Metagenomics: novel enzymes from non-culturable microbes

Berini, Francesca; Casciello, Carmine; Marcone, Giorgia Letizia; Marinelli, Flavia

doi:10.1093/femsle/fnx211

Cited by 131 publications

(102 citation statements)

References 191 publications

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“…Metagenomic libraries provide access to the vast reservoir of uncultivated genetic diversity encoded in microbial communities inhabiting natural and engineered ecosystems [19][20][21] . Emerging sophisticated sequence-and functionbased screening technologies are being deployed to identify novel enzymes, including CAZymes, within these libraries [21][22][23][24] . However, to our knowledge no function-based metagenomics screening approach has yet been developed that targets GP-encoded genes.…”

Section: Introductionmentioning

confidence: 99%

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library

Macdonald

Patel

Larmour

et al. 2018

Journal of Biological Chemistry

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Glycoside phosphorylases have considerable potential as catalysts for the assembly of useful glycans for products ranging from functional foods and prebiotics to novel materials. However, the substrate diversity of currently identified phosphorylases is relatively small, limiting their practical applications. To address this limitation, we developed a high-throughput screening approach using the activated substrate 2,4-dinitrophenyl β-D-glucoside (DNPGlc) and inorganic phosphate for identifying glycoside phosphorylase activity and used it to screen a large insert metagenomic library. The initial screen, based on release of 2,4-dinitrophenol from DNPGlc in the presence of phosphate, identified the gene bglP, encoding a retaining β-glycoside phosphorylase from the CAZy GH3 family. Kinetic and mechanistic analysis of the gene product, BglP, confirmed a double displacement ping-pong mechanism involving a covalent glycosyl-enzyme intermediate. X-ray crystallographic analysis provided insights into the phosphate-binding mode and identified a key glutamine residue in the active site important for substrate recognition. Substituting this glutamine for a serine swapped the substrate specificity from glucoside to Nacetylglucosaminide. In summary, we present a high-throughput screening approach for identifying β-glycoside phosphorylases, which was robust, simple to implement, and useful in identifying active clones within a metagenomics library. GH3 β-glycoside phosphorylase from a metagenomic library 2 Implementation of this screen enabled discovery of a new glycoside phosphorylase class and has paved the way to devising simple ways in which enzyme specificity can be encoded and swapped, which has implications for biotechnological applications.Carbohydrate active enzymes (CAZymes) are the biocatalysts responsible for the assembly, degradation and modification of glycans in biological systems 1 . They are also widely employed enzymes in industry, being used in brewing and food processing, animal feed preparation, industrial pulp and paper applications and increasingly in biofuel and bioproduct development [2][3][4][5] . While the use of CAZymes is cost-effective in glycan degradation, glycan assembly generally requires the use of expensive starting materials, such as nucleotide phosphosugars 6 . The high-cost of these materials makes de novo industrial-scale glycan synthesis difficult and usually non-viable.One class of CAZyme that offers a potential solution to the high costs typically associated with enzymatic glycan synthesis is that of the glycoside phosphorylases (GPs), which are increasingly being recognized and used for the biocatalysis and biotransformation of glycans 7-9 . These enzymes ordinarily carry out phosphorolysis by transferring a glycosyl moiety from the nonreducing end of a di-or polysaccharide substrate onto inorganic phosphate, thereby generating a sugar-1-phosphate 10 ( Figure 1A). GPs distinguish themselves from most CAZymes in that the hydrolytic free energy associated with the glycosidic e...

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Section: Introductionmentioning

confidence: 99%

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library

Macdonald

Patel

Larmour

et al. 2018

Journal of Biological Chemistry

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“…In this context, metagenomic approaches may demonstrate to be a powerful technology for discovering new enzymes and other valuable biomolecules produced by non-cultivable microorganisms. Specifically, functional screening in metagenomic libraries, which has shown to be useful for discovering new genes since sequence homology is not required for gene identification 22,23 . Despite these advantages, large-scale production of biosurfactants remains to be an expensive procedure, in part because of the complicated extraction and purification processes as well as the dependence on suitable substrates for their production 24 .…”

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confidence: 99%

MBSP1: a biosurfactant protein derived from a metagenomic library with activity in oil degradation

Araújo

Silva-Portela

Lima

et al. 2020

Sci Rep

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Microorganisms represent the most abundant biomass on the planet; however, because of several cultivation technique limitations, most of this genetic patrimony has been inaccessible. Due to the advent of metagenomic methodologies, such limitations have been overcome. Prevailing over these limitations enabled the genetic pool of non-cultivable microorganisms to be exploited for improvements in the development of biotechnological products. By utilising a metagenomic approach, we identified a new gene related to biosurfactant production and hydrocarbon degradation. Environmental DNA was extracted from soil samples collected on the banks of the Jundiaí River (Natal, Brazil), and a metagenomic library was constructed. Functional screening identified the clone 3C6, which was positive for the biosurfactant protein and revealed an open reading frame (ORF) with high similarity to sequences encoding a hypothetical protein from species of the family Halobacteriaceae. This protein was purified and exhibited biosurfactant activity. Due to these properties, this protein was named metagenomic biosurfactant protein 1 (MBSP1). In addition, E. coli Rosetta tM (DE3) strain cells transformed with the MBSP1 clone showed an increase in aliphatic hydrocarbon degradation. In this study, we described a single gene encoding a protein with marked tensoactive properties that can be produced in a host cell, such as Escherichia coli, without substrate dependence. Furthermore, MBSP1 has been demonstrated as the first protein with these characteristics described in the Archaea or Bacteria domains.Surfactants are amphipathic compounds that have a hydrophobic moiety that is directed towards the surface and a hydrophilic portion that is directed towards the solution 1 . These amphiphilic molecules can reduce surface tension at air/water and oil/water interfaces 2,3 . Surfactants produced by organisms are called biosurfactants, which are extracellular products or components within the cell membranes of prokaryotes and eukaryotes 1,4,5 . Biosurfactants are classified into four major categories: glycolipids, fatty acids, lipopeptides, and polymeric types. These categories are represented by amphipathic polysaccharides, lipopolysaccharides, lipoproteins, fatty acids, or complex mixtures of these biopolymers. In general, the synthesis of biosurfactants involves elaborate genetic systems, including operons, non-ribosomal peptide synthetases, and/or multiprotein assembly complexes 6-9 .The synthesis of biosurfactants occurs in the presence of different substrates as a carbon source. To reduce production costs, cheaper substrates have been used. The most commonly used substrates for biosurfactant production are agro-industrial products such as molasses, marc, or vegetable oils 6-8 . Rhamnolipids and surfactin are among the best studied biosurfactants. Rhamnolipids are glycolipids first discovered in Pseudomonas aeruginosa, which are formed by the bonding between a rhamnose moiety and a 3-(3-hydroxyalkanoyloxy)alkanoic acid (HAA) fatty acid tail. The essen...

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“…(Bruni et al 1997;Smith et al 2015), or for bioremediation (Lovley 2003;Gihring et al 2011). Additionally, the industry strives for discovering novel enzymes by metagenomics (Maurer 2004) and consequently 332 relevant enzymes were discovered between 2014 and 2017 (Berini et al 2017). Microorganisms also impose a significant threat to human health (https://www.who.int/healthinfo/global_burden_disease / GHE_DthWBInc_Proj_2016-2060 and metagenomics is becoming increasingly popular among medical practitioners (Forbes et al 2018).…”

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MetaGenomic analysis of short and long reads

Manske¹,

Grundmann²,

Makałowski³

2020

Preprint

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Identifying single organisms in environmental samples is one of the key tasks of metagenomics.During the last few years, third generation sequencing technologies have enabled researchers to sequence much longer molecules, but at the expense of sequencing accuracy. Thus, new algorithms needed to be developed to cope with this new type of data. With this in mind, we developed a tool called MetaG. An intuitive web interface makes the software accessible to a vast range of users, including those without extensive bioinformatic expertise. Evaluation of MetaG's performance showed that it makes nearly perfect classifications of viral isolates using simulated short and long reads.MetaG also outperformed current state-of-the-art algorithms on data from targeted sequencing of the 16S and 28S rRNA genes. Since MetaG's output is also supplemented with information about hosts and antibiotic resistances of pathogens, we expect it to be especially useful to the healthcare sector.Moreover, the outstanding accuracy of the taxonomic assignments will make MetaG a serious alternative for anyone working with metagenomic sequences. MetaG can be accessed at

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Metagenomics: novel enzymes from non-culturable microbes

Cited by 131 publications

References 191 publications

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library

MBSP1: a biosurfactant protein derived from a metagenomic library with activity in oil degradation

MetaGenomic analysis of short and long reads

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