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classifi ed into 233 unique T-RFLPs or ribotypes. Using this method, Liu et al . (1997) were able to
distinguish all bacterial strains in a model bacterial community. It has been shown to be an effective
technique for discriminating microbial communities in a range of environments (Tiedje et al ., 1999) and
also found to be relatively stable to variability in PCR conditions (Osborn et al ., 2000; Ramakrishnan
et al ., 2000). A web-based research tool for microbial community analysis was developed by Marsh
et al . (2000) for T-RFLP analysis and was located at the Ribosomal Database Project website (http://
www.cme.msu:edu/RDP/html/analyses.html). According to these workers, it is important to know
(i) the type of restriction enzyme(s) that will provide the most discriminating activity for estimates of
population diversity, (ii) the enzymes that will provide the best resolution for the best phylogenetic
group and (iii) the particular primer-enzyme combination which will be optimal for the community
under investigation. Each unique T-RF is considered equivalent to one OTU and so can be equated
to a single species/strain within a given community (Moesender et al ., 2001). Thus T-RFLP technique
can be used to assess spatial and temporal changes in 16S rDNAs from microbial communities (Kitts,
2001; Osborn et al ., 2000; Dunbar et al ., 2001; Sessitsch et al ., 2001). T-RFLP technique is highly sensitive
and helpful in acquiring data very rapidly compared to other methods such as denaturing gradient
gel electrophoresis (DGGE) or ARDRA (Ferris and Ward, 1997; Moesender et al ., 1999; Muyzer, 1999;
Horz et al ., 2001). Blackwood et al . (2003) are of the opinion that T-RFLP data provide inaccurate
estimates of true diversity in microbial communities. Wherever signifi cant differences in T-RFLP
diversity indices have been found, all such work should be reinterpreted by the application of a
correction factor TRF-E var as a refl ection of differences in community composition rather than a true
difference in community. In addition, molecular profi ling methods such as these normally represent
only “dominant” organisms in the community (that constitute less than 1% of the community) and
rare species are not represented. Detecting the diversity of rare species is also important because
in some microbial communities the vast majority of the diversity is constituted by the rare species
(Gans et al ., 2005; Pedrós-Alió, 2006). There is every possibility for the generation of T-RFs of the
same size from multiple taxa that are distantly related. In that case, the diversity of the dominant
taxa will be underestimated (Dunbar et al ., 2001; Engebretson and Moyer, 2003; Blackwood and
Buyer, 2007). Blackwood et al . (2007) advocated the physical capture of T-RFLP using a biotynylated
primer and streptavidin-coated beads. They were able to show that the physical capture method
described by them created similar profi les such as those generated by fl uorescent T-RFLP. When
sequencing of such biotynylated captured T-RFs was done, most of the sequences did not match
with those already present in database suggesting that these belonged to rare species, although the
T-RFs were of the same size. So these workers emphasized that the T-RFs should best be identifi ed
on the basis of sequencing rather than by comparing their sizes to T-RFs of computer digests
(of database sequences). They selected T-RFLP of bacterial ribosomal gene because of its popularity,
availability of database of sequences and bioinformatic tools. Engebretson et al . (2003) explored
the possibility of resolving single populations in model communities by using selected restriction
endonucleases. They also measured the success of restriction endonucleases in detecting sequence
variants from model communities that showed variations in species abundance. From the database
of gene sequences, the restriction endonucleases have been classifi ed on the basis of their ability
to resolve T-RFs. Of the 18 restriction endonucleases tested, BstUI , DdeI , Sau 96I and MspI showed
highest resolving potential of identifying single populations in model communities. All restriction
endonucleases used by these workers could generate T-RFs of more than 70% OTUs at richness
values greater than 50 OTUs per model community.
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