Abstract
Nature is a diverse and rich source of bioactive pathways or novel building blocks for synthetic biology. In this Perspective, we describe the emerging research field in which metagenomes are functionally interrogated using synthetic biology. This approach substantially expands the set of identified biological activities and building blocks. In reviewing this field, we find that its potential for new biological discovery is dramatically increasing. Functional metagenomic mining using genetic circuits has led to the discovery of novel bioactivity such as amidases, NF-κB modulators, naphthalene degrading enzymes, cellulases, lipases and transporters. Using these genetic circuits as a template, improvements are made by designing biosensors, such as in vitro–evolved riboswitches and computationally redesigned transcription factors. Thus, powered by the rapidly expanding repertoire of biosensors and streamlined processes for automated genetic circuit design, a greater variety of complex selection circuits can be built, with resulting impacts on drug discovery and industrial biotechnology.
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References
Turnbaugh, P. J. & Gordon, J. I. An invitation to the marriage of metagenomics and metabolomics. Cell 134, 708–713 (2008).
Schloss, P. D. & Handelsman, J. Toward a census of bacteria in soil. PLoS Comput. Biol. 2, e92 (2006).
Amann, R. I., Ludwig, W. & Schleifer, K.-H. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 59, 143–169 (1995).
Torsvik, V., Goksøyr, J. & Daae, F. L. High diversity in DNA of soil bacteria. Appl. Environ. Microbiol. 56, 782–787 (1990).
Staley, J. T. & Konopka, A. Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats. Annu. Rev. Microbiol. 39, 321–346 (1985).
Hess, M. et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science 331, 463–467 (2011).
Burstein, D. et al. New CRISPR-Cas systems from uncultivated microbes. Nature 542, 237–241 (2017).
Li, J. et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 32, 834–841 (2014).
Escobar-Zepeda, A., Vera-Ponce de León, A. & Sanchez-Flores, A. The road to metagenomics: From microbiology to DNA sequencing technologies and bioinformatics. Front. Genet. 6, 348 (2015).
Handelsman, J., Rondon, M. R., Brady, S. F., Clardy, J. & Goodman, R. M. Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. Chem. Biol. 5, R245–R249 (1998).
Nielsen, A. A. et al. Genetic circuit design automation. Science 352, aac7341 (2016).The authors used an automated process to design and construct 60 distinct genetic circuits of which 45 were experimentally validated to show the correct function.
Eggeling, L., Bott, M. & Marienhagen, J. Novel screening methods–biosensors. Curr. Opin. Biotechnol. 35, 30–36 (2015).
Michener, J. K., Thodey, K., Liang, J. C. & Smolke, C. D. Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways. Metab. Eng. 14, 212–222 (2012).
Rondon, M. R. et al. Cloning the soil metagenome: a strategy for accessing the genetic and functional diversity of uncultured microorganisms. Appl. Environ. Microbiol. 66, 2541–2547 (2000).
Henne, A., Schmitz, R. A., Bömeke, M., Gottschalk, G. & Daniel, R. Screening of environmental DNA libraries for the presence of genes conferring lipolytic activity on Escherichia coli. Appl. Environ. Microbiol. 66, 3113–3116 (2000).
Brady, S. F. & Clardy, J. Long-chain N-acyl amino acid antibiotics isolated from heterologously expressed environmental DNA. J. Am. Chem. Soc. 122, 12903–12904 (2000).
MacNeil, I. A. et al. Expression and isolation of antimicrobial small molecules from soil DNA libraries. J. Mol. Microbiol. Biotechnol. 3, 301–308 (2001).
Gillespie, D. E. et al. Isolation of antibiotics turbomycin A and turbomycin B from a metagenomic library of soil microbial DNA. Appl. Environ. Microbiol. 68, 4301–4306 (2002).
Entcheva, P., Liebl, W., Johann, A., Hartsch, T. & Streit, W. R. Direct cloning from enrichment cultures, a reliable strategy for isolation of complete operons and genes from microbial consortia. Appl. Environ. Microbiol. 67, 89–99 (2001).
Simon, C., Herath, J., Rockstroh, S. & Daniel, R. Rapid identification of genes encoding DNA polymerases by function-based screening of metagenomic libraries derived from glacial ice. Appl. Environ. Microbiol. 75, 2964–2968 (2009).
Charlop-Powers, Z., Banik, J. J., Owen, J. G., Craig, J. W. & Brady, S. F. Selective enrichment of environmental DNA libraries for genes encoding nonribosomal peptides and polyketides by phosphopantetheine transferase-dependent complementation of siderophore biosynthesis. ACS Chem. Biol. 8, 138–143 (2013).
Riesenfeld, C. S., Goodman, R. M. & Handelsman, J. Uncultured soil bacteria are a reservoir of new antibiotic resistance genes. Environ. Microbiol. 6, 981–989 (2004).
Wichmann, F., Udikovic-Kolic, N., Andrew, S. & Handelsman, J. Diverse antibiotic resistance genes in dairy cow manure. MBio 5, e01017–13 (2014).
Sommer, M. O. A., Dantas, G. & Church, G. M. Functional characterization of the antibiotic resistance reservoir in the human microflora. Science 325, 1128–1131 (2009).
Culligan, E. P., Sleator, R. D., Marchesi, J. R. & Hill, C. Metagenomic identification of a novel salt tolerance gene from the human gut microbiome which encodes a membrane protein with homology to a brp/blh-family β-carotene 15,15′-monooxygenase. PLoS One 9, e103318 (2014).
Culligan, E. P., Sleator, R. D., Marchesi, J. R. & Hill, C. Functional environmental screening of a metagenomic library identifies stlA; a unique salt tolerance locus from the human gut microbiome. PLoS One 8, e82985 (2013).
Guazzaroni, M. E., Morgante, V., Mirete, S. & González-Pastor, J. E. Novel acid resistance genes from the metagenome of the Tinto River, an extremely acidic environment. Environ. Microbiol. 15, 1088–1102 (2013).
Varaljay, V. A. et al. Functional metagenomic selection of ribulose 1,5-bisphosphate carboxylase/oxygenase from uncultivated bacteria. Environ. Microbiol. 18, 1187–1199 (2016).
Henning, H. et al. Identification of novel benzoylformate decarboxylases by growth selection. Appl. Environ. Microbiol. 72, 7510–7517 (2006).
Sommer, M. O., Church, G. M. & Dantas, G. A functional metagenomic approach for expanding the synthetic biology toolbox for biomass conversion. Mol. Syst. Biol. 6, 360 (2010).
Forsberg, K. J. et al. Identification of genes conferring tolerance to lignocellulose-derived inhibitors by functional selections in soil metagenomes. Appl. Environ. Microbiol. 82, 528–537 (2015).
Uchiyama, T., Abe, T., Ikemura, T. & Watanabe, K. Substrate-induced gene-expression screening of environmental metagenome libraries for isolation of catabolic genes. Nat. Biotechnol. 23, 88–93 (2005).
Uchiyama, T. & Miyazaki, K. Metagenomic screening for aromatic compound-responsive transcriptional regulators. PLoS One 8, e75795 (2013).
Han, S. S., Lee, J. Y., Kim, W. H., Shin, H. J. & Kim, G. J. Screening of promoters from metagenomic DNA and their use for the construction of expression vectors. J. Microbiol. Biotechnol. 18, 1634–1640 (2008).
Lee, S. H., Kim, J. M., Lee, H. J. & Jeon, C. O. Screening of promoters from rhizosphere metagenomic DNA using a promoter-trap vector and flow cytometric cell sorting. J. Basic Microbiol. 51, 52–60 (2011).
Meier, M. J., Paterson, E. S. & Lambert, I. B. Use of substrate-induced gene expression in metagenomic analysis of an aromatic hydrocarbon-contaminated soil. Appl. Environ. Microbiol. 82, 897–909 (2015).
de Lorenzo, V. Problems with metagenomic screening. Nat. Biotechnol. 23, 1045–1046 (2005). author reply 1045–1046.
Williamson, L. L. et al. Intracellular screen to identify metagenomic clones that induce or inhibit a quorum-sensing biosensor. Appl. Environ. Microbiol. 71, 6335–6344 (2005).
Guan, C. et al. Signal mimics derived from a metagenomic analysis of the gypsy moth gut microbiota. Appl. Environ. Microbiol. 73, 3669–3676 (2007).
Nasuno, E. et al. Phylogenetically novel LuxI/LuxR-type quorum sensing systems isolated using a metagenomic approach. Appl. Environ. Microbiol. 78, 8067–8074 (2012).
Schipper, C. et al. Metagenome-derived clones encoding two novel lactonase family proteins involved in biofilm inhibition in Pseudomonas aeruginosa. Appl. Environ. Microbiol. 75, 224–233 (2009).
Uchiyama, T. & Miyazaki, K. Product-induced gene expression, a product-responsive reporter assay used to screen metagenomic libraries for enzyme-encoding genes. Appl. Environ. Microbiol. 76, 7029–7035 (2010).
Lakhdari, O. et al. Functional metagenomics: a high throughput screening method to decipher microbiota-driven NF-κB modulation in the human gut. PLoS One 5, e13092 (2010).
de Wouters, T. et al. A robust and adaptable high throughput screening method to study host-microbiota interactions in the human intestine. PLoS One 9, e105598 (2014).
Cohen, L. J. et al. Functional metagenomic discovery of bacterial effectors in the human microbiome and isolation of commendamide, a GPCR G2A/132 agonist. Proc. Natl Acad. Sci. USA 112, E4825–E4834 (2015).
Cohen, L. J. et al. Commensal bacteria make GPCR ligands that mimic human signalling molecules. Nature 549, 48–53 (2017).
Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 12, 174–180 (2011).
Schloissnig, S. et al. Genomic variation landscape of the human gut microbiome. Nature 493, 45–50 (2013).
Guo, C. J. et al. Discovery of reactive microbiota-derived metabolites that inhibit host proteases. Cell 168, 517–526.e18 (2017).
Wang, Y. et al. A culture-independent approach to unravel uncultured bacteria and functional genes in a complex microbial community. PLoS One 7, e47530 (2012).
Choi, S.L. Toward a generalized and high-throughput enzyme screening system based on artificial genetic circuits. ACS Synth. Biol. 3, 163–171 (2014).This study is the first to couple a genetic circuit to mine metagenomic library to high-throughput FACS screening.
Kim, H., Kwam, K. K., Rha, E. & Lee, S.-G. in Hydrocarbon and Lipid Microbiology Protocols. (eds. McGenity T., Timmis K., Nogales B.) 3–12 (Springer Protocols Handbooks, Springer, Berlin, Heidelberg, 2015).
Lee, D.-H. et al. A novel psychrophilic alkaline phosphatase from the metagenome of tidal flat sediments. BMC Biotechnol. 15, 1–13 (2015).
Jeong, Y. S. et al. High-throughput screening system based on phenolics-responsive transcription activator for directed evolution of organophosphate-degrading enzymes. Protein Eng. Des. Sel. 25, 725–731 (2012).
Siedler, S. et al. Development of a bacterial biosensor for rapid screening of yeast p-coumaric acid production. ACS Synth. Biol. 6, 1860–1869 (2017).
Genee, H. J. et al. Functional mining of transporters using synthetic selections. Nat. Chem. Biol. 12, 1015–1022 (2016).The study is the first report of applying functional selection (instead of screening) using a genetic circuit to mine metagenomic libraries for bioactivity in a high-throughput format.
Muranaka, N., Sharma, V., Nomura, Y. & Yokobayashi, Y. An efficient platform for genetic selection and screening of gene switches in Escherichia coli. Nucleic Acids Res. 37, e39 (2009).
Jenison, R. D., Gill, S. C., Pardi, A. & Polisky, B. High-resolution molecular discrimination by RNA. Science 263, 1425–1429 (1994).
Novichkov, P. S. et al. RegPrecise 3.0–a resource for genome-scale exploration of transcriptional regulation in bacteria. BMC Genom. 14, 745 (2013).
Mellin, J. R. & Cossart, P. Unexpected versatility in bacterial riboswitches. Trends Genet. 31, 150–156 (2015).
Dar, D. et al. Term-seq reveals abundant ribo-regulation of antibiotics resistance in bacteria. Science 352, aad9822 (2016).
Wittmann, A. & Suess, B. Engineered riboswitches: expanding researchers’ toolbox with synthetic RNA regulators. FEBS Lett. 586, 2076–2083 (2012).
Espah Borujeni, A., Mishler, D. M., Wang, J., Huso, W. & Salis, H. M. Automated physics-based design of synthetic riboswitches from diverse RNA aptamers. Nucleic Acids Res. 44, 1–13 (2016).
Domin, G. et al. Applicability of a computational design approach for synthetic riboswitches. Nucleic Acids Res. 45, 4108–4119 (2017).
Jha, R. K., Chakraborti, S., Kern, T. L., Fox, D. T. & Strauss, C. E. M. Rosetta comparative modeling for library design: Engineering alternative inducer specificity in a transcription factor. Proteins 83, 1327–1340 (2015).
Taylor, N. D. et al. Engineering an allosteric transcription factor to respond to new ligands. Nat. Methods 13, 177–183 (2016). By coupling the Rosetta framework to redesign bacterial allosteric transcription factors with a genetic circuit to interrogate the success of a design, this paper reports a promising method to expand the repertoire of biosensors.
Feng, J. et al. A general strategy to construct small molecule biosensors in eukaryotes. eLife 4, 7250–7257 (2015).
Tinberg, C. E. et al. Computational design of ligand-binding proteins with high affinity and selectivity. Nature 501, 212–216 (2013).
Libis, V., Delépine, B. & Faulon, J.-L. Expanding biosensing abilities through computer-aided design of metabolic pathways. ACS Synth. Biol. 5, 1076–1085 (2016).
Ausländer, S., Ausländer, D., Müller, M., Wieland, M. & Fussenegger, M. Programmable single-cell mammalian biocomputers. Nature 487, 123–127 (2012).
Chen, Y. J. et al. Characterization of 582 natural and synthetic terminators and quantification of their design constraints. Nat. Methods 10, 659–664 (2013).
Stanton, B. C. et al. Genomic mining of prokaryotic repressors for orthogonal logic gates. Nat. Chem. Biol. 10, 99–105 (2014).
Lorenz, P. & Eck, J. Metagenomics and industrial applications. Nat. Rev. Microbiol. 3, 510–516 (2005).
Taupp, M., Mewis, K. & Hallam, S. J. The art and design of functional metagenomic screens. Curr. Opin. Biotechnol. 22, 465–472 (2011).
Milshteyn, A., Schneider, J. S. & Brady, S. F. Mining the metabiome: identifying novel natural products from microbial communities. Chem. Biol. 21, 1211–1223 (2014).
Huang, W. E., Song, Y. & Xu, J. Single cell biotechnology to shed a light on biological ‘dark matter’ in nature. Microb. Biotechnol. 8, 15–16 (2015).
Raman, S., Rogers, J. K., Taylor, N. D. & Church, G. M. Evolution-guided optimization of biosynthetic pathways. Proc. Natl Acad. Sci. USA 111, 17803–17808 (2014).
Gallagher, R. R., Patel, J. R., Interiano, A. L., Rovner, A. J. & Isaacs, F. J. Multilayered genetic safeguards limit growth of microorganisms to defined environments. Nucleic Acids Res. 43, 1945–1954 (2015).
Chan, C. T. Y., Lee, J. W., Cameron, D. E., Bashor, C. J. & Collins, J. J. ‘Deadman’ and ‘Passcode’ microbial kill switches for bacterial containment. Nat. Chem. Biol. 12, 82–86 (2016).
Rugbjerg, P., Myling-Petersen, N., Porse, A., Sarup-Lytzen, K. & Sommer, M. O. A. Diverse genetic error modes constrain large-scale bio-based production. Nat. Commun. 9, 787 (2018).
Iftime, D. et al. Streptocollin, a type IV lanthipeptide produced by Streptomyces collinus Tü 365. ChemBioChem 16, 2615–2623 (2015).
Laureti, L. et al. Identification of a bioactive 51-membered macrolide complex by activation of a silent polyketide synthase in Streptomyces ambofaciens. Proc. Natl Acad. Sci. USA 108, 6258–6263 (2011).
Gabor, E. M., Alkema, W. B. L. & Janssen, D. B. Quantifying the accessibility of the metagenome by random expression cloning techniques. Environ. Microbiol. 6, 879–886 (2004).
Craig, J. W., Chang, F.-Y., Kim, J. H., Obiajulu, S. C. & Brady, S. F. Expanding small-molecule functional metagenomics through parallel screening of broad-host-range cosmid environmental DNA libraries in diverse proteobacteria. Appl. Environ. Microbiol. 76, 1633–1641 (2010).
Angov, E., Hillier, C. J., Kincaid, R. L. & Lyon, J. A. Heterologous protein expression is enhanced by harmonizing the codon usage frequencies of the target gene with those of the expression host. PLoS One 3, e2189 (2008).
Bailly, J. et al. Soil eukaryotic functional diversity, a metatranscriptomic approach. ISME J. 1, 632–642 (2007).
Ferrer, M., Beloqui, A., Timmis, K. N. & Golyshin, P. N. Metagenomics for mining new genetic resources of microbial communities. J. Mol. Microbiol. Biotechnol. 16, 109–123 (2009).
Stevens, D. C. et al. Alternative sigma factor over-expression enables heterologous expression of a type II polyketide biosynthetic pathway in Escherichia coli. PLoS One 8, e64858 (2013).
Gaida, S. M. et al. Expression of heterologous sigma factors enables functional screening of metagenomic and heterologous genomic libraries. Nat. Commun. 6, 7045 (2015).This paper shows how addition of heterologous sigma factors to a metagenomic expression host increases the fraction of transcribed DNA.
Kim, Y. J. et al. Improved metagenome screening efficiency by random insertion of T7 promoters. J. Biotechnol. 230, 47–53 (2016).
Kushwaha, M. & Salis, H. M. A portable expression resource for engineering cross-species genetic circuits and pathways. Nat. Commun. 6, 7832 (2015).
Kosuri, S. & Church, G. M. Large-scale de novo DNA synthesis: technologies and applications. Nat. Methods 11, 499–507 (2014).
Schmidt, M. & de Lorenzo, V. Synthetic constructs in/for the environment: managing the interplay between natural and engineered biology. FEBS Lett. 586, 2199–2206 (2012).
Tuerk, C. & Gold, L. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249, 505–510 (1990).
Gredell, J. A., Frei, C. S. & Cirino, P. C. Protein and RNA engineering to customize microbial molecular reporting. Biotechnol. J. 7, 477–499 (2012).
Mishra, D., Rivera, P. M., Lin, A., Del Vecchio, D. & Weiss, R. A load driver device for engineering modularity in biological networks. Nat. Biotechnol. 32, 1268–1275 (2014).
Acknowledgements
This research was funded by the Novo Nordisk Foundation and the European Union Seventh Framework Programme (FP7-KBBE-2013-7-single-stage) under grant agreement no. 613745, Promys. M.O.A.S. acknowledges additional funding from The Lundbeck Foundation. E.v.d.H. acknowledges funding from the EU FP7- People-2012-ITN BacTory (317058).
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H.J.G. and M.O.A.S. are co-founders of Biosyntia, with commercial interest in the topic of the Perspective.
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van der Helm, E., Genee, H.J. & Sommer, M.O.A. The evolving interface between synthetic biology and functional metagenomics. Nat Chem Biol 14, 752–759 (2018). https://doi.org/10.1038/s41589-018-0100-x
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DOI: https://doi.org/10.1038/s41589-018-0100-x
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