Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

The Polymorphic Membrane Protein G Has a Neutral Effect and the Plasmid Glycoprotein 3 an Antagonistic Effect on the Ability of the Major Outer Membrane Protein to Elicit Protective Immune Responses against a Chlamydia muridarum Respiratory Challenge.

Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen. The number of chlamydial infections continuous to increase and there is an urgent need for a safe and efficacious vaccine. To assess the ability of the Chlamydia muridarum polymorphic membrane protein G (PmpG) and the plasmid glycoprotein 3 (Pgp3) as single antigens, and in combination with the major outer-membrane protein (MOMP) to induce protection, BALB/c mice were immunized utilizing CpG-1826 and Montanide ISA 720 VG as adjuvants. Following vaccination with MOMP, significant humoral and cell-mediated immune responses were observed, while immunization with PmpG, or Pgp3, elicited weaker immune responses. Weaker immune responses were induced with MOMP+Pgp3 compared with MOMP alone. Following the intranasal challenge with C. muridarum, mice vaccinated with MOMP showed robust protection against body-weight loss, inflammatory responses in the lungs and number of Chlamydia recovered from the lungs. PmpG and Pgp3 elicited weaker protective responses. Mice immunized with MOMP+PmpG, were no better protected than animals vaccinated with MOMP only, while Pgp3 antagonized the protection elicited by MOMP. In conclusion, PmpG and Pgp3 elicited limited protective immune responses in mice against a respiratory challenge with C. muridarum and failed to enhance the protection induced by MOMP alone. The virulence of Pgp3 may result from its antagonistic effect on the immune protection induced by MOMP.

Bacterial exometabolites influence Chlamydomonas cell cycle and double algal productivity.

Algal-bacterial interactions provide clues to algal physiology, but mutualistic interactions are complicated by dynamic exchange. We characterized the response of Chlamydomonas reinhardtii to the presence of a putative alga-benefitting commensal bacterium (Arthrobacter strain 'P2b'). Co-cultivation promoted chlorophyll content, biomass, average cell size, and number of dividing cells, relative to axenic cultures. Addition of bacterial spent medium (whole, size-fractionated and heat-treated) had similar effects, indicating P2b does not require algal interaction to promote growth. Nutrients and pH were excluded as putative effectors, collectively indicating a commensal interaction mediated by Arthrobacter-released small exometabolite(s). Proteogenomic comparison revealed similar response to co-cultivation and spent media, including differential cell cycle regulation, extensive downregulation of flagellar genes and histones, carbonic anhydrase and RubisCO downregulation, upregulation of some chlorophyll, amino acid and carbohydrate biosynthesis genes, and changes to redox and Fe homeostasis. Further, Arthrobacter protein expression indicated some highly expressed putative secondary metabolites. Together, these results revealed that low molecular weight bacterial metabolites can elicit major physiological changes in algal cell cycle regulation, perhaps through a more productive G1 phase, that lead to substantial increases in photosynthetically-produced biomass. This work illustrates that model commensal interactions can be used to shed light on algal response to stimulating bacteria.

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei.

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical 'Rosetta Stone' to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.

Encapsulin carrier proteins for enhanced expression of antimicrobial peptides.

Antimicrobial peptides (AMPs) are regarded as attractive alternatives to conventional antibiotics, but their production in microbes remains challenging due to their inherent bactericidal nature. To address these limitations, we have developed a novel AMP fusion protein system based on an encapsulin nanocompartment protein and have demonstrated its utility in enhancing expression of HBCM2, an AMP with activity against Gram-negative bacteria. Here, HBCM2 was fused to the N-terminus of several Encapsulin monomer (Enc) variants engineered with multiple TEV protease recognition site insertions to facilitate proteolytic release of the fused HBCM2. Fusion of HBCM2 to the Enc variants, but not other common carrier proteins, enabled robust overexpression in Escherichia coli C43(DE3) cells. Interestingly, variants with a TEV site insertion following residue K71 in Enc exhibited the highest overexpression and HBCM2 release efficiencies compared to other variants but were deficient in cage formation. HBCM2 was purified from the highest expressing variant following TEV protease digestion and was found to be highly active in inhibiting E. coli growth (MIC = 5 µg/ml). Our study demonstrates the potential use of the Enc system to enhance expression of AMPs for biomanufacturing and therapeutic applications.

Combining multiple functional annotation tools increases coverage of metabolic annotation.

BACKGROUND: Genome-scale metabolic modeling is a cornerstone of systems biology analysis of microbial organisms and communities, yet these genome-scale modeling efforts are invariably based on incomplete functional annotations. Annotated genomes typically contain 30-50% of genes without functional annotation, severely limiting our knowledge of the "parts lists" that the organisms have at their disposal. These incomplete annotations may be sufficient to derive a model of a core set of well-studied metabolic pathways that support growth in pure culture. However, pathways important for growth on unusual metabolites exchanged in complex microbial communities are often less understood, resulting in missing functional annotations in newly sequenced genomes. RESULTS: Here, we present results on a comprehensive reannotation of 27 bacterial reference genomes, focusing on enzymes with EC numbers annotated by KEGG, RAST, EFICAz, and the BRENDA enzyme database, and on membrane transport annotations by TransportDB, KEGG and RAST. Our analysis shows that annotation using multiple tools can result in a drastically larger metabolic network reconstruction, adding on average 40% more EC numbers, 3-8 times more substrate-specific transporters, and 37% more metabolic genes. These results are even more pronounced for bacterial species that are phylogenetically distant from well-studied model organisms such as E. coli. CONCLUSIONS: Metabolic annotations are often incomplete and inconsistent. Combining multiple functional annotation tools can greatly improve genome coverage and metabolic network size, especially for non-model organisms and non-core pathways.

Proteomic Profiling of Burkholderia thailandensis During Host Infection Using Bio-Orthogonal Noncanonical Amino Acid Tagging (BONCAT).

Burkholderia pseudomallei and B. mallei are the causative agents of melioidosis and glanders, respectively, and are often fatal to humans and animals. Owing to the high fatality rate, potential for spread by aerosolization, and the lack of efficacious therapeutics, B. pseudomallei and B. mallei are considered biothreat agents of concern. In this study, we investigate the proteome of Burkholderia thailandensis, a closely related surrogate for the two more virulent Burkholderia species, during infection of host cells, and compare to that of B. thailandensis in culture. Studying the proteome of Burkholderia spp. during infection is expected to reveal molecular mechanisms of intracellular survival and host immune evasion; but proteomic profiling of Burkholderia during host infection is challenging. Proteomic analyses of host-associated bacteria are typically hindered by the overwhelming host protein content recovered from infected cultures. To address this problem, we have applied bio-orthogonal noncanonical amino acid tagging (BONCAT) to B. thailandensis, enabling the enrichment of newly expressed bacterial proteins from virtually any growth condition, including host cell infection. In this study, we show that B. thailandensis proteins were selectively labeled and efficiently enriched from infected host cells using BONCAT. We also demonstrate that this method can be used to label bacteria in situ by fluorescent tagging. Finally, we present a global proteomic profile of B. thailandensis as it infects host cells and a list of proteins that are differentially regulated in infection conditions as compared to bacterial monoculture. Among the identified proteins are quorum sensing regulated genes as well as homologs to previously identified virulence factors. This method provides a powerful tool to study the molecular processes during Burkholderia infection, a much-needed addition to the Burkholderia molecular toolbox.

Metagenomic analysis of intertidal hypersaline microbial mats from Elkhorn Slough, California, grown with and without molybdate.

Cyanobacterial mats are laminated microbial ecosystems which occur in highly diverse environments and which may provide a possible model for early life on Earth. Their ability to produce hydrogen also makes them of interest from a biotechnological and bioenergy perspective. Samples of an intertidal microbial mat from the Elkhorn Slough estuary in Monterey Bay, California, were transplanted to a greenhouse at NASA Ames Research Center to study a 24-h diel cycle, in the presence or absence of molybdate (which inhibits biohydrogen consumption by sulfate reducers). Here, we present metagenomic analyses of four samples that will be used as references for future metatranscriptomic analyses of this diel time series.

Genome Sequence of the Historical Clinical Isolate Burkholderia pseudomallei PHLS 6.

Here, we present the draft genome sequence of Burkholderia pseudomallei PHLS 6, a virulent clinical strain isolated from a melioidosis patient in Bangladesh in 1960. The draft genome consists of 39 contigs and is 7,322,181 bp long.

Phylogenomically guided identification of industrially relevant GH1 ß-glucosidases through DNA synthesis and nanostructure-initiator mass spectrometry.

Harnessing the biotechnological potential of the large number of proteins available in sequence databases requires scalable methods for functional characterization. Here we propose a workflow to address this challenge by combining phylogenomic guided DNA synthesis with high-throughput mass spectrometry and apply it to the systematic characterization of GH1 ß-glucosidases, a family of enzymes necessary for biomass hydrolysis, an important step in the conversion of lignocellulosic feedstocks to fuels and chemicals. We synthesized and expressed 175 GH1s, selected from over 2000 candidate sequences to cover maximum sequence diversity. These enzymes were functionally characterized over a range of temperatures and pHs using nanostructure-initiator mass spectrometry (NIMS), generating over 10,000 data points. When combined with HPLC-based sugar profiling, we observed GH1 enzymes active over a broad temperature range and toward many different ß-linked disaccharides. For some GH1s we also observed activity toward laminarin, a more complex oligosaccharide present as a major component of macroalgae. An area of particular interest was the identification of GH1 enzymes compatible with the ionic liquid 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]), a next-generation biomass pretreatment technology. We thus searched for GH1 enzymes active at 70 °C and 20% (v/v) [C2mim][OAc] over the course of a 24-h saccharification reaction. Using our unbiased approach, we identified multiple enzymes of different phylogentic origin with such activities. Our approach of characterizing sequence diversity through targeted gene synthesis coupled to high-throughput screening technologies is a broadly applicable paradigm for a wide range of biological problems.

Discovery and characterization of ionic liquid-tolerant thermophilic cellulases from a switchgrass-adapted microbial community.

BACKGROUND: The development of advanced biofuels from lignocellulosic biomass will require the use of both efficient pretreatment methods and new biomass-deconstructing enzyme cocktails to generate sugars from lignocellulosic substrates. Certain ionic liquids (ILs) have emerged as a promising class of compounds for biomass pretreatment and have been demonstrated to reduce the recalcitrance of biomass for enzymatic hydrolysis. However, current commercial cellulase cocktails are strongly inhibited by most of the ILs that are effective biomass pretreatment solvents. Fortunately, recent research has shown that IL-tolerant cocktails can be formulated and are functional on lignocellulosic biomass. This study sought to expand the list of known IL-tolerant cellulases to further enable IL-tolerant cocktail development by developing a combined in vitro/in vivo screening pipeline for metagenome-derived genes. RESULTS: Thirty-seven predicted cellulases derived from a thermophilic switchgrass-adapted microbial community were screened in this study. Eighteen of the twenty-one enzymes that expressed well in E. coli were active in the presence of the IL 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]) concentrations of at least 10% (v/v), with several retaining activity in the presence of 40% (v/v), which is currently the highest reported tolerance to [C2mim][OAc] for any cellulase. In addition, the optimum temperatures of the enzymes ranged from 45 to 95°C and the pH optimum ranged from 5.5 to 7.5, indicating these enzymes can be used to construct cellulase cocktails that function under a broad range of temperature, pH and IL concentrations. CONCLUSIONS: This study characterized in detail twenty-one cellulose-degrading enzymes derived from a thermophilic microbial community and found that 70% of them were [C2mim][OAc]-tolerant. A comparison of optimum temperature and [C2mim][OAc]-tolerance demonstrates that a positive correlation exists between these properties for those enzymes with a optimum temperature >70°C, further strengthening the link between thermotolerance and IL-tolerance for lignocelluolytic glycoside hydrolases.

Metatranscriptomic analysis of lignocellulolytic microbial communities involved in high-solids decomposition of rice straw.

BACKGROUND: New lignocellulolytic enzymes are needed that maintain optimal activity under the harsh conditions present during industrial enzymatic deconstruction of biomass, including high temperatures, the absence of free water, and the presence of inhibitors from the biomass. Enriching lignocellulolytic microbial communities under these conditions provides a source of microorganisms that may yield robust lignocellulolytic enzymes tolerant to the extreme conditions needed to improve the throughput and efficiency of biomass enzymatic deconstruction. Identification of promising enzymes from these systems is challenging due to complex substrate-enzyme interactions and requirements to assay for activity. In this study, metatranscriptomes from compost-derived microbial communities enriched on rice straw under thermophilic and mesophilic conditions were sequenced and analyzed to identify lignocellulolytic enzymes overexpressed under thermophilic conditions. To determine differential gene expression across mesophilic and thermophilic treatments, a method was developed which pooled gene expression by functional category, as indicated by Pfam annotations, since microbial communities performing similar tasks are likely to have overlapping functions even if they share no specific genes. RESULTS: Differential expression analysis identified enzymes from glycoside hydrolase family 48, carbohydrate binding module family 2, and carbohydrate binding module family 33 domains as significantly overexpressed in the thermophilic community. Overexpression of these protein families in the thermophilic community resulted from expression of a small number of genes not currently represented in any protein database. Genes in overexpressed protein families were predominantly expressed by a single Actinobacteria genus, Micromonospora. CONCLUSIONS: Coupling measurements of deconstructive activity with comparative analyses to identify overexpressed enzymes in lignocellulolytic communities provides a targeted approach for discovery of candidate enzymes for more efficient biomass deconstruction. Glycoside hydrolase family 48 cellulases and carbohydrate binding module family 33 polysaccharide monooxygenases with carbohydrate binding module family 2 domains may improve saccharification of lignocellulosic biomass under high-temperature and low moisture conditions relevant to industrial biofuel production.

Discovery of two novel ß-glucosidases from an Amazon soil metagenomic library.

An Amazon soil microbial community metagenomic fosmid library was functionally screened for ß-glucosidase activity. Contig analysis of positive clones revealed the presence of two ORFs encoding novel ß-glucosidases, AmBGL17 and AmBGL18, from the GH3 and GH1 families, respectively. Both AmBGL17 and AmBGL18 were functionally identified as ß-glucosidases. The enzymatic activity of AmBGL17 was further characterized. AmBGL17 was tested with different substrates and showed highest activity on pNPßG substrate with an optimum temperature of 45 °C and an optimum pH of 6. AmBGL17 showed a Vmax of 116 mM s(-1) and Km of 0.30 ± 0.017 mM. This is the first report of ß-glucosidases from an Amazon soil microbial community using a metagenomic approach.

Discovery of microorganisms and enzymes involved in high-solids decomposition of rice straw using metagenomic analyses.

High-solids incubations were performed to enrich for microbial communities and enzymes that decompose rice straw under mesophilic (35°C) and thermophilic (55°C) conditions. Thermophilic enrichments yielded a community that was 7.5 times more metabolically active on rice straw than mesophilic enrichments. Extracted xylanase and endoglucanse activities were also 2.6 and 13.4 times greater, respectively, for thermophilic enrichments. Metagenome sequencing was performed on enriched communities to determine community composition and mine for genes encoding lignocellulolytic enzymes. Proteobacteria were found to dominate the mesophilic community while Actinobacteria were most abundant in the thermophilic community. Analysis of protein family representation in each metagenome indicated that cellobiohydrolases containing carbohydrate binding module 2 (CBM2) were significantly overrepresented in the thermophilic community. Micromonospora, a member of Actinobacteria, primarily housed these genes in the thermophilic community. In light of these findings, Micromonospora and other closely related Actinobacteria genera appear to be promising sources of thermophilic lignocellulolytic enzymes for rice straw deconstruction under high-solids conditions. Furthermore, these discoveries warrant future research to determine if exoglucanases with CBM2 represent thermostable enzymes tolerant to the process conditions expected to be encountered during industrial biofuel production.

Metagenomes of tropical soil-derived anaerobic switchgrass-adapted consortia with and without iron.

Tropical forest soils decompose litter rapidly with frequent episodes of anoxia, making it likely that bacteria using alternate terminal electron acceptors (TEAs) such as iron play a large role in supporting decomposition under these conditions. The prevalence of many types of metabolism in litter deconstruction makes these soils useful templates for improving biofuel production. To investigate how iron availability affects decomposition, we cultivated feedstock-adapted consortia (FACs) derived from iron-rich tropical forest soils accustomed to experiencing frequent episodes of anaerobic conditions and frequently fluctuating redox. One consortium was propagated under fermenting conditions, with switchgrass as the sole carbon source in minimal media (SG only FACs), and the other consortium was treated the same way but received poorly crystalline iron as an additional terminal electron acceptor (SG + Fe FACs). We sequenced the metagenomes of both consortia to a depth of about 150 Mb each, resulting in a coverage of 26× for the more diverse SG + Fe FACs, and 81× for the relatively less diverse SG only FACs. Both consortia were able to quickly grow on switchgrass, and the iron-amended consortium exhibited significantly higher microbial diversity than the unamended consortium. We found evidence of higher stress in the unamended FACs and increased sugar transport and utilization in the iron-amended FACs. This work provides metagenomic evidence that supplementation of alternative TEAs may improve feedstock deconstruction in biofuel production.

Proteogenomic analysis of a thermophilic bacterial consortium adapted to deconstruct switchgrass.

Thermophilic bacteria are a potential source of enzymes for the deconstruction of lignocellulosic biomass. However, the complement of proteins used to deconstruct biomass and the specific roles of different microbial groups in thermophilic biomass deconstruction are not well-explored. Here we report on the metagenomic and proteogenomic analyses of a compost-derived bacterial consortium adapted to switchgrass at elevated temperature with high levels of glycoside hydrolase activities. Near-complete genomes were reconstructed for the most abundant populations, which included composite genomes for populations closely related to sequenced strains of Thermus thermophilus and Rhodothermus marinus, and for novel populations that are related to thermophilic Paenibacilli and an uncultivated subdivision of the little-studied Gemmatimonadetes phylum. Partial genomes were also reconstructed for a number of lower abundance thermophilic Chloroflexi populations. Identification of genes for lignocellulose processing and metabolic reconstructions suggested Rhodothermus, Paenibacillus and Gemmatimonadetes as key groups for deconstructing biomass, and Thermus as a group that may primarily metabolize low molecular weight compounds. Mass spectrometry-based proteomic analysis of the consortium was used to identify >3000 proteins in fractionated samples from the cultures, and confirmed the importance of Paenibacillus and Gemmatimonadetes to biomass deconstruction. These studies also indicate that there are unexplored proteins with important roles in bacterial lignocellulose deconstruction.

Rapid countermeasure discovery against Francisella tularensis based on a metabolic network reconstruction.

In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of active versus tested compounds over an elapsed time period of 32 weeks, from pathogen strain identification to selection and validation of novel antimicrobial compounds.

From soil to structure, a novel dimeric ß-glucosidase belonging to glycoside hydrolase family 3 isolated from compost using metagenomic analysis.

A recent metagenomic analysis sequenced a switchgrass-adapted compost community to identify enzymes from microorganisms that were specifically adapted to switchgrass under thermophilic conditions. These enzymes are being examined as part of the pretreatment process for the production of "second-generation" biofuels. Among the enzymes discovered was JMB19063, a novel three-domain ß-glucosidase that belongs to the GH3 (glycoside hydrolase 3) family. Here, we report the structure of JMB19063 in complex with glucose and the catalytic variant D261N crystallized in the presence of cellopentaose. JMB19063 is first structure of a dimeric member of the GH3 family, and we demonstrate that dimerization is required for catalytic activity. Arg-587 and Phe-598 from the C-terminal domain of the opposing monomer are shown to interact with bound ligands in the D261N structure. Enzyme assays confirmed that these residues are absolutely essential for full catalytic activity.