Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software.

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

A manually curated compendium of expression profiles for the microbial cell factory Corynebacterium glutamicum.

Corynebacterium glutamicum is the major host for the industrial production of amino acids and has become one of the best studied model organisms in microbial biotechnology. Rational strain construction has led to an improvement of producer strains and to a variety of novel producer strains with a broad substrate and product spectrum. A key factor for the success of these approaches is detailed knowledge of transcriptional regulation in C. glutamicum. Here, we present a large compendium of 927 manually curated microarray-based transcriptional profiles for wild-type and engineered strains detecting genome-wide expression changes of the 3,047 annotated genes in response to various environmental conditions or in response to genetic modifications. The replicates within the 927 experiments were combined to 304 microarray sets ordered into six categories that were used for differential gene expression analysis. Hierarchical clustering confirmed that no outliers were present in the sets. The compendium provides a valuable resource for future fundamental and applied research with C. glutamicum and contributes to a systemic understanding of this microbial cell factory. Measurement(s) Gene Expression Analysis Technology Type(s) Two Color Microarray Factor Type(s) WT condition A vs. WT condition B • Plasmid-based gene overexpression in parental strain vs. parental strain with empty vector control • Deletion mutant vs. parental strain Sample Characteristic - Organism Corynebacterium glutamicum Sample Characteristic - Environment laboratory environment Sample Characteristic - Location Germany.

Nutrient-driven genome evolution revealed by comparative genomics of chrysomonad flagellates.

Phototrophic eukaryotes have evolved mainly by the primary or secondary uptake of photosynthetic organisms. A return to heterotrophy occurred multiple times in various protistan groups such as Chrysophyceae, despite the expected advantage of autotrophy. It is assumed that the evolutionary shift to mixotrophy and further to heterotrophy is triggered by a differential importance of nutrient and carbon limitation. We sequenced the genomes of 16 chrysophyte strains and compared them in terms of size, function, and sequence characteristics in relation to photo-, mixo- and heterotrophic nutrition. All strains were sequenced with Illumina and partly with PacBio. Heterotrophic taxa have reduced genomes and a higher GC content of up to 59% as compared to phototrophic taxa. Heterotrophs have a large pan genome, but a small core genome, indicating a differential specialization of the distinct lineages. The pan genome of mixotrophs and heterotrophs taken together but not the pan genome of the mixotrophs alone covers the complete functionality of the phototrophic strains indicating a random reduction of genes. The observed ploidy ranges from di- to tetraploidy and was found to be independent of taxonomy or trophic mode. Our results substantiate an evolution driven by nutrient and carbon limitation.

Intraspecific Variation in Protists: Clues for Microevolution from Poteriospumella lacustris (Chrysophyceae).

Species delimitation in protists is still a challenge, attributable to the fact that protists are small, difficult to observe and many taxa are poor in morphological characters, whereas most current phylogenetic approaches only use few marker genes to measure genetic diversity. To address this problem, we assess genome-level divergence and microevolution in strains of the protist Poteriospumella lacustris, one of the first free-living, nonmodel organisms to study genome-wide intraspecific variation. Poteriospumella lacustris is a freshwater protist belonging to the Chrysophyceae with an assumed worldwide distribution. We examined three strains from different geographic regions (New Zealand, China, and Austria) by sequencing their genomes with the Illumina and PacBio platforms. The assembled genomes were small with 49-55 Mb but gene-rich with 16,000-19,000 genes, of which ∼8,000 genes could be assigned to functional categories. At least 68% of these genes were shared by all three species. Genetic variation occurred predominantly in genes presumably involved in ecological niche adaptation. Most surprisingly, we detected differences in genome ploidy between the strains (diploidy, triploidy, and tetraploidy). In analyzing intraspecific variation, several mechanisms of diversification were identified including SNPs, change of ploidy and genome size reduction.

CAMISIM: simulating metagenomes and microbial communities.

BACKGROUND: Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. RESULTS: We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM. CONCLUSIONS: CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.