Appl Microbiol Biotechnol (2012) 93:1005–1020 the extraction factors (meaning, adding extra extraction modules) in comparison to the most effective single extraction strategy. Simple stochasticity thus dictates that the prevalence of genes from the dominant biosphere will greatly exceed that of genes from the rare biosphere. Therefore, the selection of the vector/host system is ideally guided by prior knowledge about the prevalence and distribution of different bacterial types in the sampled habitat. Once a metagenomic library has been constructed, screens need to be performed in high throughput to uncover the genes of interest. The two common strategies, i.e., (1) functional and (2) sequence-based (genetic) screening, have been widely applied. It is obvious that functional screening provides a very straightforward way towards the objective. Thus, the target genes in metagenomic libraries are expressed in a relevant experimental setup in order to visualize (detect) them and confirm their assignment to the func- tion. In contrast, genetic screening is dependent on prior knowledge of expected gene sequences or motifs. Direct hybridization of PCR-based screenings has been the method of choice; however, current high-throughput sequencing has opened up the way to employ direct sequencing-based analyses. In most metagenomics studies performed thus far, Escherichia coli has been used as the cloning host as an extended genetic toolkit is available for this host. Depending on the size of the DNA fragment that needs to be inserted, different vectors have been employed. For small fragments, plasmids <15 kb, for larger fragments cosmids (15–40 kb), fosmids (25–45 kb), and/or bacterial artificial chromosomes (BACs) (100–200 kb) have been successfully used (Angelov et al. 2009; Kakirde et al. 2011; Uchiyama and Miyazaki 2009; Van Elsas et al. 2008a). In order to eliminate the limitations generated by using E. coli as a single host, shuttle vectors and non-E. coli host systems have been developed. Bacterial strains from genera like Burkholderia, Bacillus, Sphingomonas, Streptomyces, and Pseudomonas have thus been reported as alternative hosts (Courtois et al. 2003; Eyers et al. 2004; Martinez et al. 2004; Van Elsas et al. 2008a). When expressing the metagenomic library material in a host organism, two strategies can be applied: (1) single-host expression and (2) multi-host expression. Although most functional expression screens have been conducted with a single host, in recent years a shift to multi-host gene expression has been taking place. This is due to the idea that a substantial part of the transformed genes cannot be successfully expressed in a single organism and that the use of multiple hosts either sequentially or in parallel offers great advantages. Possible causes of lack of gene expression A central issue concerning the detectable expression of genes of metagenomes 1009 in suitable hosts is, thus, the inability to detectably express a major fraction of the target genes. This might be due to a plethora of factors, such as codon usage differences, improper promoter recognition, lack of proper initiation factors, ribosomal entry, improper protein folding, absence of essential co-factors, accelerated enzymatic breakdown of the gene product, inclusion body formation, toxicity of the gene product, or the inability of the host to secrete the gene expression product. To what degree these different factors contribute to the inability to detect the expression of genes in a metagenomic library will differ per host/gene combination. This makes the question as to what percentage of genes within a library can be expressed by an available host very difficult to answer. What we do know is that codon usage is a particularly important factor in the successful expression of foreign genes (Kudla et al. 2009). Most organisms have a preference for specific codons when generating proteins or encoding signals for initiation or termination of translation. The preferred codons are referred to as “optimal” codons. However, the nature of such codons varies between species (Goodarzi et al. 2008). The occurrence of the resulting “codon dialects” between different species is termed codon usage bias (CUB). This phenomenon is particularly important regarding the expression of foreign genes in a metagenomics host, as is done in functional metagenome screens. Kudla et al. (2009) clearly showed the effect of codon bias by synthesizing and expressing 154 genes encoding the green fluorescent protein (GFP) with randomly introduced silent mutations in the third base position. The resulting expression levels varied 250-fold across all variants, clearly illustrating the dramatic effect that CUB has on gene expression. Besides overall codon usage, also the preference for start codons can vary greatly across bacterial species (Villegas and Kropinski 2008). Furthermore, CUB has been shown to be important in translation (Sørensen et al. 1989), protein folding (Zalucki et al. 2009), and secretion (Power et al. 2004; Zalucki and Jennings 2007). Gabor et al. (2004) quantified the probability of detection of particular genes by random expression cloning on a theoretical basis using 32 prokaryotic genomes (belonging to Euryarchaeota, Crenarchaeota, Firmicutes, Actinobacteria, and Proteobacteria). Three theoretical modes of expression were examined: i.e. (1) independent expression with the ribosomal binding site (RBS) and promoter provided by the insert, (2) expression by transcriptional fusion with the RBS on the insert, and (3) expression by translational fusion with both RBS and promoter on the vector. The latter option was considered to be irrelevant due to its low chance of expression in a real-life experiment. About 40% of the extant enzymatic activities may be accessible by random cloning in E. coli, with a range of 7–73% between the five taxa examined. However, this study was based on purely theoretical bioinformatics considerations