identities of bands separated on the gel, those bands can be excised from the gel and
further analyzed via re-amplification, cloning, and sequencing, or by hybridization
with molecular probes specific for particular taxonomic groups.
Although being valuable for the identification of changes in dominant species
within a community, fingerprints generated from DGGE/TGGE can be very complex, especially when using universal bacterial primers. Those bands in which the
fragments have similar melting points can be difficult to separate. Also, the rRNA
operons of the same bacterium can show heterogeneity, leading to multiple bands
and an overestimation of the microbial diversity; further, quantification of the
extracted bands is not possible.
Compared to DGGE/TGGE, T-RFLP analysis has the advantage that fragments
can be relatively quantified by the intensity of the fluorescent signal, and the method
is quicker and less labor intensive. The inherent difficulty with T-RFLP, however, is
that a collection or recovery of the fragments and thereby a subsequent analysis and
identification of the microorganism via sequencing is not possible. To overcome
this, fragments have been identified via comparison against databases of fragments
produced by known gene sequences (Kent et al. 2003). Combining T-RFLP with
clone library construction and sequencing, Huang et al. (2011) were able to find
close associations of the four most dominant operational taxonomic units detected in
T-RFLP to phylum or genus level, when analyzing spatial and temporal variations of
the microbial community in a tailings basin of a Pb–Zn mine.
Different studies have used DGGE/TGGE and T-RFLP to assess microbial
community composition in different contaminated environments. Spatial and temporal variations of microbial community composition were analyzed in different
mining environments such as an acidic stream draining across a pyrite mine in China
(Tan et al. 2009) or in a low-temperature, acidic, pyrite mine, where Kimura et al.
(2011) were able to highlight the importance of bacterial species in iron transformation using T-RFLP and fluorescent in situ hybridization (FISH). Kim et al. (2009)
used DGGE to examine the effects of mine tailings and waste rocks on the
hydrogeochemistry and microbiology of a stream and groundwater near an abandoned copper mine. The effects of metal pollution on microbial community structure
and composition in a salt marsh were analyzed by Cordova-Kreylos et al. (2006),
who used T-RFLP to aid the development of bioindicators of toxicant-induced stress
and bioavailability of contaminants for wetland biota. In another study, Gough and
Stahl (2011) used T-RFLP to follow microbial community changes in lake sediments along a metal contamination gradient. In a recent study by Thavamani et al.
(2012), the authors employed a holistic approach. To determine the soil microbial
activity affected by a mix of polyaromatic hydrocarbons (PAHs) and heavy metals,
they combined physicochemical, biological, and advanced molecular methods to
analyze the activities of the soil microbial community in long-term mixed contaminated soils collected from a former manufactured gas plant (MGP) site. The study
highlighted the difficulties of implementing remediation strategies when studying
mixed contaminations, as well as the importance of combining different analysis
methods.
18 Molecular Technologies for Assessment of Bioremediation and. . .
445
further analyzed via re-amplification, cloning, and sequencing, or by hybridization
with molecular probes specific for particular taxonomic groups.
Although being valuable for the identification of changes in dominant species
within a community, fingerprints generated from DGGE/TGGE can be very complex, especially when using universal bacterial primers. Those bands in which the
fragments have similar melting points can be difficult to separate. Also, the rRNA
operons of the same bacterium can show heterogeneity, leading to multiple bands
and an overestimation of the microbial diversity; further, quantification of the
extracted bands is not possible.
Compared to DGGE/TGGE, T-RFLP analysis has the advantage that fragments
can be relatively quantified by the intensity of the fluorescent signal, and the method
is quicker and less labor intensive. The inherent difficulty with T-RFLP, however, is
that a collection or recovery of the fragments and thereby a subsequent analysis and
identification of the microorganism via sequencing is not possible. To overcome
this, fragments have been identified via comparison against databases of fragments
produced by known gene sequences (Kent et al. 2003). Combining T-RFLP with
clone library construction and sequencing, Huang et al. (2011) were able to find
close associations of the four most dominant operational taxonomic units detected in
T-RFLP to phylum or genus level, when analyzing spatial and temporal variations of
the microbial community in a tailings basin of a Pb–Zn mine.
Different studies have used DGGE/TGGE and T-RFLP to assess microbial
community composition in different contaminated environments. Spatial and temporal variations of microbial community composition were analyzed in different
mining environments such as an acidic stream draining across a pyrite mine in China
(Tan et al. 2009) or in a low-temperature, acidic, pyrite mine, where Kimura et al.
(2011) were able to highlight the importance of bacterial species in iron transformation using T-RFLP and fluorescent in situ hybridization (FISH). Kim et al. (2009)
used DGGE to examine the effects of mine tailings and waste rocks on the
hydrogeochemistry and microbiology of a stream and groundwater near an abandoned copper mine. The effects of metal pollution on microbial community structure
and composition in a salt marsh were analyzed by Cordova-Kreylos et al. (2006),
who used T-RFLP to aid the development of bioindicators of toxicant-induced stress
and bioavailability of contaminants for wetland biota. In another study, Gough and
Stahl (2011) used T-RFLP to follow microbial community changes in lake sediments along a metal contamination gradient. In a recent study by Thavamani et al.
(2012), the authors employed a holistic approach. To determine the soil microbial
activity affected by a mix of polyaromatic hydrocarbons (PAHs) and heavy metals,
they combined physicochemical, biological, and advanced molecular methods to
analyze the activities of the soil microbial community in long-term mixed contaminated soils collected from a former manufactured gas plant (MGP) site. The study
highlighted the difficulties of implementing remediation strategies when studying
mixed contaminations, as well as the importance of combining different analysis
methods.
18 Molecular Technologies for Assessment of Bioremediation and. . .
445