There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce Microbiome sequencing projects continue to grow rapidly, both in the number of samples considered and sequencing reads collected. With MEGAN Community Edition (CE), we provide a highly efficient program for interactive analysis and comparison of such data, allowing one to explore hundreds of samples and billions of reads. While taxonomic profiling is performed based on the NCBI taxonomy, we provide a number of different functional profiling approaches such as SEED, eggNOG, KEGG, and a new InterPro2GO classification scheme. MEGAN CE also supports the use of metadata in the context of principal coordinate analysis and clustering analysis.

Microbial nitrogen transformation processes such as denitrification represent major sources of the potent greenhouse gas nitrous oxide (N₂O). Soil biochar amendment has been shown to significantly decrease N₂O emissions in various soils. However, the effect of biochar on the structure and function of microbial communities that actively perform nitrogen redox transformations has not been studied in detail yet. To analyse the community composition of actively denitrifying and N₂O-reducing microbial communities, we collected RNA samples at different time points from a soil microcosm experiment conducted under denitrifying conditions and performed Illumina amplicon sequencing targeting nirK, typical nosZ and atypical nosZ mRNA transcripts. Within 10 days, biochar significantly increased the diversity of nirK and typical nosZ transcripts and resulted in taxonomic shifts among the typical nosZ-expressing microbial community. Furthermore, biochar addition led to a significant increase in transcript production among microbial species that are specialized on direct N₂O reduction from the environment. Our results point towards a potential coupling of biochar-induced N₂O emission reduction and an increase in microbial N₂O reduction activity among specific groups of typical and atypical N₂O reducers. However, experiments with other soils and biochars will be required to verify the transferability of these findings to other soil-biochar systems.

The human gut forms a dynamic reservoir of antibiotic resistance genes (ARGs). Treatment with antimicrobial agents has a significant impact on the intestinal resistome and leads to enhanced horizontal transfer and selection of resistance. We have monitored the development of intestinal ARGs over a 6-day course of ciprofloxacin (Cp) treatment in two healthy individuals by using sequenced-based metagenomics and different ARG quantification methods. Fixed- and random-effect models were applied to determine the change in ARG abundance per defined daily dose of Cp as an expression of the respective selection pressure. Among various shifts in the composition of the intestinal resistome, we found in one individual a strong positive selection for class D beta-lactamases which were partly located on a mobile genetic element. Furthermore, a trend to a negative selection has been observed with class A beta-lactamases (−2.66 hits per million sample reads/defined daily dose; P = 0.06). By 4 weeks after the end of treatment, the composition of ARGs returned toward their initial state but to a different degree in both subjects. We present here a novel analysis algorithm for the determination of antibiotic selection pressure which can be applied in clinical settings to compare therapeutic regimens regarding their effect on the intestinal resistome. This information is of critical importance for clinicians to choose antimicrobial agents with a low selective force on their patients' intestinal ARGs, likely resulting in a diminished spread of resistance and a reduced burden of hospital-acquired infections with multidrug-resistant pathogens.

In soils halogens (fluorine, chlorine, bromine, iodine) are cycled through the transformation of inorganic halides into organohalogen compounds and vice versa. There is evidence that these reactions are microbially driven but the key enzymes and groups of microorganisms involved are largely unknown. Our aim was to uncover the diversity, abundance and distribution of genes encoding for halogenating and dehalogenating enzymes in a German forest soil by shotgun metagenomic sequencing. Metagenomic libraries of three soil horizons revealed the presence of genera known to be involved in halogenation and dehalogenation processes such as Bradyrhizobium or Pseudomonas. We detected a so far unknown diversity of genes encoding for (de)halogenating enzymes in the soil metagenome including specific and unspecific halogenases as well as metabolic and cometabolic dehalogenases. Genes for non-heme, no-metal chloroperoxidases and haloalkane dehalogenases were the most abundant halogenase and dehalogenase genes, respectively. The high diversity and abundance of (de)halogenating enzymes suggests a strong microbial contribution to natural halogen cycling. This was also confirmed in microcosm experiments in which we quantified the biotic formation of chloroform and bromoform. Knowledge on microorganisms and genes that catalyze (de)halogenation reactions is critical because they are highly relevant to industrial biotechnologies and bioremediation applications.