SACCHARIS: an automated pipeline to streamline discovery of carbohydrate active enzyme activities within polyspecific families and de novo sequence datasets

Metagenomic and metabolomic analyses reveal differences in rumen microbiota between grass- and grain-fed Sanhe heifers

Introduction

The aim of this study was to investigate the effects of diets on the composition and function of rumen microbiome and metabolites in Sanhe heifers.

Methods

Metagenomic and metabolomic analyses were performed using rumen fluid samples collected from Sanhe heifers (n = 20) with similar body weights and ages from grass-fed and grain-fed systems.

Results

The grain-fed group exhibited more intensive rumen fermentation than the grass-fed group. However, the grass-fed group exhibited carbohydrate metabolism and methane production higher than that of the grain-fed group; these increases were observed as a higher abundance of various bacterial phyla (Firmicutes, Bacteroidetes, Actinobacteria, Lentisphaerae, and Verrucomicrobia), families (Lachnospiraceae, Eubacteriaceae, and Eggerthellaceae), and the archaeal family Methanobacteriaceae. A comparison of genes encoding carbohydrate-active enzymes, using Kyoto Encyclopedia of Genes and Genome profiles, revealed noteworthy differences in the functions of rumen microbiota; these differences were largely dependent on the feeding system.

Conclusion

These results could help manipulate and regulate feed efficiency in Sanhe cattle.

Enhanced crystalline cellulose degradation by a novel metagenome-derived cellulase enzyme

Metagenomics has revolutionized access to genomic information of microorganisms inhabiting the gut of herbivorous animals, circumventing the need for their isolation and cultivation. Exploring these microorganisms for novel hydrolytic enzymes becomes unattainable without utilizing metagenome sequencing. In this study, we harnessed a suite of bioinformatic analyses to discover a novel cellulase-degrading enzyme from the camel rumen metagenome. Among the protein-coding sequences containing cellulase-encoding domains, we identified and subsequently cloned and purified a promising candidate cellulase enzyme, Celcm05-2, to a state of homogeneity. The enzyme belonged to GH5 subfamily 4 and exhibited robust enzymatic activity under acidic pH conditions. It maintained hydrolytic activity under various environmental conditions, including the presence of metal ions, non-ionic surfactant Triton X-100, organic solvents, and varying temperatures. With an optimal temperature of 40 °C, Celcm05-2 showcased remarkable efficiency when deployed on crystalline cellulose (> 3.6 IU/mL), specifically Avicel, thereby positioning it as an attractive candidate for a myriad of biotechnological applications spanning biofuel production, paper and pulp processing, and textile manufacturing. Efficient biodegradation of waste paper pulp residues and the evidence of biopolishing suggested that Celcm05-2 can be used in the bioprocessing of cellulosic craft fabrics in the textile industry. Our findings suggest that the camel rumen microbiome can be mined for novel cellulase enzymes that can find potential applications across diverse biotechnological processes.

Conversion of Phytochemicals by Lactobacilli: (Phospho)-β-glucosidases Are Specific for Glucosylated Phytochemicals Rather than Disaccharides

Food-fermenting lactobacilli convert glycosylated phytochemicals to glycosyl hydrolases and thereby alter their biological activity. This study aimed to investigate the microbial transformation of β-glucosides of phytochemicals in comparison with utilization of cellobiose. Four homofermentative and four heterofermentative lactobacilli were selected to represent the metabolic diversity of Lactobacillaceae. The genomes of Lactobacillus crispatus, Companilactobacillus paralimentarius, Lacticaseibacillus paracasei, and Lactiplantibacillus plantarum encoded for 8 to 22 enzymes, predominantly phospho-β-glucosidases, with predicted activity on β-glucosides. Levilactobacillus hammesii and Furfurilactobacillus milii encoded for 3 β-glucosidases, Furfurilactobacillus rossiae for one, and Fructilactobacillus sanfranciscensis for none. The hydrolysis of amygdalin, esculin, salicin, glucosides of quercetin and genistein, and ginsenosides demonstrated that several strains hydrolyzed β-glucosides of phytochemicals but not cellobiose. Taken together, several of the carbohydrate-active enzymes of food-fermenting lactobacilli are specific for glycosides of phytochemicals.

Carbohydrate-active enzyme annotation in microbiomes using dbCAN

CAZymes or carbohydrate-active enzymes are critically important for human gut health, lignocellulose degradation, global carbon recycling, soil health, and plant disease. We developed dbCAN as a web server in 2012 and actively maintain it for automated CAZyme annotation. Considering data privacy and scalability, we provide run_dbcan as a standalone software package since 2018 to allow users perform more secure and scalable CAZyme annotation on their local servers. Here, we offer a comprehensive computational protocol on automated CAZyme annotation of microbiome sequencing data, covering everything from short read pre-processing to data visualization of CAZyme and glycan substrate occurrence and abundance in multiple samples. Using a real-world metagenomic sequencing dataset, this protocol describes commands for dataset and software preparation, metagenome assembly, gene prediction, CAZyme prediction, CAZyme gene cluster (CGC) prediction, glycan substrate prediction, and data visualization. The expected results include publication-quality plots for the abundance of CAZymes, CGCs, and substrates from multiple CAZyme annotation routes (individual sample assembly, co-assembly, and assembly-free). For the individual sample assembly route, this protocol takes ∼33h on a Linux computer with 40 CPUs, while other routes will be faster. This protocol does not require programming experience from users, but it does assume a familiarity with the Linux command-line interface and the ability to run Python scripts in the terminal. The target audience includes the tens of thousands of microbiome researchers who routinely use our web server. This protocol will encourage them to perform more secure, rapid, and scalable CAZyme annotation on their local computer servers.

CRISPR-Cas-based identification of a sialylated human milk oligosaccharides utilization cluster in the infant gut commensal Bacteroides dorei

The infant gut microbiome is impacted by early-life feeding, as human milk oligosaccharides (HMOs) found in breastmilk cannot be digested by infants and serve as nutrients for their gut bacteria. While the vast majority of HMO-utilization research has focused on Bifidobacterium species, recent studies have suggested additional HMO-utilizers, mostly Bacteroides, yet their utilization mechanism is poorly characterized. Here, we investigate Bacteroides dorei isolates from breastfed-infants and identify that polysaccharide utilization locus (PUL) 33 enables B. dorei to utilize sialylated HMOs. We perform transcriptional profiling and identity upregulated genes when growing on sialylated HMOs. Using CRISPR-Cas12 to knock-out four PUL33 genes, combined with complementation assays, we identify GH33 as the critical gene in PUL33 for sialylated HMO-utilization. This demonstration of an HMO-utilization system by Bacteroides species isolated from infants opens the way to further characterization of additional such systems, to better understand HMO-utilization in the infant gut.

Carbohydrate flow through agricultural ecosystems: Implications for synthesis and microbial conversion of carbohydrates

Carbohydrates are chemically and structurally diverse biomolecules, serving numerous and varied roles in agricultural ecosystems. Crops and horticulture products are inherent sources of carbohydrates that are consumed by humans and non-human animals alike; however carbohydrates are also present in other agricultural materials, such as soil and compost, human and animal tissues, milk and dairy products, and honey. The biosynthesis, modification, and flow of carbohydrates within and between agricultural ecosystems is intimately related with microbial communities that colonize and thrive within these environments. Recent advances in -omics techniques have ushered in a new era for microbial ecology by illuminating the functional potential for carbohydrate metabolism encoded within microbial genomes, while agricultural glycomics is providing fresh perspective on carbohydrate-microbe interactions and how they influence the flow of functionalized carbon. Indeed, carbohydrates and carbohydrate-active enzymes are interventions with unrealized potential for improving carbon sequestration, soil fertility and stability, developing alternatives to antimicrobials, and circular production systems. In this manner, glycomics represents a new frontier for carbohydrate-based biotechnological solutions for agricultural systems facing escalating challenges, such as the changing climate.

cazy_webscraper: local compilation and interrogation of comprehensive CAZyme datasets

Carbohydrate active enzymes (CAZymes) are pivotal in biological processes including energy metabolism, cell structure maintenance, signalling, and pathogen recognition. Bioinformatic prediction and mining of CAZymes improves our understanding of these activities and enables discovery of candidates of interest for industrial biotechnology, particularly the processing of organic waste for biofuel production. CAZy (www.cazy.org) is a high-quality, manually curated, and authoritative database of CAZymes that is often the starting point for these analyses. Automated querying and integration of CAZy data with other public datasets would constitute a powerful resource for mining and exploring CAZyme diversity. However, CAZy does not itself provide methods to automate queries, or integrate annotation data from other sources (except by following hyperlinks) to support further analysis. To overcome these limitations we developed cazy_webscraper, a command-line tool that retrieves data from CAZy and other online resources to build a local, shareable and reproducible database that augments and extends the authoritative CAZy database. cazy_webscraper's integration of curated CAZyme annotations with their corresponding protein sequences, up-to-date taxonomy assignments, and protein structure data facilitates automated large-scale and targeted bioinformatic CAZyme family analysis and candidate screening. This tool has found widespread uptake in the community, with over 35 000 downloads (from April 2021 to June 2023). We demonstrate the use and application of cazy_webscraper to: (i) augment, update and correct CAZy database accessions; (ii) explore the taxonomic distribution of CAZymes recorded in CAZy, identifying under-represented taxa and unusual CAZy class distributions; and (iii) investigate three CAZymes having potential biotechnological application for degradation of biomass, but lacking a representative structure in the PDB database. We describe in general how cazy_webscraper facilitates functional, structural and evolutionary studies to aid identification of candidate enzymes for further characterization, and specifically note that CAZy provides supporting evidence for recent expansion of the Auxiliary Activities (AA) CAZy family in eukaryotes, consistent with functions potentially specific to eukaryotic lifestyles.

Molecular characterization and in-depth genome analysis of Enterobacter sp. S-16

Enterobacter species are considered to be an opportunistic human pathogen owing to the existence of antibiotic-resistant strains and drug resides; however, the detailed analysis of the antibiotic resistance and virulence features in environmental isolates is poorly characterized. Here, in the study, we characterized the biochemical characteristics, and genome, pan-genome, and comparative genome analyses of an environmental isolate Enterobacter sp. S-16. The strain was identified as Enterobacter spp. by using 16S rRNA gene sequencing. To unravel genomic features, whole genome of Enterobacter sp. S-16 was sequenced using a hybrid assembly approach and genome assembly was performed using the Unicycler tool. The assembled genome contained the single conting size 5.3 Mbp, GC content 55.43%, and 4500 protein-coding genes. The genome analysis revealed the various gene clusters associated with virulence, antibiotic resistance, type VI secretion system (T6SS), and many stress tolerant genes, which may provide important insight for adapting to changing environment conditions. Moreover, different metabolic pathways were identified that potentially contribute to environmental survival. Various hydrolytic enzymes and motility functions equipped the strain S-16 as an active colonizer. The genome analysis confirms the presence of carbohydrate-active enzymes (CAZymes), and non-enzymatic carbohydrate-binding modules (CBMs) involved in the hydrolysis of complex carbohydrate polymers. Moreover, the pan-genome analysis provides detailed information about the core genes and shared genes with the closest related Enterobacter species. The present study is the first report showing the presence of YdhE/NorM in Enterobacter spp. Thus, the elucidation of genome sequencing will increase our understanding of the pathogenic nature of environmental isolate, supporting the One Health Concept.

dbCAN3: automated carbohydrate-active enzyme and substrate annotation

Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 (https://bcb.unl.edu/dbCAN2) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level; (iv) improved data browsing and visualization of substrate prediction results on the website. In summary, dbCAN3 not only inherits all the functions of dbCAN2, but also integrates three new methods for glycan substrate prediction.

Conserved unique peptide patterns (CUPP) online platform 2.0: implementation of +1000 JGI fungal genomes

Carbohydrate-processing enzymes, CAZymes, are classified into families based on sequence and three-dimensional fold. Because many CAZyme families contain members of diverse molecular function (different EC-numbers), sophisticated tools are required to further delineate these enzymes. Such delineation is provided by the peptide-based clustering method CUPP, Conserved Unique Peptide Patterns. CUPP operates synergistically with the CAZy family/subfamily categorizations to allow systematic exploration of CAZymes by defining small protein groups with shared sequence motifs. The updated CUPP library contains 21,930 of such motif groups including 3,842,628 proteins. The new implementation of the CUPP-webserver, https://cupp.info/, now includes all published fungal and algal genomes from the Joint Genome Institute (JGI), genome resources MycoCosm and PhycoCosm, dynamically subdivided into motif groups of CAZymes. This allows users to browse the JGI portals for specific predicted functions or specific protein families from genome sequences. Thus, a genome can be searched for proteins having specific characteristics. All JGI proteins have a hyperlink to a summary page which links to the predicted gene splicing including which regions have RNA support. The new CUPP implementation also includes an update of the annotation algorithm that uses only a fourth of the RAM while enabling multi-threading, providing an annotation speed below 1 ms/protein.

A subfamily classification to choreograph the diverse activities within glycoside hydrolase family 31

The Carbohydrate-Active Enzyme classification groups enzymes that breakdown, assemble, or decorate glycans into protein families based on sequence similarity. The glycoside hydrolases (GH) are arranged into over 170 enzyme families, with some being very large and exhibiting distinct activities/specificities towards diverse substrates. Family GH31 is a large family that contains more than 20,000 sequences with a wide taxonomic diversity. Less than 1% of GH31 members are biochemically characterized and exhibit many different activities that include glycosidases, lyases, and transglycosidases. This diversity of activities limits our ability to predict the activities and roles of GH31 family members in their host organism and our ability to exploit these enzymes for practical purposes. Here, we established a subfamily classification using sequence similarity networks that was further validated by a structural analysis. While sequence similarity networks provide a sequence-based separation, we obtained good segregation between activities among the subfamilies. Our subclassification consists of 20 subfamilies with sixteen subfamilies containing at least one characterized member and eleven subfamilies that are monofunctional based on the available data. We also report the biochemical characterization of a member of the large subfamily 2 (GH31_2) that lacked any characterized members: RaGH31 from Rhodoferax aquaticus is an α-glucosidase with activity on a range of disaccharides including sucrose, trehalose, maltose, and nigerose. Our subclassification provides improved predictive power for the vast majority of uncharacterized proteins in family GH31 and highlights the remaining sequence space that remains to be functionally explored.

Effects of dietary crude protein levels in the concentrate supplement after grazing on rumen microbiota and metabolites by using metagenomics and metabolomics in Jersey-yak

Introduction

The crude protein level in the diet will affect the fermentation parameters, microflora, and metabolites in the rumen of ruminants. It is of great significance to study the effect of crude protein levels in supplementary diet on microbial community and metabolites for improving animal growth performance. At present, the effects of crude protein level in supplementary diet on rumen fermentation parameters, microbial community, and metabolites of Jersey-Yak (JY) are still unclear.

Methods

The purpose of this experiment was to study the appropriate crude protein level in the diet of JY. The rumen fermentation indexes (volatile fatty acids and pH) were determined by supplementary diets with crude protein levels of 15.16 and 17.90%, respectively, and the microbial community and metabolites of JYs were analyzed by non-target metabonomics and metagenome sequencing technology, and the changes of rumen fermentation parameters, microbial flora, and metabolites in the three groups and their interactions were studied.

Results and Discussion

The crude protein level in the supplementary diet had significant effects on pH, valeric acid, and the ratio of acetic acid to propionic acid (p < 0.05). The protein level had no significant effect on the dominant microflora at the phylum level (p > 0.05), and all three groups were Bacteroides and Firmicutes. The results of metabolite analysis showed that the crude protein level of supplementary diet significantly affected the metabolic pathways such as Bile secretion and styrene degradation (p < 0.05), and there were different metabolites between the LP group and HP group, and these different metabolites were related to the dominant microbial to some extent. To sum up, in this experiment, the effects of crude protein level in supplementary diet on rumen microorganisms and metabolites of JY and their relationship were studied, which provided the theoretical basis for formulating a more scientific and reasonable supplementary diet in the future.

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Increases in snack consumption associated with Westernized lifestyles provide an opportunity to introduce nutritious foods into poor diets. We describe two 10-wk-long open label, single group assignment human studies that measured the effects of two snack prototypes containing fiber preparations from two sustainable and scalable sources; the byproducts remaining after isolation of protein from the endosperm of peas and the vesicular pulp remaining after processing oranges for the manufacture of juices. The normal diets of study participants were supplemented with either a pea- or orange fiber-containing snack. We focused our analysis on quantifying the abundances of genes encoding carbohydrate-active enzymes (CAZymes) (glycoside hydrolases and polysaccharide lyases) in the fecal microbiome, mass spectrometric measurements of glycan structures (glycosidic linkages) in feces, plus aptamer-based assessment of levels of 1,300 plasma proteins reflecting a broad range of physiological functions. Computational methods for feature selection identified treatment-discriminatory changes in CAZyme genes that correlated with alterations in levels of fiber-associated glycosidic linkages; these changes in turn correlated with levels of plasma proteins representing diverse biological functions, including transforming growth factor type β/bone morphogenetic protein-mediated fibrosis, vascular endothelial growth factor-related angiogenesis, P38/MAPK-associated immune cell signaling, and obesity-associated hormonal regulators. The approach used represents a way to connect changes in consumer microbiomes produced by specific fiber types with host responses in the context of varying background diets.

Structural basis of the strict specificity of a bacterial GH31 α-1,3-glucosidase for nigerooligosaccharides

Carbohydrate-active enzymes are involved in the degradation, biosynthesis, and modification of carbohydrates and vary with the diversity of carbohydrates. The glycoside hydrolase (GH) family 31 is one of the most diverse families of carbohydrate-active enzymes, containing various enzymes that act on α-glycosides. However, the function of some GH31 groups remains unknown, as their enzymatic activity is difficult to estimate due to the low amino acid sequence similarity between characterized and uncharacterized members. Here, we performed a phylogenetic analysis and discovered a protein cluster (GH31_u1) sharing low sequence similarity with the reported GH31 enzymes. Within this cluster, we showed that a GH31_u1 protein from Lactococcus lactis (LlGH31_u1) and its fungal homolog demonstrated hydrolytic activities against nigerose [α-D-Glcp-(1→3)-D-Glc]. The k_cat/K_m values of LlGH31_u1 against kojibiose and maltose were 13% and 2.1% of that against nigerose, indicating that LlGH31_u1 has a higher specificity to the α-1,3 linkage of nigerose than other characterized GH31 enzymes, including eukaryotic enzymes. Furthermore, the three-dimensional structures of LlGH31_u1 determined using X-ray crystallography and cryogenic electron microscopy revealed that LlGH31_u1 forms a hexamer and has a C-terminal domain comprising four α-helices, suggesting that it contributes to hexamerization. Finally, crystal structures in complex with nigerooligosaccharides and kojibiose along with mutational analysis revealed the active site residues involved in substrate recognition in this enzyme. This study reports the first structure of a bacterial GH31 α-1,3-glucosidase and provides new insight into the substrate specificity of GH31 enzymes and the physiological functions of bacterial and fungal GH31_u1 members.

Diverse events have transferred genes for edible seaweed digestion from marine to human gut bacteria

Humans harbor numerous species of colonic bacteria that digest fiber polysaccharides in commonly consumed terrestrial plants. More recently in history, regional populations have consumed edible macroalgae seaweeds containing unique polysaccharides. It remains unclear how extensively gut bacteria have adapted to digest these nutrients. Here, we show that the ability of gut bacteria to digest seaweed polysaccharides is more pervasive than previously appreciated. Enrichment-cultured Bacteroides harbor previously discovered genes for seaweed degradation, which have mobilized into several members of this genus. Additionally, other examples of marine bacteria-derived genes, and their mobile DNA elements, are involved in gut microbial degradation of seaweed polysaccharides, including genes in gut-resident Firmicutes. Collectively, these results uncover multiple separate events that have mobilized the genes encoding seaweed-degrading-enzymes into gut bacteria. This work further underscores the metabolic plasticity of the human gut microbiome and global exchange of genes in the context of dietary selective pressures.

Mechanistic insights into the digestion of complex dietary fibre by the rumen microbiota using combinatorial high-resolution glycomics and transcriptomic analyses

There is a knowledge gap regarding the factors that impede the ruminal digestion of plant cell walls or if rumen microbiota possess the functional activities to overcome these constraints. Innovative experimental methods were adopted to provide a high-resolution understanding of plant cell wall chemistries, identify higher-order structures that resist microbial digestion, and determine how they interact with the functional activities of the rumen microbiota. We characterized the total tract indigestible residue (TTIR) from cattle fed a low-quality straw diet using two comparative glycomic approaches: ELISA-based glycome profiling and total cell wall glycosidic linkage analysis. We successfully detected numerous and diverse cell wall glycan epitopes in barley straw (BS) and TTIR and determined their relative abundance pre- and post-total tract digestion. Of these, xyloglucans and heteroxylans were of higher abundance in TTIR. To determine if the rumen microbiota can further saccharify the residual plant polysaccharides within TTIR, rumen microbiota from cattle fed a diet containing BS were incubated with BS and TTIR ex vivo in batch cultures. Transcripts coding for carbohydrate-active enzymes (CAZymes) were identified and characterized for their contribution to cell wall digestion based on glycomic analyses, comparative gene expression profiles, and associated CAZyme families. High-resolution phylogenetic fingerprinting of these sequences encoded CAZymes with activities predicted to cleave the primary linkages within heteroxylan and arabinan. This experimental platform provides unprecedented precision in the understanding of forage structure and digestibility, which can be extended to other feed-host systems and inform next-generation solutions to improve the performance of ruminants fed low-quality forages.

Overview of lignocellulolytic enzyme systems with special reference to valorization of lignocellulosic biomass

Lignocellulosic biomass, one of the most valuable natural resources, is abundantly present on earth. Being a renewable feedstock, it harbors a great potential to be exploited as a raw material, to produce various value-added products. Lignocellulolytic microorganisms hold a unique position regarding the valorization of lignocellulosic biomass as they contain efficient enzyme systems capable of degrading this biomass. The ubiquitous nature of these microorganisms and their survival under extreme conditions have enabled their use as an effective producer of lignocellulolytic enzymes with improved biochemical features crucial to industrial bioconversion processes. These enzymes can prove to be an exquisite tool when it comes to the eco-friendly manufacturing of value-added products using waste material. This review focuses on highlighting the significance of lignocellulosic biomass, microbial sources of lignocellulolytic enzymes and their use in the formation of useful products.

Discovery and Development of Promiscuous O-Glycan Hydrolases for Removal of Intact Sialyl T-Antigen

Mucin-type O-glycosylation (O-glycosylation) is a common post-translational modification that confers distinct biophysical properties to proteins and plays crucial roles in intercellular signaling. Yet, despite the importance of O-glycans, relatively few tools exist for their analysis and modification. In particular, there is a need for enzymes that can cleave the wide range of O-glycan structures found on protein surfaces, to facilitate glycan profiling and editing. Through functional metagenomic screening of the human gut microbiome, we discovered endo-O-glycan hydrolases from CAZy family GH101 that are capable of slowly cleaving the intact sialyl T-antigen trisaccharide (a ubiquitous O-glycan structure in humans) in addition to their primary activity against the T-antigen disaccharide. We then further explored this sequence space through phylogenetic profiling and analysis of representative enzymes, revealing large differences in the levels of this promiscuous activity between enzymes within the family. Through structural and sequence analysis, we identified active site residues that modulate specificity. Through subsequent rational protein engineering, we improved the activity of an enzyme identified by phylogenetic profiling sufficiently that substantial removal of the intact sialyl T-antigen from proteins could be readily achieved. Our best sialyl T-antigen hydrolase mutant, SpGH101 Q868G, is further shown to function on a number of proteins, tissues, and cells. Access to this enzyme opens up improved methodologies for unraveling the glycan code.

FiberGrowth Pipeline: A Framework Toward Predicting Fiber-Specific Growth From Human Gut Bacteroidetes Genomes

Dietary fibers impact gut colonic health, through the production of short-chain fatty acids. A low-fiber diet has been linked to lower bacterial diversity, obesity, type 2 diabetes, and promotion of mucosal pathogens. Glycoside hydrolases (GHs) are important enzymes involved in the bacterial catabolism of fiber into short-chain fatty acids. However, the GH involved in glycan breakdown (adhesion, hydrolysis, and fermentation) are organized in polysaccharide utilization loci (PUL) with complex modularity. Our goal was to explore how the capacity of strains, from the Bacteroidetes phylum, to grow on fiber could be predicted from their genome sequences. We designed an in silico pipeline called FiberGrowth and independently validated it for seven different fibers, on 28 genomes from Bacteroidetes-type strains. To do so, we compared the existing GH annotation tools and built PUL models by using published growth and gene expression data. FiberGrowth's prediction performance in terms of true positive rate (TPR) and false positive rate (FPR) strongly depended on available data and fiber: arabinoxylan (TPR: 0.89 and FPR: 0), inulin (0.95 and 0.33), heparin (0.8 and 0.22) laminarin (0.38 and 0.17), levan (0.3 and 0.06), mucus (0.13 and 0.38), and starch (0.73 and 0.41). Being able to better predict fiber breakdown by bacterial strains would help to understand their impact on human nutrition and health. Assuming further gene expression experiment along with discoveries on structural analysis, we hope computational tools like FiberGrowth will help researchers prioritize and design in vitro experiments.

Recent advances in the enzymatic production and applications of xylooligosaccharides

The majority of lignocellulosic biomass on the planet originates from plant cell walls, which are complex structures build up mainly by cellulose, hemicellulose and lignin. The largest part of hemicellulose, xylan, is a polymer with a β-(1→4)-linked xylose residues backbone decorated with α-D-glucopyranosyl uronic acids and/or L-arabinofuranose residues. Xylan is the second most abundant biopolymer in nature, which can be sustainably and efficiently degraded into decorated and undecorated xylooligosaccharides (XOS) using combinations of thermochemical pretreatments and enzymatic hydrolyses, that have broad applications in the food, feed, pharmaceutical and cosmetic industries. Endo-xylanases from different complex carbohydrate-active enzyme (CAZyme) families can be used to cleave the backbone of arabino(glucurono)xylans and xylooligosaccharides and degrade them into short XOS. It has been shown that XOS with a low degree of polymerization have enhanced prebiotic effects conferring health benefits to humans and animals. In this review we describe recent advances in the enzymatic production of XOS from lignocellulosic biomass arabino- and glucuronoxylans and their applications as food and feed additives and health-promoting ingredients. Comparative advantages of xylanases from different CAZy families in XOS production are discussed and potential health benefits of different XOS are presented.

Phylogenetic, functional and structural characterization of a GH10 xylanase active at extreme conditions of temperature and alkalinity

Endoxylanases active under extreme conditions of temperature and alkalinity can replace the use of highly pollutant chemicals in the pulp and paper industry. Searching for enzymes with these properties, we carried out a comprehensive bioinformatics study of the GH10 family. The phylogenetic analysis allowed the construction of a radial cladogram in which protein sequences putatively ascribed as thermophilic and alkaliphilic appeared grouped in a well-defined region of the cladogram, designated TAK Cluster. One among five TAK sequences selected for experimental analysis (Xyn11) showed extraordinary xylanolytic activity under simultaneous conditions of high temperature (90 °C) and alkalinity (pH 10.5). Addition of a carbohydrate binding domain (CBM2) at the C-terminus of the protein sequence further improved the activity of the enzyme at high pH. Xyn11 structure, which has been solved at 1.8 Å resolution by X-ray crystallography, reveals an unusually high number of hydrophobic, ionic and hydrogen bond atomic interactions that could account for the enzyme’s extremophilic nature.

New Method for Identifying Fungal Kingdom Enzyme Hotspots from Genome Sequences

Fungal genome sequencing data represent an enormous pool of information for enzyme discovery. Here, we report a new approach to identify and quantitatively compare biomass-degrading capacity and diversity of fungal genomes via integrated function-family annotation of carbohydrate-active enzymes (CAZymes) encoded by the genomes. Based on analyses of 1932 fungal genomes the most potent hotspots of fungal biomass processing CAZymes are identified and ranked according to substrate degradation capacity. The analysis is achieved by a new bioinformatics approach, Conserved Unique Peptide Patterns (CUPP), providing for CAZyme-family annotation and robust prediction of molecular function followed by conversion of the CUPP output to lists of integrated “Function;Family” (e.g., EC 3.2.1.4;GH5) enzyme observations. An EC-function found in several protein families counts as different observations. Summing up such observations allows for ranking of all analyzed genome sequenced fungal species according to richness in CAZyme function diversity and degrading capacity. Identifying fungal CAZyme hotspots provides for identification of fungal species richest in cellulolytic, xylanolytic, pectinolytic, and lignin modifying enzymes. The fungal enzyme hotspots are found in fungi having very different lifestyle, ecology, physiology and substrate/host affinity. Surprisingly, most CAZyme hotspots are found in enzymatically understudied and unexploited species. In contrast, the most well-known fungal enzyme producers, from where many industrially exploited enzymes are derived, are ranking unexpectedly low. The results contribute to elucidating the evolution of fungal substrate-digestive CAZyme profiles, ecophysiology, and habitat adaptations, and expand the knowledge base for novel and improved biomass resource utilization.

Predicted Input of Uncultured Fungal Symbionts to a Lichen Symbiosis from Metagenome-Assembled Genomes

Basidiomycete yeasts have recently been reported as stably associated secondary fungal symbionts of many lichens, but their role in the symbiosis remains unknown. Attempts to sequence their genomes have been hampered both by the inability to culture them and their low abundance in the lichen thallus alongside two dominant eukaryotes (an ascomycete fungus and chlorophyte alga). Using the lichen Alectoria sarmentosa, we selectively dissolved the cortex layer in which secondary fungal symbionts are embedded to enrich yeast cell abundance and sequenced DNA from the resulting slurries as well as bulk lichen thallus. In addition to yielding a near-complete genome of the filamentous ascomycete using both methods, metagenomes from cortex slurries yielded a 36- to 84-fold increase in coverage and near-complete genomes for two basidiomycete species, members of the classes Cystobasidiomycetes and Tremellomycetes. The ascomycete possesses the largest gene repertoire of the three. It is enriched in proteases often associated with pathogenicity and harbors the majority of predicted secondary metabolite clusters. The basidiomycete genomes possess ∼35% fewer predicted genes than the ascomycete and have reduced secretomes even compared with close relatives, while exhibiting signs of nutrient limitation and scavenging. Furthermore, both basidiomycetes are enriched in genes coding for enzymes producing secreted acidic polysaccharides, representing a potential contribution to the shared extracellular matrix. All three fungi retain genes involved in dimorphic switching, despite the ascomycete not being known to possess a yeast stage. The basidiomycete genomes are an important new resource for exploration of lifestyle and function in fungal–fungal interactions in lichen symbioses.

Approaches to Investigate Selective Dietary Polysaccharide Utilization by Human Gut Microbiota at a Functional Level

The human diet is temporally and spatially dynamic, and influenced by culture, regional food systems, socioeconomics, and consumer preference. Such factors result in enormous structural diversity of ingested glycans that are refractory to digestion by human enzymes. To convert these glycans into metabolizable nutrients and energy, humans rely upon the catalytic potential encoded within the gut microbiome, a rich collective of microorganisms residing in the gastrointestinal tract. The development of high-throughput sequencing methods has enabled microbial communities to be studied with more coverage and depth, and as a result, cataloging the taxonomic structure of the gut microbiome has become routine. Efforts to unravel the microbial processes governing glycan digestion by the gut microbiome, however, are still in their infancy and will benefit by retooling our approaches to study glycan structure at high resolution and adopting next-generation functional methods. Also, new bioinformatic tools specialized for annotating carbohydrate-active enzymes and predicting their functions with high accuracy will be required for deciphering the catalytic potential of sequence datasets. Furthermore, physiological approaches to enable genotype-phenotype assignments within the gut microbiome, such as fluorescent polysaccharides, has enabled rapid identification of carbohydrate interactions at the single cell level. In this review, we summarize the current state-of-knowledge of these methods and discuss how their continued development will advance our understanding of gut microbiome function.

Quantifying fluorescent glycan uptake to elucidate strain-level variability in foraging behaviors of rumen bacteria

Gut microbiomes, such as the microbial community that colonizes the rumen, have vast catabolic potential and play a vital role in host health and nutrition. By expanding our understanding of metabolic pathways in these ecosystems, we will garner foundational information for manipulating microbiome structure and function to influence host physiology. Currently, our knowledge of metabolic pathways relies heavily on inferences derived from metagenomics or culturing bacteria in vitro. However, novel approaches targeting specific cell physiologies can illuminate the functional potential encoded within microbial (meta)genomes to provide accurate assessments of metabolic abilities. Using fluorescently labeled polysaccharides, we visualized carbohydrate metabolism performed by single bacterial cells in a complex rumen sample, enabling a rapid assessment of their metabolic phenotype. Specifically, we identified bovine-adapted strains of Bacteroides thetaiotaomicron that metabolized yeast mannan in the rumen microbiome ex vivo and discerned the mechanistic differences between two distinct carbohydrate foraging behaviors, referred to as "medium grower" and "high grower." Using comparative whole-genome sequencing, RNA-seq, and carbohydrate-active enzyme fingerprinting, we could elucidate the strain-level variability in carbohydrate utilization systems of the two foraging behaviors to help predict individual strategies of nutrient acquisition. Here, we present a multi-faceted study using complimentary next-generation physiology and "omics" approaches to characterize microbial adaptation to a prebiotic in the rumen ecosystem. Video abstract.

Combined whole cell wall analysis and streamlined in silico carbohydrate-active enzyme discovery to improve biocatalytic conversion of agricultural crop residues

The production of biofuels as an efficient source of renewable energy has received considerable attention due to increasing energy demands and regulatory incentives to reduce greenhouse gas emissions. Second-generation biofuel feedstocks, including agricultural crop residues generated on-farm during annual harvests, are abundant, inexpensive, and sustainable. Unlike first-generation feedstocks, which are enriched in easily fermentable carbohydrates, crop residue cell walls are highly resistant to saccharification, fermentation, and valorization. Crop residues contain recalcitrant polysaccharides, including cellulose, hemicelluloses, pectins, and lignin and lignin-carbohydrate complexes. In addition, their cell walls can vary in linkage structure and monosaccharide composition between plant sources. Characterization of total cell wall structure, including high-resolution analyses of saccharide composition, linkage, and complex structures using chromatography-based methods, nuclear magnetic resonance, -omics, and antibody glycome profiling, provides critical insight into the fine chemistry of feedstock cell walls. Furthermore, improving both the catalytic potential of microbial communities that populate biodigester reactors and the efficiency of pre-treatments used in bioethanol production may improve bioconversion rates and yields. Toward this end, knowledge and characterization of carbohydrate-active enzymes (CAZymes) involved in dynamic biomass deconstruction is pivotal. Here we overview the use of common "-omics"-based methods for the study of lignocellulose-metabolizing communities and microorganisms, as well as methods for annotation and discovery of CAZymes, and accurate prediction of CAZyme function. Emerging approaches for analysis of large datasets, including metagenome-assembled genomes, are also discussed. Using complementary glycomic and meta-omic methods to characterize agricultural residues and the microbial communities that digest them provides promising streams of research to maximize value and energy extraction from crop waste streams.

In silico screening and experimental analysis of family GH11 xylanases for applications under conditions of alkaline pH and high temperature

BACKGROUND

Xylanases are one of the most extensively used enzymes for biomass digestion. However, in many instances, their use is limited by poor performance under the conditions of pH and temperature required by the industry. Therefore, the search for xylanases able to function efficiently at alkaline pH and high temperature is an important objective for different processes that use lignocellulosic substrates, such as the production of paper pulp and biofuels.

RESULTS

A comprehensive in silico analysis of family GH11 sequences from the CAZY database allowed their phylogenetic classification in a radial cladogram in which sequences of known or presumptive thermophilic and alkalophilic xylanases appeared in three clusters. Eight sequences from these clusters were selected for experimental analysis. The coding DNA was synthesized, cloned and the enzymes were produced in E. coli. Some of these showed high xylanolytic activity at pH values > 8.0 and temperature > 80 °C. The best enzymes corresponding to sequences from Dictyoglomus thermophilum (Xyn5) and Thermobifida fusca (Xyn8). The addition of a carbohydrate-binding module (CBM9) to Xyn5 increased 4 times its activity at 90 °C and pH > 9.0. The combination of Xyn5 and Xyn8 was proved to be efficient for the saccharification of alkali pretreated rice straw, yielding xylose and xylooligosaccharides.

CONCLUSIONS

This study provides a fruitful approach for the selection of enzymes with suitable properties from the information contained in extensive databases. We have characterized two xylanases able to hydrolyze xylan with high efficiency at pH > 8.0 and temperature > 80 °C.

Combinatorial Glycomic Analyses to Direct CAZyme Discovery for the Tailored Degradation of Canola Meal Non-Starch Dietary Polysaccharides

Canola meal (CM), the protein-rich by-product of canola oil extraction, has shown promise as an alternative feedstuff and protein supplement in poultry diets, yet its use has been limited due to the abundance of plant cell wall fibre, specifically non-starch polysaccharides (NSP) and lignin. The addition of exogenous enzymes to promote the digestion of CM NSP in chickens has potential to increase the metabolizable energy of CM. We isolated chicken cecal bacteria from a continuous-flow mini-bioreactor system and selected for those with the ability to metabolize CM NSP. Of 100 isolates identified, Bacteroides spp. and Enterococcus spp. were the most common species with these capabilities. To identify enzymes specifically for the digestion of CM NSP, we used a combination of glycomics techniques, including enzyme-linked immunosorbent assay characterization of the plant cell wall fractions, glycosidic linkage analysis (methylation-GC-MS analysis) of CM NSP and their fractions, bacterial growth profiles using minimal media supplemented with CM NSP, and the sequencing and de novo annotation of bacterial genomes of high-efficiency CM NSP utilizing bacteria. The SACCHARIS pipeline was used to select plant cell wall active enzymes for recombinant production and characterization. This approach represents a multidisciplinary innovation platform to bioprospect endogenous CAZymes from the intestinal microbiota of herbivorous and omnivorous animals which is adaptable to a variety of applications and dietary polysaccharides.

Conserved unique peptide patterns (CUPP) online platform: peptide-based functional annotation of carbohydrate active enzymes

The CUPP platform includes a web server for functional annotation and sub-grouping of carbohydrate active enzymes (CAZymes) based on a novel peptide-based similarity assessment algorithm, i.e. protein grouping according to Conserved Unique Peptide Patterns (CUPP). This online platform is open to all users and there is no login requirement. The web server allows the user to perform genome-based annotation of carbohydrate active enzymes to CAZy families, CAZy subfamilies, CUPP groups and EC numbers (function) via assessment of peptide-motifs by CUPP. The web server is intended for functional annotation assessment of the CAZy inventory of prokaryotic and eukaryotic organisms from genomic DNA (up to 30MB compressed) or directly from amino acid sequences (up to 10MB compressed). The custom query sequences are assessed using the CUPP annotation algorithm, and the outcome is displayed in interactive summary result pages of CAZymes. The results displayed allow for inspection of members of the individual CUPP groups and include information about experimentally characterized members. The web server and the other resources on the CUPP platform can be accessed from https://cupp.info.

eCAMI: simultaneous classification and motif identification for enzyme annotation

MOTIVATION

Carbohydrate-active enzymes (CAZymes) are extremely important to bioenergy, human gut microbiome, and plant pathogen researches and industries. Here we developed a new amino acid k-mer-based CAZyme classification, motif identification and genome annotation tool using a bipartite network algorithm. Using this tool, we classified 390 CAZyme families into thousands of subfamilies each with distinguishing k-mer peptides. These k-mers represented the characteristic motifs (in the form of a collection of conserved short peptides) of each subfamily, and thus were further used to annotate new genomes for CAZymes. This idea was also generalized to extract characteristic k-mer peptides for all the Swiss-Prot enzymes classified by the EC (enzyme commission) numbers and applied to enzyme EC prediction.

RESULTS

This new tool was implemented as a Python package named eCAMI. Benchmark analysis of eCAMI against the state-of-the-art tools on CAZyme and enzyme EC datasets found that: (i) eCAMI has the best performance in terms of accuracy and memory use for CAZyme and enzyme EC classification and annotation; (ii) the k-mer-based tools (including PPR-Hotpep, CUPP and eCAMI) perform better than homology-based tools and deep-learning tools in enzyme EC prediction. Lastly, we confirmed that the k-mer-based tools have the unique ability to identify the characteristic k-mer peptides in the predicted enzymes.

AVAILABILITY AND IMPLEMENTATION

https://github.com/yinlabniu/eCAMI and https://github.com/zhanglabNKU/eCAMI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Insights into Metatranscriptome, and CAZymes of Buffalo Rumen Supplemented with Blend of Essential Oils

The aim of this study was to investigate the rumen microbial diversity and functionality in buffaloes fed with a blend of essential oils (BEO) using LSD switch over design. The BEO consisting of blend of Trachyspermum copticum (Ajwain) oil, Cymbopogon citratus (lemon grass) oil and Syzygium aromaticum (clove bud) oleoresin mixed in equal proportion, was fed at the rate of 0, 0.75 and 1.5 ml/100 kg of body weight in 0 (control), 0.75 and 1.5 groups, respectively. The metatranscriptomic libraries of the rumen microbiome were represented by 7 domains, 84 phyla, 64 archeal genera and 663 bacterial genera with Bacteroidetes and Firmicutes constituting 80% of phyla abundance irrespective of feeding regime. Methanogenic archaea was represented by 22 phyla with Methanobrevibacter as the major genus. BEO feeding reduced the abundance of Methanococcus and Thermoplasma (P < 0.05) at all levels. The results revealed that the feeding of BEO shifted the archeal and bacterial population at very low magnitude. The study explored the vast diversity of buffalo rumen bacteria and archaea, and the diverse wealth of rumen enzymes (CAZymes), which revealed that a major part of CAZymes comes from the less known rumen microbes indicating alternative paths of fiber degradation along with the very well known ones.

Metagenomic Analyses of Microbial and Carbohydrate-Active Enzymes in the Rumen of Dairy Goats Fed Different Rumen Degradable Starch

The objective of this study was to investigate the effects of different dietary rumen degradable starch (RDS) on the diversity of carbohydrate-active enzymes (CAZymes) and Kyoto Encyclopedia of Genes and Genomes Orthology functional categories to explore carbohydrate degradation in dairy goats. Eighteen dairy goats (second lactation, 45.8 ± 1.54 kg) were divided in three groups fed low RDS (LRDS), medium RDS (MRDS), and high RDS (HRDS) diets. The results showed that, HRDS treatment group significantly decreased the ruminal pH (P < 0.05), and increased the propionate proportion (P < 0.05), fumarate and succinate concentrations (P < 0.05), trended to increase lactate concentration (P = 0.50) compared with LRDS group. The relative abundance of acetogens, such as family Clostridiaceae and Ruminococcaceae, genera Clostridium and Blautia were higher in HRDS than LRDS feeding goats. The GH9 family (responsible for cellulose degradation) genes were lower in HRDS than MRDS diet samples, and mainly produced by Prevotellaceae, Ruminococcaceae, and Bacteroidaceae. Amylose (EC3.2.1.3) genes under HRDS treatment were more abundant than under LRDS treatment. However, the abundance of GH13_9 and CBM48 (responsible for starch degradation) were reduced in HRDS group indicating the decreased binding activity from catalytic modules to starch. This study revealed that HRDS-fed dairy goats had decreased CAZymes, which encode enzymes degrade cellulose and starch in the dairy goats.

Fungal secretome profile categorization of CAZymes by function and family corresponds to fungal phylogeny and taxonomy: Example Aspergillus and Penicillium

Fungi secrete an array of carbohydrate-active enzymes (CAZymes), reflecting their specialized habitat-related substrate utilization. Despite its importance for fitness, enzyme secretome composition is not used in fungal classification, since an overarching relationship between CAZyme profiles and fungal phylogeny/taxonomy has not been established. For 465 Ascomycota and Basidiomycota genomes, we predicted CAZyme-secretomes, using a new peptide-based annotation method, Conserved-Unique-Peptide-Patterns, enabling functional prediction directly from sequence. We categorized each enzyme according to CAZy-family and predicted molecular function, hereby obtaining a list of "EC-Function;CAZy-Family" observations. These "Function;Family"-based secretome profiles were compared, using a Yule-dissimilarity scoring algorithm, giving equal consideration to the presence and absence of individual observations. Assessment of "Function;Family" enzyme profile relatedness (EPR) across 465 genomes partitioned Ascomycota from Basidiomycota placing Aspergillus and Penicillium among the Ascomycota. Analogously, we calculated CAZyme "Function;Family" profile-similarities among 95 Aspergillus and Penicillium species to form an alignment-free, EPR-based dendrogram. This revealed a stunning congruence between EPR categorization and phylogenetic/taxonomic grouping of the Aspergilli and Penicillia. Our analysis suggests EPR grouping of fungi to be defined both by "shared presence" and "shared absence" of CAZyme "Function;Family" observations. This finding indicates that CAZymes-secretome evolution is an integral part of fungal speciation, supporting integration of cladogenesis and anagenesis.

Analysis of Active Site Architecture and Reaction Product Linkage Chemistry Reveals a Conserved Cleavage Substrate for an Endo-alpha-mannanase within Diverse Yeast Mannans

Yeast α-mannan (YM) is a densely branched N-linked glycan that decorates the surface of yeast cell walls. Owing to the high degree of branching, cleavage of the backbone of YM appears to rely on the coupled action of side-chain-cleaving enzymes. Upon examining the genome sequences of bovine-adapted Bacteroides thetaiotaomicron strains, isolated for their ability to degrade YM, we have identified a tandem pair of genes inserted into an orphan pathway predicted to be involved in YM metabolism. Here, we investigated the activity of one of these enzymes, a predicted endo-mannanase from glycoside hydrolase (GH) family 76 (BtGH76-MD40). Purified recombinant BtGH76-MD40 displayed activity on structurally distinct YMs from Saccharomyces cerevisiae and Schizosaccharomyces pombe. Linkage analysis of released oligosaccharide products from S. cerevisiae and S. pombe mannan determined BtGH76-MD40 targets a specific linkage that is conserved in structurally diverse YM substrates. In addition, using two differential derivatization methods, we have shown that there is an absolute requirement for undecorated d-mannopyranose in the -1 subsite. Determination of the BtGH76-MD40 X-ray crystal structure and structural superimposition and molecular docking of a branched alpha-mannopentatose substrate supported these findings. In contrast, BtGH76-MD40 can accommodate extended side chains in the +1 and -2 subsites, highlighting that a single alpha-1,6-mannosyl residue is a prerequisite for activity, and cleavage occurs at the reducing end of the undecorated monosaccharide. Collectively these results demonstrate how acquisition of new enzymes within extant pathways contributes to the functional abilities of saccharolytic bacteria persisting in complex digestive ecosystems.

Prospecting for microbial α-N-acetylgalactosaminidases yields a new class of GH31 O-glycanase

α-Linked GalNAc (α-GalNAc) is most notably found at the nonreducing terminus of the blood type-determining A-antigen and as the initial point of attachment to the peptide backbone in mucin-type O-glycans. However, despite their ubiquity in saccharolytic microbe-rich environments such as the human gut, relatively few α-N-acetylgalactosaminidases are known. Here, to discover and characterize novel microbial enzymes that hydrolyze α-GalNAc, we screened small-insert libraries containing metagenomic DNA from the human gut microbiome. Using a simple fluorogenic glycoside substrate, we identified and characterized a glycoside hydrolase 109 (GH109) that is active on blood type A-antigen, along with a new subfamily of glycoside hydrolase 31 (GH31) that specifically cleaves the initial α-GalNAc from mucin-type O-glycans. This represents a new activity in this GH family and a potentially useful new enzyme class for analysis or modification of O-glycans on protein or cell surfaces.

Enzymes of early-diverging, zoosporic fungi

The secretome, the complement of extracellular proteins, is a reflection of the interaction of an organism with its host or substrate, thus a determining factor for the organism’s fitness and competitiveness. Hence, the secretome impacts speciation and organismal evolution. The zoosporic Chytridiomycota, Blastocladiomycota, Neocallimastigomycota, and Cryptomycota represent the earliest diverging lineages of the Fungal Kingdom. The review describes the enzyme compositions of these zoosporic fungi, underscoring the enzymes involved in biomass degradation. The review connects the lifestyle and substrate affinities of the zoosporic fungi to the secretome composition by examining both classical phenotypic investigations and molecular/genomic-based studies. The carbohydrate-active enzyme profiles of 19 genome-sequenced species are summarized. Emphasis is given to recent advances in understanding the functional role of rumen fungi, the basis for the devastating chytridiomycosis, and the structure of fungal cellulosome. The approach taken by the review enables comparison of the secretome enzyme composition of anaerobic versus aerobic early-diverging fungi and comparison of enzyme portfolio of specialized parasites, pathogens, and saprotrophs. Early-diverging fungi digest most major types of biopolymers: cellulose, hemicellulose, pectin, chitin, and keratin. It is thus to be expected that early-diverging fungi in its entirety represents a rich and diverse pool of secreted, metabolic enzymes. The review presents the methods used for enzyme discovery, the diversity of enzymes found, the status and outlook for recombinant production, and the potential for applications. Comparative studies on the composition of secretome enzymes of early-diverging fungi would contribute to unraveling the basal lineages of fungi.

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

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.

Metagenomic Analyses of Microbial and Carbohydrate-Active Enzymes in the Rumen of Holstein Cows Fed Different Forage-to-Concentrate Ratios

The objectives of this study were to investigate the effects of different forage-to-concentrate ratios and sampling times on the genetic diversity of carbohydrate-active enzymes (CAZymes) and the taxonomic profile of rumen microbial communities in dairy cows. Six ruminally cannulated Holstein cows were arbitrarily divided into groups fed high-forage (HF) or low-forage (LF) diets. The results showed that, for glycoside hydrolase (GH) families, there were greater differences based on dietary forage-to-concentrate ratio than sampling time. The HF treatment group at 4 h after feeding (AF4h) had the most microbial diversity. Genes that encode GHs had the highest number of CAZymes, and accounted for 57.33% and 56.48% of all CAZymes in the HF and LF treatments, respectively. The majority of GH family genes encode oligosaccharide-degrading enzymes, and GH2, GH3, and GH43 were synthesized by a variety of different genera. Notably, we found that GH3 was higher in HF than LF diet samples, and mainly produced by Prevotella, Bacteroides, and unclassified reads. Most predicted cellulase enzymes were encoded by GH5 (the BF0h group under HF treatment was highest) and GH95 (the BF0h group under LF treatment was highest), and were primarily derived from Bacteroides, Butyrivibrio, and Fibrobacter. Approximately 67.5% (GH28) and 65.5% (GH53) of the putative hemicellulases in LF and HF treatments, respectively. GH28 under LF treatment was more abundant than under HF treatment, and was mainly produced by Ruminococcus, Prevotella, and Bacteroides. This study revealed that HF-fed cows had increased microbial diversity of CAZyme producers, which encode enzymes that efficiently degrade plant cell wall polysaccharides in the cow rumen.

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

Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2 (http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme sequence database and (iii) Hotpep search against the conserved CAZyme short peptide database. Combining the three outputs and removing CAZymes found by only one tool can significantly improve the CAZome annotation accuracy. In addition, dbCAN2 now also accepts nucleotide sequence submission, and offers the service to predict physically linked CAZyme gene clusters (CGCs), which will be a very useful online tool for identifying putative polysaccharide utilization loci (PULs) in microbial genomes or metagenomes.

Identification of novel enzymes to enhance the ruminal digestion of barley straw

Crude enzyme extracts typically contain a broad spectrum of enzyme activities, most of which are redundant to those naturally produced by the rumen microbiome. Identification of enzyme activities that are synergistic to those produced by the rumen microbiome could enable formulation of enzyme cocktails that improve fiber digestion in ruminants. Compared to untreated barley straw, Viscozyme® increased gas production, dry matter digestion (P < 0.01) and volatile fatty acid production (P < 0.001) in ruminal batch cultures. Fractionation of Viscozyme® by Blue Native PAGE and analyses using a microassay and mass-spectrometry revealed a GH74 endoglucanase, GH71 α-1,3-glucanase, GH5 mannanase, GH7 cellobiohydrolase, GH28 pectinase, and esterases from Viscozyme® contributed to enhanced saccharification of barley straw by rumen mix enzymes. Grouping of these identified activities with their carbohydrate active enzymes (CAZy) counterparts enabled selection of similar CAZymes for downstream production and screening. Mining of these specific activities from other biological systems could lead to high value enzyme formulations for ruminants.