Targeted metatranscriptomics of compost derived consortia reveals a GH11 exerting an unusual exo-1,4-β-xylanase activity

Background: Using globally abundant crop residues as a carbon source for energy generation and renewable chemicals production stands out as a promising solution to reduce current dependency on fossil fuels. In nature, such as in compost habitats, microbial communities efficiently degrade the available plant biomass using a diverse set of synergistic enzymes. However, deconstruction of lignocellulose remains a challenge for industry due to recalcitrant nature of the substrate and the inefficiency of the enzyme systems available, making the economic production of lignocellulosic biofuels difficult. Metatranscriptomic studies of microbial communities can unveil the metabolic functions employed by lignocellulolytic consortia and identify new biocatalysts that could improve industrial lignocellulose conversion. Results: In this study, a microbial community from compost was grown in minimal medium with sugarcane bagasse sugarcane bagasse as the sole carbon source. Solid-state nuclear magnetic resonance was used to monitor lignocellulose degradation; analysis of metatranscriptomic data led to the selection and functional characterization of several target genes, revealing the first glycoside hydrolase from Carbohydrate Active Enzyme family 11 with exo-1,4-β-xylanase activity. The xylanase crystal structure was resolved at 1.76 Å revealing the structural basis of exo-xylanase activity. Supplementation of a commercial cellulolytic enzyme cocktail with the xylanase showed improvement in Avicel hydrolysis in the presence of inhibitory xylooligomers. Conclusions: This study demonstrated that composting microbiomes continue to be an excellent source of biotechnologically important enzymes by unveiling the diversity of enzymes involved in in situ lignocellulose degradation

Methods for comparative metagenomics

<p>Abstract</p> <p>Background</p> <p>Metagenomics is a rapidly growing field of research that aims at studying uncultured organisms to understand the true diversity of microbes, their functions, cooperation and evolution, in environments such as soil, water, ancient remains of animals, or the digestive system of animals and humans. The recent development of ultra-high throughput sequencing technologies, which do not require cloning or PCR amplification, and can produce huge numbers of DNA reads at an affordable cost, has boosted the number and scope of metagenomic sequencing projects. Increasingly, there is a need for new ways of comparing multiple metagenomics datasets, and for fast and user-friendly implementations of such approaches.</p> <p>Results</p> <p>This paper introduces a number of new methods for interactively exploring, analyzing and comparing multiple metagenomic datasets, which will be made freely available in a new, comparative version 2.0 of the stand-alone metagenome analysis tool MEGAN.</p> <p>Conclusion</p> <p>There is a great need for powerful and user-friendly tools for comparative analysis of metagenomic data and MEGAN 2.0 will help to fill this gap.</p

Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine

Background Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. Methods and Findings Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400–1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. Conclusions The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genus-level with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate well with pyrosequencing-based compositions, especially for lower-order ranks, indicating high robustness of both approaches. However, incompatible grouping schemes make exact comparison difficult

Metatranscriptomics Reveals the Diversity of Genes Expressed by Eukaryotes in Forest Soils

Eukaryotic organisms play essential roles in the biology and fertility of soils. For example the micro and mesofauna contribute to the fragmentation and homogenization of plant organic matter, while its hydrolysis is primarily performed by the fungi. To get a global picture of the activities carried out by soil eukaryotes we sequenced 2×10,000 cDNAs synthesized from polyadenylated mRNA directly extracted from soils sampled in beech (Fagus sylvatica) and spruce (Picea abies) forests. Taxonomic affiliation of both cDNAs and 18S rRNA sequences showed a dominance of sequences from fungi (up to 60%) and metazoans while protists represented less than 12% of the 18S rRNA sequences. Sixty percent of cDNA sequences from beech forest soil and 52% from spruce forest soil had no homologs in the GenBank/EMBL/DDJB protein database. A Gene Ontology term was attributed to 39% and 31.5% of the spruce and beech soil sequences respectively. Altogether 2076 sequences were putative homologs to different enzyme classes participating to 129 KEGG pathways among which several were implicated in the utilisation of soil nutrients such as nitrogen (ammonium, amino acids, oligopeptides), sugars, phosphates and sulfate. Specific annotation of plant cell wall degrading enzymes identified enzymes active on major polymers (cellulose, hemicelluloses, pectin, lignin) and glycoside hydrolases represented 0.5% (beech soil)–0.8% (spruce soil) of the cDNAs. Other sequences coding enzymes active on organic matter (extracellular proteases, lipases, a phytase, P450 monooxygenases) were identified, thus underlining the biotechnological potential of eukaryotic metatranscriptomes. The phylogenetic affiliation of 12 full-length carbohydrate active enzymes showed that most of them were distantly related to sequences from known fungi. For example, a putative GH45 endocellulase was closely associated to molluscan sequences, while a GH7 cellobiohydrolase was closest to crustacean sequences, thus suggesting a potentially significant contribution of non-fungal eukaryotes in the actual hydrolysis of soil organic matter

Human Disturbance of Karst Environments

Karst environments have been impacted by human activity for thousands of years, ever since people started living in caves for shelter, needing building supplies and water. As human population has increased, so has its disturbance of the karst landscape. Quarrying, pollution, groundwater extraction, construction, and agriculture are the major culprits for disturbing both surface and subsurface karst. Ecosystems in this type of environment have been shown to be quite vulnerable to human activities. Methods to quantify this disturbance, such as the karst disturbance index, have been created to help resource managers formulate approaches to reduce this anthropogenic impact. In addition, models to measure karst vulnerability, in particular karst aquifers, have grown in number over the last two decades. When measuring human disturbance, it is important to consider matters of time and scale, as both will influence how and what data is collected

Organic carbon transformations in high-Arctic peat soils: key functions and microorganisms

A substantial part of the Earths’ soil organic carbon (SOC) is stored in Arctic permafrost peatlands, which represent large potential sources for increased emissions of the greenhouse gases CH4 and CO2 in a warming climate. The microbial communities and their genetic repertoire involved in the breakdown and mineralisation of SOC in these soils are, however, poorly understood. In this study, we applied a combined metagenomic and metatranscriptomic approach on two Arctic peat soils to investigate the identity and the gene pool of the microbiota driving the SOC degradation in the seasonally thawed active layers. A large and diverse set of genes encoding plant polymer-degrading enzymes was found, comparable to microbiotas from temperate and subtropical soils. This indicates that the metabolic potential for SOC degradation in Arctic peat is not different from that of other climatic zones. The majority of these genes were assigned to three bacterial phyla, Actinobacteria, Verrucomicrobia and Bacteroidetes. Anaerobic metabolic pathways and the fraction of methanogenic archaea increased with peat depth, evident for a gradual transition from aerobic to anaerobic lifestyles. A population of CH4-oxidising bacteria closely related to Methylobacter tundripaludum was the dominating active group of methanotrophs. Based on the in-depth characterisation of the microbes and their genes, we conclude that these Arctic peat soils will turn into CO2 sources owing to increased active layer depth and prolonged growing season. However, the extent of future CH4 emissions will critically depend on the response of the methanotrophic bacteria