Comparison of dry- and wet-based fine bead homogenizations to extract DNA from fungal spores

Journal of Bioscience and Bioengineering VOL. 107 No. 4, 464 – 470, 2009 www.elsevier.com/locate/jbiosc

Comparison of dry- and wet-based fine bead homogenizations to extract DNA from fungal spores Naomichi Yamamoto,1,2,⁎ Yasunari Matsuzaka,3 Minoru Kimura,4 Hideaki Matsuki,1 and Yukio Yanagisawa5 Department of Nursing, School of Health Sciences, Tokai University, Bohseidai, Isehara-shi, Kanagawa 259-1193, Japan 1 Japan Society for the Promotion of Science (JSPS), Ichiban-cho 8, Chiyoda-ku, Tokyo 102-8472, Japan 2 Institute of Experimental Genetics, Helmholtz Zentrum München, Ingolstädter Landstraβe 1, D-85764 Neuherberg, Germany 3 Department of Molecular Life Science, Division of Basic Medical Science and Molecular Medicine, School of Medicine, Tokai University, Bohseidai, Isehara-shi, Kanagawa 259-1193, Japan 4 and Department of Environment Systems, Institute of Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-no-ha 5-1-5, Kashiwa-shi, Chiba 277-8561, Japan 5 Received 13 August 2008; accepted 6 December 2008

The present study explored DNA extraction kinetics from fungal spores, i.e., Aspergillus niger, Penicillium chrysogenum and Cladosporium sphaerospermum, by fine bead mill homogenization. In particular, the study aimed to investigate basic differences between the dry- and wet-based methods. The results showed higher initial rates of the DNA extractions by the dry-based method than by the wet-based method, due to higher collision efficiency among fine beads and fungal spores. Based on the experimental results, we constructed kinetic models. While the results by the wet-based method were fitted well with an existing first-order release-degradation model, the results by the dry-based method were not fitted well. Meanwhile, a newly constructed first-order release-degradation model, assuming a proportion of the DNA remained inside the disrupted spore cells and protected from further sheer stress, showed good correlations. The real-time PCR assays showed the PCR efficiencies of the DNA obtained by the dry-based method were higher than those by the wet-based method likely due to increased moderate fragmentation of the DNA by the dry-based method. Thus, although wet-based methods have been commonly used, dry-based methods might also be applicable to achieve efficient extraction and PCR amplification of fungal DNA. © 2008, The Society for Biotechnology, Japan. All rights reserved. [Key words: Fungi; DNA extraction; Fine bead homogenization; Kinetic model; Dry-based disruption]

In recent years, molecular biology techniques such as polymerase chain reaction (PCR) have been widely used to detect fungi in a variety of environments including air (1, 2), house dust (3, 4), soil (5–7), plant tissue (5) and so on. To detect environmental fungal samples by molecular biology techniques, efficient DNA extraction is important because variation in the efficiency can affect detectability and/or quantitativity by following downstream applications such as PCR. Meanwhile, DNA extraction from fungal cells is known to be difficult since fungal cell walls consisting of thick layers of chitin, glucans, mannans and glycolproteins (8) are physically rigid and resistant to various chemical and enzymatic agents. Although various physical, chemical and enzymatic techniques have been attempted (6,9,10), it is considered no single method is applicable to complete DNA extraction for all species of fungi (10). Among various DNA extraction techniques, fine bead mill homogenization is one of the most widely used pre-treatment methods for rigid fungal cells (1, 3, 9–12). In this method, fine glass or zirconia ⁎ Corresponding author. Department of Nursing, School of Health Sciences, Tokai University, Bohseidai, Isehara-shi, Kanagawa 259-1193, Japan. Tel.: +81 463 93 1121 ext. 4336; fax: +81 463 90 2074. E-mail address: [email protected] (N. Yamamoto).

beads of a few hundred micrometers in diameter are shaken with fungal samples to mechanically disrupt fungal cells. In general, this method is employed on the wet basis. Fungal samples are enclosed in test tubes, immersed in liquid media (e.g., lysis buffer) and shaken with the fine beads. Because of its simplicity, fine bead mill homogenization has been widely used for a variety of fungal samples. Meanwhile, few theoretical studies have been performed to characterize its basic kinetics. For instance, parameters related to fine bead mill homogenization, including bead diameter, amount and kind of liquid media, milling speed and/or duration, and so on, are generally optimized on empirical bases. Therefore, it is necessary to characterize details of its kinetic mechanisms. Meanwhile, numerous theoretical and experimental studies have been performed to characterize kinetics of bead and ball millings in the field of powder technology (13, 14). For instance, extensive studies have been performed to investigate basic differences in grinding kinetics of the dry- and wet-based ball millings using quartz (14), coal (15), quartzite (16) and glass of soda–lime silica (17) as ground materials. In general, advantages of the dry-based methods lie in their capabilities of producing the very smallest particles (14, 16, 17) and obtaining higher initial rates of the particle breakage (16). Therefore, even though wetbased methods have been commonly used to extract fungal DNA from a

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variety of environmental fungal samples, dry-based methods might be applicable for more efficient extraction of fungal DNA. The present study reported here aimed to investigate kinetics of DNA extractions from fungal spores by fine bead mill homogenization. In particular, the study aimed to explore basic differences between the dry- and wet-based fine bead millings since no study has ever been performed to characterize the DNA extractions by the dry-based method. To characterize the DNA extraction kinetics, we analyzed time-course changes of the DNA yields and the DNA fragment sizes. Based on time-course observations, we constructed kinetic models for the DNA extraction from fungal spores. Moreover, real-time PCR assays were performed for each DNA extract to ensure its quality for following PCR applications. MATERIALS AND METHODS Preparation of fungal spore samples Fungi generally observed in indoor and/ or outdoor environments, i.e., Aspergillus niger (NBRC 31384), Penicillium chrysogenum (NBRC 6223) and Cladosporium sphaerospermum (NBRC 4460), were used as test fungal species. These 3 species were selected because of their importance as allergens. The fungi were cultured in plastic containers in which absorbent pads were placed in the bottoms (Microcheck® II Beverage Monitor; Pall Corp., MI, USA). Before culture, the absorbent pads were impregnated by liquid culture media (m-Green Yeast and Mold; Millipore Corp., MA, USA). To prepare the fungal samples including only the spores, sporulated fungal colonies cultured on the bottom of the plastic container were immersed in approximately 50-ml 70% ethanol and vigorously shaken by a test tube mixer for several seconds to suspend only the fungal spores in the ethanol. The fungal spore suspension was divided into 2-ml polypropylene sampling tubes (No. 72.695, Assist Co., Ltd., Tokyo, Japan) to obtain 70–90 subsamples for each experiment. The tubes were centrifuged at 15,000 g for 5 min to precipitate the spores. The supernatant ethanol was removed from the tubes, and the remaining fungal spore pellets were desiccated approximately for 3 days. 70% ethanol was used as a dispersant since no residue in the sample was remained after desiccation. We established the present methodology since residual dispersants (e.g., Tween 80) in the desiccated samples might affect the disruption characteristics by fine bead milling. To characterize the numbers of fungal spores in each subsample, several tubes were subject to microscopic observation at a magnification of × 400 (×40 and × 10 for objective and ocular lenses, respectively; Eclipse E200; Nikon Corp., Tokyo, Japan). The tubes containing desiccated fungal pellets were added with 2-ml Tween 80 solution (0.05% (v/v)) and 20-μl gentian violet R solution (0.05% (w/w) in absolute ethanol). The fungal suspensions prepared in this manner were introduced to the cell count plate to enumerate the fungal spores. The numbers of the fungal spores used in each experiment are summarized in Table 1. The numbers of the fungal spores were adjusted at an order of 106 spores/tube for Experiments 1–3. Furthermore, A. niger samples with different spore counts (2.76 × 106 and 1.82 × 107 spores/tube for Experiments 1 and 4, respectively) were also prepared. Extraction of the fungal DNA In this study, 400-mg zirconia beads with a diameter of 500cm (YTZ ball, Nikkato Corp., Osaka, Japan) were used for fine bead mill homogenization. For the wet-based disruption method, 600-μl lysis buffer of a commercially available DNA extraction and purification kit (Template Extraction Buffer; Plant Geno-DNA-Template; G-Biosciences, MO, USA) was preliminarily added to the tubes containing the fungal spore pellets before fine bead milling. For the dry-based disruption method, 600-μl lysis buffer was added after fine bead milling. The tubes containing the fine beads were shaken up to 60 min at a maximal speed of a tube mixer (=10) (MT-360 or MT-300; TOMY Tech USA, Inc., CA, USA). The zirconia beads enclosed in the plastic microtube were collided each other by vibration generated by the tube mixer. The collision between the beads could disrupt fungal spores. The buffer containing the extracted fungal DNA after fine bead milling was purified by following a standard protocol given by the Plant Geno-DNA-Template. The fungal DNA extracted and purified by the abovementioned procedures was eluted by TE to a final volume of 100 μl. It is known that each DNA extraction kit shows different sensitivity, purity, duration and cost (18, 19). For instance, Löffler et al. (19) noted that the sensitivities differed by an order of 103 by each extraction protocol. In this study, Plant Geno-

TABLE 1. Summary of fungal spore counts characterized by microscopic observation Experiment 1 2 3 4 a b

Fungal species

Spore count

SD a (n = 4)

CV b (%)

A. niger P. chrysogenum C. sphaerospermum A. niger

2.76 × 106 2.69 × 106 2.30 × 106 1.82 × 107

0.38 × 106 0.65 × 106 0.45 × 106 0.31 × 107

14 24 20 17

Standard deviation. Coefficient of variation.

FIG. 1. Schematic diagram of the release-degradation models for the DNA extraction from fungal spores by (A) dry- and (B) wet-based disruption methods.

DNA-Template was used since it showed the highest DNA extraction efficiency among several commercially available DNA extraction kits we tested. We found the DNA recovery efficiency intrinsic to this DNA extraction kit was sufficiently high (i.e., 95%). The intrinsic recovery efficiency was defined as a fraction of the DNA recovered from the DNA introduced to the DNA extraction kit. For instance, 3.47 ng of the fungal DNA was recovered from 3.67 ng of the DNA introduced. To confirm the abovementioned intrinsic recovery efficiency, the naked fungal DNA extracted from A. niger was used. Evaluation of the DNA yields To quantitate the DNA yields obtained by the dry and wet based disruption methods, PicoGreen® dsDNA Kit (Invitrogen Corp., CA, USA) was used. The DNA extracts (50 μl) obtained by the abovementioned procedures were added with PicoGreen® dsDNA reagent (100 μl) and TE (50 μl), applied to each well of a 96-well microplate (Kartell, Milano, Italy) and analyzed by a fluorescence plate reader (FL600; Bio-Tek Instruments, Inc., VT, USA). Evaluation of the DNA fragment sizes To evaluate the DNA fragment sizes, the DNA extracts (5 μl) obtained by Experiment 4 were electrophoresed along with Wide-Range DNA Ladder (50–10,000 bp) (Takara Bio Inc., Shiga, Japan) on a 2.4% (w/w) agarose gel (Agarose ME; Iwai Chemicals Company Ltd., Tokyo, Japan) at 17 V/cm for 25 min. The DNA on the gel was visualized by staining with SYBR® Green I Nucleic Acid Gel Stain (Lonza Group Ltd., Basel, Switzerland) and detected by the LAS-1000 lumino-image analyzer (Fujifilm Corp., Tokyo, Japan). The DNA densities on the stained gel were analyzed by using an image analysis software (Image Gauge Version 3.0) in LAS-1000. Real-time PCR assay Although several primers are available to amplify fungal DNA (11), we used primer sets of NS1/NS4 (NS1, 5′-GTAGTCATATGCTTGTCTC-3′; NS4, 5′-CTTCCGTCAATTCCTTTAAG-3′; product size, 1,100 bp) and NS5/NS6 (NS5, 5′AACTTAAAGGAATTGACGGAAG-3′; NS6, 5′-GCATCACAGACCTGTTATTGCCTC-3′; product size, 310 bp) for real-time PCR assays. These primer pairs amplify 18S rDNA region of fungal DNA. Each 50-μl reaction mixture consisting of 25 μl of SYBR® Premix Ex Taq™ II (×2), 1 μl of ROX reference Dye II (×50) (Takara Bio Inc., Shiga, Japan), 2 μl of each primer (10 μM), 16 μl of deionized water and 4 μl of the DNA extracts was used for real-time PCR assays by a real-time PCR system (ABI 7500 Fast Real-time PCR System; Applied Biosystems, CA, USA). Cycling conditions were: 95 °C for 20 s and then 50 cycles of 95 °C for 4 s and 60 °C for 90 s for NS1/NS4; 95 °C for 20 s and then 50 cycles of 95 °C for 4 s and 60 °C for 34 s for NS5/NS6. The threshold cycles (Ct) were calculated by setting a threshold level at 0.2 and using the auto-baseline function in ABI 7500. Modeling In general, amount of DNA extracted from cell tissues by mechanical disruption increases early in the disruption process, but decreases with the further process. The decrease of DNA is thought due to degradation of DNA molecules by shearing at the molecular level and denaturing by local frictional overheating in the media (20). In this study, we used a first-order kinetic model previously examined by Carlson et al. (20) using Escherichia coli. Briefly, this model assumes series reactions of release-degradation with first-order rate constants. A schematic of this first-order kinetics model is illustrated in Fig. 1B. According to this model, a first-order rate constant of cell disruption is given by dN =
k1 N dt

ð1Þ

where N is the number of intact spore cells and k1 is a first-order cell disruption constant per minute. By solving Eq. (1) with an initial condition (t = 0) of N = N0, a following equation can be obtained N = N0 expð
k1 t Þ

ð2Þ

where N0 represents the initial number of intact spore cells. Meanwhile, the DNA released from fungal spore cells is assumed to be degraded by a following first-order

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FIG. 2. DNA yields from (A) A. niger (2.76 × 106 spores), (B) P. chrysogenum (2.69 × 106 spores), (C) C. sphaerospermum (2.30 × 106 spores) and (D) A. niger (1.82 × 107 spores). The solid and dotted curves indicate estimates by the dry- and wet-based disruption models, respectively. process. Therefore, the material balance of the DNA present in the solution, i.e., the DNA released into the solution but not degraded, is given by dD = ck1 N
k2 D dt

ð3Þ

where D is the amount of the DNA in the solution, c is genome size per each fungal spore and k2 is a first-order degradation constant per minute. By inserting Eq. (2) to Eq. (3), a following equation can be obtained dD = k1 D0 expð
k1 t Þ
k2 D dt

ð4Þ

where D0 (=cN0) is the amount of the DNA that would be released from the fungal spores if the spores were completely disrupted without any DNA degradation. By solving this first-order ordinary differential equation, a following formula can be obtained D=

k1 D0 ½expð
k1 t Þ
expð
k2 t Þ k2
k1

ð5Þ

In this study, the rate constants for disruption and degradation (k1 and k2) were estimated by least square fitting using a fitting function in a data analysis software (DeltaGraph 5.4.5v J).

RESULTS DNA yields Fig. 2 shows the DNA yields from 2.76 × 106 spores of A. niger (Experiment 1), 2.69 × 106 spores of P. chrysogenum (Experiment 2), 2.30 × 106 spores of C. sphaerospermum (Experiment

3) and 1.82 × 107 spores of A. niger (Experiment 4). As the figure illustrates, initial rates of the DNA extractions by the dry-based method were higher than those by the wet-based method. For instance, the maximum DNA yields were obtained at 2 and 45 min by the dry- and wet-based methods, respectively, in Experiment 3 (Fig. 2C). Fig. 2 also demonstrates the initial rates of the DNA extractions differed by the experiments. While the DNA yields from A. niger (Experiment 1) and C. sphaerospermum (Experiment 3) were peaked immediately after the dry-based fine bead milling (Fig. 2A and C), the maximum DNA yield was obtained at 20 min for P. chrysogenum (Experiment 2) (Fig. 2B). Table 2 summarizes the maximum DNA yields and extraction efficiencies. To calculate the DNA extraction efficiencies, genome sizes of 0.037 and 0.035 pg per fungal cell (spore) were assumed for A. niger and P. chrysogenum, respectively (Kullman, B., Tamm, H., and Kullman, K., Fungal genome size database, 2005) (http://www. zbi.ee/fungal-genomesize). Since no literature data are available for C. sphaerospermum, we tentatively assigned a genome size of 0.035 pg. The extraction efficiencies of the DNA shown in Table 2 were calculated based on the numbers of fungal spores used in each experiment (Table 1) and genome sizes of each fungus. Model fitting Overall, the results obtained by the wet-based method were fitted well with the existing first-order kinetics model.

TABLE 2. Summary of the maximum DNA yields and extraction efficiencies Experiment

Fungal species

Dry/wet

1

A. niger

2

P. chrysogenum

3

C. sphaerospermum

4

A. niger

Dry Wet Dry Wet Dry Wet Dry Wet

a

Maximum DNA yield (± SD a) (ng) 34.1 (± 5.2) ≥54.9 (± 4.5) 25.6 (± 2.1) 20.9 (± 3.7) 30.8 (± 2.4) 33.3 (± 9.8) 296 (± 39) ≥236 (± 18)

Maximum extraction efficiency b (± SD a) (%) 33.5 (± 5.1) ≥53.9 (± 4.4) 27.2 (± 2.2) 22.2 (± 4.0) 38.3 (± 3.0) 41.4 (± 12.1) 44.0 (± 5.8) ≥35.0 (± 2.6)

Time c (min) 30 ≥60 20 45 2 45 5 ≥30

Standard deviation (n = 4). Genome sizes of 0.037 and 0.035 pg per fungal cell (spore) are assumed for A. niger and P. chrysogenum, respectively (Kullman, B., Tamm, H., and Kullman, K. Fungal genome size database, 2005) (http://www.zbi.ee/fungal-genomesize). A genome size of 0.035 pg is tentatively assigned for C. sphaerospermum. c Time the maximum DNA yields was observed. b

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TABLE 3. Summary of fitted results by the first-order kinetics models a Experiment

Fungal species

1

A. niger

2

P. chrysogenum

3

C. sphaerospermum

4

A. niger

First-order rate constant (min− 1)

Dry/wet

Dry Wet Dry Wet Dry Wet Dry Wet

Disruption, k1

Degradation outside the cell, k2

Degradation inside the cell, k3

2.9 1.7 × 10− 2 3.3 × 10− 2 c 9.3 × 10− 3 7.1 × 10− 1 1.6 × 10− 2 1.3 × 10− 1 c ND f

2.4 5.6 × 10− 3 1.8 × 10− 1 c 2.3 × 10− 2 1.1 1.7 × 10− 2 1.7 × 10− 1 c ND f

− 3.1 × 10− 4 NA b 0d NA b − 6.7 × 10− 4 NA b 0d NA b

Fraction of the DNA remained inside the cell, α

Coefficient of determination, R2

0.31 NA b 0.29 e NA b 0.27 NA b 0.29 e NA b

0.985 0.964 0.749 c 0.935 0.991 0.930 0.868 c ND f

a

Two different models, i.e., Eqs. (5) and (11) in text, were used for the wet- and dry-based methods, respectively. Not available because the wet-based method doesn't assume a fraction of the DNA remained inside the cell. c These values were estimated by fixing the values of k3 and α at 0 and 0.29, respectively. d The fixed value (= 0) was assumed for the least square fittings. The value of 0 was assumed based on the fitted results of Experiments 1 and 3 (dry-based method) since the fitted values of k3 (=− 3.1 × 10− 4 and − 7.2 × 10− 4, respectively) were negligibly small compared to the remaining rate constants. e The fixed value (= 0.29) was assumed for the least square fittings. The average of the fitted results by Experiments 1 and 3 (dry-based method) was assumed. f Not determined because of limited data points. b

Table 3 summarizes the fitted results by the first-order kinetics models, indicating coefficients of determination (R2) were larger than 0.9 in all the wet-based experiments. Meanwhile, the results obtained by the dry-based method were not fitted well with the existing model, i.e., R2 = 0.419, 0.822, 0.134 and 0.841 for Experiments 1, 2, 3 and 4, respectively (data not shown). Alternatively, we introduced a modified first-order kinetics model for the dry-based method and obtained good correlations with the model estimates, i.e., R2 = 0.985, 0.749, 0.991 and 0.868 for Experiments 1, 2, 3 and 4, respectively (Table 3). The details of the newly introduced model will be discussed later in this paper. DNA fragment sizes Fig. 3 exhibits the agarose gel analysis of the DNA obtained from 1.82 × 107 spores of A. niger (Experiment 4), indicating the size distributions were shifted to smaller side along with disruption time. This tendency was more distinct in the drybased method than in the wet-based method. For instance, the ratios of the DNA larger than 1,100 bp to total extracted DNA at 30 min of disruption time were 30% and 81% by the dry- and wet-based methods, respectively. PCR amplifications Fig. 4 exhibits the values of Ct measured by real-time PCR (Experiment 4). The values of Ct for the dry-based method decreased more rapidly than those for the wet-based method. Overall, the time-course trends obtained by real-time PCR were consistent with those by PicoGreen. For instance, the largest DNA amount measured by PicoGreen was observed around 5–10 min while

FIG. 3. Agarose gel analysis of the DNA obtained by the dry- and wet-based fine bead millings (Experiment 4).

the smallest Ct (i.e., the largest DNA amount) by real-time PCR was observed at 10 min for the dry-based method. Fig. 5 illustrates the relationships between the DNA amounts measured by PicoGreen and the values of Ct characterized by real-time PCR. The correlations between the two methods were R2 = 0.3045 and 0.7199 with NS1/ NS4 and NS5/NS4 primers, respectively. DISCUSSION The initial rates of the DNA extractions were higher for the drybased method than for the wet-based method in all the experiments (Fig. 2). Interestingly, this tendency was consistent with the result reported in the field of powder technology (16). Berube et al. (16) reported the data showing the initial breakage rate of quartzite grains was higher for the dry-based method than for the wet-based method. It should be noted, however, that the results reported in this study might not be directly comparable to the results reported

FIG. 4. Threshold cycle numbers (Ct) measured by real-time PCR with (A) NS1/NS4 and (B) NS5/NS6 primers (n = 4) (Experiment 4). The Ct values are not shown for the data of 2 and 5 min by the wet-based method because some samples (out of 4 trials) were not amplified.

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J. BIOSCI. BIOENG., the extraction efficiencies, respectively. To account for this stable fraction of the DNA, we hypothesized a proportion of the DNA remained inside the disrupted spore cells and protected from further sheer stress. Unlike the wet-based method, the dry-based method does not have surrounding liquid medium into which the extracted DNA can be eluted. Consequently, the DNA in the dry-based extraction system has to remain to stick to the disrupted cell tissues, for instance, by the abovementioned adhesive forces even after spore disruption. Based on this hypothesis, we newly introduced a modified firstorder kinetics model for the dry-based disruption method (Fig. 1A). In this model, we assumed two kinds of the DNA; (i) DNA remained inside the disrupted spore cells and protected from further sheer stress by fine bead milling, (ii) DNA protruded outside the disrupted spore cells and directly exposed to further sheer stress by fine bead milling. Similar to the wet-based method, the rate of the cell disruption can be given by Eq. (1). However, two different degradation rate constants were assumed for these two kinds of the DNA

FIG. 5. Relationships of the DNA amounts measured by PicoGreen and threshold cycle numbers (Ct) characterized by real-time PCR with (A) NS1/NS4 and (B) NS5/NS6 primers (Experiment 4).

by Berube et al. (16) since size of steel balls used by Berube et al. (16) (i.e., 2.54 cm in diameter) was much larger than the size of the zirconia beads used in this study (i.e., 500 μm in diameter). Since the grinding kinetics is known to depend on various factors including size environments of balls and ground materials, mechanical strength of ground materials (15) and so on, the underlying mechanisms might be different between the two studies. Nevertheless, it is interesting to observe the distinct differences in the DNA extraction characteristics between the dry- and wet-based methods, as it is inferentially suggested from the result reported in the field of powder technology. The higher DNA extraction rates by the dry-based methods are expected due to adhesive forces on the fungal spores to the surface of the zirconia beads. In general, adhesive forces (e.g., van der Waals, electrostatic and surface tension forces) on a particle smaller than 10 μm are much greater than removal forces (e.g., gravitational, vibrational and centrifugal forces, and air current), making detachment of such a particle from surfaces much more difficult (21). Since sizes of the fungal spores used in this study are smaller than 10 μm, it is likely the fungal spores were adhered to the surface of the zirconia beads by the abovementioned adhesive forces. Indeed, we observed the adhesion of the zirconia beads to the inner wall surface of the polypropylene sampling tube, probably due to static buildup in the drybased method. The adhesive forces, including electrostatic force, might cause adhesion of the fungal spores to the surface of the zirconia beads, resulting in the increase of collision efficiency among the zirconia beads, the fungal spores and the inner wall surface of the polypropylene sampling tube. While the results obtained by the wet-based method were fitted well with the existing first-order kinetics model, the results by the dry-based method were not fitted well with the model. It is worth noting that the DNA amounts obtained by the dry-based experiments, Experiments (1) and (3) in particular, appeared to be stabilized after 10 min of disruption (Fig. 2A and C). The amounts of the DNA stabilized after 10 min corresponded to approximately 31% and 27% of

dDout = ð1
aÞD0 k1 expð
k1 t Þ
k2 t dt

ð6Þ

dDin = aD0 k1 expð
k1 t Þ
k3 t dt

ð7Þ

where Dout and Din are the amounts of the DNA outside and inside the disrupted spore cells, respectively, α is the fraction of the DNA remained inside the disrupted spore cells, and k2 and k3 are the firstorder rate constants for the degradation outside and inside the disrupted spore cells, respectively. By solving Eqs. (6) and (7), we obtain Dout =

Din =

ð1
aÞk1 D0 ½expð
k1 t Þ
expð
k2 t Þ k2
k1

ak1 D0 ½expð
k1 t Þ
expð
k3 t Þ k3
k1

ð8Þ

ð9Þ

Since the DNA remained inside the spore tissues is still recoverable by adding the lysis buffer and eluting in it after the disruption process, total amount of the DNA extracted in the solution can be written by D = Dout + Din

ð10Þ

By inserting Eqs. (8) and (9) to Eq. (10), we obtain D=

ð1
aÞk1 D0 ½expð
k1 t Þ
expð
k2 t Þ k2
k1 ak1 D0 + ½expð
k1 t Þ
expð
k3 t Þ k3
k1

ð11Þ

Here, the rate constants for disruption and degradation (k1, k2 and k3) as well as the fraction of the DNA inside the disrupted spore cells (α) were estimated by the least square fitting using a fitting function of the data analysis software (DeltaGraph 5.4.5v J). Table 3 summarizes fitted results for the dry-based method by the abovementioned modified first-order kinetics model. In Table 3, fixed values of k3 = 0 and α = 0.29 were assumed for the least square fitting for Experiments 1 and 4 (dry-based method) since the durations of the data set were not sufficient to represent the abovementioned stable fraction of the DNA. The fixed value of k3 = 0 was assumed since the fitted values of k3 for Experiments 1 and 3 (dry-based method) were negligibly small (i.e., k3 = −3.1 × 10− 4 and −7.2 × 10− 4 min− 1, respectively) compared to the remaining rate constants. Meanwhile, the fixed value of α = 0.29 was assumed as an average value of the fitted results by Experiments 1

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and 3 (i.e., α = 0.31 and 0.27, respectively). Overall, we confirmed good correlations with the modified first-order kinetics model for the dry-based method, i.e., R2 = 0.985, 0.749, 0.991 and 0.868 for Experiments 1, 2, 3 and 4, respectively, supporting validity of the newly introduced first-order kinetics model. The initial DNA extraction rates differed by the experiments (Fig. 2). Factors potentially affecting the rates of the DNA extractions include size of the fungal spores. For instance, Haugland et al. (9) suggested DNA yields from fungi with small spore sizes were lower than those from fungi with large spore sizes. However, spore sizes of the fungal species used in this study are almost same, i.e., 3.5–5, 3– 4.5 μm (22) and 2.5–3.5 μm (23) for A. niger, C. sphaerospermum and P. chrysogenum, respectively. Therefore, it is reasonable to conclude the observed differences in the rates of the DNA extraction were not likely owing to the differences in the spore sizes. An additional factor affecting the rates of the DNA extractions is mechanical strength of fungal cell walls. For instance, Bowman and Free (8) described amounts of chitin, a structurally important component of fungal cell walls, are different by fungal species. They noted chitin accounted for 1%–2% and 10%–20% of cell walls of yeasts and filamentous fungi, respectively. The differences in cell wall constituents, chitin in particular, might affect DNA extraction efficiencies from fungi. Indeed, Löffler et al. (19) reported DNA release from spores of A. niger (filamentous fungi) was much more difficult than that from Candida albicans (yeast). Although it is difficult to confirm its effect only by the present data set, variations in cell wall constituents might affect the rates of the DNA extraction from fungal spores. Future research should further elucidate this viewpoint. The conditions of the fungal spore pellets might be much more important to determine the rates of the DNA extraction. For instance, initial rates of the DNA extraction were different even though the same fungal species, i.e., A. niger, was used in Experiments 1 and 4. The number of the fungal spores in Experiment 4 was approximately 6.6 times larger than that in Experiment 1 (Table 1). Meanwhile, Table 3 shows the first-order cell disruption constant by Experiment 4 was higher than that by Experiment 1, i.e., k1 = 2.9 and 1.3 × 10− 1 min− 1, respectively. Thus, increase in the quantity of the pellet appeared to decrease the rate of the spore disruption. Furthermore, Table 3 demonstrates variation in the first-order spore disruption constants across the experiments was larger for the dry-based method (i.e., k1 = 3.3 × 10− 2–2.9 min− 1) than for the wet-based method (i.e., k1 = 9.3 × 10− 3–1.7 × 10− 2 min− 1). Given variation in the conditions of the fungal pellets is negligible in all the wet-based experiments since the fungal pellets were made into the states of the fungal suspensions, the excess in the variation in the rate constants observed across the dry-based experiments is expected to be derived from variation in the conditions of the fungal spore pellets. Thus, the conditions of the fungal spore pellets, such as thickness, firmness and/or degree of agglomeration of the pellets, might play an important role in determining the rate constants for the dry-based spore disruption. The PCR efficiencies of each DNA extract were likely deviated depending on disruption time and/or disruption methods since the size distributions of the DNA fragments were different by each sample (Fig. 3). Since denaturation temperature of DNA is known to depend on the length of DNA (24), the optimal denaturation conditions for each DNA extract were likely different as well. Such variations in the optimal DNA denaturation conditions could cause deviation in the DNA amplification efficiencies, too. Fig. 6 exhibits the PCR efficiencies of the DNA obtained by the dryand wet-based methods. In this figure, the PCR efficiencies are on the relative basis. The relative PCR efficiency was defined as a ratio of the DNA amount characterized by real-time PCR to that measured by PicoGreen. The DNA amounts by real-time PCR were inversely calculated by assigning the values of Ct measured by real-time PCR

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FIG. 6. Relative amplification efficiency of the DNA by real-time PCR with (A) NS1/NS4 and (B) NS5/NS6 primers (Experiment 4). The relative amplification efficiency by PCR was defined as a ratio of the DNA amount characterized by real-time PCR to that measured by PicoGreen. The DNA amounts by real-time PCR were inversely calculated by assigning the values of Ct measured by real-time PCR to the regression equations shown in Fig. 5. The data for 2 and 5 min by the wet-based method are not shown because some samples (out of 4 trials) were not amplified.

to the regression equations shown in Fig. 5. The figure illustrates the higher PCR efficiencies of the DNA by the dry-based method than those by the wet-based method. Since melting temperature of DNA is known to increase with the length of the DNA (24), denaturation efficiencies of the less-fragmented DNA by the wet-based method are expected to be lower than those of the more-fragmented DNA by the dry-based method. This might result in the decrease in the PCR efficiencies of the DNA by the wet-based extraction method. Moreover, the relative PCR efficiencies of the DNA obtained by the dry-based method appeared to increase around 5–10 min of disruption due potentially to the increase of the DNA fragmentation as well. Meanwhile, the further fragmentation of the template DNA is expected to decrease the PCR efficiency. In theory, template DNA needs to be larger than sizes of PCR amplicons at least since each template needs to contain both sites for forward and reverse primers for successful PCR. To examine an effect of the template sizes relative to the sizes of PCR amplicons, fragment size distributions of the DNA extracts, i.e., total, N300 and N1,100 bp, were calculated. These size segregations roughly correspond to the sizes of the PCR products, i.e., 310 and 1,100 bp for NS5/NS6 and NS1/NS4, respectively. For the drybased method, the ratios of the DNA larger than 1,100 bp to total extracted DNA were decreased along with disruption time, i.e., 78%, 45%, 30% and 30% at 5, 10, 20 and 30 min, respectively, indicating decrease of the fraction of the template DNA available for successful PCR amplification with NS1/NS4 primers. The decrease of the template DNA with sufficient lengths for NS1/NS4 primers is expected to decrease the PCR efficiency by NS1/NS4 primers. However, the PCR efficiencies were not considerably decreased, i.e., 0.82, 1.24, 1.20 and 1.20 at 5, 10, 20 and 30 min, respectively (Fig. 6), but rose slightly between 5 and 10 min. As previously explained, the observed rise in the PCR efficiency was likely due to the increase of the denaturation efficiency owing to the moderate, but not excess, fragmentation of the DNA. Therefore, the unchanged PCR efficiencies between 10 and

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30 min might be an offset effect by the increased PCR efficiencies due to the moderate fragmentation of the extracted DNA.

J. BIOSCI. BIOENG.,

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ACKNOWLEDGMENT 12.

Naomichi Yamamoto receives the grant from the Japan Society for the Promotion of Science (JSPS) for this research. References

13. 14. 15.

1. Wu, Z., Blomquist, G., Westermark, S.-O., and Wang, X.-R.: Application of PCR and probe hybridization techniques in detection of airborne fungal spores in environmental samples, J. Environ. Monit., 4, 673–678 (2002). 2. Zeng, Q.-Y., Westermark, S.-O., Rasmuson-Lestander, A., and Wang, X.-R.: Detection and quantification of Cladosporium in aerosols by real-time PCR, J. Environ. Monit., 8, 153–160 (2006). 3. Meklin, T., Haugland, R. A., Reponen, T., Varma, M., Lummus, Z., Bernstein, D., Wymer, L. J., and Vesper, S. J.: Quantitative PCR analysis of house dust can reveal abnormal mold conditions, J. Environ. Monit.,, 6, 615–620 (2004). 4. Vesper, S., McKinstry, C., Ashley, P., Haugland, R., Yeatts, K., Bradham, K., and Svendsen, E.: Quantitative PCR analysis of molds in the dust from homes of asthmatic children in North Carolina, J. Environ. Monit., 9, 826–830 (2007). 5. Borneman, J. and Hartin, R. J.: PCR primers that amplify fungal rRNA genes from environmental samples, Appl. Environ. Microbiol., 66, 4356–4360 (2000). 6. Kabir, S., Rajendran, N., Amemiya, T., and Itoh, K.: Quantitative measurement of fungal DNA extracted by three different methods using real-time polymerase chain reaction, J. Biosci. Bioeng., 96, 337–343 (2003). 7. Viaud, M., Pasquier, A., and Brygoo, Y.: Diversity of soil fungi studied by PCR-RFLP of ITS, Mycol. Res., 104, 1027–1032 (2000). 8. Bowman, S. M. and Free, S. J.: The structure and synthesis of the fungal cell wall, BioEssays, 28, 799–808 (2006). 9. Haugland, R. A., Heckman, J. L., and Wymer, L. J.: Evaluation of different methods for the extraction of DNA from fungal conidia by quantitative competitive PCR analysis, J. Microbiol. Methods, 37, 165–176 (1999). 10. Karakousis, A., Tan, L., Ellis, D., Alexiou, H., and Wormald, P. J.: An assessment of the efficiency of fungal DNA extraction methods for maximizing the detection

16.

17.

18.

19.

20. 21. 22. 23.

24.

of medically important fungi using PCR, J. Microbiol. Methods, 65, 38–48 (2006). Wu, Z., Wang, X. R., and Blomquist, G.: Evaluation of PCR primers and PCR conditions for specific detection of common airborne fungi, J. Environ. Monit., 4, 377–382 (2002). Zhou, G., Whong, W.-Z., Ong, T., and Chen, B.: Development of a fungus-specific PCR assay for detecting low-level fungi in an indoor environment, Mol. Cell. Probes, 14, 339–348 (2000). Annapragada, A. and Adjei, A.: Numerical simulation of milling processes as an aid to process design, Int. J. Pharm., 136, 1–11 (1996). Yekeler, M., Ozkan, A., and Austin, L. G.: Kinetics of fine wet grinding in a laboratory ball mill, Powder Technol., 114, 224–228 (2001). Celik, M. S.: A comparison of dry and wet fine grinding of coals in a ball mill, Powder Technol., 55, 1–9 (1988). Berube, M. A., Berube, Y., and Le Houillier, R.: A comparison of dry and wet grinding of a quartzite ground in a small batch ball mill, Powder Technol., 23, 169–178 (1979). Kanda, Y., Abe, Y., Yamaguchi, M., and Endo, C.: A fundamental study of dry and wet grinding from the viewpoint of breaking strength, Powder Technol., 56, 57–62 (1988). Fredricks, D. N., Smith, C., and Meier, A.: Comparison of six DNA extraction methods for recovery of fungal DNA as assessed by quantitative PCR, J. Clin. Microbiol., 43, 5122–5128 (2005). Löffler, J., Hebart, H., Schumacher, U., Reitze, H., and Einsele, H.: Comparison of different methods for extraction of DNA of fungal pathogens from cultures and blood, J. Clin. Microbiol., 35, 3311–3312 (1997). Carlson, A., Signs, M., Liermann, L., Boor, R., and Jem, K. J.: Mechanical disruption of Escherichia coli for plasmid recovery, Biotechnol. Bioeng., 48, 303–315 (1995). Hinds, W. C.: Aerosol technology: properties, behavior, and measurement of airborne particles, 2nd ed.Wiley, NY, 1999. Cole, G. T. and Samson, R. A.: In: Y. Al-Doory, J. F. Domson (Eds.), The conidia, Chapter 5, Mould allergy, Lea & Febiger, Philadelphia, PA, 1984, pp. 66–103. Rydjord, B., Namork, E., Nygaard, U. C., Wiker, H. G., and Hetland, G.: Quantification and characterisation of IgG binding to mould spores by flow cytometry and scanning electron microscopy, J. Immunol. Methods, 323, 123–131 (2007). Ririe, K. M., Rasmussen, R. P., and Wittwer, C. T.: Product differentiation by analysis of DNA melting curves during the polymerase chain reaction, Anal. Biochem., 245, 154–160 (1997).