High-throughput sequencing of ribosomal RNA gene (rDNA) amplicons has opened up the door to large-scale comparative studies of microbial community structures. The short reads currently produced by massively parallel sequencing technologies make the choice of sequencing region crucial for accurate phylogenetic assignments. While for 16S rDNA, relevant regions have been well described, no truly systematic design of 18S rDNA primers aimed at resolving eukaryotic diversity has yet been reported. Here we used 31,862 18S rDNA sequences to design a set of broad-taxonomic range degenerate PCR primers. We simulated the phylogenetic information that each candidate primer pair would retrieve using paired- or single-end reads of various lengths, representing different sequencing technologies. Primer pairs targeting the V4 region performed best, allowing discrimination with paired-end reads as short as 150 bp (with 75% accuracy at genus level). The conditions for PCR amplification were optimised for one of these primer pairs and this was used to amplify 18S rDNA sequences from isolates as well as from a range of environmental samples which were then Illumina sequenced and analysed, revealing good concordance between expected and observed results. In summary, the reported primer sets will allow minimally biased assessment of eukaryotic diversity in different microbial ecosystems.

Perturbations to the colonization process of the human gastrointestinal tract have been suggested to result in adverse health effects later in life. Although much research has been performed on bacterial colonization and succession, much less is known about the other two domains of life, archaea and eukaryotes. Here we describe the colonization and succession by bacteria, archaea and microeukaryotes during the first year of life (samples collected around days 1, 3, 5, 28, 150 and 365) within the gastrointestinal tract of infants delivered either vaginally or by caesarean section and using a combination of quantitative real-time PCR as well as 16S and 18S rRNA gene sequencing. Sequences from organisms belonging to all three domains of life were detectable in all of the collected meconium samples. The microeukaryotic community composition fluctuated strongly over time and early diversification was delayed in infants receiving formula milk. Caesarean section-delivered (CSD) infants experienced a delay in colonization and succession, which was observed for all three domains of life. Shifts in prokaryotic succession in CSD infants compared to vaginally delivered (VD) infants were apparent as early as on days 3 and 5, which were characterized by increased relative abundances of the genera Streptococcus and Staphylococcus, and a decrease in relative abundance for the genera Bifidobacterium and Bacteroides. Generally, a depletion in Bacteroidetes was detected as early as day 5 postpartum in CSD infants, causing a significantly increased Firmicutes/Bacteroidetes ratio between days 5 and 150 when compared to VD infants. Although the delivery mode appeared to have the strongest influence on differences between the infants, other factors such as a younger gestational age or maternal antibiotics intake likely contributed to the observed patterns as well. Our findings complement previous observations of a delay in colonization and succession of CSD infants, which likely affects not only bacteria but also archaea and microeukaryotes. This further highlights the need for resolving bacterial, archaeal and microeukaryotic dynamics in future longitudinal studies of microbial colonization and succession within the neonatal gastrointestinal tract.

Methylotrophy describes the ability of organisms to grow on reduced organic compounds without carbon-carbon bonds. The genomes of two pink-pigmented facultative methylotrophic bacteria of the Alpha-proteobacterial genus Methylobacterium, the reference species Methylobacterium extorquens strain AM1 and the dichloromethane-degrading strain DM4, were compared. The 6.88 Mb genome of strain AM1 comprises a 5.51 Mb chromosome, a 1.26 Mb megaplasmid and three plasmids, while the 6.12 Mb genome of strain DM4 features a 5.94 Mb chromosome and two plasmids. The chromosomes are highly syntenic and share a large majority of genes, while plasmids are mostly strain-specific, with the exception of a 130 kb region of the strain AM1 megaplasmid which is syntenic to a chromosomal region of strain DM4. Both genomes contain large sets of insertion elements, many of them strain-specific, suggesting an important potential for genomic plasticity. Most of the genomic determinants associated with methylotrophy are nearly identical, with two exceptions that illustrate the metabolic and genomic versatility of Methylobacterium. A 126 kb dichloromethane utilization (dcm) gene cluster is essential for the ability of strain DM4 to use DCM as the sole carbon and energy source for growth and is unique to strain DM4. The methylamine utilization (mau) gene cluster is only found in strain AM1, indicating that strain DM4 employs an alternative system for growth with methylamine. The dcm and mau clusters represent two of the chromosomal genomic islands (AM1: 28; DM4: 17) that were defined. The mau cluster is flanked by mobile elements, but the dcm cluster disrupts a gene annotated as chelatase and for which we propose the name “island integration determinant” (iid). These two genome sequences provide a platform for intra- and interspecies genomic comparisons in the genus Methylobacterium, and for investigations of the adaptive mechanisms which allow bacterial lineages to acquire methylotrophic lifestyles.

Anaerobic digestion (AD) is a microbe-driven process of biomass decomposition to CH4 and CO2. In addition to renewable and cost-effective energy production, AD has emerged in the European Union as an environmentally friendly model of bio-waste valorisation and nutrient recycling. Nevertheless, due to the high diversity of uncharacterised microbes, a typical AD microbiome is still considered as “dark matter”. Using the high-throughput sequencing of small rRNA gene, and a monthly monitoring of the physicochemical parameters for 20 different mesophilic full-scale bioreactors over 1 year, we generated a detailed view of AD microbial ecology towards a better understanding of factors that influence and shape these communities. By studying the broadly distributed OTUs present in over 80% of analysed samples, we identified putatively important core bacteria and archaea to the AD process that accounted for over 70% of the whole microbial community relative abundances. AD reactors localised at the wastewater treatment plants were shown to operate with distinct core microbiomes than the agricultural and bio-waste treating biogas units. We also showed that both the core microbiomes were composed of low (with average community abundance ≤ 1%) and highly abundant microbial populations; the vast majority of which remains yet uncharacterised, e.g. abundant candidate Cloacimonetes. Using non-metric multidimensional scaling, we observed microorganisms grouping into clusters that well reflected the origin of the samples, e.g. wastewater versus agricultural and bio-waste treating biogas units. The calculated diversity patterns differed markedly between the different community clusters, mainly due to the presence of highly diverse and dynamic transient species. Core microbial communities appeared relatively stable over the monitoring period. In this study, we characterised microbial communities in different AD systems that were monitored over a 1-year period. Evidences were shown to support the concept of a core community driving the AD process, whereas the vast majority of dominant microorganisms remain yet to be characterised.

Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license).

The moose (Alces alces) is a ruminant that harvests energy from fiber-rich lignocellulose material through carbohydrate-active enzymes (CAZymes) produced by its rumen microbes. We applied shotgun metagenomics to rumen contents from six moose to obtain insights into this microbiome. Following binning, 99 metagenome-assembled genomes (MAGs) belonging to 11 prokaryotic phyla were reconstructed and characterized based on phylogeny and CAZyme profile. The taxonomy of these MAGs reflected the overall composition of the metagenome, with dominance of the phyla Bacteroidetes and Firmicutes. Unlike in other ruminants, Spirochaetes constituted a significant proportion of the community and our analyses indicate that the corresponding strains are primarily pectin digesters. Pectin-degrading genes were also common in MAGs of Ruminococcus, Fibrobacteres and Bacteroidetes and were overall overrepresented in the moose microbiome compared with other ruminants. Phylogenomic analyses revealed several clades within the Bacteriodetes without previously characterized genomes. Several of these MAGs encoded a large numbers of dockerins, a module usually associated with cellulosomes. The Bacteroidetes dockerins were often linked to CAZymes and sometimes encoded inside polysaccharide utilization loci, which has never been reported before. The almost 100 CAZyme-annotated genomes reconstructed in this study provide an in-depth view of an efficient lignocellulose-degrading microbiome and prospects for developing enzyme technology for biorefineries.