Development and Use of Flow Cytometry for Detection of Airborne Fungi

Traditional methods for the enumeration of airborne fungi areslow, tedious, and rather imprecise. In this study, the possibilityof using flow cytometry (FCM) for the assessment of exposureto the fungus aerosol was evaluated. Epifluorescence microscopydirect counting was adopted as the standard for comparison.Setting up of the method was achieved with pure suspensionsof Aspergillus fumigatus and Penicillium brevicompactum conidiaat different concentrations, and then analyses were extendedto field samples collected by an impinger device. Detectionand quantification of airborne fungi by FCM was obtained combininglight scatter and propidium iodide red fluorescence parameters.Since inorganic debris are unstainable with propidium iodide,the biotic component could be recognized, whereas the preanalysisof pure conidia suspensions of some species allowed us to selectthe area corresponding to the expected fungal population. Aclose agreement between FCM and epifluorescence microscopy countswas found. Moreover, data processing showed that FCM can beconsidered more precise and reliable at any of the tested concentrations.

INTRODUCTION

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Introduction

Among the numerous microorganisms present in the air, fungalpropagules are the most frequently encountered in both outdoorand indoor environments, where they are sometimes the sourceof infections, allergic reactions, and toxicoses. Aerobiologicalsurveys of fungi are frequently required for assessment of airquality in such places as hospitals, near sewage works, aroundor inside industrial plants, in clean room and in areas wherepeople or their livestock and crops are concentrated (10).

The predominant analytical methods for evaluating exposure tomycoaerosol are culture and microscopic techniques. In culturemethods, the collected airborne organisms are grown on nutritivemedia so that visible colonies form, which can be successivelyenumerated and identified. This method has important limitsmainly due to the inability of media to satisfy the specificgrowth requirements of all species, to the presence of propaguleaggregates and to the fungistasis. Moreover, only the viablefungus aerosol can be detected. However, viability is not anecessary requirement for the development of noninfectious diseases,since allergens and toxins are also present in dead cells (13).Microscopy, after the collection of samples with an impingerdevice, is a currently available method for evaluating the totalload of fungus aerosol, including both viable and unculturableor dead propagules. Nevertheless microscopic analytical methodsbased on the use of hemocytometer chambers are slow, tedious,and time-consuming. When the fungus aerosol is directly examinedby microscope on the trapping surface, the assessments are verysubjective, and hyaline and/or small propagules such as Aspergillusand Penicillium conidia are often underestimated or even notrecognized. These fungi, however, are the most frequently occurringcomponents of the fungus aerosol (7, 8).

Flow cytometry (FCM) is a tool with great potential for usein environmental microbiology because of the quantity and qualityof the data it provides in a timely fashion, since multipleparameters (e.g., forward light scatter [FSC] and side lightscatter [SSC] and fluorescence emission at wavelengths of interest)can be determined individually for a large number of cells ina short time (up to several thousand cells per second). Besides,FCM has the advantage of operating with large samples, enablingcollection of statistically reliable results (5).

In recent years, FCM has been widely applied for the enumerationand identification, of both prokaryotic and eukaryotic microorganismsfrom aquatic environments (see, for example, references 5, 6,and 14).

On the other hand, the use of FCM in aerobiological studiesis still unusual, and it has been tested to evaluate the exposureto bacteria only. In this case, comparison with traditionalmethods highlighted the tremendous potential of this technique,especially when combined with fluorescence in situ hybridizationfor the detection and quantitative identification of health-threateningorganisms (9).

To our knowledge, FCM has never been applied to enumerate naturallyoccurring airborne fungal spores and conidia. One of the majorlimitations to the application of this technique to the fungiwas the lack of "stainability" of most fungal propagules sincethey proved to be quite unstainable or fluorescent in a smallpercentage only (1, 4, 11, 12). Nevertheless, staining withfluorescent dyes is required to distinguish between fungal propagulesand abiotic background. Actually, spores and conidia have avery thick and resistant cell wall that protects the protoplastfrom physical, chemical, and biological injuries in the troposphere,but at the same time, prevents them from staining. To overcomethis handicap, we have recently set up a method to avoid thepropagule resistance to fluorochromes applying microwave irradiation(V. Prigione and V. Filipello Marchisio, Abstr. 7th Int. Mycol.Cong., abstr. 872, 2002).

The aim of the present study was to develop a reliable methodof analysis based on FCM for the rapid enumeration of totalairborne fungal load in selected environments that used bothlight scatter and fluorescence parameters. The sensitivity andreliability of flow cytometric quantitative analyses were demonstratedat first with suspensions of Aspergillus fumigatus and Penicilliumbrevicompactum conidia at different concentrations (simulatedsamples). Then, the analyses were extended to field samplescollected by an impinger device. Epifluorescence direct countingwas adopted as the standard for comparison.

MATERIALS AND METHODS

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Materials and Methods

Organisms and culture conditions.
A. fumigatus Fresenius var. fumigatus (MUT 1564), P. brevicompactumDierkx (MUT 2430), and Cladosporium cladosporioides (Fres.)de Vries (MUT 3155), isolated outdoors and kindly supplied byMycotheca Universitatis Taurinensis (Turin, Italy), were grownon malt extract agar in the darkness at 24°C for 4 weeksin order to obtain completely mature conidia.

Simulated samples.
Conidia from fruiting cultures were harvested by gently touchingthe colony surface by means of a sterile wet Pasteur pipette,and then they were suspended in quarter strength Ringer Solution(Oxoid, Ltd., Basingstoke, England) supplemented with 0.01%Antifoam A and 0.02% Tween 80 (Sigma Aldrich Co., Ltd.) to facilitatethe suspension of the hydrophobic conidia. Suspensions werethen repeatedly syringed to break conidial chains and adjustedto 10⁶ conidia ml^-1 by using a Bürker chamber. For comparativepurpose between flow cytometry and epifluorescence microscopycounting, serial dilutions of suspensions of A. fumigatus andP. brevicompactum conidia were carried out to work on concentrationsof 1 x 10⁶, 5 x 10⁵, 1 x 10⁵, 1 x 10⁴, or 1 x 10³ conidia ml^-1.

For FCM analyses of field samples, a preanalysis of pure andmixed suspensions of P. brevicompactum and C. cladosporioidesconidia (10⁶ conidia ml^-1) was performed as a reference to discriminatethe relevant fungal population from the background. These twofungal species were chosen as test organisms since they aredominant in the air (7, 8), and the shape and size of theirconidia are representative of the morphological and dimensionalvariability of the most common airborne fungi.

Collection of field samples.
Air sampling was performed with an impinger device ("Charlie"model; TCR, Tecora, Italy). The liquid collection medium consistedof 12 ml of sterile quarter-strength Ringer solution (Oxoid)modified as described above. The sampling sites were the compostingtunnel of a compost plant (site A, total sampling time 60 min),a woodland in a town area (site B, total sampling time 360 min),and a polluted dwelling house (site C, total sampling time 60min). At sites A and C one sample was collected; at site B foursamples were collected (B1 to B4). Preliminary tests with asurface air sampler (Pool Bioanalyse, Milan, Italy) had shown,at sites A and C, a very high fungal load compared to the outdoormean values and site B values. Therefore, different volumesof air were sampled to avoid meeting with loads too low to beread by the Bürker chamber. During the sampling, an operatorinspected the instrument to avoid the evaporative loss of thecollection medium; if this occurred, additional medium was gentlyadded. The sampling flow rate was always 10 liters min^-1.

Staining procedures.
To optimize propagule staining, samples were microwave treatedaccording to the method proposed by Prigione and Filipello Marchisio(Abstr. 7th Int. Mycol. Cong.). Microwave irradiation was performedby using a domestic Panasonic NN-K257-W microwave oven at thepower of 440 W and a frequency of 2,450 MHz, for 30 s. Each1-ml suspension in Pyrex tube was placed in the center of theoven and irradiated separately to have constant and reproducibleconditions. Samples were stained for 2 h at room temperaturewith propidium iodide (Sigma) at a final concentration of 100µg ml^-1. This fluorochrome is an intercalator that bindswith a good specificity to nucleic acids, allowing the userto distinguish between abiotic and biotic particles; it wasfound very suitable for the staining of fungal propagules aftermicrowave treatment (V. Prigione and V. Filipello Marchisio,Abstr. 7th Int. Mycol. Cong.).

Epifluorescence microscopy.
Epifluorescence direct counting was performed by using a Bürkerchamber and a Nikon Eclipse E-600 epifluorescence microscopeequipped with a 100-W mercury lamp and a 510- to 560-nm filterfor the detection of red fluorescence. For each sample, fivecounts were achieved, each one corresponding to a volume of0.192 µl, reading three of the nine major squares in thegrid. Final data were the mean of the five replicates. Workingwith simulated samples two sets of experiments were carriedout.

FCM.
Flow cytometric analyses were performed by using a Partec PASflow cytometer (Partec GmbH, Münster, Germany) equippedwith a 20-mW argon-ion laser and calibrated by using 4.2-µmdiameter beads (Polyscience, Warrington, Pa.). The instrumenthas a built-in volumetric system based on the positioning oftwo electrodes and is set by the factory to sample a volumeof exactly 200 µl. The sensitivity and reliability ofthe instrument were first tested in simulated samples by collectingdata on a logarithmic intensity scale with respect to FSC, theparameter related to the particle size (3), SSC, the parameterrelated to the cytoplasmic granularity of the particles (3)and red fluorescence (>620 nm) separately and combining theparameters two by two.

The latter method has been used in field samples, where FCMwas evaluated for its ability to distinguish relevant fungalpopulation from other biotic and background events of instrumentnoise and environmental debris; a multiparametric approach isessential in this context (3). The scatter and fluorescencecharacteristics of pure and mixed laboratory suspensions ofP. brevicompactum and C. cladosporioides were used to set theinstrument by selecting the area corresponding to the fungalpopulation. The area where the fungal propagules were localizedwas noted on a bidimensional scattergram. A polygon drawn togate the particles falling in this area was used to analyzethe field samples.

For each sample, five counts were achieved, each one correspondingto a volume of 200 µl. Final data were the mean of thefive replicates. Conidial suspension values were then convertedinto load values per cubic meter of air. Two sets of experimentswere carried out with simulated samples.

Data processing.
Acquisition and analysis of FCM data were performed by usingthe FloMax program, associated with the instrument.

A correlation was calculated between the counting results obtainedby FCM and microscopy for each concentration of simulated samples.

The data obtained from microscopy and FCM have been plottedlooking for a possible mathematical relation between the percentcoefficient of variation (%CV; a value related to the standarddeviation and therefore to the variation of the sample) andthe log of the concentration of the conidia in suspension. Fourkinds of regression (linear, exponential, logistic, and parabolic)were calculated by using the Systat software package.

The nonparametric Mann-Whitney test was run with the StatviewII statistical package to assess the significance (P $<=$ 0.05)of differences between results by the two counting methods forfield samples.

RESULTS

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Results

Simulated samples.
During microscopic observation a small portion of coupled conidiawas observed even though the conidial suspension had been syringedmany times. The FSC frequency histogram allowed us to discriminatebetween the conidial population going through the flow chamberone by one, represented by the higher peak, and the populationof coupled conidia, represented by the lower peak (Fig. 1A and D).Indeed, coupled conidia are able to give a higher FSC signal.The SSC frequency histogram did not allow such a discrimination(Fig. 1C and F). FCM analysis by red fluorescence was able toshow single and coupled conidia populations in the case of A.fumigatus only (Fig. 1B and E). Therefore, counting of totalconidia for each species was possible by calculating the integralof the two FSC histogram peaks of the particles with red fluorescence;that is, the number of conidia was obtained by the additionof the integral of the single conidium peak to twice the integralof the coupled conidium peak.

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FIG. 1. Histograms obtained by flow cytometric analysis of simulated samples after microwave irradiation and propidium iodide staining. (A to C) A. fumigatus; (D to F) P. brevicompactum. Counts, number of conidia; FL-III, red fluorescence; S, conidia passing singly through the flow cell; P, conidia passing in pairs through the flow cell.

Tables 1 and 2 show the counting results for each species andset of experiments as determined by both FCM and epifluorescencemicroscopy. The degree of correlation between the FCM and microscopycounts was quite high: A. fumigatus gave R² values of 0.97 and0.99 in the first and second tests, respectively, whereas theP. brevicompactum values were 0.99 and 0.95 (one of the plotsis shown in Fig. 2).

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TABLE 1. Quantitative analysis of simulated samples of A. fumigatus conidia by FCM and epifluorescence microscopy^a

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TABLE 2. Quantitative analysis of simulated samples of P. brevicompactum conidia by FCM and epifluorescence microscopy^a

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FIG. 2. Correlation between FCM and microscopy counting results (log of the conidia concentration) for one of the experiments with P. brevicompactum. A linear least-squares best-fit line was calculated and is shown with correlation coefficient R².

However, the %CV values of FCM counts were, on average, lowerthan those of microscopy counts. The best-fitting models formicroscopy data were represented by the linear regression (oneof the plots is shown in Fig. 3). Consistently high and repeatableR² values (0.85 < R² < 0.95) were obtained in all of thetests. The curves showed a negative angular coefficient, indicatinga negative correlation between the concentration of the conidiain the suspension and the error in the measure. None of thetested regressions adequately described the distribution ofthe dot plot for the FCM data (R² was always lower than 0.36),suggesting that the distribution of the datum points is randomand not dependent on the concentration of the conidia.

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FIG. 3. Dot plot of the log of the conidium concentration in the analyzed suspension versus the %CV for one of the experiments with P. brevicompactum. A line with equation y = -49.931x + 298.49 and R² = 0.9597 fitted the microscopy data, whereas no curve fitted the dot distribution of flow cytometry data. Plots and lines with similar results were obtained for all of the other experiments as well (not shown).

Field samples.
Histograms and dot plots obtained by the combination of SSCand FSC displayed an abundant background that did not allowus to discriminate the fungal population. The staining withpropidium iodide could gate the abiotic background, leavingit out from further data acquisition. Preanalysis of pure andmixed laboratory suspensions of P. brevicompactum and C. cladosporioidesenabled us to gate the area corresponding to the expected fungalpopulation. Figure 4 shows the area gated for counting in theB1 field sample.

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FIG. 4. Histograms and dot plots obtained by flow cytometric analysis of B1 field sample after microwave irradiation and propidium iodide staining. Counts, number of particles; FL-III, red fluorescence; R2, area gated for counting; P, background.

Table 3 shows the counting results by FCM and epifluorescencemicroscopy for each field sample. It was not possible to distinguishbetween single and coupled conidia owing to the greater heterogeneityof airborne particles in comparison with simulated samples;on the other hand, a negligible share of coupled conidia hadbeen observed by microscopy. The Mann-Whitney test showed thatthe results by FCM were always not significantly different fromthose by epifluorescence microscopy. As for simulated samples,the %CV values of FCM counts were, on average, lower than thoseof microscopy counts.

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TABLE 3. Quantitative analysis of fungal propagules in field samples by FCM and microscopy^a

DISCUSSION

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Discussion

Detection and quantification by FCM of the dominant and stablecomponent of the airborne fungi, as described by Filipello Marchisioand Airaudi (7), are feasible, by combining light scatter andpropidium iodide red fluorescence and pretreating the suspensionsby microwave irradiation to achieve the cell wall permeabilizationof fungal propagules (Prigione and Filipello Marchisio, Abstr.7th Int. Mycol. Cong.).

Working with simulated samples at different concentrations ofconidia, a close agreement between the FCM and epifluorescencemicroscopy results was always found. Moreover, data processingshows that FCM can be considered more precise and reliable atany of the tested concentrations. In addition to the fact thatthe range of the %CV was always lower in the FCM counts thanin the microscopy counts, the search for the best-fitting curvesshowed that the two methods provide results with completelydifferent reliabilities. A systematic error was introduced whenmicroscopy was used for the count of conidia: the lower theirconcentration in the suspension, the higher the %CV (i.e., theerror in the count). On the other hand, no curve could be consistentlyand repeatedly fitted to the dot distribution of the FCM data,showing that results were not dependent on the concentrationof the conidia nor subject to a systematic instrumental error.This fact is important for the development of reliable routinemethods for counting total airborne fungal load, but of specialsignificance in cases in which rare particles, such as the propagulesof a potentially pathogenic species, must be detected in a sample.Since FCM is performed on a sample size ca. 1,000 times greater(200 µl versus 0.192 µl) and its results are notas much dependent on particle concentration as those of microscopy,this technique could greatly increase the chance of detectingrare conidia. Highly species-specific detection of rare conidiawill require further development and improvement of the methodthrough the combination of FCM with immunochemical and/or molecularmethods. This approach, besides increasing the analysis specificity,could also reduce the instrumental limit of quantification that,in the present study, was not investigated below a concentrationof 10³ propagules ml^-1. Actually, the aim of the present studywas to verify the capability of surveying the total load ofairborne fungi in selected environments which, in the specificinstance, had loads of about 10⁴ to 10⁵ propagules m^-3 of air.According to some researchers, the limit of quantification inaquatic environments is 10² cells ml^-1 (9, 14).

The application of FCM to samples collected in some naturalenvironments by using an impinger device, the most suitableinstrument for this kind of analysis, gave good results as well.FCM analysis of field samples involves two main difficulties:the possibility that the background events hide the fungal propagulesin the sample and the need for selecting the coordinates ofthe region in which fungal population is included. Since propidiumiodide is a nucleic acid-specific dye, the biotic componentcould be recognized, whereas the preanalysis (concerning propidiumfluorescence, FSC, and SSC) of P. brevicompactum and C. cladosporioidessuspended conidia allowed us to select the area correspondingto the expected fungal population. Propidium iodide is not specificfor fungi; therefore, labeled particles might not be only fungalpropagules. However, strong support of the correct identificationof the particles came, in the first place, from the close agreementbetween microscopy and FCM counting results. Moreover, the particlesconsidered for the count were selected by relying on three parameters(propidium iodide staining, FSC, and SSC) and not only on thebasis of red fluorescence. The use of multiple parameters todetect and select the particles of interest represents one ofthe technical key features of FCM, allowing researchers to differentiatefungal propagules from different cells and biotic debris infield samples. In environments different from the ones we haveconsidered, and especially in agricultural environments, pollenscould pose a problem due to their abundance in some periodsof the year. The size range of some of the smallest pollens,in fact, overlaps that of some fungal propagules. Nevertheless,most are much larger than the most common airborne fungal propagules(2). In the present study pollens did not cause problems sincethey were never observed during microscopic counts and analysesof our field samples. Day et al. (4), working with simulatedsamples and combining light scatter and intrinsic fluorescenceparameters, could differentiate sporangia of the late-blightpathogen Phytophthora infestans from conidia of Alternaria andBotrytis spp., rust urediniospores, and the pollen of grassesand plantain. Differentiation between P. infestans sporangiaand powdery mildew conidia could also be achieved in the samestudy after the samples were stained with Calcofluor White M2Rand analytical rules evolved by genetic programming methodswere applied. These data suggest that FCM could also be usedto detect and quantify airborne fungi in environments differentfrom the ones we chose to examine, including agricultural environments.

FOOTNOTES

* Corresponding author. Mailing address: Dipartimento di Biologia Vegetale, Viale Mattioli 25, I-10125 Turin, Italy. Phone: 39-11-6705984. Fax: 39-11-6705962. E-mail: valeria.filipello{at}unito.it.

REFERENCES

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