Technical variation in metagenomic analysis must be minimized to confidently assess the contributions of microbiota to human health. Here we tested 21 representative DNA extraction protocols on the same fecal samples and quantified differences in observed microbial community composition. We compared them with differences due to library preparation and sample storage, which we contrasted with observed biological variation within the same specimen or within an individual over time. We found that DNA extraction had the largest effect on the outcome of metagenomic analysis. To rank DNA extraction protocols, we considered resulting DNA quantity and quality, and we ascertained biases in estimates of community diversity and the ratio between Gram-positive and Gram-negative bacteria. We recommend a standardized DNA extraction method for human fecal samples, for which transferability across labs was established and which was further benchmarked using a mock community of known composition. Its adoption will improve comparability of human gut microbiome studies and facilitate meta-analyses.

Summary: MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assignments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes.Availability and Implementation: MOCAT2 is implemented in Perl 5 and Python 2.7, designed for 64-bit UNIX systems and offers support for high-performance computer usage via LSF, PBS or SGE queuing systems; source code is freely available under the GPL3 license at http://mocat.embl.de.Contact: bork@embl.deSupplementary information: Supplementary data are available at Bioinformatics online.

The whole zebrafish embryo model (ZFE) has proven its applicability in developmental toxicity testing. Since functional hepatocytes are already present from 36 h post fertilization onwards, whole ZFE have been proposed as an attractive alternative to mammalian in vivo models in hepatotoxicity testing. The goal of the present study is to further underpin the applicability of whole ZFE for hepatotoxicity testing by combining histopathology and next-generation sequencing-based gene expression profiling. To this aim, whole ZFE and adult zebrafish were exposed to a set of hepatotoxic reference compounds. Histopathology revealed compound and life-stage-specific effects indicative of toxic injury in livers of whole ZFE and adult zebrafish. Next-generation sequencing (NGS) was used to compare transcript profiles in pooled individual RNA samples of whole ZFE and livers of adult zebrafish. This revealed that hepatotoxicity-associated expression can be detected beyond the overall transcription noise in the whole embryo. In situ hybridization verified liver specificity of selected highly expressed markers in whole ZFE. Finally, cyclosporine A (CsA) was used as an illustrative case to support applicability of ZFE in hepatotoxicity testing by comparing CsA-induced gene expression between ZFE, in vivo mouse liver and HepaRG cells on the levels of single genes, pathways and transcription factors. While there was no clear overlap on single gene level between the whole ZFE and in vivo mouse liver, strong similarities were observed between whole ZFE and in vivo mouse liver in regulated pathways related to hepatotoxicity, as well as in relevant overrepresented transcription factors. In conclusion, both the use of NGS of pooled RNA extracts analysis combined with histopathology and traditional microarray in single case showed the potential to detect liver-related genes and processes within the transcriptome of a whole zebrafish embryo. This supports the applicability of the whole ZFE model for compound-induced hepatotoxicity screening.