Next Generation Sequence Assembly with AMOS

Treangen, Todd J.; Sommer, Dan; Angly, Florent E.; Koren, Sergey; Pop, Mihai

doi:10.1002/0471250953.bi1108s33

Cited by 194 publications

(155 citation statements)

References 27 publications

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“…Since these libraries often had in excess of 20,000 times coverage, to prevent the accumulation of sequencing errors interfering with proper sequence assembly, the minimum k-mer multiplicity was calculated by 1% of the estimated coverage of a fosmid. Outside of the python script, assemblies which yielded more than one contig were then scaffolded using minimus2 53 . Parameterized commands can be found in both documentation on the GitHub page and in the python script itself.…”

Section: P-nitrophenyl N-acetyl-β-d-glucosaminidementioning

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: P-nitrophenyl N-acetyl-β-d-glucosaminidementioning

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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“…Using the Illumina sequence reads, two preliminary assemblies were obtained with Velvet (17) and Edena (7) and merged with the minimus2 utility (16). The resulting 27 contigs were scaffolded with SSPACE (3), and gaps were filled with GapFiller (4).…”

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confidence: 99%

Genome Sequence of “Candidatus Microthrix parvicella” Bio17-1, a Long-Chain-Fatty-Acid-Accumulating Filamentous Actinobacterium from a Biological Wastewater Treatment Plant

et al. 2012

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“…This paradigm was more commonly used with Sanger data and HTS longer reads as the process is computationally intensive and, in the past, has not performed as well with high volumes of short, high-coverage HTS reads, although advances have been made to improve the performance of OLC-based assemblers (93). For example, the AMOS suite of assembly tools remains a popular choice for OLC-based assembly of HTS data (96). De Bruijn graph assemblers partition the reads into overlapping subsequences of length k, called k-mers, to create the nodes for efficient graph structures, allowing programs to computationally handle larger data sets.…”

Section: De Novo Assemblymentioning

confidence: 99%

A Primer on Infectious Disease Bacterial Genomics

et al. 2016

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SUMMARYThe number of large-scale genomics projects is increasing due to the availability of affordable high-throughput sequencing (HTS) technologies. The use of HTS for bacterial infectious disease research is attractive because one whole-genome sequencing (WGS) run can replace multiple assays for bacterial typing, molecular epidemiology investigations, and more in-depth pathogenomic studies. The computational resources and bioinformatics expertise required to accommodate and analyze the large amounts of data pose new challenges for researchers embarking on genomics projects for the first time. Here, we present a comprehensive overview of a bacterial genomics projects from beginning to end, with a particular focus on the planning and computational requirements for HTS data, and provide a general understanding of the analytical concepts to develop a workflow that will meet the objectives and goals of HTS projects.

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Next Generation Sequence Assembly with AMOS

Cited by 194 publications

References 27 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

Genome Sequence of “Candidatus Microthrix parvicella” Bio17-1, a Long-Chain-Fatty-Acid-Accumulating Filamentous Actinobacterium from a Biological Wastewater Treatment Plant

A Primer on Infectious Disease Bacterial Genomics

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