1008 ones using the addition of a substrate labeled with a stable isotope (13C or 15N) to the environmental sample. If sufficient isotope has been incorporated into the DNA of the active microorganisms, this labeled (“heavy”) DNA can be separated from unlabeled (“light”) DNA by density gradient ultracen- trifugation and further analyzed. The method thus enables the establishment of a direct link between function and identity (Chen and Murrell 2010; Cupples 2011; Dumont and Murrell 2005; Radajewski et al. 2003; Uhlik et al. 2009). Depending on the type of labeled substrate used, one can additionally bias the sample in much the same way as in ecological enhancement, targeting specific active ecotypes within a sample. However, a major drawback of SIP remains the fact that unnaturally high concentrations of labeled substrate may be required, next to too extended incubation times, in order to attain sufficient yields of labeled DNA in the active organisms. The former may result in growth inhibition, whereas the latter might accrue an accumulation of the label in the “wrong” trophic classes. An additional prac- tical disadvantage is the prohibitively high cost of labeled substrate. Another problem of SIP is technical as the differentiation between labeled and unlabeled DNA may be difficult: unlabeled high G–C% DNA may have a density profile that approaches that of labeled low G–C% DNA (Buckley et al. 2007). Despite such limitations, SIP is a very valuable tool to reduce sample complexity and increase the hit rates of particular target genes (Chen and Murrell 2010). It is especially practical in the search for target metabolic genes for biotechnical applications. DNA extraction and processing Extraction of microbial community DNA for use in meta- genomic library construction can be roughly divided into two strategies: (1) “direct extraction”—the microbial commu- nity DNA is directly isolated from the sample and (2) “indirect extraction”—the microbial cells are first isolated from the sample prior to cell lysis (Robe et al. 2003; Van Elsas et al. 2008a). Both methods have their own specific advantages and biases. Four key parameters that define the suitability of the DNA extracted by each method for subsequent metagenomics analysis have been identified: yield, purity, fragment size, and representativeness. Unfortunately, in practice, these factors often stand in negative relation to one another. Enhancing one will often have a negative effect on other factors. As a matter of example, these extraction trade-offs may result in either low-yield extracts containing large DNA fragment sizes versus high-yield small-fragment DNA. A low average fragment size obviously impedes the subsequent analysis of larger operons, for which larger insert libraries are needed (Williamson et al. 2011). Appl Microbiol Biotechnol (2012) 93:1005–1020 A recent study (Delmont et al. 2011) showed that the apparent functional diversity present in an ecosystem is not severely affected by the DNA extraction method, possibly reflecting the high functional redundancy in most natural microbial communities. However, the inevitable biases inherent to any DNA extraction method can lead to unrepresentative (biased) microbial community DNA. This caveat also impacts our strategies to explore the rare biosphere. An interesting new method for separating DNA from highly contaminated samples, called synchronous coefficient of drag alteration, applies a rotating dipole and quadruple electric field in an aqueous gel by which DNA is concentrated at a focal point while contaminants are pushed outwards (Pel et al. 2009). In particular cases (Neufeld et al. 2008), e.g., after indirect extraction of DNA from a sample or in a SIP experiment, DNA yields may be low, indicating the need for pre-amplification to allow metagenomic library construction. Regular PCR amplification is often not suitable due to the requirement for specific annealing sites of the primers. A suitable technique is offered by multiple displacement ampli- fication (MDA). MDA is based on the use of phi29 DNA polymerase and random hexamer primers and results in high- fidelity replication, in a random fashion, of the different DNA fragments present in the sample. Although under debate, the method was shown to work without biases due to primer specificity (Binga et al. 2008; Blanco and Salas 1985; Blanco et al. 1989; Nelson et al. 2002). However, MDA can also yield chimeric artifacts (Neufeld et al. 2008; Simon et al. 2009). Neufeld et al. (2008) clearly showed the potential of SIP combined with MDA. They incubated a marine microbial community with in situ concentrations of labeled substrate (methanol) and subsequently performed MDA on the labeled DNA for construction of a fosmid library. They found that the amplified DNA was very representative of the sample. Metagenomic library construction and gene expression Construction of a metagenomic library should be accompa- nied by the careful selection of the appropriate average DNA fragment size. Moreover, suitable vectors and expression hosts should be selected. It is vital to understand that, for most natural ecosystems, complete coverage of the extant diversity cannot be achieved, and so most libraries will consist of fragmentary randomly sampled genes from an overall DNA pool. Only the most abundant fraction of the gene pool will be present in the library, and hence the extracted DNA pool is a sub-selection of the complete metagenome. The extracted DNA pool is further biased by factors such as the effect of sampling, cell separation, lysis intensity, and DNA size variation. Delmont et al. (2011) recently showed that up to 80% increase in genetic diversity is achievable by diversifying