MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce     

Characterization of the Gut Microbial Community of Obese Patients Following a Weight-Loss Intervention Using Whole Metagenome Shotgun Sequencing

Background/Objectives

Cross-sectional studies suggested that obesity is promoted by the gut microbiota. However, longitudinal data on taxonomic and functional changes in the gut microbiota of obese patients are scarce. The aim of this work is to study microbiota changes in the course of weight loss therapy and the following year in obese individuals with or without co-morbidities, and to asses a possible predictive value of the gut microbiota with regard to weight loss maintenance.

Subjects/Methods

Sixteen adult patients, who followed a 52-week weight-loss program comprising low calorie diet, exercise and behavioral therapy, were selected according to their weight-loss course. Over two years, anthropometric and metabolic parameters were assessed and microbiota from stool samples was functionally and taxonomically analyzed using DNA shotgun sequencing.

Results

Overall the microbiota responded to the dietetic and lifestyle intervention but tended to return to the initial situation both at the taxonomical and functional level at the end of the intervention after one year, except for an increase in Akkermansia abundance which remained stable over two years (12.7x10³ counts, 95%CI: 322–25100 at month 0; 141x10³ counts, 95%CI: 49-233x10³ at month 24; p = 0.005). The Firmicutes/Bacteroidetes ratio was higher in obese subjects with metabolic syndrome (0.64, 95%CI: 0.34–0.95) than in the “healthy obese” (0.27, 95%CI: 0.08–0.45, p = 0.04). Participants, who succeeded in losing their weight consistently over the two years, had at baseline a microbiota enriched in Alistipes, Pseudoflavonifractor and enzymes of the oxidative phosphorylation pathway compared to patients who were less successful in weight reduction.

Conclusions

Successful weight reduction in the obese is accompanied with increased Akkermansia numbers in feces. Metabolic co-morbidities are associated with a higher Firmicutes/Bacteroidetes ratio. Most interestingly, microbiota differences might allow discrimination between successful and unsuccessful weight loss prior to intervention.