**3. Fingerprinting techniques and their application areas**

Fingerprinting techniques provide a separation in microbial community according to their genetic pattern or profile (Muyzer, 1998). A variety of fingerprinting techniques such as *denaturing/temperature gradient gel electrophoresis, amplified ribosomal DNA restriction analysis, terminal restriction fragment length polymorphism, and single strand confirmation polymorphism* has been developed to assess diversity and dynamics in the ecosystem (Hofman-Bang, 2003). The first fingerprinting technique was used in 1980's, which based on the electrophoretic separation in high-resolution polyacrylamide gels of 5S rRNA and tRNA

Gel Electrophoresis Based Genetic Fingerprinting Techniques on Environmental Ecology 55

clone libraries (Muyzer and Smalla, 1998). Furthermore, DGGE can be used as qualitative

The optimal gradient is the main concern for DGGE/TGGE experiments since the main purpose is separation of DNA fragments according to their melting behaviours. Perpendicular polyacrylamide gels are used according to incremental gradients of denaturants or temperature. The sample including same-length DNA fragment mixtures is loaded to gel for running by electrophoresis. After completing electrophoresis, the gel is stained by a dye such as ethidium bromide, SYBR gold, SYBR green, etc. for obtaining sample pattern. While linear gradient is created by chemical denaturants as urea and formamide for DGGE, temporal temperature gradient is used to separate the DNA fragments in TGGE. Melting pattern of double strand DNA fragments is based on their hydrogen bond content: GC rich DNA fragments melts at higher denaturant/temperature region of the gradient. Complete separation of the double strand DNA is prevented by using GC-clamp primer during the amplification of target DNA region (Dorigo *et al.*, 2005). The schematic explanation of DGGE is

A B C D E M

Fig. 3. Principle of DGGE (A: organism a, B: organism b, C: organism c, D: organism d, E:

3. Limitations on sensitivity for detection of rare community members (Vallaeys *et al.*, 1997) 4. Separation of only small DNA fragments up to 500 bp (Muyzer and Smalla, 1998) 5. Biases coming from PCR amplification such as chimeric products or fidelity errors 6. Heteroduplex formations, multiple bands or due to resolution of the gel, or different fragments resulting from existence of several rRNA coding regions, (Curtis and Craine,

organism E, M: mix sample) (Plant Research International, 2011).

2. Optimization of electrophoresis conditions (Muyzer *et al.*, 1993)

1. Proper primer selection to represent whole community

The main difficulties and limitations of the DGGE/TGGE can be listed as:

and semi-quantitative approach for biodiversity estimations.

**3.1.1 Principles of the experiment** 

given in Figure 3.

1998).

Fig. 2. Secondary structure of the 16S rRNA of E. coli, showing conserved and variable regions (Van de Peer *et al.*, 1996).

obtained from natural samples (Hofle, 1988 and 1990). In 1993, Muyzer *et al.* introduced a new fingerprinting technique to apply on microbial ecology, *denaturing gradient gel electrophoresis* (DGGE). In this method, PCR amplified DNA fragments can be separated according to their nucleic acid pattern. This method has become widespread in a short time. Then another similar technique has been developed, *temperature gradient gel electrophoresis* (TGGE). These methods provide not only analysis of the structure and species composition of microbial communities but also identification of several uncultured microorganisms (Heuer *et al.*, 1997 and Cetecioglu *et al.*, 2009).

#### **3.1 Denaturing/Temperature Gradient Gel Electrophoresis (DGGE/TGGE)**

DGGE is a gel electrophoresis technique to separate same length-DNA fragments based on their base sequence differences. In theory, it is sensitive to observe even one base difference on sequence because of melting patterns of the fragments (Muyzer *et al.*, 1993). This method provides a fast, and labor-intensive approach to determine the diversity and the microbial community within an ecosystem, to monitor the changes on dynamics and also to screen the clone libraries (Muyzer and Smalla, 1998). Furthermore, DGGE can be used as qualitative and semi-quantitative approach for biodiversity estimations.

### **3.1.1 Principles of the experiment**

54 Gel Electrophoresis – Advanced Techniques

Fig. 2. Secondary structure of the 16S rRNA of E. coli, showing conserved and variable

**3.1 Denaturing/Temperature Gradient Gel Electrophoresis (DGGE/TGGE)** 

obtained from natural samples (Hofle, 1988 and 1990). In 1993, Muyzer *et al.* introduced a new fingerprinting technique to apply on microbial ecology, *denaturing gradient gel electrophoresis* (DGGE). In this method, PCR amplified DNA fragments can be separated according to their nucleic acid pattern. This method has become widespread in a short time. Then another similar technique has been developed, *temperature gradient gel electrophoresis* (TGGE). These methods provide not only analysis of the structure and species composition of microbial communities but also identification of several uncultured microorganisms

Increasing variabilit

y

DGGE is a gel electrophoresis technique to separate same length-DNA fragments based on their base sequence differences. In theory, it is sensitive to observe even one base difference on sequence because of melting patterns of the fragments (Muyzer *et al.*, 1993). This method provides a fast, and labor-intensive approach to determine the diversity and the microbial community within an ecosystem, to monitor the changes on dynamics and also to screen the

regions (Van de Peer *et al.*, 1996).

(Heuer *et al.*, 1997 and Cetecioglu *et al.*, 2009).

The optimal gradient is the main concern for DGGE/TGGE experiments since the main purpose is separation of DNA fragments according to their melting behaviours. Perpendicular polyacrylamide gels are used according to incremental gradients of denaturants or temperature. The sample including same-length DNA fragment mixtures is loaded to gel for running by electrophoresis. After completing electrophoresis, the gel is stained by a dye such as ethidium bromide, SYBR gold, SYBR green, etc. for obtaining sample pattern. While linear gradient is created by chemical denaturants as urea and formamide for DGGE, temporal temperature gradient is used to separate the DNA fragments in TGGE. Melting pattern of double strand DNA fragments is based on their hydrogen bond content: GC rich DNA fragments melts at higher denaturant/temperature region of the gradient. Complete separation of the double strand DNA is prevented by using GC-clamp primer during the amplification of target DNA region (Dorigo *et al.*, 2005). The schematic explanation of DGGE is given in Figure 3.

Fig. 3. Principle of DGGE (A: organism a, B: organism b, C: organism c, D: organism d, E: organism E, M: mix sample) (Plant Research International, 2011).

The main difficulties and limitations of the DGGE/TGGE can be listed as:


Gel Electrophoresis Based Genetic Fingerprinting Techniques on Environmental Ecology 57

a

c

d

b

Fig. 4. Steps of ARDRA (a: Genomic DNA extraction, b: PCR reaction for specific region,

The application areas of this technique are also similar to DGGE. It is varied from detection isolates or clones to determination of whole community in an environment. For these different purposes, different gel types can be used. While agarose gel is sufficient to detect isolates or clones, polyacrylamide gels are necessary for better resolution in the community

In the literature, there are different studies performed by ARDRA. Lagace *et al.* (2004) identified the bacterial community of maple trees. A wide variety of the organisms were detected from different groups. Barbeiro and Fani used this technique to investigate more

c: restriction digestion, d: gel electrophoresis) (Dijkshoorn *et al.*, 2007).

analysis (Martinez-Murcia *et al.*, 1995).

### **3.1.2 Application area**

DGGE/TGGE is used for several purposes in microbial ecology. The first and the most common application is to reveal and to compare community complex of the microbial diversity within different environments. Curtis and Craine (1998) used this technique to show the bacterial complexity of different activated sludge samples. Connaughton *et al.* (2006) used PCR-DGGE method to find out bacterial and archaeal community structure in a high-rate anaerobic reactor operated at 18 C. This technique was used to reveal the microbial community in a lab-scale thermophilic trickling biofilter producing hydrogen (Ahn *et al.*, 2005). Another biofilm study showed the bacterial diversity in a river by 16S rDNA PCR-DGGE method (Lyautey *et al.*, 2005). In another study, the authors showed that the different bacterial and archaeal profiles within the highly polluted anoxic marine sediments in the different locations from the Marmara Sea (Cetecioglu *et al.*, 2009). Ye *et al.* (2011) showed the temporal variability of cyanobacteria in the water and sediment of a lake.

Furthermore the scientists use these techniques, mostly DGGE, to analyse the community changes over time. Santagoeds *et al.* (1998) used PCR-DGGE method to monitor the changes in sulphate reducing bacteria in biofilm. Ferris and Ward (1997) also performed similar approach to reveal seasonal changes in bacterial community from hot spring microbial mat. Kolukirik *et al.* (2011) used 16S rDNA PCR-DGGE technique to represent the local and seasonal bacterial and archaeal shifts in hydrocarbon polluted anoxic marine sediments.

These fingerprinting techniques are widely used to monitor simple communities instead of complex environments. It is one of the detection methods to analyse the cultivation/ isolation approaches and to determine the enrichment cultures (Santagoeds *et al.*, 1996; Ward *et al.*, 1996; Teske *et al.*, 1996; Muyzer, 1997; Bucholz-Cleven *et al.*, 1997).

Also DGGE/TGGE are commonly chosen for comparison of the efficiency of the DNA extraction protocols (Heuer and Smalla, 1997; Lieasack *et al.*, 1997) and the screening of the clone libraries (Heuer and Smalla, 1997; Lieasack *et al.*, 1997, Kolukirik *et al.*, 2011) because rapid and reliable results are caused to perform less time (Kowalchuk *et al.*, 1997).
