Community ecology of hot spring cyanobacterial mats: predominant populations and their functional potential

Phototrophic microbial mat communities from 60 °C and 65 °C regions in the effluent channels of Mushroom and Octopus Springs (Yellowstone National Park, WY, USA) were investigated by shotgun metagenomic sequencing. Analyses of assembled metagenomic sequences resolved six dominant chlorophototrophic populations and permitted the discovery and characterization of undescribed but predominant community members and their physiological potential. Linkage of phylogenetic marker genes and functional genes showed novel chlorophototrophic bacteria belonging to uncharacterized lineages within the order Chlorobiales and within the Kingdom Chloroflexi. The latter is the first chlorophototrophic member of Kingdom Chloroflexi that lies outside the monophyletic group of chlorophototrophs of the Order Chloroflexales. Direct comparison of unassembled metagenomic sequences to genomes of representative isolates showed extensive genetic diversity, genomic rearrangements and novel physiological potential in native populations as compared with genomic references. Synechococcus spp. metagenomic sequences showed a high degree of synteny with the reference genomes of Synechococcus spp. strains A and B′, but synteny declined with decreasing sequence relatedness to these references. There was evidence of horizontal gene transfer among native populations, but the frequency of these events was inversely proportional to phylogenetic relatedness.     

Individual genome assembly from complex community short-read metagenomic datasets

Assembling individual genomes from complex community metagenomic data remains a challenging issue for environmental studies. We evaluated the quality of genome assemblies from community short read data (Illumina 100 bp pair-ended sequences) using datasets recovered from freshwater and soil microbial communities as well as in silico simulations. Our analyses revealed that the genome of a single genotype (or species) can be accurately assembled from a complex metagenome when it shows at least about 20 × coverage. At lower coverage, however, the derived assemblies contained a substantial fraction of non-target sequences (chimeras), which explains, at least in part, the higher number of hypothetical genes recovered in metagenomic relative to genomic projects. We also provide examples of how to detect intrapopulation structure in metagenomic datasets and estimate the type and frequency of errors in assembled genes and contigs from datasets of varied species complexity.     

Comparative metagenomic,phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients

Terrestrial ecosystems are receiving elevated inputs of nitrogen (N) from anthropogenic sources and understanding how these increases in N availability affect soil microbial communities is critical for predicting the associated effects on belowground ecosystems. We used a suite of approaches to analyze the structure and functional characteristics of soil microbial communities from replicated plots in two long-term N fertilization experiments located in contrasting systems. Pyrosequencing-based analyses of 16S rRNA genes revealed no significant effects of N fertilization on bacterial diversity, but significant effects on community composition at both sites; copiotrophic taxa (including members of the Proteobacteria and Bacteroidetes phyla) typically increased in relative abundance in the high N plots, with oligotrophic taxa (mainly Acidobacteria) exhibiting the opposite pattern. Consistent with the phylogenetic shifts under N fertilization, shotgun metagenomic sequencing revealed increases in the relative abundances of genes associated with DNA/RNA replication, electron transport and protein metabolism, increases that could be resolved even with the shallow shotgun metagenomic sequencing conducted here (average of 75 000 reads per sample). We also observed shifts in the catabolic capabilities of the communities across the N gradients that were significantly correlated with the phylogenetic and metagenomic responses, indicating possible linkages between the structure and functioning of soil microbial communities. Overall, our results suggest that N fertilization may, directly or indirectly, induce a shift in the predominant microbial life-history strategies, favoring a more active, copiotrophic microbial community, a pattern that parallels the often observed replacement of K-selected with r-selected plant species with elevated N.     

A metagenome of a full-scale microbial community carrying out enhanced biological phosphorus removal

Enhanced biological phosphorus removal (EBPR) is widely used for removal of phosphorus from wastewater. In this study, a metagenome (18.2 Gb) was generated using Illumina sequencing from a full-scale EBPR plant to study the community structure and genetic potential. Quantitative fluorescence in situ hybridization (qFISH) was applied as an independent method to evaluate the community structure. The results were in qualitative agreement, but a DNA extraction bias against gram positive bacteria using standard extraction protocols was identified, which would not have been identified without the use of qFISH. The genetic potential for community function showed enrichment of genes involved in phosphate metabolism and biofilm formation, reflecting the selective pressure of the EBPR process. Most contigs in the assembled metagenome had low similarity to genes from currently sequenced genomes, underlining the need for more reference genomes of key EBPR species. Only the genome of ‘Candidatus Accumulibacter'', a genus of phosphorus-removing organisms, was closely enough related to the species present in the metagenome to allow for detailed investigations. Accumulibacter accounted for only 4.8% of all bacteria by qFISH, but the depth of sequencing enabled detailed insight into their microdiversity in the full-scale plant. Only 15% of the reads matching Accumulibacter had a high similarity (>95%) to the sequenced Accumulibacter clade IIA strain UW-1 genome, indicating the presence of some microdiversity. The differences in gene complement between the Accumulibacter clades were limited to genes for extracellular polymeric substances and phage-related genes, suggesting a selective pressure from phages on the Accumulibacter diversity.     

Metagenomic Exploration of Viruses throughout the Indian Ocean

The characterization of global marine microbial taxonomic and functional diversity is a primary goal of the Global Ocean Sampling Expedition. As part of this study, 19 water samples were collected aboard the Sorcerer II sailing vessel from the southern Indian Ocean in an effort to more thoroughly understand the lifestyle strategies of the microbial inhabitants of this ultra-oligotrophic region. No investigations of whole virioplankton assemblages have been conducted on waters collected from the Indian Ocean or across multiple size fractions thus far. Therefore, the goals of this study were to examine the effect of size fractionation on viral consortia structure and function and understand the diversity and functional potential of the Indian Ocean virome. Five samples were selected for comprehensive metagenomic exploration; and sequencing was performed on the microbes captured on 3.0-, 0.8- and 0.1 µm membrane filters as well as the viral fraction (<0.1 µm). Phylogenetic approaches were also used to identify predicted proteins of viral origin in the larger fractions of data from all Indian Ocean samples, which were included in subsequent metagenomic analyses. Taxonomic profiling of viral sequences suggested that size fractionation of marine microbial communities enriches for specific groups of viruses within the different size classes and functional characterization further substantiated this observation. Functional analyses also revealed a relative enrichment for metabolic proteins of viral origin that potentially reflect the physiological condition of host cells in the Indian Ocean including those involved in nitrogen metabolism and oxidative phosphorylation. A novel classification method, MGTAXA, was used to assess virus-host relationships in the Indian Ocean by predicting the taxonomy of putative host genera, with Prochlorococcus, Acanthochlois and members of the SAR86 cluster comprising the most abundant predictions. This is the first study to holistically explore virioplankton dynamics across multiple size classes and provides unprecedented insight into virus diversity, metabolic potential and virus-host interactions.     

Phylogenetic and Metagenomic Analyses of Substrate-Dependent Bacterial Temporal Dynamics in Microbial Fuel Cells

Understanding the microbial community structure and genetic potential of anode biofilms is key to improve extracellular electron transfers in microbial fuel cells. We investigated effect of substrate and temporal dynamics of anodic biofilm communities using phylogenetic and metagenomic approaches in parallel with electrochemical characterizations. The startup non-steady state anodic bacterial structures were compared for a simple substrate, acetate, and for a complex substrate, landfill leachate, using a single-chamber air-cathode microbial fuel cell. Principal coordinate analysis showed that distinct community structures were formed with each substrate type. The bacterial diversity measured as Shannon index decreased with time in acetate cycles, and was restored with the introduction of leachate. The change of diversity was accompanied by an opposite trend in the relative abundance of Geobacter-affiliated phylotypes, which were acclimated to over 40% of total Bacteria at the end of acetate-fed conditions then declined in the leachate cycles. The transition from acetate to leachate caused a decrease in output power density from 243±13 mW/m² to 140±11 mW/m², accompanied by a decrease in Coulombic electron recovery from 18±3% to 9±3%. The leachate cycles selected protein-degrading phylotypes within phylum Synergistetes. Metagenomic shotgun sequencing showed that leachate-fed communities had higher cell motility genes including bacterial chemotaxis and flagellar assembly, and increased gene abundance related to metal resistance, antibiotic resistance, and quorum sensing. These differentially represented genes suggested an altered anodic biofilm community in response to additional substrates and stress from the complex landfill leachate.     

Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries Using Sparse Linear Regression

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome.     

Metagenomic Sequencing of an In Vitro-Simulated Microbial Community

Background

Microbial life dominates the earth, but many species are difficult or even impossible to study under laboratory conditions. Sequencing DNA directly from the environment, a technique commonly referred to as metagenomics, is an important tool for cataloging microbial life. This culture-independent approach involves collecting samples that include microbes in them, extracting DNA from the samples, and sequencing the DNA. A sample may contain many different microorganisms, macroorganisms, and even free-floating environmental DNA. A fundamental challenge in metagenomics has been estimating the abundance of organisms in a sample based on the frequency with which the organism''s DNA was observed in reads generated via DNA sequencing.

Methodology/Principal Findings

We created mixtures of ten microbial species for which genome sequences are known. Each mixture contained an equal number of cells of each species. We then extracted DNA from the mixtures, sequenced the DNA, and measured the frequency with which genomic regions from each organism was observed in the sequenced DNA. We found that the observed frequency of reads mapping to each organism did not reflect the equal numbers of cells that were known to be included in each mixture. The relative organism abundances varied significantly depending on the DNA extraction and sequencing protocol utilized.

Conclusions/Significance

We describe a new data resource for measuring the accuracy of metagenomic binning methods, created by in vitro-simulation of a metagenomic community. Our in vitro simulation can be used to complement previous in silico benchmark studies. In constructing a synthetic community and sequencing its metagenome, we encountered several sources of observation bias that likely affect most metagenomic experiments to date and present challenges for comparative metagenomic studies. DNA preparation methods have a particularly profound effect in our study, implying that samples prepared with different protocols are not suitable for comparative metagenomics.     

One Bacterial Cell,One Complete Genome

While the bulk of the finished microbial genomes sequenced to date are derived from cultured bacterial and archaeal representatives, the vast majority of microorganisms elude current culturing attempts, severely limiting the ability to recover complete or even partial genomes from these environmental species. Single cell genomics is a novel culture-independent approach, which enables access to the genetic material of an individual cell. No single cell genome has to our knowledge been closed and finished to date. Here we report the completed genome from an uncultured single cell of Candidatus Sulcia muelleri DMIN. Digital PCR on single symbiont cells isolated from the bacteriome of the green sharpshooter Draeculacephala minerva bacteriome allowed us to assess that this bacteria is polyploid with genome copies ranging from approximately 200–900 per cell, making it a most suitable target for single cell finishing efforts. For single cell shotgun sequencing, an individual Sulcia cell was isolated and whole genome amplified by multiple displacement amplification (MDA). Sanger-based finishing methods allowed us to close the genome. To verify the correctness of our single cell genome and exclude MDA-derived artifacts, we independently shotgun sequenced and assembled the Sulcia genome from pooled bacteriomes using a metagenomic approach, yielding a nearly identical genome. Four variations we detected appear to be genuine biological differences between the two samples. Comparison of the single cell genome with bacteriome metagenomic sequence data detected two single nucleotide polymorphisms (SNPs), indicating extremely low genetic diversity within a Sulcia population. This study demonstrates the power of single cell genomics to generate a complete, high quality, non-composite reference genome within an environmental sample, which can be used for population genetic analyzes.     

Quantitative Molecular Assay for Fingerprinting Microbial Communities of Wastewater and Estrogen-Degrading Consortia

A quantitative fingerprinting method, called the real-time terminal restriction fragment length polymorphism (real-time-t-RFLP) assay, was developed for simultaneous determination of microbial diversity and abundance within a complex community. The real-time-t-RFLP assay was developed by incorporating the quantitative feature of real-time PCR and the fingerprinting feature of t-RFLP analysis. The assay was validated by using a model microbial community containing three pure strains, an Escherichia coli strain (gram negative), a Pseudomonas fluorescens strain (gram negative), and a Bacillus thuringiensis strain (gram positive). Subsequently, the real-time-t-RFLP assay was applied to and proven to be useful for environmental samples; the richness and abundance of species in microbial communities (expressed as the number of 16S rRNA gene copies of each ribotype per milliliter) of wastewater and estrogen-degrading consortia (enriched with 17α-estradiol, 17β-estradiol, or estrone) were successfully characterized. The results of this study strongly suggested that the real-time-t-RFLP assay can be a powerful molecular tool for gaining insight into microbial communities in various engineered systems and natural habitats.     

Strategies for Enhancing the Effectiveness of Metagenomic-based Enzyme Discovery in Lignocellulolytic Microbial Communities

Producing cellulosic biofuels from plant material has recently emerged as a key US Department of Energy goal. For this technology to be commercially viable on a large scale, it is critical to make production cost efficient by streamlining both the deconstruction of lignocellulosic biomass and fuel production. Many natural ecosystems efficiently degrade lignocellulosic biomass and harbor enzymes that, when identified, could be used to increase the efficiency of commercial biomass deconstruction. However, ecosystems most likely to yield relevant enzymes, such as tropical rain forest soil in Puerto Rico, are often too complex for enzyme discovery using current metagenomic sequencing technologies. One potential strategy to overcome this problem is to selectively cultivate the microbial communities from these complex ecosystems on biomass under defined conditions, generating less complex biomass-degrading microbial populations. To test this premise, we cultivated microbes from Puerto Rican soil or green waste compost under precisely defined conditions in the presence dried ground switchgrass (Panicum virgatum L.) or lignin, respectively, as the sole carbon source. Phylogenetic profiling of the two feedstock-adapted communities using SSU rRNA gene amplicon pyrosequencing or phylogenetic microarray analysis revealed that the adapted communities were significantly simplified compared to the natural communities from which they were derived. Several members of the lignin-adapted and switchgrass-adapted consortia are related to organisms previously characterized as biomass degraders, while others were from less well-characterized phyla. The decrease in complexity of these communities make them good candidates for metagenomic sequencing and will likely enable the reconstruction of a greater number of full-length genes, leading to the discovery of novel lignocellulose-degrading enzymes adapted to feedstocks and conditions of interest.     

Facility-Specific “House” Microbiome Drives Microbial Landscapes of Artisan Cheesemaking Plants

Cheese fermentations involve the growth of complex microbial consortia, which often originate in the processing environment and drive the development of regional product qualities. However, the microbial milieus of cheesemaking facilities are largely unexplored and the true nature of the fermentation-facility relationship remains nebulous. Thus, a high-throughput sequencing approach was employed to investigate the microbial ecosystems of two artisanal cheesemaking plants, with the goal of elucidating how the processing environment influences microbial community assemblages. Results demonstrate that fermentation-associated microbes dominated most surfaces, primarily Debaryomyces and Lactococcus, indicating that establishment of these organisms on processing surfaces may play an important role in microbial transfer, beneficially directing the course of sequential fermentations. Environmental organisms detected in processing environments dominated the surface microbiota of washed-rind cheeses maturing in both facilities, demonstrating the importance of the processing environment for populating cheese microbial communities, even in inoculated cheeses. Spatial diversification within both facilities reflects the functional adaptations of microbial communities inhabiting different surfaces and the existence of facility-specific “house” microbiota, which may play a role in shaping site-specific product characteristics.     

Variability in Microbial Community Composition and Function Between Different Niches Within a Coral Reef

To explore how microbial community composition and function varies within a coral reef ecosystem, we performed metagenomic sequencing of seawater from four niches across Heron Island Reef, within the Great Barrier Reef. Metagenomes were sequenced from seawater samples associated with (1) the surface of the coral species Acropora palifera, (2) the surface of the coral species Acropora aspera, (3) the sandy substrate within the reef lagoon and (4) open water, outside of the reef crest. Microbial composition and metabolic function differed substantially between the four niches. The taxonomic profile showed a clear shift from an oligotroph-dominated community (e.g. SAR11, Prochlorococcus, Synechococcus) in the open water and sandy substrate niches, to a community characterised by an increased frequency of copiotrophic bacteria (e.g. Vibrio, Pseudoalteromonas, Alteromonas) in the coral seawater niches. The metabolic potential of the four microbial assemblages also displayed significant differences, with the open water and sandy substrate niches dominated by genes associated with core house-keeping processes such as amino acid, carbohydrate and protein metabolism as well as DNA and RNA synthesis and metabolism. In contrast, the coral surface seawater metagenomes had an enhanced frequency of genes associated with dynamic processes including motility and chemotaxis, regulation and cell signalling. These findings demonstrate that the composition and function of microbial communities are highly variable between niches within coral reef ecosystems and that coral reefs host heterogeneous microbial communities that are likely shaped by habitat structure, presence of animal hosts and local biogeochemical conditions.     

MiMiC: a bioinformatic approach for generation of synthetic communities from metagenomes

Environmental and host-associated microbial communities are complex ecosystems, of which many members are still unknown. Hence, it is challenging to study community dynamics and important to create model systems of reduced complexity that mimic major community functions. Therefore, we developed MiMiC, a computational approach for data-driven design of simplified communities from shotgun metagenomes. We first built a comprehensive database of species-level bacterial and archaeal genomes (n = 22 627) consisting of binary (presence/absence) vectors of protein families (Pfam = 17 929). MiMiC predicts the composition of minimal consortia using an iterative scoring system based on maximal match-to-mismatch ratios between this database and the Pfam binary vector of any input metagenome. Pfam vectorization retained enough resolution to distinguish metagenomic profiles between six environmental and host-derived microbial communities (n = 937). The calculated number of species per minimal community ranged between 5 and 11, with MiMiC selected communities better recapitulating the functional repertoire of the original samples than randomly selected species. The inferred minimal communities retained habitat-specific features and were substantially different from communities consisting of most abundant members. The use of a mixture of known microbes revealed the ability to select 23 of 25 target species from the entire genome database. MiMiC is open source and available at https://github.com/ClavelLab/MiMiC .     

Enrichment and physiological characterization of a novel comammox Nitrospira indicates ammonium inhibition of complete nitrification

The recent discovery of bacteria within the genus Nitrospira capable of complete ammonia oxidation (comammox) demonstrated that the sequential oxidation of ammonia to nitrate via nitrite can also be performed within a single bacterial cell. Although comammox Nitrospira exhibit a wide distribution in natural and engineered ecosystems, information on their physiological properties is scarce due to the limited number of cultured representatives. Additionally, most available genomic information is derived from metagenomic sequencing and high-quality genomes of Nitrospira in general are limited. In this study, we obtained a high (90%) enrichment of a novel comammox species, tentatively named “Candidatus Nitrospira kreftii”, and performed a detailed genomic and physiological characterization. The complete genome of “Ca. N. kreftii” allowed reconstruction of its basic metabolic traits. Similar to Nitrospira inopinata, the enrichment culture exhibited a very high ammonia affinity (K_{m(app)_NH3} ≈ 0.040 ± 0.01 µM), but a higher nitrite affinity (K_{m(app)_NO2}- = 12.5 ± 4.0 µM), indicating an adaptation to highly oligotrophic environments. Furthermore, we observed partial inhibition of ammonia oxidation at ammonium concentrations as low as 25 µM. This inhibition of “Ca. N. kreftii” indicates that differences in ammonium tolerance rather than affinity could potentially be a niche determining factor for different comammox Nitrospira.Subject terms: Bacterial genomics, Environmental microbiology, Bacterial physiology     

Time-series metagenomic analysis reveals robustness of soil microbiome against chemical disturbance

Soil microbial communities have great potential for bioremediation of recalcitrant aromatic compounds. However, it is unclear which taxa and genes in the communities, and how they contribute to the bioremediation in the polluted soils. To get clues about this fundamental question here, time-course (up to 24 weeks) metagenomic analysis of microbial community in a closed soil microcosm artificially polluted with four aromatic compounds, including phenanthrene, was conducted to investigate the changes in the community structures and gene pools. The pollution led to drastic changes in the community structures and the gene sets for pollutant degradation. Complete degradation of phenanthrene was strongly suggested to occur by the syntrophic metabolism by Mycobacterium and the most proliferating genus, Burkholderia. The community structure at Week 24 (∼12 weeks after disappearance of the pollutants) returned to the structure similar to that before pollution. Our time-course metagenomic analysis of phage genes strongly suggested the involvement of the ‘kill-the-winner’ phenomenon (i.e. phage predation of Burkholderia cells) for the returning of the microbial community structure. The pollution resulted in a decrease in taxonomic diversity and a drastic increase in diversity of gene pools in the communities, showing the functional redundancy and robustness of the communities against chemical disturbance.     

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using ¹⁴C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of ¹⁴C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)''s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.     

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.