27
microbe communities (Jousset et al. 2010; Costa et al. 2006). DGGE has certain
limitations: similar to any other 16S rRNA-based technique, it also faces the artifacts of polymerase chain reaction (PCR)-based amplification (Martin-Laurent
et al. 2001). An inherent problem with DGGE is that all the samples cannot be
loaded on one gel; thus, variations among the different gels also produce lower
reproducibility (Nunan et al. 2005). TGGE is another variant of this technique, in
which temperature acts as the denaturing agent instead of chemical-based denaturation of the DGGE (Ogier et al. 2002). DGGE helped to identify potential aluminumtolerant bacterial strains, which improved plant health and phosphorus nutrients in
ryegrass cultivated with cattle dung manure in volcanic soil (de la Luz Mora et al.
2017). The technique helped to map diverse microbial community profiling under
the heavy metal-polluted soil (Becker et al. 2006). Application of DGGE along with
Biolog Ecoplates and microbial biomass helped to analyse the impact of glyphosate
on microbe-mediated soil properties, which deciphered glyphosate-mediated
structural- functional changes in communities of microbes after 15 days of herbicide
application (Mijangos et al. 2009). In Zea mays, DGGE showed the protease activity of the rhizosphere and bulk soil microbes with different N uptake, leading to the
conclusion that the abundance of npr and apr genes increases nitrogen use efficiency along with the higher soil enzyme activity (Baraniya et al. 2016).
3.4 Terminal Restriction Fragment Length Polymorphism
(T-RFLP)
Terminal restriction fragment length polymorphism (T-RFLP) has been widely used
for exploring the predominant microbe population in different habitats. It also helps
in studying the spatiotemporal changes in the community structure of microorganisms (Lukow et al. 2000). T-RFLP is a high-throughput fingerprinting technique
exploiting the 16S rRNA sequences of prokaryotic organisms. However, 18S rRNA
genes are used for fungal diversity analysis (Liu et al. 2016a, b). These rRNA
sequences are amplified from the soil DNA samples using fluorescent primers.
Further amplified sequences are then cleaved with the desired restriction enzyme
(RE) having four base-pair restriction sites; the RE with four base-pair restriction
sites has higher frequencies of these sequences in the DNA samples. The number
and the size of the fluorescent terminal restriction fragments (TRFs) are then analysed through a DNA sequencer. The diversity among the phylogenetically distinct
microorganisms is reflected by the differences in the length of TRFs. Thus, the
structure of the numerically dominant communities of the microbes can be analysed
by T-RFLP. As in a PCR-dependent technique such as T-RFLP, primer selection
should be specific to the targeted microbial group and also generalized in nature, so
that most of the desired bacterial population can be amplified. Sometimes, different
microbial populations may have similar TRF size for a primer–RE combination. In
such situations, use of more than one RE gives a better prediction of the microbial
3.4 Terminal Restriction Fragment Length Polymorphism (T-RFLP)
microbe communities (Jousset et al. 2010; Costa et al. 2006). DGGE has certain
limitations: similar to any other 16S rRNA-based technique, it also faces the artifacts of polymerase chain reaction (PCR)-based amplification (Martin-Laurent
et al. 2001). An inherent problem with DGGE is that all the samples cannot be
loaded on one gel; thus, variations among the different gels also produce lower
reproducibility (Nunan et al. 2005). TGGE is another variant of this technique, in
which temperature acts as the denaturing agent instead of chemical-based denaturation of the DGGE (Ogier et al. 2002). DGGE helped to identify potential aluminumtolerant bacterial strains, which improved plant health and phosphorus nutrients in
ryegrass cultivated with cattle dung manure in volcanic soil (de la Luz Mora et al.
2017). The technique helped to map diverse microbial community profiling under
the heavy metal-polluted soil (Becker et al. 2006). Application of DGGE along with
Biolog Ecoplates and microbial biomass helped to analyse the impact of glyphosate
on microbe-mediated soil properties, which deciphered glyphosate-mediated
structural- functional changes in communities of microbes after 15 days of herbicide
application (Mijangos et al. 2009). In Zea mays, DGGE showed the protease activity of the rhizosphere and bulk soil microbes with different N uptake, leading to the
conclusion that the abundance of npr and apr genes increases nitrogen use efficiency along with the higher soil enzyme activity (Baraniya et al. 2016).
3.4 Terminal Restriction Fragment Length Polymorphism
(T-RFLP)
Terminal restriction fragment length polymorphism (T-RFLP) has been widely used
for exploring the predominant microbe population in different habitats. It also helps
in studying the spatiotemporal changes in the community structure of microorganisms (Lukow et al. 2000). T-RFLP is a high-throughput fingerprinting technique
exploiting the 16S rRNA sequences of prokaryotic organisms. However, 18S rRNA
genes are used for fungal diversity analysis (Liu et al. 2016a, b). These rRNA
sequences are amplified from the soil DNA samples using fluorescent primers.
Further amplified sequences are then cleaved with the desired restriction enzyme
(RE) having four base-pair restriction sites; the RE with four base-pair restriction
sites has higher frequencies of these sequences in the DNA samples. The number
and the size of the fluorescent terminal restriction fragments (TRFs) are then analysed through a DNA sequencer. The diversity among the phylogenetically distinct
microorganisms is reflected by the differences in the length of TRFs. Thus, the
structure of the numerically dominant communities of the microbes can be analysed
by T-RFLP. As in a PCR-dependent technique such as T-RFLP, primer selection
should be specific to the targeted microbial group and also generalized in nature, so
that most of the desired bacterial population can be amplified. Sometimes, different
microbial populations may have similar TRF size for a primer–RE combination. In
such situations, use of more than one RE gives a better prediction of the microbial
3.4 Terminal Restriction Fragment Length Polymorphism (T-RFLP)