Ines Thiele

TL;DR: In this paper , the authors report the first use of constraint-based microbial community modelling on a single individual with IBD, covering seven dates over 16 months, enabling them to identify a number of time-correlated microbial species and metabolites.

TL;DR: DistributedFBA.jl as discussed by the authors is a high-level, high-performance, open-source implementation of flux balance analysis in Julia, tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks.

TL;DR: This paper presents a meta-analysis of Metabolic-Expression networks, a large and comprehensive networks that explicitly accounts for the demands of macromolecular synthesis at single nucleotide resolution, which shows how reaction rates can vary over many orders of magnitude.

Abstract: The effects of the microbiome on the hosts metabolism are core to understanding the role of the microbiome in health and disease. Herein, we develop the paradigm of in silico in vivo association pattern analyses, entailing a methodology to combine microbiome metabolome association studies with in silico constraint-based microbial community modelling. By dissecting confounding and causal paths, we show that in silico in vivo association pattern analyses allows for causal inference on microbiome-metabolome relations in observational data. Then, we demonstrate the feasibility and validity of our approach on a published multi-omics dataset (n=346), demonstrating causal microbiome-metabolite relations for 43 out of 53 metabolites from faeces. Finally, we utilise the identified in silico in vivo association pattern to estimate the microbial component of the faecal metabolome, revealing that the retrieved metabolite prediction scores correlate with the measured metabolite concentrations, and they also reflect the multivariate structure of the faecal metabolome. Concluding, we integrate with hypothesis free screening association studies and knowledge-based in silico modelling two major paradigms of systems biology, generating a promising new paradigm for causal inference in metabolic host-microbe interactions.

TL;DR: The first use of constraint-based microbial community modeling on a single individual with episodic inflammation of the gastrointestinal tract, who has a well documented set of colonic inflammatory biomarkers, as well as metagenomically-sequenced fecal time series covering seven dates over 16 months, was reported in this article .