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A roadmap for metagenomic enzyme discovery

Robinson, Serina L ; Piel, Jörn ; Sunagawa, Shinichi

Natural product reports, 2021-11, Vol.38 (11), p.1994-223 [Periódico revisado por pares]

England: Royal Society of Chemistry

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  • Título:
    A roadmap for metagenomic enzyme discovery
  • Autor: Robinson, Serina L ; Piel, Jörn ; Sunagawa, Shinichi
  • Assuntos: Amino Acid Sequence ; Biological Products - metabolism ; Biosynthesis ; Catalytic Domain ; Chemical reactions ; Chemistry ; Computer applications ; Cytochrome P-450 Enzyme System - chemistry ; Cytochrome P-450 Enzyme System - physiology ; Deoxyribonucleic acid ; DNA ; Enzymes ; Enzymes - chemistry ; Enzymes - isolation & purification ; Enzymology ; Functionals ; Gene expression ; Genomics ; Genotypes ; Learning algorithms ; Machine Learning ; Metabolic pathways ; Metabolism ; Metagenomics ; Metagenomics - methods ; Microbial activity ; Microbiota ; Microorganisms ; Natural products ; Pathways ; Phenotypes ; Phylogeny ; Polymerase chain reaction ; Screening ; Substrates
  • É parte de: Natural product reports, 2021-11, Vol.38 (11), p.1994-223
  • Notas: Jörn Piel studied Chemistry at the University of Bonn, Germany, and obtained a PhD in 1998 (advisor: Wilhelm Boland). After a postdoc with Bradley S. Moore and Heinz G. Floss he became group leader at the Max Planck Institute for Chemical Ecology in Jena, Germany, in 2000. From 2004-2013 he was associate professor at the University of Bonn and subsequently full professor at the Institute of Microbiology, ETH Zürich. His lab works at the interface of Chemistry and Biology, studying bacterial metabolism with an emphasis on microbial and biosynthetic 'dark matter', symbiosis, marine natural products, biosynthetic engineering, and chemical ecology.
    Shinichi Sunagawa studied Biochemistry and Marine Ecology in Germany, and obtained his PhD in 2010 at the University of California, Merced, USA. After returning to Germany, he joined the European Molecular Biology Laboratory in Heidelberg as a postdoctoral fellow, and continued to work on ocean and human gut microbial communities as a research- and staff scientist. In 2016, he established the Microbiome Research Laboratory at the Institute of Microbiology at ETH Zürich, which combines bioinformatic and experimental approaches to integrate quantitative 'meta-omics' readouts with contextual information to study and the role of environmental microorganisms and mechanisms of host-microbial homeostasis.
    Serina Robinson is an ETH Zürich postdoctoral fellow with Dr Jörn Piel and will start her independent career as a tenure-track group leader at the Swiss Federal Institute of Aquatic Science and Technology (Eawag) in autumn 2021. She obtained her PhD in Microbiology and MSc in Bioinformatics and Computational Biology from the University of Minnesota, Minneapolis, USA (advisor: Larry Wackett), where she applied machine learning and genome mining techniques to investigate β-lactone synthetases, a newly-discovered family of enzymes involved in natural product biosynthesis. Her current research focuses on the discovery of new biosynthetic enzymes from marine, freshwater, and wastewater metagenomes.
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  • Descrição: Covering: up to 2021 Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods. Shotgun metagenomic approaches to uncover new enzymes are underdeveloped relative to PCR- or activity-based functional metagenomics. Here we review computational and experimental strategies to discover biosynthetic enzymes from metagenomes.
  • Editor: England: Royal Society of Chemistry
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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