Peptide-based functional annotation of carbohydrate-active enzymes by conserved unique peptide patterns (CUPP)

Abstract

Background Insight into the function of carbohydrate-active enzymes is required to understand their biological role and industrial potential. There is a need for better use of the ample genomic data in order to enable selection of the most interesting proteins for further studies. The basis for elaborating a new approach to sequence analysis is the hypothesis that when using conserved peptide patterns to determine the similarities between proteins, the exact spacing between conserved adjacent amino acids in the proteins plays a prominent functional role. Thus, the objective of developing the method of conserved unique peptide patterns (CUPP) is to construct a peptide-based grouping and validate the method to provide evidence that CUPP captures function-related features of the individual carbohydrate-active enzymes (as defined by CAZy families). This approach facilitates grouping of enzymes at a level lower than protein families and/or subfamilies. A standardized, efficient, and robust approach to functional annotation of carbohydrate-active enzymes would support improved molecular insight into enzyme–substrate interaction. Results A new nonalignment-based clustering and functional annotation tool was developed that uses conserved unique peptides patterns to perform automated clustering of proteins and formation of protein groups. A peptide-based model was constructed for each of these protein CUPP groups to be used to automatically annotate protein family, subfamily, and EC function of carbohydrate-active enzymes. CUPP prediction can annotate proteins (from any CAZy family) with high F-score to existing family (0.966), subfamily (0.961), and EC-function (0.843). The speed of the CUPP program was estimated and exemplified by prediction of the 504,017 nonredundant proteins of CAZy in less than four CPU hours. Conclusion It was possible to construct an automated system for clustering proteins within families and use the resulting CUPP groups to directly build peptide-based models for genome annotation. The CUPP runtime, F-score, sensitivity, and precisions of family and subfamily annotations match or represent an improvement compared to state-of-the-art tools. The speed of the CUPP annotation is similar to the rapid DIAMOND annotation tool. CUPP facilitates automated annotation of full genome assemblies to any CAZy family. Electronic supplementary material The online version of this article (10.1186/s13068-019-1436-5) contains supplementary material, which is available to authorized users.

Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity

“…Pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG, ec00531, (Kanehisa et al, 2017)), in combination with literature annotation of these pathways for specific bacteria (Hobbs et al, 2018;Robb et al, 2017;Ndeh et al, 2017), were used to identify reactions (enzyme commission (EC) numbers) associated with the modification task. (Table S3) Finally, we used CAZy, dbCAN, and CUPP (Barrett and Lange, 2019;Lombard et al, 2014;Yin et al, 2012;Zhang et al, 2018) to map EC numbers to microbial genes associated with glycan modification ( Table S3).…”

Comparative Characterization of Aspergillus Pectin Lyases by Discriminative Substrate Degradation Profiling

“…Although Al PelF differs most in terms of structure ( Figure 3 ), CUPP singled out AlPelC as being more different. The detailed grouping provided by CUPP relies on an unsupervised peptide-based clustering algorithm that can provide systematic grouping and functional annotation of carbohydrate-active enzymes (CAZymes) based on comparison of peptide motifs in the enzyme amino acid sequences ( Barrett and Lange, 2019 ). This emphasizes that Al PelC may be functionally different from the other pectin lyases studied here.…”

“…Using the CUPP webserver for functional annotation (Barrett and Lange, 2019;Barrett et al, 2020a) confirmed that all the included enzymes are predicted to belong to PL1_4. AaPelA, AtPelA, AlPelB, AlPelD, and AlPelF were all assigned EC 4.2.2.10 and CUPP group PL1:12.1 1 (Barrett et al, 2020a).…”

“…Secondary structure prediction was performed with PSIPRED (Buchan and Jones, 2019). The CUPP webserver for functional annotation was accessed at cupp.info (Barrett and Lange, 2019;Barrett et al, 2020a).…”

Transcriptome Profiling-Based Analysis of Carbohydrate-Active Enzymes in Aspergillus terreus Involved in Plant Biomass Degradation

“…Genes encoding hydrolytic enzymes glycoside hydrolases, glycosyltransferases, carbohydrate-binding modules and carbohydrate esterases were identified through gene sequence alignment against the updated Carbohydrate-Active Enzymes (CAZymes) database (see text footnote 1) ( Cantarel et al, 2009 ). Annotation validation at the family and subfamily level was conducted using CUPP for analysis of predicted conserved unique octamer peptide signatures ( Barrett and Lange, 2019 ; Barrett et al, 2020 ).…”