Nucleic Acid Based Methods

The genetic diversity of soil microorganisms is an indicator of genetic resources. Among the various nucleic acid techniques used to estimate microbial community composition and diversity in complex habitats, the most useful involves determining the sequences of 16 S ribosomal RNA (rRNA) genes (i.e., encoded by rDNA) in prokaryotes and 5 S or 18 S rRNA genes in eukaryotes.

These techniques are particularly well suited to such studies for a number of reasons:

• They are found universally in all three forms of life: Bacteria, Archaea, and Eucarya.

• These molecules are composed of both highly conserved regions and regions with considerable sequence variation.

• The phylogenetic information held in the SSU rDNA molecule is further enhanced by its relatively large size and the presence of many secondary structural domains.

Consequently, evolutionary changes in one domain do not affect the rates of change in other domains. • They are easily amplified using the polymerase chain reaction (PCR), and rapidly sequenced.

Soil DNA extraction techniques mainly involve either separating the cells from the soil and then performing the DNA extraction or using a direct lysis approach for extracting DNA from cells in the soil. The direct lysis approach is now generally preferred because it gives a higher DNA recovery, the DNA is thought to be more representative of the entire community, and progress has been made in purifying the DNA of coextracted humic compounds. Though the majority of the work in this area has been done on agricultural soils, DNA extraction and purification protocols have also been developed and tested for heavy metal polluted soils (Kozdroj and van Elsas 2000; Fortin et al. 2004).

Once the DNA has been extracted from the soil, methods that can be used in relation to molecular microbial ecology include cloning and sequence analysis of rRNA genes (to yield clone ''libraries'') as well as a number of fingerprinting approaches for rapidly comparing communities. Both of these techniques rely on the use of the polymerase chain reaction (PCR) to amplify (make multiple copies of) a particular region of DNA so that enough material is available for subsequent analysis. However, the PCR amplification can be inhibited when contaminants have not been removed beforehand, and preferential or selective amplification in the presence of DNA from mixed communities can occur. PCR-based techniques also present other drawbacks; for example, the relative proportions of amplified sequences from different species may not reflect those of the original sample.

Fingerprinting techniques that provide a rapid assessment of a microbial community are particularly useful for monitoring soil health. In this case, the PCR-amplified genes of organisms within a community are separated based on length or sequence polymorphism, which produces a visual pattern - or fingerprint - of the community. PCR-based community fingerprinting techniques have several advantages: (a) they are rapid and allow parallel analyses of multiple samples; (b) they are reliable and highly reproducible, and; (c) they provide both qualitative and quantitative information on populations within a community.

Genetic fingerprinting methods include, among others, denaturing and temperature gradient gel electrophoresis (D/TGGE), ribosomal intergenic spacer analysis (RISA), and terminal restriction fragment length polymorphism (T-RFLP). The results obtained from these analyses can then be expressed as matrices of presence, intensity or similarity, and groups of samples with similar microbial structure can be identified by clustering or ordination analyses.

Clone libraries are generally used to identify soil microorganisms. This approach involves cloning (inserting DNA into a bacterial plasmid) a large number of PCR-amplified genes, determining the DNA sequences of these cloned fragments, and comparing the sequences with those of known organisms in a large public database (such as GenBank), as the number of rRNA gene sequences that can be used for comparison is constantly growing.

Applications of some of these techniques to evaluate the effects of heavy metal pollution in soil microbial communities are discussed below. Percentage of Guanine-Cytosine and DNA Reassociation Techniques

Low-resolution methods include analyzing the base distribution of the DNA and determining the rate at which denatured single-stranded DNA reassociates (Torsvik et al. 1994). The base distribution of the DNA [mol% guanine+cytosine (%G+C)] can be determined by thermal denaturation due to the fact that single-stranded DNA has a higher absorbency than double-stranded DNA at 260 nm (Torsvik et al. 1996). Despite the fact that this is considered to be a low-resolution analysis, it has been used to indicate overall changes in microbial community structure, especially in soil samples with low diversity. The major limitation of such analyses is that there is not a clear-cut relationship between base composition and species composition; thus, two communities with similar base distributions do not necessarily have similar species compositions, since different species often have the same base composition. On the other hand, when communities have different base distributions, this method provides strong evidence that they have different species compositions. The main advantage of this approach is the possibility of detecting and analyzing microorganisms that are not identified by PCR.

The DNA reassociation technique, which measures the genetic complexity of the microbial community, has also been used to estimate microbial diversity (Torsvik et al. 1996). In this case, the total DNA is extracted from natural soil samples, purified, denatured, and allowed to reanneal. The rate of hybridization or reassociation will depend on the similarity of the sequences present. As the complexity or diversity of the DNA sequences increases, the rate at which the DNA reassociates will decrease. Under specific conditions, the time taken for half the DNA to reassociate (the half-association value C0t1/2) can be used as a diversity index, as it takes both the amount and the distribution of DNA reassociation into account (Torsvik et al. 1998). Determining the sequence complexity of DNA, as measured by reassociation, provides a better assessment of the total microbial diversity in soil than the %G+C technique.

Sandaa et al. (1999) studied the microbial diversity, as determined by both the %G+C and DNA reassociation techniques, of field soils amended with "uncon-taminated" sewage sludge, and the results were compared with those obtained for field soils treated with metal-amended sewage sludge at two rates of application (low and high metal contamination) for several years. They found no differences in the %G+C profiles of the bacterial communities of these soils. However, DNA reassociation analysis indicated a dramatic decrease in bacterial diversity from 16,000 bacterial genomes (g soil [wet wt]) in the uncontaminated soil to 6,400 bacterial genomes (g soil [wet wt]) in soil with low metal amendments, and only 2,000 bacterial genomes (g soil [wet wt]) in soil with high metal.

Recently, Gans et al. (2005) applied sophisticated computational methods to reanalyze the reassociation kinetics for bacterial community DNA using the original data from Sandaa et al. (1999), and estimated that one million distinct genomes occurred in the pristine soil - exceeding previous estimates by two orders of magnitude. Furthermore, they found that metal pollution reduced diversity by more than 99.9%, thus revealing a highly toxic effect of heavy metals, especially on rare taxa. These results have been criticized by Volkov et al. (2006) and Bunge et al. (2006), who suggested that the studies of Gans et al. (2005) do not allow us to conclude that metal pollutants have such a devastating effect on microbial diversity. Denaturing and Temperature Gradient Gel Electrophoresis (DGGE/TGGE)

Among the intermediate-resolution techniques, denaturing gradient gel electropho-resis (DGGE) and temperature gradient gel electrophoresis (TGGE) have been widely used to characterize microbial communities in heavy metal polluted soils (Sandaa et al. 1999; Li et al. 2006). These techniques are able to separate mixtures of PCR products that are similar in length but differ in their sequences. The separating power of each technique depends on the melting behavior of the double-stranded DNA molecule. As the DNA molecules are electrophoresed they remain double-stranded until they reach the denaturing concentration or temperature that melts the double-stranded molecule. Since the melting behavior is largely dictated by the nucleotide sequence, the separation yields individual bands, each corresponding to a unique sequence. DNA with many pairs of guanine and cytosine nucleotides melt less easily than those with many adenine and thymidine bases.

However, DGGE/TGGE techniques can underestimate the microbial diversity because bands from more than one species can appear as a single band (Heuer et al. 1997). Soil communities can easily contain several hundred bacterial strains, which contrasts with the relatively low resolution of the gel (typically less than 50 bands, and so the bands represent the predominant microbial populations). These techniques are thus highly recommended for communities with low to moderate complexity.

DGGE/TGGE techniques, when applied to heavy metal pollution, have revealed changes in community structures of and reduced numbers of bands for eubacteria, b-proteobacteria, and ammonia-oxidizing bacteria present in environments with elevated heavy metal levels (Gremion et al. 2004). However, other studies have shown that the numbers of bands are independent of the level of contamination with heavy metals (Kozdroj and van Elsas 2001). For example, Sandaa et al. (1999) revealed differences in community structure in soils with increasing heavy-metal contamination; however, while the control soils were characterized by twelve bands, low-metal soils gave patterns with six bands, and soils with a high level of heavy metals gave eleven bands. On the other hand, Anderson et al. (2008) found (using DGGE analysis) that soil fungi did not appear to be affected after the addition of heavy metal containing sewage sludge at levels up to the current UK legislated limit for Cd and Zn, and at levels well above the current legislative limit for Cu.

The main advantages of DGGE/TGGE are that it enables spatial/temporal changes in microbial community structure to be monitored and that it provides a simple view of the dominant microbial species within a sample. In addition to the simplicity and rapidity of these methodologies, the identities of bands can be investigated via hybridization with specific probes or by extraction and sequencing. Amplified Ribosomal DNA Restriction Analysis (ARDRA)

Amplified ribosomal DNA restriction analysis (ARDRA) is a powerful tool for microbial identification and classification, even at species level, and it has been used to group and classify large sets of isolates and clones. Automated ARDRA has been performed with fluorescent PCR amplicons obtained by incorporating fluores-cently labeled dUTP during PCR. After restriction enzyme digestion, the fragments are separated on an automated DNA sequencing gel. Different DNA sequences result in a unique profile of the analyzed community. The restriction pattern data can then be compared with the results of restriction analyses of rDNA sequences of known bacteria obtained using database sequences. ARDRA is a simple, rapid, and cost-effective technique that can be useful for detecting structural changes in simple microbial communities, but is unable to measure microbial diversity or to detect specific phylogenetic groups within a community fingerprinting profile.

This technique has been widely used to evaluate changes in microbial community structure (mainly bacteria). For example, Smit et al. (1997) and Torsvik et al. (1998) found distinct differences in microbial community structure in soil contaminated with heavy metals compared to uncontaminated soil. In a recent study, Pérez De Mora et al. (2006) evaluated the effects of the in situ remediation of a heavy metal contaminated soil on microbial structural diversity after 18 months. Results revealed differences in both bacterial and fungal community structures as a consequence of the various treatments assayed. However, different results were obtained with the two restriction enzymes employed in the bacterial and fungal fingerprinting patterns. Terminal Restriction Fragment Length Polymorphism (T-RFLP)

Terminal restriction fragment length polymorphism (TRFLP) is a modification of ARDRA. TRFLP analysis is based on the restriction enzyme digestion of PCR-amplified DNA that has been fluorescently labeled at one end. Fragments are resolved by size on polyacrylamide gels using an automated analyzer with laser detection of the terminally labeled products, producing a highly reproducible fingerprint of the community.

The use of fluorescently tagged primers limits the analysis to only the terminal fragments of the digestion. This simplifies the banding patterns, thus allowing for the analysis of complex communities as well as providing information on diversity, as each visible band represents a single operational taxonomic unit or ribotype

(Tiedje et al. 1999). The banding pattern is used to measure species richness and evenness, as well as similarities between samples (Fig. 9.4).

Moreover, T-RFLP can be automated to enable the analysis of a large number of soil samples (Osborn et al. 2000). However, T-RFLP requires expensive equipment

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