dbCAN2: a meta server for automated carbohydrate-active enzyme annotation

Zhang, Han; Yohe, Tanner; Huang, Le; Entwistle, Sarah; Wu, Peizhi; Yang, Zhenglu; Busk, Peter Kamp; Xu, Ying; Yin, Yanbin

doi:10.1093/nar/gky418

Cited by 1,885 publications

(1,583 citation statements)

References 27 publications

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“…All protein predictions were searched against the CAZy database using dbCAN2 49 and HMMER 74 , and polysaccharide utilisation loci (PUL) were predicted for Bacteroidetes RUGs using PULpy 56 .…”

Section: Methodsmentioning

confidence: 99%

“…The RUG proteins were compared to the CAZy 48 database of 31 st July 2018 using dbCAN2 49 . Of the 10.69 million proteins, 442917 are predicted to be involved in carbohydrate metabolism, including 235001 glycoside hydrolases, 120494 glycosyltransferases, 55523 carbohydrate esterases, 23928 proteins with carbohydrate binding modules, 6834 polysaccharide lyases, 907 proteins with predicted auxiliary activities, 80 proteins with a predicted cohesin domain, and 150 proteins with an S-layer homology module (SLH).…”

Section: A Dataset Of Rumen Proteins For Functional and Proteomic Anamentioning

confidence: 99%

See 1 more Smart Citation

The genomic and proteomic landscape of the rumen microbiome revealed by comprehensive genome-resolved metagenomics

Stewart¹,

Auffret²,

Warr³

et al. 2018

Preprint

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Ruminants provide essential nutrition for billions of people worldwide. The rumen is a specialised stomach adapted to the breakdown of plant-derived complex polysaccharides, and collectively the rumen microbiota encode the thousands of enzymes responsible. Here we present a comprehensive analysis of over 6.5 terabytes of Illumina and Nanopore sequence data, including assembly of 4941 metagenome-assembled genomes, and several single-contig, whole-chromosome assemblies of novel rumen bacteria. We also present the largest dataset of predicted proteins from the rumen, and provide rich annotation against public datasets. Together these data will form an essential part of future studies of rumen microbiome structure and function.

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Section: Methodsmentioning

confidence: 99%

Section: A Dataset Of Rumen Proteins For Functional and Proteomic Anamentioning

confidence: 99%

The genomic and proteomic landscape of the rumen microbiome revealed by comprehensive genome-resolved metagenomics

Stewart¹,

Auffret²,

Warr³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Despite their immensely important status as "industry standard" databases, both CAZy and PULDB suffer from problems. As others have noted 17,18 , CAZy and PULDB are optimised for simple, single user queries. Bulk querying, bulk download and bulk search are not enabled; annotation of new or user genomes is not possible; and certain aspects of the annotation methods are opaque.…”

Section: Background and Summarymentioning

confidence: 96%

Open prediction of polysaccharide utilisation loci (PUL) in 5414 publicBacteroidetesgenomes using PULpy

Stewart¹,

Auffret²,

Roehe³

et al. 2018

Preprint

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words maximumPolysaccharide utilisation loci (PUL) are regions within bacterial genomes that encode all the necessary machinery for the cleavage of particular carbohydrates. For the Bacteroidetes phylum, prediction of PUL from genomic data alone involves the identification of carbohydrate-active enzymes (CAZymes) co-localised with susCD gene pairs. Here we present the open prediction of PUL in 5414 public Bacteroidetes genomes, and an open-source pipeline to reproduce or extend the results.

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“…The list is sorted according to the most 221 specifically enriched proteins in xylem sap (green) and SXM (red), respectively. CAZy database (http://www.cazy.org) and dbCAN2 [37]. All details are given in S2 248 Table. The Venn diagram in Fig All 399 identified secreted proteins were classified into functional groups according to 262 the predicted domains (S2 Table, Fig 2C).…”

Section: Xylem Sap and Pectin-rich Sxm Trigger Specific Exoproteomicmentioning

confidence: 99%

V. longisporumelicits media-dependent secretome responses with a further capacity to distinguish between plant-related environments

Leonard

Kühn

Harting

et al. 2020

Preprint

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23 material. Importantly, the xylem sap-specific exoproteome pinpointed Nlp2 and Nlp3 49 as single effectors required for successful V. dahliae colonization. 50 51 Author Summary 52 Verticillium spp. infect hundreds of different plants world-wide leading to enormous 53 economic losses. Verticillium wilt is a disease of the vasculature. The fungus colonizes 54 the xylem of its host plant where it exploits the vascular system to colonize the whole 55 plant. Therefore, the fungus spends part of its lifetime in this nutrient-low and 56 imbalanced environment where it is inaccessible for disease control treatments. This 57 lifestyle as well requires the fungus to react to plant defense responses by secreting 58 specific effector molecules to establish a successful infection. We addressed the 59 differences in media-dependent secretion responses of Verticillium longisporum. We 60 identified a broad response pattern induced by several media, and a similar response 61 (but with some distinct differences) for the plant-related environments: the pectin-rich 62 medium SXM and xylem sap from the host rapeseed. Importantly, we show that the 63 necrosis and ethylene inducing-like proteins Nlp2 and Nlp3 are xylem sap-specific 64 proteins that are required for full V. dahliae pathogenicity on tomato. These factors 65 play a role during the colonization phase and represent potential targets for new control 66 strategies for Verticillium wilt. 67 68 associated molecular patterns (PAMPs); examples include the fungal cell-wall polymer 95 chitin [16]. PAMP perception elicits a basal defense response which halts colonization 96 by non-adapted pathogens and results in PAMP-triggered immunity (PTI). Host-97 adapted pathogens circumvent PTI by secretion of specific effector proteins as 98 virulence factors for different phases of the infection cycle [17]. These secreted 99 effectors may act passively or actively to combat plant defense responses [18]. 100 Well known examples of fungal effectors include the Avr4 and Ecp6 effectors from the 101 leaf mold fungus Cladosporum fulvum that bind to chitin oligosaccharides via a 102 carbohydrate-binding module (CBM) or LysM domain, respectively [18-21]. Similarly, 103 a chitin scavenging function has also been assigned to Cp1 in V. dahliae strain XH-8. 104 CP1 knockout mutants were affected in cotton virulence [22]. This chitin protection 105 leads to the suppression of the PTI of the plant and shields the fungal cell wall from 106 plant chitinases that hydrolyze chitin [18-21]. Other fungal effectors such as 107 metalloproteases possess enzymatic activity and are able to truncate plant chitinases 108 that attack the fungal cell wall [23, 24]. Toxins provide another means for pathogens 109 to attack plant hosts. For example, necrosis and ethylene inducing-like proteins (NLP) 110 induce immune responses and cell death in host tissues and are conserved among 111 fungi including Verticillium spp. [25, 26]. V. dahliae isolates encode up to eight NLP 112 homologs [26, 27] whereas most other fungi gene...

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dbCAN2: a meta server for automated carbohydrate-active enzyme annotation

Cited by 1,885 publications

References 27 publications

The genomic and proteomic landscape of the rumen microbiome revealed by comprehensive genome-resolved metagenomics

The genomic and proteomic landscape of the rumen microbiome revealed by comprehensive genome-resolved metagenomics

Open prediction of polysaccharide utilisation loci (PUL) in 5414 publicBacteroidetesgenomes using PULpy

V. longisporumelicits media-dependent secretome responses with a further capacity to distinguish between plant-related environments

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