Motivation: The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenetic resolution. Because 16S rRNA sequencing is more cost-effective than whole metagenome shotgun sequencing, marker gene analysis is frequently used for broad studies that involve a large number of different samples. However, in comparison to shotgun sequencing approaches, insights into the functional capabilities of the community get lost when restricting the analysis to taxonomic assignment of 16S rRNA data.Results: Tax4Fun is a software package that predicts the functional capabilities of microbial communities based on 16S rRNA datasets. We evaluated Tax4Fun on a range of paired metagenome/16S rRNA datasets to assess its performance. Our results indicate that Tax4Fun provides a good approximation to functional profiles obtained from metagenomic shotgun sequencing approaches.Availability and implementation: Tax4Fun is an open-source R package and applicable to output as obtained from the SILVAngs web server or the application of QIIME with a SILVA database extension. Tax4Fun is freely available for download at http://tax4fun.gobics.de/.Contact: kasshau@gwdg.deSupplementary information: Supplementary data are available at Bioinformatics online.

Phylogenetic surveys of soil ecosystems have shown that the number of prokaryotic species found in a single sample exceeds that of known cultured prokaryotes. Soil metagenomics, which comprises isolation of soil DNA and the production and screening of clone libraries, can provide a cultivation-independent assessment of the largely untapped genetic reservoir of soil microbial communities. This approach has already led to the identification of novel biomolecules. However, owing to the complexity and heterogeneity of the biotic and abiotic components of soil ecosystems, the construction and screening of soil-based libraries is difficult and challenging. This review describes how to construct complex libraries from soil samples, and how to use these libraries to unravel functions of soil microbial communities.

BackgroundSoil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition.Methodology/Principal FindingsWe used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found.Conclusions/SignificanceSoil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH.

Metagenomics has revolutionized microbiology by paving the way for a cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. Metagenomics comprising construction and screening of metagenomic DNA libraries has proven to be a powerful tool to isolate new enzymes and drugs of industrial importance. So far, the majority of the metagenomically exploited habitats comprised temperate environments, such as soil and marine environments. Recently, metagenomes of extreme environments have also been used as sources of novel biocatalysts. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body, and ocean water. Analyses of these data sets opened a window into the enormous taxonomic and functional diversity of environmental microbial communities. To assess the functional dynamics of microbial communities, metatranscriptomics and metaproteomics have been developed. The combination of DNA-based, mRNA-based, and protein-based analyses of microbial communities present in different environments is a way to elucidate the compositions, functions, and interactions of microbial communities and to link these to environmental processes.

BackgroundListeria monocytogenes is an important food-borne pathogen and model organism for host-pathogen interaction, thus representing an invaluable target considering research on the forces governing the evolution of such microbes. The diversity of this species has not been exhaustively explored yet, as previous efforts have focused on analyses of serotypes primarily implicated in human listeriosis. We conducted complete genome sequencing of 11 strains employing 454 GS FLX technology, thereby achieving full coverage of all serotypes including the first complete strains of serotypes 1/2b, 3c, 3b, 4c, 4d, and 4e. These were comparatively analyzed in conjunction with publicly available data and assessed for pathogenicity in the Galleria mellonella insect model.ResultsThe species pan-genome of L. monocytogenes is highly stable but open, suggesting an ability to adapt to new niches by generating or including new genetic information. The majority of gene-scale differences represented by the accessory genome resulted from nine hyper variable hotspots, a similar number of different prophages, three transposons (Tn916, Tn554, IS3-like), and two mobilizable islands. Only a subset of strains showed CRISPR/Cas bacteriophage resistance systems of different subtypes, suggesting a supplementary function in maintenance of chromosomal stability. Multiple phylogenetic branches of the genus Listeria imply long common histories of strains of each lineage as revealed by a SNP-based core genome tree highlighting the impact of small mutations for the evolution of species L. monocytogenes. Frequent loss or truncation of genes described to be vital for virulence or pathogenicity was confirmed as a recurring pattern, especially for strains belonging to lineages III and II. New candidate genes implicated in virulence function were predicted based on functional domains and phylogenetic distribution. A comparative analysis of small regulatory RNA candidates supports observations of a differential distribution of trans-encoded RNA, hinting at a diverse range of adaptations and regulatory impact.ConclusionsThis study determined commonly occurring hyper variable hotspots and mobile elements as primary effectors of quantitative gene-scale evolution of species L. monocytogenes, while gene decay and SNPs seem to represent major factors influencing long-term evolution. The discovery of common and disparately distributed genes considering lineages, serogroups, serotypes and strains of species L. monocytogenes will assist in diagnostic, phylogenetic and functional research, supported by the comparative genomic GECO-LisDB analysis server (http://bioinfo.mikrobio.med.uni-giessen.de/geco2lisdb).