1
Enumeration of airborne bacteria and fungi using solid phase cytometry
Lies M. E. Vanhee, Hans J. Nelis, Tom Coenye*
Laboratory for Pharmaceutical Microbiology, Ghent University, Harelbekestraat 72,
B-9000, Ghent, Belgium
*Corresponding author:
Tom Coenye
Laboratory for Pharmaceutical Microbiology
Ghent University
Tel.: +32 9 2648141
Fax: +32 9 2648195
Email: Tom.Coenye@UGent.be
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Abstract
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Conventional methods for the enumeration of airborne micro-organisms are
3
inaccurate and time-consuming, hence the interest in novel approaches is increasing.
4
In the present study, the use of solid phase cytometry (SPC) was evaluated for the
5
enumeration of airborne micro-organisms. A 4 h SPC procedure based on viability
6
staining was applied to samples from 50 locations and compared with an optimised
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culture-based method. Plate counts after air sampling were repeatable but strongly
8
dependent on sampling volume. Samples with low or high microbial load were
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difficult to analyse using the culture-based method, unlike with SPC. Results show
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that SPC can be considered superior to the culture-based method because of its much
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higher dynamic range, its speed and its ability to enumerate not only culturable but all
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viable micro-organisms.
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Keywords: Solid phase cytometry (SPC); Bioaerosol; Airborne micro-organisms
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1. Introduction
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In recent years, monitoring of the number of airborne micro-organisms has
18
gained interest due to increasing concerns about public health, the threat of
19
bioterrorism, surface biodeterioration and spread of plant diseases (Douwes et al.,
20
2003; Pieckova and Jesenska, 1999; Stetzenbach et al., 2004). Exposure to
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bioaerosols, containing airborne micro-organisms and their by-products, can result in
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respiratory disorders and other adverse health effects such as infections,
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hypersensitivity pneumonitis and toxic reactions (Fracchia et al., 2006; Gorny et al.,
24
2002). In many environments including hospitals, animal sheds, clean-rooms,
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pharmaceutical facilities and spacecraft environments, the presence of bioaerosols can
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compromise normal activities, making efficient monitoring crucial (Gorny, 2004;
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Stetzenbach, 2007; Venkateswaran et al., 2003).
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Conventional enumeration of airborne micro-organisms relies on culture-
29
based or microscopic methods. Although culture-based analysis is most widely used
30
for bioaerosol quantification, it often results in an underestimation of the number of
31
micro-organisms. First of all, only culturable micro-organisms are detected, while the
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non-culturable ones, which can comprise a significant percentage of the bioaerosol,
33
are overlooked (Angenent et al., 2005; Chen and Li, 2005; Dillon et al., 1999; Wu,
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2007). Secondly, because of differences in growth requirements, no single culture
35
condition will allow detection of every type of micro-organism (Green et al., 2005;
36
Venkateswaran et al., 2003). Finally, because of the need of microbial multiplication,
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analysis usually takes at least three days to complete and fast-growing micro-
38
organisms may overgrow slow growers (Niemeier et al., 2006; Wu, 2007).
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In contrast, microscopic methods allow the detection of both culturable and
40
non-culturable micro-organisms and results can be obtained within hours of sample
4
41
collection (Angenent et al., 2005). However, microscopic enumeration is laborious,
42
requires a high level of expertise and results are often highly variable (Cruz and
43
Buttner, 2007). The inaccuracy and the time-consuming nature of conventional
44
methods underscore the need for new, rapid techniques that generate reliable data.
45
Recently flow cytometry, immunofluorescence, PCR and different biochemical assays
46
targeting e.g. ß,1-3-D-glucan, ergosterol and ATP, were suggested as alternative
47
strategies for the quantification of airborne bacteria and fungi (Alvarez et al., 1995;
48
Giovannangelo et al., 2007; Lange et al., 1997; Prigione et al., 2004; Robine et al.,
49
2005; Venkateswaran et al., 2003).
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In solid phase cytometry (SPC), the principles of epifluorescence microscopy
51
and flow cytometry (Lisle et al., 2004) are combined. Micro-organisms are retained
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on a membrane filter, fluorescently labelled and automatically counted by the
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Chemscan RDI laser-scanning device. Each detected spot can visually be inspected
54
using an epifluorescence microscope (De Vos and Nelis, 2003; Mignon-Godefroy et
55
al.,
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carboxyfluorescein diacetate (ChemChrome V6) by esterases, resulting in the
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formation of fluorescent carboxyfluorescein in intact and metabolically active cells
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only (Joux and Lebaron, 2000). SPC is considerably faster than conventional
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enumeration methods, does not depend on culture and has a theoretical detection limit
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of only one cell per filter and, hence per filtered volume (Van Poucke and Nelis,
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2000; Vermis et al., 2002). Additionally, SPC can successfully be used to determine
62
the microbial load of highly contaminated samples, since it has a high dynamic range
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with an upper limit of approximately 10, 000 cells per membrane filter (De Vos and
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Nelis, 2006; Reynolds and Fricker, 1999).
1997).
Fluorescent
viability staining is
based
on
the
cleavage
of
5
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In the present study, the total number of bacteria and fungi in air samples is
66
determined by SPC and compared with results obtained by a conventional culture-
67
based method. To this end, airborne micro-organisms from a large number of diverse
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locations were impacted on culture media and on a water soluble bio-polymer and
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analysed by SPC.
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2. Materials and methods
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2.1. Air sampling device
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For the collection of airborne micro-organisms, the MAS-100 Eco impaction
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air-sampler (Merck) with an airflow of 100 l min-1 was used. All culture results were
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converted using a positive hole conversion table according to the manufacturers
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instructions and expressed as colony forming units (CFU) m-3.
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2.2. Culture-based method
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2.2.1. Repeatability of air sampling
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To examine the variation in bioaerosol sampling, 100 l of air was impacted
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successively onto 10 culture plates. For this analysis, tryptic soy agar (TSA, Oxoid),
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TSA supplemented with 0.2% cycloheximide (Sigma) (TSAc) and rose bengal
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chloramphenicol (0.1 g l-1) agar (RBCA, Sigma) were used. Subsequently, plates were
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incubated at 20°C and colonies were counted after 3 days.
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2.2.2. Optimisation of the culture-based method
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Different media were tested for the growth of airborne micro-organisms: TSA,
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TSAc, RBCA, Sabouraud agar (Oxoid) supplemented with 0.1% chloramphenicol
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(Sigma) (SABc), R2A agar (containing yeast extract [0.5 g/l], proteose pepton n°3
6
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[0.5 g/l], casamino acids [0.5 g/l], dextrose [0.5 g/l], soluble starch [0.5 g/l], sodium
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pyruvate [0.3 g/l], potassium phosphate dibasic [0.3 g/l], magnesium sulfate [0.05 g/l]
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and agar [15 g/l]) and different dilutions (1:2, 1:10, 1:100) of TSA and TSAc. For
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these experiments, air samples (100 l) were collected at several locations, plates were
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incubated at 30°C and colonies were counted after 3 days. To determine the influence
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of the sampling volume, samples of 10, 50, 100 and 1000 l were collected on TSA
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and colonies were counted after 4 days of incubation at 20°C. For the comparison of
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different incubation conditions, samples (100 l) were collected on TSA, TSAc and
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RBCA. The plates were incubated at 20°C or 30°C and colonies were counted after 2,
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3, 4 and 7 days.
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2.2.3. Air sampling and culturing
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Air samples were collected using the MAS-100 Eco at 50 locations, expected
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to range from a very low bioaerosol concentration in clean-rooms to a high
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concentration in agricultural settings. According to the expected concentration of
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airborne micro-organisms, a sampling volume of 10 or 100 l was chosen (Table 1). At
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each location, samples were collected in triplicate on petri dishes containing 25 ml of
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agar medium. Culture conditions were based on results obtained during optimisation
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of the method and are described below.
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2.3. Solid phase cytometry
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2.3.1. Collection of air samples
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For analysis with SPC, air samples were collected at each location on three
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ready-to-use Polym’Air plates (Chemunex), containing a synthetic, nutrient-free,
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water soluble polymer.
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2.3.2. Preparation of samples
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Immediately after sampling, the polymer was aseptically removed from the
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petri dish and subsequently dissolved in 20 ml of physiological saline, which had
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previously been filtered (0.22 µm pore size membrane filter, Whatman Schleicher &
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Schuell) to eliminate particles. For each sample the total viable count (TVC) and the
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fungal count were determined.
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2.3.3. Total viable count labelling protocol
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Depending on the estimated bioaerosol concentration, different volumes
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(Table 1) of the dissolved Polym’Air samples were filtered over a 0.4 µm Cycloblack-
126
coated
127
counterstained by filtration of one ml CSE/2 (Catala et al., 1999), the filter was
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transferred to a cellulose pad soaked with 600 µl of the activation medium ChemSol
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A4 and incubated at 37°C for 3h. Finally, the filters were incubated at 30°C for 30
130
min on a cellulose pad saturated with 600 µl of staining reagent (ChemChrome V6
131
diluted 1:100 in the labelling buffer ChemSol B16). All reagents were obtained from
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Chemunex and filtered before use.
polyester
membrane
filter
(Chemunex).
Interfering
particles
were
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2.3.4. Fungal count labelling protocol
135
Samples were filtered over a 2.0 µm Cycloblack-coated polyester membrane
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filter and filters were incubated at 30°C for 3h on 600 µl of the activation medium
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Chemsol A6. Subsequently, viable micro-organisms were fluorescently labelled by
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incubating the filters at 37°C for 1h on a cellulose pad saturated with 600 µl of fungal
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staining reagent (ChemChrome V6 diluted 1:100 in the labelling buffer ChemSol B2).
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2.3.5. Laser scanning
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After labelling of the micro-organisms, the 25 mm diameter membrane filter
143
was placed in a holder, on top of a support pad (Chemunex) moistened with 600 µl of
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labelling buffer. The filters were subsequently scanned by the Chemscan RDI. This
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solid phase cytometer consists of a argon laser, emitting light of 488 nm and two
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photomultiplier tubes, which detect the fluorescent light emitted by the labelled cells.
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The produced signals are processed by a PC, applying a series of software
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discriminants to differentiate valid signals (labelled bacteria/fungi) from fluorescent
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particles. Different software settings were used for the two protocols as bacteria and
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fungi or only fungi had to be retained, respectively. Results were displayed as green
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spots on a membrane filter image in a primary and, after software elimination of
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background, secondary scan map.
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2.3.6. Microscopic validation
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To confirm and further analyse the properties of the detected spots, visual
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inspection using an epifluorescence microscope (Olympus BX40) equipped with a
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computer-driven moving stage, was performed. In practice, the filter holder was
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placed on the moving stage so as to retain the holder and the membrane filter in
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exactly the same position as in the Chemscan RDI. Subsequent highlighting of a green
160
spot in the secondary scan map resulted in the direction of the microscope to the
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respective position on the membrane filter. For the TVC-protocol, the fluorescent
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spots were validated based on fluorescense intensity, line amplitudes and shape,
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discriminating between bacteria, fungi and particles. For the fungi-protocol, the
164
validation consisted only of the differentiation between fungi and fluorescent
9
165
particles. Results were expressed as the mean corresponding number of bacteria or
166
fungi per m3.
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2.3.7. Storage of the dissolved samples
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In order to investigate if storage in the dissolved Polym’Air has an influence
170
on the viability of the collected micro-organisms, analysis was performed
171
immediately and 4 h and 24 h after dissolution of the Polym’Air. To that end, airborne
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micro-organisms were collected onto six Polym’Air plates which were immediately
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dissolved into 20 ml of physiological saline. Each sample was analysed with the
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modified TVC-protocol at t = 0 and subsequently stored at 4°C and re-analysed after
175
4 h or 24 h.
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2.4. Statistical analysis
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Ratios between the cells detected using SPC and the corresponding colony
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counts were calculated and Mann-Whitney and Kolmogorov-Smirnov tests were used
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to determine if there was a statistically significant difference between the results
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obtained with the culture-based method and SPC (SPSS 15.0.0, SPSS Inc.). The
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criterion for significance for all analyses was p < 0.05.
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3. Results and discussion
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3.1. Culture-based method
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3.1.1. Optimisation of the culture-based method
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Results demonstrated that upon successive air sampling plate counts are
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repeatable (data not shown). In order to optimise the culture-based method before
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comparison with SPC, different media, sampling volumes and incubation conditions
10
190
were examined. To check the specificity of the different media, the recovered micro-
191
organisms were Gram-stained. As expected, TSAc and RBCA were specific for
192
bacteria and fungi, respectively. SABc allowed the growth of both bacteria and fungi,
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and was therefore excluded from further experiments. Sampling on R2A agar and
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TSA resulted in similar counts (data not shown), but as incubation periods were
195
longer for R2A agar, we prefered the use of TSA as a general growth medium.
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Dilution of TSA led to lower counts than undiluted TSA (data not shown). It was also
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noted that, as the sampling volume increased, the number of CFU m-3 decreased (Fig.
198
1). This phenomenon was previously described by Nesa et al. (2001) and can be
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explained by desiccation of the micro-organisms and dehydration of the agar medium
200
when longer sampling times (required to sample larger volumes) are used. Sampling
201
volumes should therefore be as low and sampling times as short as possible. However,
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extremely low colony counts obtained after sampling small volumes may lead to
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considerable error in the estimation of the microbial load. Finally, different incubation
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conditions were examined and results show that incubation at 20°C for four days
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yields optimal recovery of both fungi and bacteria (data not shown). In summary,
206
TSA, TSAc and RBCA are proposed for growing all micro-organisms, bacteria and
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fungi, respectively and incubation is performed at 20°C for a minimum of four days.
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The sampling volume might need adjustment after initial determination of the
209
bioaerosol concentration and should be kept to a minimum sufficient to obtain
210
representative counts.
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3.1.2. Air sampling and culturing
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The optimised cultured-based method was subsequently used to enumerate
214
micro-organisms in air samples collected at 50 diverse locations (Table 1). The
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culturable microbial population in the samples ranged from 7 to 5.9 x 106 CFU m-3
216
with bacterial counts ranging from 9 to 6.0 x 106 CFU m-3 and fungal counts ranging
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from 0 to 6033 CFU m-3. For most locations, plates were countable when 100 l of air
218
was sampled. However, when locations with extremely high (e.g. pig and chicken
219
stables) or low (e.g. clean-rooms) microbial loads were sampled, reliable estimation
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of the number of micro-organisms present became impossible (Table 1).
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3.2. Solid phase cytometry
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Table 2 presents results on the viability of micro-organisms after storage in
224
solutions of Polym’Air. After 4h storage the number of cells detected is similar to the
225
one obtained after immediate analysis (Mann-Whitney test). Since the SPC procedure
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takes 4 h, this indicates that samples can be re-analysed, using a lower volume, when
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counts initially fall outside the dynamic range of the Chemscan RDI. However,
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storage of micro-organisms in the Polym’Air solution for 24 h led to a marked decline
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in the number of viable cells (Table 2).
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Validation was easy to perform using both SPC protocols, since
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counterstaining with Chemsol CSE/2 and use of a membrane with a 2.0 µm pore size
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for the TVC and the fungi protocol respectively, were sufficient to eliminate most
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interfering particles. Less than ten particles, which could easily be recognized by their
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shape, were present in all secondary scan maps.
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Table 1 gives an overview of the SPC results obtained for all samplings. Total
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counts ranged from 141 to 9.4 x 105 CFU m-3, with bacterial counts ranging from 89
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to 9.3 x 105 CFU m-3 and fungal counts ranging from 30 to 1.2 x 104 CFU m-3. Fungal
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counts obtained with the TVC-protocol and the fungi-protocol were comparable (data
239
not shown). Consequently, the use of the fungi protocol can be avoided and counts for
12
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both bacteria and fungi can be obtained using one protocol, making analysis less
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complicated and expensive. Accurate analysis of air samples containing low numbers
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of micro-organisms was possible with SPC. Analysis of samples with high microbial
243
load, however, led to aborted scans due to an excessive number of fluorescent spots
244
(Table 1). These samples can be re-analysed by filtering a lower volume of the stored
245
sample.
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3.3. Comparison between the culture-based method and solid phase cytometry
248
When comparing the culture-based method and SPC, SPC is a technically
249
more demanding technique for the enumeration of airborne micro-organisms.
250
However, an important advantage of SPC is that results are obtained very rapidly
251
(within 4 to 8h) while culture-based analysis requires at least 4 days.
252
Results obtained for 50 locations using both the culture-based method and
253
SPC were compared by calculating the ratio between the number of cells determined
254
by SPC and the CFU obtained with the culture-based method, and by performing the
255
Mann-Whitney and Kolmogorov-Smirnov tests for TVC, bacterial and fungal counts
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(Table 1). The ratios for TVC, bacteria, and fungi were higher than one for 81%, 85%
257
and 84% of the samples respectively (Fig. 2). This indicates that in general more
258
micro-organisms were detected with SPC than with the culture-based method. The
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Mann-Whitney test revealed that there was a statistically significant difference
260
between the SPC counts and plate counts for 64%, 59% and 58% of the samples for
261
the TVC, bacterial and fungal counts, respectively. For only three samples (12, 13,
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38), counts obtained with SPC and the culture-based method for TVC and bacteria
263
were significantly higher for the latter. For only two samples (10, 16) significantly
264
more fungi were detected with the culture-based method. These unexpected results are
13
265
most likely due to sudden changes in the microbial load between samplings by
266
environmental variation.
267
Although SPC requires more manipulation of the samples, standard errors are
268
comparable between both methods (Kolmogorov-Smirnov test), suggesting that
269
differences between samplings are only caused by variation in air sampling caused by
270
sudden changes in the environment.
271
Enumeration of airborne micro-organisms in samples with low microbial load
272
with the culture-based method was prone to error since only very low numbers of
273
colonies were obtained. However, SPC can be used to analyse these samples because
274
it has a much lower detection limit (one cel per membrane filter). Accurate analysis of
275
samples with high microbial load was impossible with the culture-based method
276
because the colonies present on the plates were too numerous to count. Using SPC,
277
however, it is possible to analyse these samples, although re-analysis of the
278
appropriate dilution may be necessary.
279
280
3.4. Comparison between other non-culture-based techniques and solid phase
281
cytometry
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Limitations to conventional methods for the enumeration of airborne micro-
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organisms have led to the development of techniques for bioaerosol monitoring with
284
increased sensitivity and accuracy. One of these techniques is flow cytometry (FC).
285
FC was used by Lange et al. (1997) and Prigione et al. (2004) to quantify the
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microbial load in air samples. The results obtained in these studies clearly showed that
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FC was more precise and reliable than epifluorescence microscopy but that it suffered
288
from a relatively high detection limit (103 cells/ml). In addition, high background
289
fluorescence was observed for several samples. In contrast, SPC has a theoretical
14
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detection limit of one cell per filter and our results from clean-room environments
291
confirm that SPC can be used for the enumeration of airborne micro-organisms in
292
setting with low numbers of micro-organisms. In SPC, the implementation of a
293
counterstaining procedure (Catala et al., 1999) and visual validation by
294
epifluorescence microscopy allows to easily make the distinction between particles
295
and micro-organisms.
296
Several biochemical assays for the enumeration of airborne micro-organisms
297
are available, targeting biological compounds like ß,1-3-D-glucan, ergosterol or ATP
298
(Giovannangelo et al., 2007; Robine et al., 2005; Venkateswaran et al., 2003).
299
However, the applicability of some of these assays is limited (e.g. ß,1-3-D-glucan and
300
ergosterol can be used only for fungi) and it is often difficult or impossible to
301
correlate the results obtained with cell numbers.
302
Although PCR-based approaches are widely used to quantify micro-organisms
303
(for a review see Zhang and Fang, 2006), there is only a single study in which PCR is
304
used for bioaerosol monitoring (Alvarez et al.,1995). In this study, it was concluded
305
that the PCR procedure has a detection limit of 10 cells when an additional
306
reamplification and hybridization was performed, leading to a 9 h procedure.
307
Compared to this method, SPC is much faster.
308
309
4. Conclusions
310
To our knowledge, SPC has so far not been used to enumerate airborne
311
bacteria and fungi. Our data suggest that SPC is superior to culture-based methods
312
because of its much higher dynamic range, its speed and the ability to enumerate all
313
viable micro-organisms. The main advantage of SPC is the low detection limit
15
314
making it particularly suited for the analysis of air samples with low numbers of
315
micro-organisms.
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Acknowledgements
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We acknowledge the excellent technical assistance of Margherita Battista. We
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also thank Nadine Carchon, Linda De Bock, Anneke Derore, Sarah De Smet, Kurt
320
Houf and Peter Van Daele for giving the opportunity to collect air samples at special
321
locations. This research was financially supported by the BOF of the Ghent
322
University (project nr B/07601/02).
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References
325
Alvarez, A.J., Buttner, M.P., Stetzenbach, L.D., 1995. PCR for bioaerosol monitoring:
326
sensitivity and environmental interference. Appl. Environ. Microbiol. 61, 3639-3644.
327
328
Angenent, L.T., Kelley, S.T., St. Amand, A., Pace, N.R., Hernandez, M.T., 2005.
329
Molecular identification of potential pathogens in water and air of a hospital therapy
330
pool. Proc. Natl. Acad. Sci. USA 102, 4860-4865.
331
332
Aurell, H., Catala, P., Farge, P., Wallet, F., Le Brun, M., Helbig, J.H., Jarraud, S.,
333
Lebaron, P., 2004. Rapid detection and enumeration of Legionella pneumophila in hot
334
water systems by solid-phase cytometry. Appl. Environ. Microbiol. 70, 1651-1657.
335
336
Catala, P., Parthuisot, N., Bernard, L.,Baudart, J., Lemarchand, K., Lebaron, P., 1999.
337
Effectiveness of CSE to counterstain particles and dead bacterial cells with
16
338
permeabilised membranes: application to viability assessment in waters. FEMS
339
Microbiol. Lett. 178, 219-226.
340
341
Chen, P.-S., Li, C.-S., 2005. Bioaerosol characterization by flow cytometry with
342
fluorochrome. J. Environ. Monit. 7, 950-959.
343
344
Cruz, P., Buttner, M.P., 2007. Analysis of bioaerosol samples. In: Hurst, C.J.,
345
Crawford, R.L., Garland, J.L., Lipson, D.A., Mills, A.L., Stetzenbach, L.D. (Eds.),
346
Manual of Environmental Microbiology, Ed. 3 , ASM Press, Washington D.C., pp.
347
952-960.
348
349
De Vos, M.M., Nelis, H.J., 2003. Detection of Aspergillus fumigatus hyphae by solid
350
phase cytometry. J. Microbiol. Meth. 55, 557-564.
351
352
De Vos, M.M., Nelis, H.J., 2006. An improved method for the selective detection of
353
fungi in hospital waters by solid phase cytometry. J. Microbiol. Meth. 67, 557-565.
354
355
Dillon, H.K., Miller, J.D., Sorenson, W.G., Douwes, J., Jacobs, R.R., 1999. Review of
356
methods applicable to the assessment of mold exposure to children. Environ. Health
357
Perspect. 107, 473-480.
358
359
Douwes, J., Thorne, P., Pearce, N., Heederik, D., 2003. Bioaerosol health effects and
360
exposure assessment: progress and prospects. Ann. Occup. Hyg. 47, 187-200.
361
17
362
Fracchia, L., Pietronave, S., Rinaldi, M., Martinotti, M.G., 2006. The assessment of
363
airborne bacterial contamination in three composting plants revealed site-related
364
biological hazard and seasonal variations. J. Appl. Microbiol. 100, 973-984.
365
366
Giovannangelo, M.E.C.A., Gehring, U., Nordling, E., Oldenwening, M., van Rijswijk,
367
K., de Wind, S., Hoek, G., Heinrich, J., Bellander, T., Brunekreef, B., 2007. Levels
368
and determinants of ß (13)-glucans and fungal extracellular polysaccharides in
369
house dust of (pre-)schoolchildren in three European countries. Environ. Internat. 33,
370
9-16.
371
372
Gorny, R.L., Reponen, T., Willeke, K., Schmechel, D., Robine, E., Boissier, M.,
373
Grinshpun, S.A., 2002. Fungal fragments as indoor biocontaminants. Appl. Environ.
374
Microbiol. 68, 3522-3531.
375
376
Gorny, R.L., 2004. Filamentous microorganisms and their fragments in indoor air - a
377
review. Ann. Agric. Environ. Med. 11, 185-197.
378
379
Green, B.J., Schmechel, D., Kingsley Sercombe, J., Tovey, E.R., 2005. Enumeration
380
and detection of aerosolized Aspergillus fumigatus and Penicillium chrysogenum
381
conidia and hyphae using a novel immunostaining technique. J. Immunol. Meth. 307,
382
127-134.
383
384
Grinshpun, S.A., Buttner, M.P., Willeke, K., 2007. Sampling for airborne
385
microorganisms. In: Hurst, C.J., Crawford, R.L., Garland, J.L., Lipson, D.A., Mills,
18
386
A.L., Stetzenbach, L.D. (Eds.), Manual of Environmental Microbiology, Ed. 3 , ASM
387
Press, Washington D.C., pp. 939-951.
388
389
Joux, F., Lebaron, P., 2000. Use of fluorescent probes to assess physiological
390
functions of bacteria at single-cell level. Microbes Infect. 2, 1523-1535.
391
392
Lange, J.L., Thorne, P.S., Lynch, N., 1997. Application of flow cytometry and
393
fluorescent in situ hybridization for assessment of exposures to airborne bacteria.
394
Appl. Environ. Microbiol. 63, 1557-1563.
395
396
Lisle, J.T., Hamilton, M.A., Willse, A.R., McFeters, G.A., 2004. Comparison of
397
fluorescence microscopy and solid-phase cytometry methods for counting bacteria in
398
water. Appl. Environ. Microbiol. 70, 5343-5348.
399
400
Mignon-Godefroy, K., Guillet, J.-G., Butor, C., 1997. Solid phase cytometry for
401
detection of rare events. Cytometry 27, 336-344.
402
403
Nesa, D., Lortholary, J., Bouakline, A., Bordes, M., Chandenier, J., Derouin, F.,
404
Gangneux, J.P., 2001. Comparative performance of impactor air samplers for
405
quantification of fungal contamination. J. Hosp. Inf. 47, 149-155.
406
407
Niemeier, R.T., Sivasubramani, S.K., Reponen, T., 2006. Assessment of fungal
408
contamination in moldy homes: comparison of different methods. J. Occ. Environ.
409
Hyg. 3, 262-273.
410
19
411
Pieckova, E., Jesenska, Z., 1999. Microscopic fungi in dwellings and their health
412
implications in humans. Ann. Agric. Environ. Med. 6, 1-11.
413
414
Prigione, V., Lingua, G., Filipello Marchisio, V., 2004. Development and use of flow
415
cytometry for detection of airborne fungi. Appl. Environ. Microbiol. 70, 1360-1365.
416
417
Reynolds, D.T., Fricker, C.R., 1999. Application of laser scanning for the rapid and
418
automated detection of bacteria in water samples. J. Appl. Microbiol. 86, 785-795.
419
420
Robine, E., Lacaze, I., Moularat, S., Ritoux, S., Boissier, M., 2005. Characterisation
421
of exposure to airborne fungi: measurement of ergosterol. J. Microbiol. Meth. 63,
422
185-192.
423
424
Stetzenbach, L.D., 2007. Introduction to aerobiology. In: Hurst, C.J., Crawford, R.L.,
425
Garland, J.L., Lipson, D.A., Mills, A.L., Stetzenbach, L.D. (Eds.), Manual of
426
Environmental Microbiology, Ed. 3 , ASM Press, Washington D.C., pp. 925-938.
427
428
Stetzenbach, L.D., Buttner, M.P., Cruz, P., 2004. Detection and enumeration of
429
airborne biocontaminants. Curr. Opin. Biotechnol. 15, 170-174.
430
431
Van Poucke, S.O., Nelis, H.J., 2000. Rapid detection of fluorescent and
432
chemiluminescent total coliforms and Escherichia coli on membrane filters. J.
433
Microbiol. Meth. 42, 233-244.
434
20
435
Venkateswaran, K., Hattori, N., La Duc, M.T., Kern, R., 2003. ATP as a biomarker of
436
viable microorganisms in clean-room facilities. J. Microbiol. Meth. 52, 367-377.
437
438
Vermis, K., Vandamme, A.R., Nelis, H.J., 2002. Enumeration of viable anaerobic
439
bacteria by solid phase cytometry under aerobic conditions. J. Microbiol. Meth. 50,
440
123-130.
441
442
Wu, F.Q., 2007. Culture-based analytical methods for investigation of indoor fungi.
443
In: Yang, C.S., Heinsohn, P.A. (Eds.) Sampling and analysis of indoor
444
microorganisms. John Wiley & Sons, New Jersey, pp 105-122.
445
446
Zhang, T., Fang, H.H., 2006. Applications of real-time polymerase chain reaction for
447
quantification of micro-organisms in environmental samples. Appl. Microbiol.
448
Biotechnol.70,281-289.
21
Fig.1: Comparison between the number (CFU m-3) of micro-organisms detected after
sampling of different volumes of air on TSA and subsequent incubation at 20°C for
four days (error bars present SE).
Fig.2: Ratios between the total number of cells detected with SPC and the number of
CFU on TSA with the culture-based method in air sampled at various locations. The
numbers correspond to the locations in Table 1 and 7 values (light grey) are presented
using a different scale. (error bars present SE).
22
Table 1: Plate counts and SPC counts in air sampled at different locations
Microbial population as determined by:
Filtered volume
Sampling (SPC) (ml)
volume (l)
Location
SPC counts CFU-1 SE
Culture-based method
(Mean CFU m-3  SE)
Solid phase cytometry (SPC)
(Mean cells m-3  SE)
TVC
Fungi
Total (TSA)
Bacteria (TSAc)
Fungi (RBCA)
Total
(tvc-protocol)
Bacteria
(tvc-protocol)
Fungi
(fungi-protocol)
Total
Bacteria
Fungi
1.
Laboratory 1
100
9
9
353  38
150  6
173  15
1533  59
807  52
593  41
4.34  0.50 *
5.38  0.41 *
3.42  0.38 *
2.
Laboratory 2
100
9
9
107  18
77  9
57  3
319  27
178  22
185  45
2.99  0.56 *
2.32  0.40 *
3.27  0.81 *
3.
Laboratory 3
100
9
9
150  20
57  9
97  19
289  34
133  22
148  27
1.93  0.34 *
2.35  0.54 *
1.53  0.41
4.
Living room
100
9
9
320  6
110  20 b
177  23
578  97
230  37
333  34
1.81  0.31 *
2.09  0.51
1.89  0.31 *
5.
Bedroom
100
9
9
480  32
273  62
150  21
837  39
348  49
622  154
1.74  0.14 *
1.27  0.34
4.15  1.18 *
6.
Kitchen
100
9
9
350  92
370  50
340  29
526  129
326  78
281  93
1.50  0.54
0.88  0.24
0.83  0.28
7.
Hall
100
9
9
300  30
183  35
47  18
274  7
156  22
163  58
0.91  0.09
0.85  0.20
3.49  1.83
8.
Student room
100
9
9
440  15
323  15
53  19
667  46
370  45
156  38
1.52  0.12 *
1.15  0.15
2.92  1.26
9.
Office 1
100
9
9
1130  47
627  42
273  28
4615  3416
2867  2256
311  26
4.08  3.03
4.57  3.61
1.14  0.15
10. Office 2
100
9
9
1310  136
213  35
560  44
1000  198
563  162
326  78
0.76  0.17
2.64  0.87 *
0.58  0.15 *
100
9
9
387  30
173  30
53  7
1422  198
511  78
2119  90
3.68  0.59 *
2.95  0.68 *
39.72  5.48 *
12. False ceiling (office) 100
9
9
723  50
597  57
33  15
467  59
185  39
96  30
0.65  0.09 *
0.31  0.07 *
2.89  1.58 *
13. Bathroom 1
100
9
9
1050  191
427  26
47  12
541  109
252  45
326  95
0.51  0.14 *
0.59  0.11 *
6.98  2.71 *
14. Bathroom 2
100
9
9
1637  56
2157  141
603  98
3963  426
3111  386
689  64
2.42  0.27 *
1.44  0.20
1.68  0.43
15. Toilet
100
9
9
553  12
447  33
290  10
704  37
400  26
304  32
1.27  0.07 *
0.90  0.09
1.05  0.12
Car
100
(airconditioning off)
9
9
2787  232
550  50
810  40
9319  7747
7874  6935
593  41
3.34  2.79
14.32  12.68
0.73  0.06 *
11.
16.
False
(kitchen)
ceiling
23
17. Car
100
(airconditioning on)
9
9
473  111
343  83
253  27
719  291
533  280
185  63
1.52  0.71
1.55  0.90
0.73  0.26
18. Student hall
100
9
9
807  159
583  27
257  45
756  67
430  53
600  89
0.94  0.02
0.74  0.10
2.34  0.54 *
19. Student restaurant
100
9
9
19207  60
163  22
230  21
444  64
222  22
281  15
1.68  0.45 *
1.36  0.23
1.22  0.13
1443  52
4400  814
2067  412
1719  262
1.30  0.27
1.04  0.22
1.19  0.19
141  63
89  22
104  7
1.21  0.56
1.16  0.32
1.83  0.41 *
20.
Station
(entrance hall)
100
9
9
3373  334
1990  142
21.
Station
(platform)
100
9
9
117  13
77  9
22. Swimming pool 1
100
9
9
410  159
140  10
37  19
1889  328
1148  161
348  119
4.61  1.96 *
8.20  1.29 *
9.49  5.89 *
23. Swimming pool 2
100
9
9
700  61
330  50
50  10
3311  2445
2422  1889
96  53
4.73  3.52
7.34  5.83 *
1.93  1.13
24. Parking outdoor
100
9
9
1747  20
80  0
1167 24
1600  78
578  13
1067  84
0.92  0.05
7.22  0.16 *
0.91  0.07
57  12
25.
Outdoor
environment 1
100
9
9
293  28
83  19
73  9
837  71
407  52
311  64
2.85  0.36 *
4.89  1.28 *
4.24  1.02 *
26.
Outdoor
environment 2
100
9
9
300  46
137  23
143  15
696  39
341  7
304  15
2.32  0.38 *
2.49  0.42 *
2.12  0.25 *
100
9
9
747  27
340  36
463  23
2481  334
1511  244
1074  52
3.32  0.46 *
4.44  0.86 *
2.32  0.16 *
28. Botanical garden 1 100
9
9
1130  60
223  22
657  35
3163  924
1985  763
948  7
2.80  0.83 *
8.89  3.53 *
1.44  0.08 *
29. Botanical garden 2 100
9
9
3020  150
220  25
3320  121
2793  1526
941  686
8941  1303
0.92  0.51
4.28  3.16
2.69  0.40 *
30. Botanical garden 3 100
6
9
980 a
193  24
353  101
9344  2024
6344  1367
778  223
9.54  2.07
32.82  8.16 *
2.20  0.89
31. Botanical garden 4 100
6
9
757  101
147  9
437  22
1211  78
722  80
333  71
1.60  0.24 *
4.92  0.62 *
0.76  0.17
27. Park
32.
Pigs stable 1
(ground-level)
100
0.1
6
NC
6.6 104  2.6 104
567  70
7.9 104  5.0 104
7.5 104  5.0 104
1022  111
-
1.14  0.76
1.80  0.30 *
33.
Pigs stable 1
(1m high)
100
0.1
6
NC
1.4 105  8.9 103
580  21
7.1 105  3.0 104
7.1 105  3.0 104
1011  156
-
4.89  0.36 *
1.74  0.28 *
34.
Pigs stable 2
(ground-level)
100
0.1
6
NC
6.0 104  1.3 104
580  31
1.2 105  3.3 104
1.2 105  3.3 104
1244  238
-
1.99  0.70
2.15  0.43 *
35.
Pigs stable 2
(1m high)
100
0.1
6
NC
6.2 104  3.8 103
530  17
1.6 105  3.1 104
1.6 105  3.1 104
1733  204
-
2.51  0.52 *
3.27  0.40 *
10
1
9
1.4 105  1.1 105
1.3 104  1.3 103
1767  186
-d
-d
9506  428
-
-
5.38  0.61 *
36. Pigs stable 1
24
37. Pigs stable 1
100
0.1
6
1.7 104  1.2 104
5210  377
887  115
8.0 105  5.1 105
7.8 105  5.0 105
9922  6732
45.94  43.12 *
149.64  97.05 *
11.19  7.73 *
38. Pigs stable 2
10
1
9
1.7 106  1.4 105
1.7 106  2.2 105
6033  2459
9.4 105  7.3 104
9.3 105  7.2 104
1.2 104  3.9 103
0.57  0.06 *
0.56  0.08 *
1.98  1.04
39. Pigs stable 2
100
0.1
6
2.3 105  2.4 104
2.6 105  1.9 104
2550  953
8.1 105  1.8 104
7.3 105  2.8 104
5078  1281
3.50  0.38 *
2.85  0.23 *
1.99  0.90
40. Pigs stable 3
100
0.1
6
1.8 104  7.2 103 b
4.0 104  4.6 103
2403  58
3.6 105  1.8 105
3.6 105  1.8 105
4622  1848
20.02  12.72
9.04  4.78
1.92  0.77
41. Chicken stable 1
10
0.1
6
3.9 106  1.8 106
5.2 106  4.5 105
2000  265
-d
-d
1667  333
-
-
0.83  0.20
42. Chicken stable 2
10
0.1
6
5.9 106  1.4 105
6.0 106  4.5 105
1233  120
-d
-d
778  111
-
-
0.63  0.11
43.
Chicken
stable
100
outdoor environment
1
6
1363  47
420  67
143  66
-d
-d
600  484
-
-
4.19  3.89
44.
Animalarium 1
(during activity)
100
9
9
470  32
367  15
57  9
3563  376
2748  175
711  270
7.58  0.95 *
7.49  0.57 *
12.55  5.16 *
45.
Animalarium 2
(after activity)
100
9
9
220  26
63  30
23  9
719  131
548  119
222  13
3.27 + 0.71 *
8.65  4.51 *
9.52  3.72 *
46.
Animalarium 3
(before activity)
100
9
9
1157  35
787  94
30  12
2822  167
1622  139
489  34
2.44  0.16 *
2.06  0.30 *
16.30  6.62 *
47.
Animalarium 4
(before activity)
100
9
9
1087  112
760  95
270  67
1622  56
1059  82
526  45
1.49  0.16 *
1.39  0.20 *
1.95  0.51 *
48.
Clean-room
(class 1000)
100
9
9
20  20
30  6
00
1233  1100 b
1044  978 b
67  44
61.67  82.63
34.81  33.34
66.67  76.98 *
49.
Clean-room
(class 10000)
100
9
9
33  19
33  9
33
207  85
185  74
30  20
6.22  4.37 *
5.56  2.68 *
8.89  10.00
50.
Clean-room
(class 100000)
100
9
9
73c
94c
00c
256  164 c
234  152 c
49  13 c
38.45  30.08 *
28.02  22.66 *
48.73  13 *
NC: not countable
*: statistically significant difference between results obtained by the culture-based method and by SPC (Mann-Whitney test, p < 0.05)
a
: result based on only 1 value
b
: result based on only 2 values
c
: result based on 6 values
d
: scan aborted
25
Table 2: Remaining viable cells after storage (4°C) of the dissolved Polym’air for 4 h
and 24 h. Data are presented as the average fraction (%) of the cells that were detected
at t = 0 ( SE).
Storage time
4h
24 h
Fraction of the cells (%) detected at t = 0
Bacteria
Total
Fungi
104  3
112  23
106  1
43  15 *
51  13 *
53  25 *
*: statistically significant difference between results obtained before and after storage (Mann-Whitney
test, p < 0.05)