Enabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico models

Figures & data

Figure 1. Health outcomes emerge from individual microbes and their survival strategies. Nutrient availability, primarily dietary, but also host secretions, drive microbes to regulate their metabolic capabilities to survive. Individual microbes adapting to their nutritional environment reconfigures the gut microbiome metabolic network and community-level metabolic output. The resultant changes can impact on host health

Table 1. List of recommended computational resources for gut microbiome in silico modeling

Resource	Summary	Available from
Personal computer	Most in silico based approaches can be ran on a basic personal computer. High specifications (e.g. 8GB of RAM or higher) are recommended to reduce modeling times
High performance computing cluster	A network of fast interconnected computer servers that are more practical for running either: 1) very large scale simulations that a personal computer would struggle to handle or 2) very high-throughput experiments (many simulations) that a computing cluster can run in a massively parallel fashion.	Most universities and research institutes now provide such facilities at modest, if not zero, cost. Alternatively, cloud-based systems such as Amazon Web Services could be set up to support such work, though this often comes at a cost.
COBRA Toolbox^Citation132	MATLAB-based software suite for modeling genome-scale metabolic networks and predicting phenotypes	https://opencobra.github.io/cobratoolbox/stable/index.html
COBRApy^Citation133	Python package for modeling and analyzing genome-scale metabolic networks	https://opencobra.github.io/cobrapy/
MICOM^Citation115	Python package for metabolic modeling of microbial communities	https://github.com/micom-dev/micom
μbialSim	A dynamic Flux-Balance-Analysis-based simulator for complex microbial communities	https://git.ufz.de/UMBSysBio/microbialsim
AutoKEEGRec^Citation134	A KEGG databases-based tool to create draft GSMs and community reconstructions, that is compatible with COBRA Toolbox	https://almaaslab.nt.ntnu.no/index.php/resources/
ModelSEED^Citation135	A web resource to create GSMs from Rapid Annotation of microbial genomes using Subsystems Technology (RAST)	https://modelseed.org/
KBase^Citation136	Open source platform that allows the creation and curation of GSMs among other functions	https://kbase.us/applist/
AGORA^Citation120	A collection of 818 GSMs for human gut microbes compatible with COBRA Toolbox and COBRApy	https://www.vmh.life/#microbes/search
GutSim^Citation40	An ABM that integrates gut environmental pressures such as peristalsis, mucin secretion and host feeding regimens.	https://github.com/marknormanread/GutSim

Figure 2. In vivo, in vitro and in silico methods each contribute complementary insights that are collectively necessary to understand gut ecology and manipulate it to achieve specific outcomes

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