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Journal of Clinical Microbiology, July 2001, p. 2513-2517, Vol. 39, No. 7
0095-1137/01/$04.00+0 DOI: 10.1128/JCM.39.7.2513-2517.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
Standardization of Antifungal Susceptibility
Variables for a Semiautomated Methodology
Juan L.
Rodríguez-Tudela,*
Manuel
Cuenca-Estrella,
Teresa M.
Díaz-Guerra, and
Emilia
Mellado
Servicio de Micología, Centro
Nacional de Microbiología, Instituto de Salud Carlos III,
28220 Majadahonda, Spain
Received 22 January 2001/Returned for modification 2 April
2001/Accepted 13 May 2001
 |
ABSTRACT |
Recently, the methodology that will serve as a basis of the
standard for antifungal susceptibility testing of fermentative yeasts
of the European Committee on Antibiotic Susceptibility Testing has been
described. This procedure employs a spectrophotometric method for both
inoculum adjustment and endpoint determination. However, the
utilization of a spectrophotometer requires studies for
standardization. The present work analyzes the following parameters: (i) accuracy of inoculum preparation, (ii) correlation between optical
density and CFU per milliliter, (iii) influence of the wavelength on
the endpoint determination, and (iv) influence of the dimethyl
sulfoxide concentration on the growth kinetics. The main results can be
summarized as follows: (i) inoculum preparation following the
methodology recommended by the National Committee for Clinical
Laboratory Standards is an exact procedure; (ii) the relationship
between optical density and CFU per milliliter is linear (coefficient
of determination, r2 = 0.84); (iii) MICs
obtained by means of spectrophotometric readings at different
wavelengths are identical (for amphotericin B, an intraclass
correlation coefficient of 0.98 was obtained; for fluconazole, the
intraclass correlation coefficient was 1); and (iv) a 2% concentration of dimethyl sulfoxide produces a significantly slower and lower growth
curve of Candida spp. than other concentrations.
 |
INTRODUCTION |
The standardization process of
antifungal susceptibility testing is in progress. The Subcommittee for
Antifungal Susceptibility Testing of the National Committee for
Clinical Laboratory Standard (NCCLS) has published an approved standard
for yeasts (document M27A) (2). In Europe, another
organization, the European Committee on Antibiotic Susceptibility
Testing, has a Subcommittee for Antifungal Susceptibility Testing
(EUCAST-AFST) that is working on this matter. Recently, the methodology
that will serve as a basis of EUCAST-AFST's proposed standard was
described (1). The NCCLS document M27-A recommends
the spectrophotometric method for inoculum preparation and visual
reading for endpoint determination (2). The visual reading
is an important source of variability and inaccuracy due to the
trailing phenomenon, which is caused by the partial inhibition of
fungal growth that is observed with fungistatic agents. The proposed
EUCAST-AFST methodology will also recommend a spectrophotometric method
for inoculum preparation, and the reading of the microtitration plates
will be performed by means of a spectrophotometer in order to overcome
the limitations of visual reading. However, information regarding the
use of these devices for antifungal susceptibility testing is limited
and some variables could have an influence on both inoculum preparation
and endpoint determination.
The aim of the present work was to study several parameters implicated
in the use of spectrophotometers and related to antifungal susceptibility testing. Briefly, in a first set of experiments the
accuracy of inoculum preparation by the spectrophotometric procedure
was evaluated. Secondly, we analyzed the correlation between the
optical density obtained by spectrophotometric reading and the CFU per
milliliter that the microbiological cultures yielded. This experiment
was designed to evaluate the limitations of spectrophotometrical procedures when especially dense or light inocula are utilized. In a
third set, we assessed the influence on the endpoint determination of
the wavelength employed in the experiment. In addition, we employed a
spectrophotometric method to examine the influence of dimethyl
sulfoxide (DMSO) on the growth kinetics of yeasts. DMSO is the solvent
which is usually employed when stock solutions of antifungal agents are
prepared. The details of these analyses and their implications are the
subject of this work.
 |
MATERIALS AND METHODS |
Strains.
Two panels of strains were used in the experiments:
(i) a reference panel formed of Candida parapsilosis ATCC
22109 (2), Candida krusei ATCC 6258 (2), Candida tropicalis MY1012
(3), Candida albicans ATCC 64550 (5), C. albicans ATCC 64548 (5), Candida glabrata ATCC 90030 (2), Candida
lusitaniae CL 2819 (3), and Saccharomyces
cerevisiae ATCC 9763 and (ii) a clinical panel constituted of 60 clinical strains. The majority of these isolates (n = 44) were obtained from blood cultures, and the remainder were
obtained from specimens from deep sites. Isolates were identified by
routine microbiological techniques and were maintained at
70°C. The
clinical panel was composed of 10 isolates of each of the following
species: C. albicans, C. parapsilosis, C. tropicalis, C. glabrata, C. krusei, and C. lusitaniae. In some
experiments all strains were included. In others, a selected sample
from the panels was used.
Assay media.
RPMI-2% glucose is RPMI 1640 medium without
sodium bicarbonate and with L-glutamine (Oxoid, Madrid,
Spain). It was buffered to pH 7.0 with 0.165 M
morpholinepropanesulfonic acid and supplemented with 18 g of
glucose per liter to reach a final concentration of 2%. Media were
prepared as a double-strength solution and sterilized by filtration.
Accuracy of inoculum preparation. (i) Strains.
In this
experiment the entire clinical panel, which comprised 60 isolates, was used.
(ii) Inoculum preparation.
The yeast isolates were grown on
Sabouraud dextrose agar (Oxoid) for 24 h at 35°C. The inoculum
preparation followed the directions of document M27-A of the NCCLS
(2). Thus, the optical density (OD) of a 0.5 McFarland
standard (Izasa, Madrid, Spain) at 530 nm (OD530) was
measured five times on different days. The range obtained was between
0.11 and 0.14. Therefore, a suspension of each of the yeasts in sterile
distilled water was adjusted in a Bausch & Lomb spectrophotometer
(Pacisa S.A., Madrid, Spain) to that OD530 range. Then,
this adjusted suspension was diluted 1:10, 1:100, and 1:1,000 in
sterile distilled water. A 50-µl aliquot of each one of these
dilutions was delivered through Autoplate 4000 (Spiral Biotech, Inc.,
Bethesda, Md.) onto Sabouraud agar. The next day the colony enumeration
was performed by means of an automated colony counter (CIA-BEN 2.0;
Spiral Biotech, Inc.).
Correlation between the OD and CFU per milliliter. (i)
Strains.
In this experiment 30 strains from the clinical panel
were used, 5 each of the following species: C. albicans, C. tropicalis, C. parapsilosis, C. glabrata, C. krusei, and C. lusitaniae. Testing of twelve strains was repeated twice.
(ii) Preparation of Candida suspensions.
For
each of the strains 14 suspensions in sterile distilled water were
prepared in a Bausch & Lomb single-beam spectrophotometer (SPEC A)
(light path, 20 nm; Spectronic 20D; Pacisa S.A.). The suspensions were
adjusted as closely as possible to the following OD530s:
0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, and
1.4. From each of these suspensions appropriate dilutions in sterile
distilled water were prepared. Fifty microliters was delivered with the
Autoplate 4000 (Spiral Biotech, Inc.) onto Sabouraud agar. The next day
the colony enumeration was performed by means of an automated colony
counter (CIA-BEN 2.0; Spiral Biotech, Inc.). In addition, 200 µl of
each suspension was deposited into the wells of a 96-well flat-bottom
microtitration plate in order to perform a new measurement of OD but
using a microdilution procedure. The OD530 of each of the
wells was recorded in a spectrophotometer for microtitration plate
reading (SPEC B) (light path, 18 ± 2 nm; Dinex MRX II; Cultek,
Madrid, Spain).
Influence of the wavelength on the MIC endpoint estimation. (i)
Strains.
The same panel employed in the experiment regarding the
correlation between OD and CFU/ml was used. In addition, C. parapsilosis ATCC 22019 and C. krusei ATCC 6258 were
used as quality control strains.
(ii) AST.
Antifungal susceptibility testing (AST) was
performed following the proposed standard of EUCAST (1).
Two antifungals were used, amphotericin B (Fluka, S.A., Madrid, Spain)
and fluconazole (Pfizer S.A., Madrid, Spain). Stock solutions were
prepared in 100% DMSO (Sigma-Aldrich Química, Madrid, Spain)
at concentrations 100 times the highest concentration to be tested and
were frozen at
70°C until used. Sterile plastic microtitration
plates containing flat-bottom wells were utilized. The plates contained
twofold serial dilutions of the antifungal drugs and two
drug-free-medium wells for sterility and growth controls, and each well
was inoculated with 100 µl of the final inoculum. Each isolate was
subcultured on Sabouraud dextrose agar plates at 35°C for 24 h
prior to testing. The final quantity of inoculum was 0.5 × 105 to 2.5 × 105 CFU/µl. The
microtitration plates were incubated at 35°C for 24 h in a humid atmosphere.
The MICs were determined at 24 h spectrophotometrically at the
following wavelengths: 340, 450, 530, and 690 nm. For amphotericin B,
the endpoint was defined as the minimal antifungal concentration that
exerts 90% growth inhibition compared with the control well growth.
For fluconazole, the endpoint was defined as the minimal antifungal
concentration that exhibited 50% growth inhibition compared with the
control well growth. The OD of the blank was subtracted from the OD of
all wells. The MICs were compared to ascertain if they were equivalent.
Influence of DMSO concentration on the growth of yeasts. (i)
Strains.
For this experiment the following strains were included:
C. parapsilosis ATCC 22109, C. krusei ATCC 6258, C. tropicalis MY1012, C. albicans ATCC 64550, C. albicans ATCC 64548, C. glabrata ATCC 90030, C. lusitaniae 2819, and S. cerevisiae ATCC 9763.
(ii) GKs.
In the next set of experiments, we measured growth
kinetics (GKs). The GKs of the eight strains were determined by the
microdilution format in RPMI-2% glucose containing three different
concentrations of DMSO: 2, 1, and 0.5%. A control growth medium
without DMSO was used in all experiments. The final yeast inoculum was
between 0.5 × 105 and 2.5 × 105
CFU/ml. Trays were inoculated (200 µl per well) and sealed with a gas
permeable sealing membrane for microtitration plates (Breathe Easy
Membrane; Sigma-Aldrich Quimica). The microplates were incubated for
48 h at 35°C inside a Labsystems IEMS Reader MFplate
(Labsystems, Madrid, Spain). The reader carried out an hourly
spectrophotometric reading at a wavelength of 540 nm. The hourly
spectrophotometric readings were saved and analyzed with the software
package Ascent Research Edition, version 2.1 (Labsystems). Curves were
constructed with the help of the Sigmaplot (version 5.0) graphs package
(SPSS S.L., Madrid, Spain).
Statistical analysis.
The significance of the differences in
the GKs and AST between methodologies was determined by the Student
t test (unpaired; unequal variance) or by the Mann-Whitney U
test. Differences in proportions were determined by Fisher's exact
test or by chi-square analysis. A P value of <0.01 was
considered significant.
The OD in the drug-free well must be >0.2 to calculate the
spectrophotometric MICs. The mean of the absorbance of eight sterility
control wells was subtracted from the absorbance value obtained
from
each well, and then spectrophotometric MICs were calculated.
The
reproducibility of the results for each reading at a different
wavelength was evaluated by an intraclass correlation coefficient
(ICC), which compared the MICs obtained at four different wavelengths
(340, 450, 530, and 690 nm). Reproducibility was calculated by
means of
a scales analysis, where reliability was the extent to
which endpoint
determinations yielded the same MICs over time.
The ICC assesses
reliability as an internal consistency statistic
by means of interitem
correlations. A two-way mixed effect model
was utilized to calculate
the ICC that was expressed over a maximum
value of 1 and with a
confidence interval of 95% (
1). All statistical
analyses
were done with the Statistical Package for the Social
Sciences (SPSS,
version 10; SPSS S.L.).
 |
RESULTS |
Accuracy of inoculum preparation.
Table 1
shows the results obtained with inoculum
preparations. Suspensions adjusted to OD530s ranging from
0.119 to 0.140 produced inocula containing 1 × 106 to
6.2 × 106 CFU/ml. The dilutions 1:10, 1:100, and
1:1,000 contained a number of CFU per milliliter inside the expected
values (Table 1). The 99% confidence interval for the CFU per
milliliter is very narrow, indicating the precision of this procedure.
Correlation between the OD and CFU per milliliter.
A Bausch & Lomb spectrophotometer was employed for the adjustment of the inoculum
suspension (SPEC A). Then, from each suspension 200 µl was deposited
in the corresponding wells of a flat-bottom microtitration plate and
the OD530 was measured by a spectrophotometer designed for
this procedure (SPEC B). In Table 2, the
equivalence among the OD530s detected by both
spectrophotometers and the corresponding CFU per milliliter for all
species together is shown. The values in SPEC B were somewhat lower
than those in SPEC A. The different volumes used (5 versus 0.2 ml) can
explain the different OD values obtained. The correlation between OD
values in SPEC A and SPEC B was excellent (coefficient of determination
[r2] = 0.96). A range of OD530s of
0.11 to 1.43 produced suspensions containing 1.48 × 106 CFU/ml to 3.72 × 109 CFU/ml (Table
2). The relationship was linear with an r2 of
0.84 (Table 3 and Fig.
1). The equation of this linear
regression was as follows: log10 CFU/ml = 6.57 + 1.69 OD530 (SPEC A).
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TABLE 3.
Coefficients of determination and coefficients of the
linear regression equation log10 CFU/ml = log10 Y0 + aOD530 for Candida
spp.a
|
|

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FIG. 1.
Linear regressions obtained between log10
CFU/ml counting and OD530 measured in a single-beam
spectrophotometer (SPEC A) and a device for microdilution procedures
(SPEC B). Graphs were constructed with data from 30 isolates. (Left
panel) The linear regression equation is log10 CFU/ml = 6.57 + 1.69 OD530 (SPEC A); the coefficient of
determination is r2 = 0.84. (Right panel)
The linear regression equation is log10 CFU/ml = 6.85 + 1.90 OD530 (SPEC B); the coefficient of
determination is r2 = 0.79.
|
|
Similar values were obtained for SPEC B. Thus, the
r2 was 0.79 and the formula of the equation was
log
10 CFU/ml = 6.85 + 1.90
OD
530
(SPEC B) (Table
3 and Fig.
1). Table
3 also displays the
r2 and the coefficients of the linear regression
equation for each
Candida species analyzed. For SPEC A, all
r2 values were

0.81, and for SPEC B they were

0.79.
Influence of the wavelength in the MIC endpoint estimation.
Thirty isolates plus two quality control strains were employed in this
experiment. Readings for quality control strains were repeated five
times on different days. The influence of MICs for amphotericin B and
fluconazole read at different wavelengths was analyzed. Table 4
shows the range of MICs for each species
and antifungal agent. For fluconazole, the MICs were identical
irrespective of the wavelength used (ICC = 1). For amphotericin B, MICs
were identical for 27 strains. In two isolates a variation of one
twofold dilution was obtained, and in one strain the range observed was 0.06 to 0.25 µg/ml. Despite this fact, the ICC value was 0.98 with a
95% confidence interval of 0.97 to 0.99.
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[in a new window]
|
TABLE 4.
Range of MICs read at different wavelengths for
amphotericin B and fluconazole for 30 strains of Candida
spp.
|
|
Influence of DMSO concentration on the growth of yeasts.
Figure 2 displays the GKs of eight ATCC
strains in RPMI-2% glucose at different DMSO concentrations. The
kinetics of growth are similar for all DMSO concentrations except at
2%. This concentration produced a significantly slower and lower
growth curve in all species tested.
 |
DISCUSSION |
The calculation of endpoint by spectrophotometric procedures
presents some advantages over visual reading. The OD values stored in
the computer make data analysis and endpoint reading truly quantitative, more flexible, and objective. Thus, a dose-response curve
can be displayed for each isolate tested in addition to the MIC
endpoint. In addition, the MIC obtained by visual determination is
immovable; therefore the in vitro-in vivo correlations applied for
obtaining breakpoints are managed by a fixed value. OD data stored in a
computer can be calculated following different approaches, taking into
consideration the clinical outcome of the patient infected by this
particular strain. A clear example of this fact is shown in two recent
works (4, 6). Rex et al. (4) showed that
isolates with trailing growth in response to fluconazole could be
identified as resistant by the NCCLS methodology. However, if the MIC
was determined at 24 h and the endpoint required a less
restrictive criterion (50% reduction in growth instead of 80%), MICs
were better matched with in vivo response. This work was performed in a
murine model of invasive candidosis, and many of the MICs were
determined spectrophotometrically. The data stored in the computer
allowed different calculations without the need for further testing. In
addition, the dose-response curves shown in this work added a better
interpretation of the animal model outcome (4). Warn et
al. (6), following a similar reading approach, obtained
similar conclusions and better chances to interpret the susceptibility
testing results. In addition, the spectrophotometer was also used for
inoculum adjustment (1, 2). However, this device can be a
source of variability in results and thus a standardization process is
mandatory. In the present work, information about parameters influencing AST methodology has been obtained. Inoculum adjustment following the recommendations of the NCCLS document M27-A is an exact
procedure. Table 1 shows the OD530 that can be used for preparation of the inoculum suspensions. Confidence intervals for 95 and 99% indicated the precision of this methodology.
There is controversy about the equivalence among different
OD530 values and CFU per milliliter. Our data show that
SPEC A and SPEC B could not detect counts of CFU per milliliter of less than 106. However, above this number of CFU per milliliter
there was a linear relationship between OD530 and numbers
of CFU per milliliter (r2 = 0.84 for SPEC
A, and r2 = 0.79 for SPEC B [Table 3 and
Fig. 1]). Two linear regression equations were obtained and they could
be used for calculating the number of CFU per milliliter at any
OD530 between 0.11 and 1.43 for SPEC A and between 0.06 and
1.34 for SPEC B (Table 3).
Another point of discussion is the wavelength designed for reading the
microtitration plates. The rational approach is to use the same
wavelength as that employed for adjusting the inoculum. Unfortunately,
a 530-nm filter is unusual and normally must be especially ordered.
This fact raised the question of whether the use of different filters
produces different MICs. The antifungal agents chosen represent two
different ways of endpoint determination. Thus, a 90% inhibition
coefficient was the endpoint for amphotericin B whereas a 50%
inhibition coefficient was the endpoint for fluconazole. The results
indicated that wavelength does not have any influence on the MIC. For
amphotericin B the ICC was 0.98, and for fluconazole it was 1. In
conclusion, any wavelength can be used for reading microtitration
plates. Shorter wavelengths produce a higher OD for a blank well, and
longer wavelengths produce the opposite. Therefore, the OD of the blank
control well must be subtracted from all inoculated wells.
Finally, a 2% concentration of DMSO produced slower growth of all
isolates tested. Lower concentrations did not have any significant influence. The NCCLS and EUCAST-AFST methodologies use 0.5% as the
final concentration of DMSO. Although 1% could be used, it is
recommended to employ the lower concentration that maintains the
hydrophobic antifungal drugs dissolved.
In summary, this work complements a previous one (1). In
that work, a proposition of a semiautomated methodology was described. This technique will be the basis of the standard proposition of EUCAST-AFST. In the present study, several variables have been analyzed
and standardized. Useful information for a better understanding of the
use of spectrophotometers as an aid for antifungal susceptibility testing is achieved.
 |
ACKNOWLEDGMENTS |
This work was supported in part by research project 99/1199 from
the Instituto de Salud Carlos III. T. M. Díaz-Guerra is a
fellow of the Instituto de Salud Carlos III (grant 99/4149).
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Servicio de
Micología, Centro Nacional de Microbiología, Instituto
de Salud Carlos III, Ctra Majadahonda-Pozuelo km. 2, 28220 Majadahonda,
Spain. Phone: 34 91 5097961. Fax: 34 91 5097966. E-mail:
juanl.rodriguez-tudela{at}isciii.es.
 |
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Journal of Clinical Microbiology, July 2001, p. 2513-2517, Vol. 39, No. 7
0095-1137/01/$04.00+0 DOI: 10.1128/JCM.39.7.2513-2517.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
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