Conservation of the glycogen metabolism pathway underlines a pivotal function of storage polysaccharides in Chlamydiae.

The order Chlamydiales includes obligate intracellular pathogens capable of infecting mammals, fishes and amoeba. Unlike other intracellular bacteria for which intracellular adaptation led to the loss of glycogen metabolism pathway, all chlamydial families maintained the nucleotide-sugar dependent glycogen metabolism pathway i.e. the GlgC-pathway with the notable exception of both Criblamydiaceae and Waddliaceae families. Through detailed genome analysis and biochemical investigations, we have shown that genome rearrangement events have resulted in a defective GlgC-pathway and more importantly we have evidenced a distinct trehalose-dependent GlgE-pathway in both Criblamydiaceae and Waddliaceae families. Altogether, this study strongly indicates that the glycogen metabolism is retained in all Chlamydiales without exception, highlighting the pivotal function of storage polysaccharides, which has been underestimated to date. We propose that glycogen degradation is a mandatory process for fueling essential metabolic pathways that ensure the survival and virulence of extracellular forms i.e. elementary bodies of Chlamydiales.

MATAM: reconstruction of phylogenetic marker genes from short sequencing reads in metagenomes.

Motivation: Advances in the sequencing of uncultured environmental samples, dubbed metagenomics, raise a growing need for accurate taxonomic assignment. Accurate identification of organisms present within a community is essential to understanding even the most elementary ecosystems. However, current high-throughput sequencing technologies generate short reads which partially cover full-length marker genes and this poses difficult bioinformatic challenges for taxonomy identification at high resolution. Results: We designed MATAM, a software dedicated to the fast and accurate targeted assembly of short reads sequenced from a genomic marker of interest. The method implements a stepwise process based on construction and analysis of a read overlap graph. It is applied to the assembly of 16S rRNA markers and is validated on simulated, synthetic and genuine metagenomes. We show that MATAM outperforms other available methods in terms of low error rates and recovered fractions and is suitable to provide improved assemblies for precise taxonomic assignments. Availability and implementation: https://github.com/bonsai-team/matam. Contact: pierre.pericard@gmail.com or helene.touzet@univ-lille1.fr. Supplementary information: Supplementary data are available at Bioinformatics online.