Development of a high throughput cell-free metagenomic screening platform
The estimated 5 × 10³⁰ prokaryotic cells inhabiting our planet sequester some 350–550 Petagrams (1 Pg = 1015 g) of carbon, 85–130 Pg of nitrogen, and 9–14 Pg of phosphorous, making them the largest reservoir of those nutrients on Earth (Whitman et al. 1998). However, reports suggest that only less than 1% of these microscopic organisms are cultivable (Torsvik et al. 1990; Sleator et al. 2008). Until recently with the development of metagenomic techniques, the knowledge of microbial diversity and their metabolic capabilities has been limited to this small fraction of cultivable organisms (Handelsman et al. 1998). While metagenomics has undoubtedly revolutionised the field of microbiology and biotechnology it has been generally acknowledged that the current approaches for metagenomic bio- rospecting / screening have limitations which hinder this approach to fully access the metabolic potentials and genetic variations contained in microbial genomes (Beloqui et al. 2008). In particular, the construction of metagenomic libraries and heterologous expression are amongst the major obstacles. The aim of this study was to develop an ultra-high throughput approach for screening enzyme activities using uncloned metagenomic DNA, thereby eliminating cloning steps, and employing in vitro heterologous expression. To achieve this, three widely used techniques: cell-free transcription-translation, in vitro compartmentalisation (IVC) and Fluorescence Activated Cell Sorting (FACS) were combined to develop this robust technique called metagenomic in vitro compartmentalisation (mIVC-FACS). Moreover, the E. coli commercial cell-free system was used in parallel to a novel, in-house Rhodococcus erythropolis based cell-free system. The versatility of this technique was tested by identifying novel beta-xylosidase encoding genes derived from a thermophilic compost metagenome. In addition, the efficiency of mIVC-FACS was compared to the traditional metagenomic approaches; function-based (clone library screening) and sequence-based (shotgun sequencing and PCR screening). The results obtained here show that the R. erythropolis cell-free system was over thirty-fold more effective than the E. coli based system based on the number of hits obtained per million double emulsions (dE) droplets screened. Six beta-xylosidase encoding genes were isolated and confirmed from twenty-eight positive dE droplets. Most of the droplets that were isolated from the same gate encoded the same enzyme, indicating that this technique is highly selective. A comparison of the hit rate of this screening approach with the traditional E. coli based fosmid library method shows that mIVC-FACS is at least 2.5 times more sensitive. Although only a few hits from the mIVC-FACS screening were selected for confirmation of beta-xylosidase activity, the proposed hit rate suggests that a significant number of positive hits are left un-accessed through the traditional clone library screening system. In addition, these results also suggest that E. coli expression system might be intrinsically sub-optimal for screening for hemicellulases from environmental genomes compared to R. erythropolis system. The workflow required for screening one million clones in a fosmid library was estimated to be about 320 hours compared to 144 hours required via the mIVC-FACS screening platform. Some of the gene products obtained in both screening platforms show multiple substrate activities, suggesting that the microbial consortia of composting material consist of microorganisms that produce enzymes with multiple lignocellulytic activities. While this platform still requires optimisation, we have demonstrated that this technique can be used to isolate genes encoding enzymes from mixed microbial genomes. mIVC-FACS is a promising technology with the potential to take metagenomic studies to the second generation of novel natural products bio-prospecting. The astonishing sensitivity and ultra-high throughput capacity of this technology offer numerous advantages in metagenomic bio-prospecting.