Modelling approaches for studying the microbiome

@article{Kumar2019ModellingAF,
  title={Modelling approaches for studying the microbiome},
  author={Manish Kumar and Boyang Ji and Karsten Zengler and Jens B Nielsen},
  journal={Nature Microbiology},
  year={2019},
  volume={4},
  pages={1253-1267}
}
Advances in metagenome sequencing of the human microbiome have provided a plethora of new insights and revealed a close association of this complex ecosystem with a range of human diseases. However, there is little knowledge about how the different members of the microbial community interact with each other and with the host, and we lack basic mechanistic understanding of these interactions related to health and disease. Mathematical modelling has been demonstrated to be highly advantageous for… 

Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists

TLDR
A review of the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems, and how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.

Understanding the host-microbe interactions using metabolic modeling

TLDR
This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health.

Synthetic gut microbiome: Advances and challenges

Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes.

TLDR
Factors that give rise to emergent spatial and temporal microbiome properties and the meta-omics and computational modeling tools that can be used to understand microbiomes at the cellular and system levels are described.

Metabolic modeling of the International Space Station microbiome reveals key microbial interactions

TLDR
A computational approach to predict possible metabolic interactions in the ISS microbiome and shed further light on its organization demonstrates the potential for understanding the organization of other such microbiomes, unravelling key organisms and their interdependencies.

Microbial Systems Ecology to Understand Cross-Feeding in Microbiomes

TLDR
An overview of a MSE framework mostly based on genome-scale metabolic-network reconstruction that combines top-down and bottom-up approaches to assess the molecular mechanisms of deterministic processes of microbial community assembly that is particularly suitable for use in synthetic biology and microbiome engineering is provided.

Integration of constraint-based modeling with fecal metabolomics reveals large deleterious effects of Fusobacterium spp. on community butyrate production

TLDR
Insight is provided into the metabolic role of Fusobacterium spp.

Ecology-guided prediction of cross-feeding interactions in the human gut microbiome

TLDR
Close to 65% of the cross-feeding interactions predicted by GutCP are supported by evidence from genome annotation; this method has the potential to greatly improve existing models of the human gut microbiome, as well as the ability to predict the metabolic profile of the gut.
...

References

SHOWING 1-10 OF 146 REFERENCES

Towards predictive models of the human gut microbiome.

Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules

TLDR
The approach presented here lays the foundation for a reverse-ecology framework for addressing key questions concerning the assembly of host-associated communities and for informing clinical efforts to manipulate the microbiome.

Understanding the interactions between bacteria in the human gut through metabolic modeling

TLDR
This work reconstructed GEMs for three key species, (Bacteroides thetaiotamicron, Eubacterium rectale and Methanobrevibacter smithii) as relevant representatives of three main phyla in the human gut and demonstrated that these models can be used as a scaffold for understanding bacterial interactions in the gut.

Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease

TLDR
A system-level approach lays the foundation for a unique framework for studying the human microbiome, its organization, and its impact on human health, by integrating metagenomic data with an in silico systems-level analysis of metabolic networks.

MICOM: metagenome-scale modeling to infer metabolic interactions in the gut microbiota

TLDR
It is shown that growth rates vary greatly across samples and that there exists a network of bacteria implicated in health and disease that mutually influence each others growth rates.

Metaproteomics as a Complementary Approach to Gut Microbiota in Health and Disease

TLDR
Some of the main limitations of metaproteomic studies in complex microbiota environments, such as the gut are presented, also addressing the up-to-date pipelines in sample preparation prior to fractionation/separation and mass spectrometry analysis.

Mathematical modeling of primary succession of murine intestinal microbiota

TLDR
The next-generation sequencing and mathematical models were used to quantify the interpopulation interactions that occurred after a germfree mouse was inoculated with a murine microbiome, and suggested a lack of mutualistic interactions within the community.

Metabolic modeling with Big Data and the gut microbiome

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

TLDR
An agent-based model of interactions between two bacterial species and between species and the gut shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.
...