This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Across many environments microbial glycoside hydrolases support the enzymatic processing of carbohydrates, a critical function in many ecosystems. Little is known about how the microbial composition of a community and the potential for carbohydrate processing relate to each other. Here, using 1,934 metagenomic datasets, we linked changes in community composition to variation of potential for carbohydrate processing across environments. We were able to show that each ecosystem-type displays a specific potential for carbohydrate utilization. Most of this potential was associated with just 77 bacterial genera. The GH content in bacterial genera is best described by their taxonomic affiliation. Across metagenomes, fluctuations of the microbial community structure and GH potential for carbohydrate utilization were correlated. Our analysis reveals that both deterministic and stochastic processes contribute to the assembly of complex microbial communities.
Fungi produce a wide range of extracellular enzymes to break down plant cell walls, which are composed mainly of cellulose, lignin and hemicellulose. Among them are the glycoside hydrolases (GH), the largest and most diverse family of enzymes active on these substrates. To facilitate research and development of enzymes for the conversion of cell-wall polysaccharides into fermentable sugars, we have manually curated a comprehensive set of characterized fungal glycoside hydrolases. Characterized glycoside hydrolases were retrieved from protein and enzyme databases, as well as literature repositories. A total of 453 characterized glycoside hydrolases have been cataloged. They come from 131 different fungal species, most of which belong to the phylum Ascomycota. These enzymes represent 46 different GH activities and cover 44 of the 115 CAZy GH families. In addition to enzyme source and enzyme family, available biochemical properties such as temperature and pH optima, specific activity, kinetic parameters and substrate specificities were recorded. To simplify comparative studies, enzyme and species abbreviations have been standardized, Gene Ontology terms assigned and reference to supporting evidence provided. The annotated genes have been organized in a searchable, online database called mycoCLAP (Characterized Lignocellulose-Active Proteins of fungal origin). It is anticipated that this manually curated collection of biochemically characterized fungal proteins will be used to enhance functional annotation of novel GH genes. Database URL: http://mycoCLAP.fungalgenomics.ca/.
Chronic wounds will impact 2% of the United States population at some point in their life. These wounds are often associated with a reoccurring, chronic infection caused by a community of microorganisms encased in an extracellular polymeric substance (EPS), or a biofilm. Biofilm-associated microbes can exhibit tolerance to antibiotics, which has prompted researchers to investigate therapeutics that improve antibiotic efficacy. Glycoside hydrolases (GHs), enzymes that target the polysaccharide linkages within the EPS, are one potential adjunctive therapy. In order to develop GH-based therapeutics, it is imperative that we understand whether the composition of biofilm EPS changes based on the environment and/or presence of other microbes. Here, we utilized α-amylase and cellulase to target the polysaccharides within the EPS of mono- and dual-species Pseudomonas aeruginosa and Staphylococcus aureus biofilms in three different models that vary in clinical relevancy. We show that biofilms established in an in vitro well-plate model are not strongly adhered to the polystyrene surface and do not accurately reflect the GH efficacy seen with biofilms grown in vivo. However, dispersal efficacy in an in vitro wound microcosm model was more reflective of that seen in a murine wound model. We also saw a striking loss of efficacy for cellulase to disperse S. aureus in both mono- and dual species biofilms grown in the wound models, suggesting that EPS constituents may be altered depending on the environment.
Processive and distributive catalysis defines the conversion continuum, thus underpinning the transformation of oligo- and polymeric substrates by enzymes. Distributive catalysis follows an association-transformation-dissociation pattern during the formation of enzyme-reactant complexes, whereas during processive catalysis, enzymes partner with substrates and complete multiple catalytic events before dissociation from an enzyme-substrate complex. Here, we focus on processive catalysis in glycoside hydrolases (GHs), which ensures efficient conversions of substrates with high precision, and has the advantage over distributive catalysis in efficiency. The work presented here examines a recent discovery of substrate-product-assisted processive catalysis in the GH3 family enzymes with enclosed pocket-shaped active sites. We detail how GH3 β-d-glucan glucohydrolases exploit a transiently formed lateral pocket for product displacement and reactants sliding (or translocation motion) through the catalytic site without dissociation, including movements during nanoscale binding/unbinding and sliding. The phylogenetic tree of putative 550 Archaean, bacterial, fungal, Viridiplantae, and Metazoan GH3 entries resolved seven lineages that corresponded to major substrate specificity groups. This analysis indicates that two tryptophan residues in plant β-d-glucan glucohydrolases that delineate the catalytic pocket, and infer broad specificity, high catalytic efficiency, and substrate-product-assisted processivity, have evolved through a complex evolutionary process, including horizontal transfer and neo-functionalisation. We conclude that the definition of thermodynamic and mechano-structural properties of processive enzymes is fundamentally important for theoretical and practical applications in bioengineering applicable in various biotechnologies.
The identification of glycoside hydrolases (GHs) for efficient polysaccharide deconstruction is essential for the development of biofuels. Here, we investigate the potential of sequential HMM-profile identification for the rapid and precise identification of the multi-domain architecture of GHs from various datasets. First, as a validation, we successfully reannotated >98% of the biochemically characterized enzymes listed on the CAZy database. Next, we analyzed the 43 million non-redundant sequences from the M5nr data and identified 322,068 unique GHs. Finally, we searched 129 assembled metagenomes retrieved from MG-RAST for environmental GHs and identified 160,790 additional enzymes. Although most identified sequences corresponded to single domain enzymes, many contained several domains, including known accessory domains and some domains never identified in association with GH. Several sequences displayed multiple catalytic domains and few of these potential multi-activity proteins combined potentially synergistic domains. Finally, we produced and confirmed the biochemical activities of a GH5-GH10 cellulase-xylanase and a GH11-CE4 xylanase-esterase. Globally, this "gene to enzyme pipeline" provides a rationale for mining large datasets in order to identify new catalysts combining unique properties for the efficient deconstruction of polysaccharides.
To efficiently deconstruct recalcitrant plant biomass to fermentable sugars in industrial processes, biocatalysts of higher performance and lower cost are required. The genetic diversity found in the metagenomes of natural microbial biomass decay communities may harbor such enzymes. Our goal was to discover and characterize new glycoside hydrolases (GHases) from microbial biomass decay communities, especially those from unknown or never previously cultivated microorganisms.
The abundance and the diversity of oligo- and polysaccharides provide a wide range of biological roles attributed either to these carbohydrates or to their relevant enzymes, i.e., the glycoside hydrolases (GHs). The biocatalysis by these families of enzymes is highly attractive for the generation of products used in potential applications, e.g., pharmaceuticals and food industries. It is thus very important to extract and characterize such enzymes, particularly from plant tissues. In this study, we characterized novel sequences of class I chitinases from seedlings extract of the common oat (Avena sativa L.) using proteomics and sequence-structure-function analysis. These enzymes, which belong to the GH19 family of protein, were extracted from oat and identified using SDS-PAGE, trypsin digestion, LC-MS-MS, and sequence-structure-function analysis. The amino acid sequences of the oat tryptic peptides were used to identify cDNAs from the Avena sativa databases of the expressed sequence tags (ESTs) and transcriptome shotgun assembly (TSA). Based upon the Avena sativa sequences of ESTs and TSA, at least 4 predicted genes that encoded oat class I chitinases were identified and reported. The structural characterization of the oat sequences of chitinases provided valuable insights to the context.
Chitosanases, enzymes that catalyze the endo-hydrolysis of glycolytic links in chitosan, are the subject of numerous studies as biotechnological tools to generate low molecular weight chitosan (LMWC) or chitosan oligosaccharides (CHOS) from native, high molecular weight chitosan. Glycoside hydrolases belonging to family GH46 are among the best-studied chitosanases, with four crystallography-derived structures available and more than forty enzymes studied at the biochemical level. They were also subjected to numerous site-directed mutagenesis studies, unraveling the molecular mechanisms of hydrolysis. This review is focused on the taxonomic distribution of GH46 proteins, their multi-modular character, the structure-function relationships and their biological functions in the host organisms.
Microorganisms constitute a reservoir of enzymes involved in environmental carbon cycling and degradation of plant polysaccharides through their production of a vast variety of Glycoside Hydrolases (GH). The CAZyChip was developed to allow a rapid characterization at transcriptomic level of these GHs and to identify enzymes acting on hydrolysis of polysaccharides or glycans.
Phytopathogenic fungi need to secrete different hydrolytic enzymes to break down complex polysaccharides in the plant cell wall in order to enter the host and develop the disease. Fungi produce various types of cell wall degrading enzymes (CWDEs) during infection. Most of the characterized CWDEs belong to glycoside hydrolases (GHs). These enzymes hydrolyze glycosidic bonds and have been identified in many fungal species sequenced to date. Many studies have shown that CWDEs belong to several GH families and play significant roles in the invasion and pathogenicity of fungi and oomycetes during infection on the plant host, but their mode of function in virulence is not yet fully understood. Moreover, some of the CWDEs that belong to different GH families act as pathogen-associated molecular patterns (PAMPs), which trigger plant immune responses. In this review, we summarize the most important GHs that have been described in eukaryotic phytopathogens and are involved in the establishment of a successful infection.
Novel anti-biofilm and dispersal agents are currently being investigated in an attempt to combat biofilm-associated wound infections. Glycoside hydrolases (GHs) are enzymes that hydrolyze the glycosidic bonds between sugars, such as those found within the exopolysaccharides of the biofilm matrix. Previous studies have shown that GHs can weaken the matrix, inducing bacterial dispersal, and improving antibiotic clearance. Yet, the number of GH enzymes that have been examined for potential therapeutic effects is limited. In this study, we screened sixteen GHs for their ability to disperse mono-microbial and polymicrobial biofilms grown in different environments. Six GHs, α-amylase (source: A. oryzae), alginate lyase (source: various algae), pectinase (source: Rhizopus sp.), amyloglucosidase (source: A. niger), inulinase (source: A. niger), and xylanase (source: A. oryzae), exhibited the highest dispersal efficacy in vitro. Two GHs, α-amylase (source: Bacillus sp.) and cellulase (source: A. niger), used in conjunction with meropenem demonstrated infection clearing ability in a mouse wound model. GHs were also effective in improving antibiotic clearance in diabetic mice. To examine their safety, we screened the GHs for toxicity in cell culture. Overall, there was an inverse relationship between enzyme exposure time and cellular toxicity, with twelve out of sixteen GHs demonstrating some level of toxicity in cell culture. However, only one GH exhibited harmful effects in mice. These results further support the ability of GHs to improve antibiotic clearance of biofilm-associated infections and help lay a foundation for establishing GHs as therapeutic agents for chronic wound infections.
Development of cellulosic biofuels from non-food crops is currently an area of intense research interest. Tailoring depolymerizing enzymes to particular feedstocks and pretreatment conditions is one promising avenue of research in this area. Here we added a green-waste compost inoculum to switchgrass (Panicum virgatum) and simulated thermophilic composting in a bioreactor to select for a switchgrass-adapted community and to facilitate targeted discovery of glycoside hydrolases. Small-subunit (SSU) rRNA-based community profiles revealed that the microbial community changed dramatically between the initial and switchgrass-adapted compost (SAC) with some bacterial populations being enriched over 20-fold. We obtained 225 Mbp of 454-titanium pyrosequence data from the SAC community and conservatively identified 800 genes encoding glycoside hydrolase domains that were biased toward depolymerizing grass cell wall components. Of these, approximately 10% were putative cellulases mostly belonging to families GH5 and GH9. We synthesized two SAC GH9 genes with codon optimization for heterologous expression in Escherichia coli and observed activity for one on carboxymethyl cellulose. The active GH9 enzyme has a temperature optimum of 50 degrees C and pH range of 5.5 to 8 consistent with the composting conditions applied. We demonstrate that microbial communities adapt to switchgrass decomposition using simulated composting condition and that full-length genes can be identified from complex metagenomic sequence data, synthesized and expressed resulting in active enzyme.
Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These enzymes are often bimodular, including a catalytic domain and carbohydrate-binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relationships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able to discriminate GH7 CBHs and EGs with up to 99% accuracy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our machine learning results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function.
Prebiotic oligosaccharides are increasingly demanded within the Food Science domain because of the interesting healthy properties that these compounds may induce to the organism, thanks to their beneficial intestinal microbiota growth promotion ability. In this regard, the development of new efficient, convenient and affordable methods to obtain this class of compounds might expand even further their use as functional ingredients. This review presents an overview on the most recent interesting approaches to synthesize lactose-derived oligosaccharides with potential prebiotic activity paying special focus on the microbial glycoside hydrolases that can be effectively employed to obtain these prebiotic compounds. The most notable advantages of using lactose-derived carbohydrates such as lactosucrose, galactooligosaccharides from lactulose, lactulosucrose and 2-α-glucosyl-lactose are also described and commented.
Commercially available cellulases and amylases can disperse the pathogenic bacteria embedded in biofilms. This suggests that polysaccharide-degrading enzymes would be useful as antibacterial therapies to aid the treatment of biofilm-associated bacteria, e.g., in chronic wounds. Using a published enzyme library, we explored the capacity of 76 diverse recombinant glycoside hydrolases to disperse Staphylococcus aureus biofilms. Four of the 76 recombinant glycoside hydrolases digested purified cellulose, amylose, or pectin. However, these enzymes did not disperse biofilms, indicating that anti-biofilm activity is not general to all glycoside hydrolases and that biofilm activity cannot be predicted from the activity on pure substrates. Only one of the 76 recombinant enzymes was detectably active in biofilm dispersion, an α-xylosidase from Aspergillus nidulans. An α-xylosidase cloned subsequently from Aspergillus thermomutatus likewise demonstrated antibiofilm activity, suggesting that α-xylosidases, in general, can disperse Staphylococcus biofilms. Surprisingly, neither of the two β-xylosidases in the library degraded biofilms. Commercial preparations of amylase and cellulase that are known to be effective in the dispersion of Staphylococcus biofilms were also analyzed. The commercial cellulase contained contaminating proteins with multiple enzymes exhibiting biofilm-dispersing activity. Successfully prospecting for additional antibiofilm enzymes may thus require large libraries and may benefit from purified enzymes. The complexity of biofilms and the diversity of glycoside hydrolases continue to make it difficult to predict or understand the enzymes that could have future therapeutic applications.
Metagenomics approaches provide access to environmental genetic diversity for biotechnology applications, enabling the discovery of new enzymes and pathways for numerous catalytic processes. Discovery of new glycoside hydrolases with improved biocatalytic properties for the efficient conversion of lignocellulosic material to biofuels is a critical challenge in the development of economically viable routes from biomass to fuels and chemicals.
The complexity of microbial biofilms offers several challenges to the use of traditional means of microbial research. In particular, it can be difficult to calculate accurate numbers of biofilm bacteria, because even after thorough homogenization or sonication, small pieces of the biofilm remain, which contain numerous bacterial cells and result in inaccurately low colony forming units (CFU). In addition, imaging of infected tissue ex vivo often results in a disparity between the CFU and the number of bacterial cells observed under the microscope. We hypothesized that this phenomenon is due to the biofilm extracellular polymeric substance decreasing the accessibility of stains and antibodies to the embedded bacterial cells. In this study, we describe incorporating EPS-degrading glycoside hydrolases for CFU determination to obtain a more accurate estimation of the viable cells and for immunohistochemistry to disrupt the biofilm matrix and increase primary antibody binding to the bacterial cells.
Some glycoside hydrolases have broad specificity for hydrolysis of glycosidic bonds, potentially increasing their functional utility and flexibility in physiological and industrial applications. To deepen the understanding of the structural and evolutionary driving forces underlying specificity patterns in glycoside hydrolase family 5, we quantitatively screened the activity of the catalytic core domains from subfamily 4 (GH5_4) and closely related enzymes on four substrates: lichenan, xylan, mannan, and xyloglucan. Phylogenetic analysis revealed that GH5_4 consists of three major clades, and one of these clades, referred to here as clade 3, displayed average specific activities of 4.2 and 1.2 U/mg on lichenan and xylan, approximately 1 order of magnitude larger than the average for active enzymes in clades 1 and 2. Enzymes in clade 3 also more consistently met assay detection thresholds for reaction with all four substrates. We also identified a subfamily-wide positive correlation between lichenase and xylanase activities, as well as a weaker relationship between lichenase and xyloglucanase. To connect these results to structural features, we used the structure of CelE from Hungateiclostridium thermocellum (PDB 4IM4) as an example clade 3 enzyme with activities on all four substrates. Comparison of the sequence and structure of this enzyme with others throughout GH5_4 and neighboring subfamilies reveals at least two residues (H149 and W203) that are linked to strong activity across the substrates. Placing GH5_4 in context with other related subfamilies, we highlight several possibilities for the ongoing evolutionary specialization of GH5_4 enzymes.
In this work we report a detailed analysis of the topology and phylogenetics of family 2 glycoside hydrolases (GH2). We distinguish five topologies or domain architectures based on the presence and distribution of protein domains defined in Pfam and Interpro databases. All of them share a central TIM barrel (catalytic module) with two β-sandwich domains (non-catalytic) at the N-terminal end, but differ in the occurrence and nature of additional non-catalytic modules at the C-terminal region. Phylogenetic analysis was based on the sequence of the Pfam Glyco_hydro_2_C catalytic module present in most GH2 proteins. Our results led us to propose a model in which evolutionary diversity of GH2 enzymes is driven by the addition of different non-catalytic domains at the C-terminal region. This model accounts for the divergence of β-galactosidases from β-glucuronidases, the diversification of β-galactosidases with different transglycosylation specificities, and the emergence of bicistronic β-galactosidases. This study also allows the identification of groups of functionally uncharacterized protein sequences with potential biotechnological interest.
Glycoside hydrolases (GHs) are greatly diverse in sequences and functions, but systematic studies of GH relationships based on structural information are lacking. Here, we report that GHs have multiple evolutionary origins and are structurally derived from 27 homologous superfamilies and 16 folds, but GHs are highly biased to distribute in a few superfamilies and folds. Six of these superfamilies are widely encoded by archaea, bacteria, and eukaryotes, indicating that they may be the most ancient in origin. Most superfamilies vary in enzyme function, and some, such as the superfamilies of (β/α)8-barrel and (α/α)6-barrel structures, exhibit extreme functional diversity; this is highly positively correlated with sequence diversity. More than one-third of glycosidase activities show a phenomenon of convergent evolution, especially the degradation functions of GHs on polysaccharides. The GHs of most superfamilies have relatively narrow environmental distributions, normally with the highest abundance in host-associated environments and a distribution preference for moderate low-temperature and acidic environments. Overall, our expanded analysis facilitates an understanding of complex GH sequence-structure-function relationships and may guide our screening and engineering of GHs.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: