Biotechnology Letters 22: 399–405, 2000. © 2000 Kluwer Academic Publishers. Printed in the Netherlands.
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Digitization of DGGE (denaturing gradient gel electrophoresis) profile and cluster analysis of microbial communities Tong Zhang & Herbert H.P. Fang∗ Centre for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pofkulam Road, Hong Kong SAR, China ∗ Author for correspondence (Fax: (852) 25595337; E-mail:
[email protected]) Received 10 December 1999; Revisions requested 16 December 1999; Revisions received 11 January 2000; Accepted 11 January 2000
Key words: biofilm, cluster analysis, DGGE, microbial community
Abstract Denaturing gradient gel electrophoresis (DGGE) of 16S rDNA profiles were objectively digitized using an image analyzer; the individual microbial species in a community can thus be precisely quantified. The similarity between various microbial communities was compared to the digitized DGGE profiles using the cluster analyses technique. The microbial community in a biofilm was considerably different from that in suspended sludge obtained from the same system.
Introduction Species identification and population enumeration are critical in the study of microbial communities. Traditionally, microbial species are cultured and then characterized by their respective physiological and biochemical properties. This method, however, has a serious drawback because most of the bacteria cannot be readily isolated and cultured. Amann (1995) estimated that only less than 1% of bacteria in the natural environment can be cultured. Recently, researchers have applied various molecular methods to the study of microbial communities, including polymerase amplification reaction (PCR) and denaturing gradient gel electrophoresis (DGGE) (Muyzer et al. 1993), cloning (Sekiguchi et al. 1998), slot-blotting hybridization (Raskin et al. 1995), fluorescence in situ hybridization (Okabe et al. 1999), single strand conformation polymorphism (Lee et al. 1996), etc. Many researchers use the method combining PCR and DGGE to the study of microbial communities in various environments (Fournier et al. 1998), such as biofilms (Devereux et al. 1996) and activated sludge (Curtis & Caine 1998). Using a selected set of primers, a fragment of microbial genomic DNA encoding for 16S rRNA can be amplified up to 107 times in PCR.
The PCR products from different microbial species have the same length but different DNA sequences. These species-specific sequences may be separated on the denaturing gradient gel due to their differences in mobility during electrophoresis. After staining, each band on the denaturing gradient gel represents a specific 16S rDNA sequence from a specific microbial species. Thus, the species can be identified by the band positions on the gel, their concentrations corresponding to the band intensities. In most studies, DGGE bands are visually selected for comparison. However, visual observation may overlook bands of low intensity and those close to each other. This study was conducted to demonstrate that the DGGE profiles of 16S rDNA can be digitized using an image analyzer, so that the band positions and intensities can be objectively and precisely measured. As a result, the digitized DGGE profiles can be used for cluster analysis to study the degrees of similarity among different microbial communities. In this study, the degrees of similarity between two anaerobic microbial communities, biofilm and suspendedgrowth, were compared over a 90-day period as a demonstration of this technique.
400 Materials and methods Biofilm and suspended-growth cultures The biofilm and suspended-growth communities rich in sulfate-reducing bacteria (SRB) were cultured anaerobically in a 20-liter seawater medium in a glass tank at pH 7.2–7.6 and 20–22 ◦ C. Biofilm was developed on steel coupons. The seawater was filtered through a 0.45 µm filter paper and dosed with the following chemicals (l−1 ): KH2 PO4 0.5 g, NH4 Cl 1.0 g, CaCl2 · 6H2 O 0.06 g, MgSO4 · 7H2 O 0.06 g, FeSO4 · 7H2 O 4.0 mg, sodium lactate 6 g, sodium citrate · 2H2O 0.3 g, and yeast extract (Difco) 1 g. It was then purged with nitrogen to remove dissolved oxygen in order to ensure the anaerobic environment. SRB was first enriched from seabed sediment in a separate reactor for three months using the same medium. The enriched culture was used as the microbial seed at the initial concentration of 1 × 106 cell ml−1 in the test medium. Every ten days, half of the medium in the glass tank was replaced by a fresh medium solution. Samples of microbial seed, biofilm and suspendedgrowth sludge were collected at various periods for PCR-DGGE analysis. DNA extraction Each biofilm sample was first washed with a phosphate buffer solution (pH 7.4), removed from the coupon and then suspended in a 10 ml phosphate buffer solution. Ten ml of suspended culture was collected for each DNA extraction. All the samples were centrifuged at 4000 rpm for 10 min, and re-suspended in 1 ml of lysis buffer (Stahl et al. 1988). The suspended samples were homogenized in a bead beater (Mini-Beadbeater, Biospec Products) with 0.2 g of glass bead with 1 µm diameter at 5000 rpm for 20 s. The process was repeated three times with cooling in between to avoid overheating. The genomic DNA in the homogenized samples was extracted using the method as detailed by Stahl et al. (1988). PCR amplification Two sets of primer were used for PCR amplification. One complements a conserved region among members of Eubacteria (Escherichia coli positions 960–975) and incorporates a 40-bp GC clamp (Muyzer et al. 1995). The other was based on a universally conserved region (E. coli positions 1392–1406) (Ferris
et al. 1996). PCR amplification was conducted following the method of Muyzer et al. (1995) with the annealing temperature of 54 ◦ C. DGGE analysis DGGE was performed following the method of Muyzer et al. (1993). The 6% (w/v) acrylamide solution was used to cast a gel with denaturant gradients ranging 40%–60%. Electrophoresis was run in a 1× TAE buffer solution at 200 V and 60 ◦ C for 5 h. The bands on the gel were then stained with silver nitrate (Riesner et al. 1989). Image analysis The band positions and intensities were recorded by an image analyzer (Q600S, Leica) with a digital CCD camera. The band positions and intensities were analyzed using a software (Quantimet Q600) provided by the manufacturer (Leica). The bands, or peaks, positions, in the DGGE profile corresponded to individual microbial identities, and the band intensities, i.e., peak heights, represented their relative quantities. The positions and the heights of the identifiable peaks of each DGGE profile could then be digitized. The similarity among various samples could be compared by cluster analysis of the digitized profile.
Results Digitization of DGGE profile The microbial seed (MS), two samples of suspendedgrowth communities (SC) collected at days 20 and 90, and six samples of biofilm communities (BC) collected at days 5, 10, 20, 40, 60 and 90, were analyzed using the PCR-DGGE method. Figure 1 illustrates the DGGE band patterns of the nine samples. Figure 2 illustrates the image of the DGGE band pattern for the MS sample. It shows that there are eleven identifiable peaks, each corresponding to a band in the DGGE gel and, thus, a microbial species in the MS communities. Without using image analysis, some of bands, such as those at 44.9%, 45.4%, 46.1% and 54.4% of denaturant, were too faint to be recognized visually. Similar DGGE profiles were also plotted for the other eight samples. A total of 21 distinct bands were identified from the nine samples. A matrix could then be constructed to show the band patterns for the microbial samples. Table 1 is such a matrix, which shows
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Fig. 1. DGGE images for microbial species in Eubacteria domain.
relative concentrations of 21 individual species in the nine samples. Table 1 shows that, out of the 21 species, only 11 species could be found in the seed sludge. The bands of the remaining ten species were too faint to be recognized. Furthermore, only four species, i.e., at the denaturant concentrations of 47.8%, 49.7%, 50.5% and 51.8%, could be found in all nine samples. Three species at 43.2%, 49.4% and 52.8% could only be found in biofilm communities, and the one at 45.4% only appeared in the suspended microbial communities. Cluster analysis of microbial communities Using the matrix in Table 1, the similarities (or dissimilarities) between the microbial seed, biofilm communities and the suspended communities could be quantified using cluster analysis. Euclidean distances were calculated from relative concentration data in the matrix, and samples were clustered using the average linkage method. Figure 3 illustrates that the six BC samples were clustered, indicating that they were closely related and significantly different from the SC and MS samples. The short distance between day-60 (BC60) and day-90 (BC90) biofilm samples indicates the high degree of similarity between these two samples.
Discussion Band selection and comparison Each microbial species has its specific DNA sequences coding for 16S rRNA. During electrophoresis, the PCR-amplified 16S rRNA gene fragments of various species migrate towards increased denaturant concentration. The migration of various DNA fragments, having the same size but different sequences, ceases at different positions on the denaturing gradient gel. The denaturant concentration at which the fragment ceased to migrate is used to identify the species. The separation of various species by the denaturant concentration is very precise. Even species with difference of one base pair in DNA sequences could be distinguished under right conditions (Muyzer 1993). The DGGE profile of a sample becomes the fingerprint of its community. The length of 16S rDNA fragment amplified by PCR is determined by the set of selected primers. Some researchers used shorter fragments of about 200 bp for better separation (Ovreas et al. 1997). In such a case, there is an increased possibility that more than one species would have the same sequence in the selected fragment, and cannot be differentiated by the DGGE. On the other hand, fragments longer 500 bp may be difficult to separate by electrophoresis
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Fig. 2. DGGE image of the microbial seed and the digitized profile of the major species in the community.
Table 1. Percentage of different species in microbial seed (MS) and individual suspended-growth communities (SC) and biofilm communities (BC). Species identified by denaturant conc. (%) 43.2 44.9 45.4 45.8 46.1 46.4 47.2 47.8 48.1 48.8 49.4 49.7 50.1 50.5 51.8 51.8 52.5 52.8 53.4 54.1 54.4 Total
MS
0.0 2.5 4.2 0.0 3.3 0.0 0.0 5.0 0.0 15.0 0.0 10.8 4.2 18.3 21.7 0.0 0.0 0.0 13.3 0.0 1.7 100
SC 20d
0.0 0.0 8.9 0.0 0.0 0.0 2.5 10.1 10.1 0.0 0.0 15.2 0.0 30.4 10.1 7.6 0.0 0.0 0.0 0.0 5.1 100
90d
0.0 5.4 0.0 8.7 0.0 15.2 2.2 2.2 0.0 0.0 0.0 13.0 9.8 20.7 20.7 0.0 0.0 0.0 0.0 2.2 0.0 100
BC 5d
0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.9 0.0 10.1 10.1 7.6 0.0 30.4 25.3 0.0 0.0 3.8 0.0 0.0 3.8 100
10d
0.0 0.0 0.0 4.6 0.0 0.0 0.0 6.2 0.0 4.6 0.0 13.8 0.0 26.2 30.8 0.0 0.0 4.6 0.0 4.6 4.6 100
20d
6.3 0.0 0.0 0.0 0.0 0.0 0.0 12.5 0.0 12.5 0.0 15.6 0.0 23.4 29.7 0.0 0.0 0.0 0.0 0.0 0.0 100
40d
6.8 0.0 0.0 0.0 0.0 6.8 8.1 9.5 0.0 0.0 8.1 9.5 0.0 20.3 31.1 0.0 0.0 0.0 0.0 0.0 0.0 100
60d
3.0 0.0 0.0 0.0 0.0 0.0 3.0 15.2 0.0 13.6 0.0 10.6 6.1 10.6 31.8 0.0 0.0 0.0 0.0 3.0 3.0 100
90d
0.0 0.0 0.0 0.0 0.0 0.0 5.9 13.2 0.0 5.9 0.0 11.8 11.8 10.3 35.3 0.0 2.9 0.0 0.0 0.0 2.9 100
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Fig. 3. Cluster analysis trees of the microbial communities.
(Myers et al. 1985). In this study, a primer set for the amplification of 466 bp (Ferris et al. 1996) was used. Separation of species appeared to be satisfactory, judging from DGGE profiles in Figures 1 and 2. Traditionally, the distinctions of bands on DGGE gel and the determination of individual species concentrations rely on visual observation (Curtis & Craine 1998). The technique becomes less reliable for samples of complex communities; bands of some species could be too close to be differentiated. Also, it may likely overlook species of low concentrations, which have low-intensity bands. The method used in this study demonstrated that the DGGE band pattern could be digitized. Using an image analyzer, the DGGE profiles of microbial communities could be objectively and precisely fingerprinted. The effectiveness of this method, however, depends to a large degree on the image document system. Quantification of the DGGE band The conventional culturing method of analyzing microbial population of a community has tremendous limitations. A number of molecular methods have been recently developed. Using the cloning method, the microbial population in an ecosystem is enumerated basing on the frequency of its sequence (Sekiguchi et al. 1998); however, the cloning process is laborious. On the other hand, the RNA in the living cell can be quantified by hybridization with oligonucletide probes; but the RNA quantity may differ from one physiological status to another (Rolleke & Muyzer 1996). Fluorescence in situ hybridization (FISH) is another tool for the quantification of specific bacteria populations (Okabe et al. 1999); but it can only identify microbes of known DNA sequence, and the
technique at present is still limited to no more than four species for each hybridization. Another molecular method to quantify microbial population in a mixed culture is single strand conformation polymorphism (Lee et al. 1996). However, it can effectively separate short fragments (150 bp) (Muyzer 1998), and thus could underestimate the species complexity of the ecosystem. The digitization method demonstrated in this study is simple in operation. Using a sophisticated image analyzer, it is capable of detecting all the major microbial species and quantifying their relative concentrations in one single analysis. However, one has to be cautious in interpreting results because of certain intrinsic limitations. Using this method, the microbial DNA has to be extracted, followed by PCR amplification and electrophoresis in denaturing gradient gel. The accuracy of this method depends on the reliability of each individual step. It is possible that the DNA of some species could not be effectively extracted because they are difficult to lysis even by vigorous bead beating (Curtis & Craine 1998). Also, some DNA fragments could be amplified more efficiently than others, so that the former would be over represented in the PCR products (Muyzer et al. 1993). Furthermore, the separation of some 16S rRNA gene fragments could be difficult if the DGGE is not operated under the optimal conditions (Vallaeys et al. 1997). Comparison of biofilm and suspended communities Most microbes in nature grow in biofilm, instead of in suspension (Costerton et al. 1987). Microbial growth in biofilm has attracted much research interests in recent years. One subject of interest is the microbial population dynamics in biofilm communities as compared to those in suspended communities. Santegoeds et al. (1998) found that the microbial community of a biofilm was different from the suspended-growth seed sludge. Using the DGGE method, they found that microbes in the biofilm had different population structure as compared to the seed sludge; some of the microbes were not even found in the seed. Acinas et al. (1999) compared the microbial communities in biofilm and in suspended-growth in the western Mediterranean waters. They found that the pelagic bacteria in suspended communities were very different from the bacteria aggregates or to those attached to the particles lager than 8 µm. Cluster analysis is a useful tool to compare and classify different systems. Curtis & Craine (1998) ap-
404 plied cluster analysis for DGGE profile of the activated sludge samples from different wastewater treatment plants. They found that the similarity of the microbial communities was high between plants treating domestic wastewater, but low between those treating domestic wastewater and those treating industrial wastewater. Fantroussi et al. (1999) compared the soil microbial communities treated with different herbicides also by applying cluster analysis method to the DGGE pattern of 16S rDNA fragments. They found that the microbial populations were significantly different between communities treated with herbicides and those untreated. In this study, biofilm samples and the suspended samples were collected at the same time to do the cluster analysis on the basis of the PCR-DGGE pattern. The cluster trees based on the DGGE pattern matrix indicated that biofilm communities were different from the suspended communities. This result was similar to those reported by Acinas et al. (1999). The cluster analysis in this study also illustrates that D60 and D90 had the highest similarity. This indicates that the biofilm had reached stable status after 60 days. At the same time, cluster analysis also illustrated that the developing biofilm (D5 and D10) was significantly different from the mature biofilm (D60 and D90). Figure 3 shows that microbial differences among the biofilm communities were less than those among suspended-growth communities. This seems to indicate that the biofilm communities are more stable and less susceptible to the conditions of the bulk solution. Acknowledgements This work was supported by the Hong Kong Research Grants Council. The authors would like to thank the technical support by Dr J.D. Gu, Dr A.K.H. Kwan and Mr C.F. Mora. References Acinas SG, Anton J, Rodriguez VF (1999) Diversity of free-living and attached bacteria in offshore western Mediterranean waters as depicted by analysis of genes encoding 16S rRNA. Appl. Environ. Microbiol. 65: 514–522. Amann RI (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 59: 143–169. Costerson JW, Cheng KJ, Geesey GG, Ladd TJ, Nickel JC, Dasgupta M, Marrie T (1987) Bacterial biofilms in nature and disease. Ann. Rev. Microbiol. 41, 435–464.
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