.
coli CIP 53.126 microcolony (A) and a 24-h E.
coli CIP 53.126 colony (B). Shading highlights the various
clusters and corresponds to the shading in Fig. 6. The labels
correspond to the measuring positions in the schematic diagram of Fig.
1 and 6. a.u., arbitrary units.
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Unlike the dendrograms obtained for 6-h cultures, the dendrograms of
spectra acquired from microorganisms grown for 12 and 24 h showed
distinct subclusters (Fig. 5B). When the members of the same cluster
were assigned to a group and the various groups were projected onto a
schematic diagram depicting the measurement location of each spectrum,
it appears that there are different layers in the 12- and 24-h colonies
(Fig. 6). Similar findings were observed
for the various strains studied for 12- and 24-h cultures. Further
examination of the spectra indicates that for S. aureus CIP
4.83, the clustering differences arise from distinct spectral peaks at
1,004, 1,158, and 1,522 cm1, which can be
assigned to the various C---C vibrations found in carotenoids
(Fig. 7) (29, 30, 33, 54).
The clustering reveals that the carotenoid concentration is higher
within the upper layers of the colony and less prominent in the deeper
layers. Carotenoids are responsible for the yellow-orange pigmentation observed in the 12- and 24-h colonies and are one of the classical characteristics of this species. Studies have shown that S. aureus is very sensitive to the bactericidal effects of fatty
acids, such as oleic acid. The incorporation of such lipophilic agents into the membranes results in increased membrane fluidity and thus in a
decrease in membrane-associated functions (5). It is
believed that the production of carotenoids might help S. aureus stabilize its cell membrane, thereby preventing
potentially lethal fatty acid-induced changes in the fluidity of its
membrane (5). Other studies have also shown that pigmented
S. aureus strains are far more resistant to singlet oxygen
lethality than are carotenoidless S. aureus mutants
(8). Hence, the bacterium might use the carotenoid pigmentation as a mechanism to resist killing by fatty acids and to
quench singlet oxygen, thus protecting against lethal effects of
photosensitization. Previous studies (18) have shown that the carotenoid production is mainly correlated with the time of growth,
and this finding has also been observed by FT-IR spectroscopy (29). Therefore, it might signify that older cells which
produce significant pigmentation are found towards the surface layers of the colony. Alternatively, our finding of higher carotenoid concentration in the upper layers of older colonies might suggest a
means by which the colony protects itself from its environment.
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FIG. 6.
Diagrammatic projection of the various clusters (*,
cluster 1;  , cluster 2;  , cluster 3; as determined from Fig. 5)
from the hierarchical cluster analysis of Raman spectra from various
measurement positions within a 24-h E. coli CIP 53.126 colony. Shading is used to highlight the various layers within the
colony.
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FIG. 7.
Averaged Raman spectra of the members of cluster 1 (surface layer) (A) and cluster 2 (layer beneath surface) (B) and the
corresponding difference spectrum (A and B) from a 24-h colony of
S. aureus CIP 4.83 (C) are shown. a.u., arbitrary
units.
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Interestingly, the Raman spectra of the other S. aureus
strain, CIP 53.154, showed that this strain does not produce the
characteristic pigmentation. Nonpigmented derivatives of S. aureus are known to exist and are often found in subcultures of
stored organisms (53). The cluster analysis shows a
similar sort of distinction, with spectra acquired from the surface
layers clustering together and those within deeper layers clustering as
a group. However, the lack of pigmentation suggests that another
spectral feature is responsible for the formation of distinct clusters.
This clustering trend was found for S. aureus CIP 53.154, E. coli CIP 53.126, E. coli CIP 54.8T, and
C. albicans ATCC 90028. Closer examination of the
Raman difference spectra showed that in the deeper layers of 12- and
24-h colonies, there are characteristic spectral peaks at 723, 783, 813, and 1,575 cm1 (Fig.
8). These features all arise from the
nucleotide and phosphate backbone vibration found in RNA
(19). It appears that the RNA concentration is higher in
the deeper layers of the colony. Observations of the decrease in RNA
content in older cells which have transitioned to the stationary phase
from the logarithmic phase have been reported with FT-IR spectra of
Bacillus subtilis (29). Hence, this finding again suggests that the colony is composed of older cells in the surface layers and younger cells in the deeper layers which are more
actively dividing, thus reflecting a higher RNA content.
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FIG. 8.
Averaged Raman spectra of the members of cluster 2 (layer beneath surface) (A) and cluster 3 (deeper layer) (B) and the
corresponding difference spectrum (A and B) from a 24-h colony of
E. coli CIP 54.8T (C) are shown. The Raman spectrum of
RNA (D) is also shown. a.u., arbitrary units.
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Aside from RNA differences, it was noted that 12- and 24-h colonies
from the bacterial strains contain a relatively higher glycogen
concentration in the surface layers (Fig.
9). This glycogen difference is not
observed with younger 6-h bacterial microcolonies (Fig.
10) or with the yeast strain. At
present it is unknown whether the glycogen is contained within the
cells of the surface layers or found extracellularly in the form of a
film. Previous FT-IR studies have also found increases in the
carbohydrate C---O stretching mode of 24-h cultures of
Bradyrhizobium japonicum strains which have been transferred
from liquid to solid culture medium. From transmission electron
micrographs, the authors ascribed such changes to alteration of the
bacterial wall component, possibly the formation of glycocalyx
(56). The organization of colonies into distinct layers
has also been observed with E. coli strains (cultured for 2 weeks) in which vertical sections through colonies revealed a
stratification of different cell types, as could be seen with standard
microscopic reagents, such as staining with toluidine blue
(41). Previous reports in the literature using scanning electron microscopy to study the surface structure of E. coli colonies growing for over 24 h on agar medium in normal
petri dishes have revealed that each colony secretes extracellular
materials, some of which form a skin or framework over its surface
(38-39). Other studies have shown that at later stages of
colony development (20 to 24 h), the surface film of E. coli colonies became thicker. On the other hand, the film was not
observed for colonies cultured for 6 to 16 h of growth
(45-48). Therefore, it is possible that the glycogen-rich
surface layer observed with Raman microspectroscopy is the
polysaccharide-rich extracellular coat, commonly known as the
glycocalyx, of bacterial cells. These exopolysaccharides are mainly
composed of homopolysaccharides (cellulose, levans, dextrans, and
glucans) and heteropolysaccharides (monosaccharides including a
uronic acid) (43). It is thought that the formation of the glycocalyx serves as an integral matrix for a biofilm and that
following the adhesion of bacteria to a substrate, the glycocalyx forms
a protective milieu for cell division and microcolony formation and
growth (7, 11). Some studies propose that the glycocalyx either acts as a diffusion barrier or, by complexing antibacterial agents, excludes and/or influences the penetration of antimicrobial agents to the underlying cells (10, 13). Modern medicine
increasingly relies on the use of indwelling medical devices such as
catheters and prosthetic joints for multiple purposes. These so-called
foreign bodies are implanted for a short period, intermittently or
permanently. One of the most frequently encountered complications of
these devices is the development of infections. The ability of bacteria to adhere to the surface of these indwelling devices by binding to
biofilm layers is still not completely understood (H. P. Endtz, personal communication). Hence, there is much interest in the development of biofilms, associated with disease in humans due to the
increasing use of medical devices and the difficulty, resulting from
resistance to antimicrobial agents, of effectively controlling infection (6, 13, 17).
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FIG. 9.
Averaged Raman spectra of the members of cluster 1 (surface layer) (A) and cluster 2 (layer beneath surface) (B) and the
corresponding difference spectrum (A and B) from a 24-h colony of
E. coli CIP 53.126 (C) are shown. The Raman spectrum of
glycogen (D) is also shown. a.u., arbitrary units.
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FIG. 10.
Raman spectra are shown from different depths
corresponding to the measuring positions in the schematic diagram of
Fig. 1, with A1 from the surface (A) and A3 from deeper within the
colony (B) and the corresponding difference spectrum (A and B)
from a 6-h microcolony of E. coli CIP 53.126 (C). a.u.,
arbitrary units.
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Overall, these infrared and Raman studies of the development of
microorganisms cultured for various growth times reveal that there is
significant colony heterogeneity in the strains cultured for 12 and
24 h. These differences can be attributed to higher glycogen
content in the surface layers and to increased levels of carotenoid
pigmentation in certain S. aureus strains. Furthermore, a
relatively higher RNA content was observed in the deeper layers of the
colony. Therefore, spectra derived from these older colonies are quite
variable, indicating the need to sample spectra from a multitude of
positions within these colonies in order to capture the biological
variance of the various cell types. The lack of group clusters and
absence of obvious spectral differences in the various spectra obtained
from 6-h cultures suggest that the microcolonies at this growth stage
are very homogenous in terms of molecular composition. Thus, these
spectra are suitable for inclusion in and building of spectral
libraries of microorganisms. With the development of a comprehensive
spectral database, it should be possible to use Raman and FT-IR
microspectroscopies to provide rapid identification and classification
of clinically relevant microorganisms. Moreover, the present study
demonstrates that vibrational microspectroscopy can be applied to
further understand the heterogeneity of microorganism growth. For
example, the attachment and microcolony formation of biofilms, as well
as the actual mechanisms of biofilm resistance to antimicrobial agents,
still remain unclear (13). FT-IR spectroscopy, including
attenuated total reflectance spectroscopy, has been used previously to
study bacterial growth and biofilm formation (56). The use
of Raman microspectroscopy to probe various layers within a colony can
be extended to study the formation of sessile communities found at the
base of the biofilm. These sessile cells are believed to be the root of
many persistent and chronic bacterial infections since they can
withstand host immune responses, unlike their nonattached planktonic
counterparts which are killed by antibiotic therapy (6).
The knowledge gained from such studies can be used to develop new
strategies for the treatment of infection, especially those associated
with indwelling medical devices.
We gratefully acknowledge financial support from the European
Union Biomed II program, Project No. BMH4-97-2054.
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Abstract
Introduction
