The fungal component of the human gut microbiome, also known as the mycobiome, plays a vital role in intestinal ecology and human health. However, the overall structure of the gut mycobiome as well as the inter-individual variations in fungal composition remains largely unknown. In this study, we collected a total of 3363 fungal sequencing samples from 16 cohorts across three continents, including 572 newly profiled samples from China.

Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain-resolved, integrated meta-genomic, transcriptomic, and proteomic analyses of paired saliva and stool samples collected from 35 individuals from eight families with multiple cases of type 1 diabetes mellitus (T1DM).

Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes.

Shotgun metagenomes contain a sample of all the genomic material in an environment, allowing for the characterization of a microbial community. In order to understand these communities, bioinformatics methods are crucial. A common first step in processing metagenomes is to compute abundance estimates of different taxonomic or functional groups from the raw sequencing data. Given the breadth of the field, computational solutions need to be flexible and extensible, enabling the combination of different tools into a larger pipeline.

Gut microbes influence their hosts in many ways, in particular by modulating the impact of diet. These effects have been studied most extensively in humans and mice. In this work, we used whole genome metagenomics to investigate the relationship between the gut metagenomes of dogs, humans, mice, and pigs.

16S ribosomal DNA (rDNA) amplicon sequencing is frequently used to analyse the structure of bacterial communities from oceans to the human microbiota. However, computational power is still a major bottleneck in the analysis of continuously enlarging metagenomic data sets. Analysis is further complicated by the technical complexity of current bioinformatics tools.

Background: 16S ribosomal DNA (rDNA) amplicon sequencing is frequently used to analyse the structure of bacterial communities from oceans to the human microbiota. However, computational power is still a major bottleneck in the analysis of continuously enlarging metagenomic data sets. Analysis is further complicated by the technical complexity of current bioinformatics tools. Results: Here we present the less operational taxonomic units scripts (LotuS), a fast and user-friendly open-source tool to calculate denoised, chimera-checked, operationa l taxonomic units (OTUs). These are the basis to generate taxonomic abundance tables and phylogenetic trees from multiplexed, next-generation sequencing data (454, illumina MiSeq and HiSeq). LotuS is outstanding in its execution speed, as it can process 16S rDNA data up to two orders of magnitude faster than other existing pipelines. This is partly due to an included stand-alone fast simultaneous demultiplexer and quality filter C++ program, simple demultiplexer (sdm), which comes packaged with LotuS. Additionally, we sequenced two MiSeq runs with the intent to validate future pipelines by sequencing 40 technical replicates; these are made available in this work. Conclusion: We show that LotuS analyses microbial 16S data with comparable or even better results than existing pipelines, requiring a fraction of the execution time and providing state-of-the-art denoising and phylogenetic reconstruction. LotuS is available through the following URL: http://psbweb05.psb.ugent.be/lotus. Keywords: OTU, 16S rDNA gene, Pipeline, Metagenomics, Demultiplexing [This corrects the article on p. 30 in vol. 2.].