Minimal Interspecies Interaction Adjustment (MIIA)

MIIA is a network inference tool for predicting member-dependent interactions in microbial communities, which can deepen our understanding of the organization principles in ecological communities.

This repository contains the MATLAB code and datasets used for demonstrating the original MIIA (Song et al., 2019) and the scaled MIIA (Lee et al., 2020).

System requirements

Matlab R2015b+ in Windows, Mac OS, Linux

Installation

1. Download 'runMiia.m' and all files in the 'data' folder.
2. Unzip ./data/glvData.zip under ./data if you want to test glv datasets (glv denotes datasets generated from a generalized Lotka-Volterra model).

Tutorial

To get started, move to the installation folder and type

runMiia

You can apply different MIIAs by commenting/uncommenting lines 5 to 11.

% Original MIIA: when species abundance data in axenic, binary, and complex
% communities is fully available.
% inferenceRule = 'miia1';

% Scaled MIIA: when only data from axenic cultures are unavailable, to pre-
% dict neighbor-dependent interactions in a relative sense
inferenceRule = 'miia2';

You can test with different datasets by commenting/uncommenting lines 13 to 17.

% dataSource = 'tutorial';
% dataSource = 'friedman';
% dataSource = 'glv';
% dataSource = 'wang';
dataSource = 'kato';

Datasets

1. Tutorial data

dataSource = 'tutorial'

Hypothetical datasets for illustration (Figure 1).

2. Friedman data

dataSource = 'friedman'

Datasets for eight competiting soil bacteria collected by Friedman et al. (2017).

3. In silico data generated by a generalized Lotka-Volterra model

dataSource = 'glv'

File name has the following format: glv_S_r_alpha_beta_trial.mat (S = # of species; r = growth rate; alpha = std of binary interaction coefficients, beta = std of interaction coefficients in complex communities deviating from binary coefficients; trial = # of random trials).

4. Wang data

dataSource = 'wang'

Datasets for three-member species derived from natural microbial community in a paddy soil, collected by Wang et al. (2017).

5. Kato data

dataSource = 'kato'

Datasets for four-member species isolated from a cellulose-degrading bacterial community enriched from a composting process, collected by Kato et al. (2008).

KBase Narrative

MIIA also has been implemented as a KBase App. Please refer to the demo narrative.

Citation

[1] Hyun-Seob Song, et al. (2019),Minimal Interspecies Interaction Adjustment (MIIA): inference of member-dependent interactions in microbiomes, Frontiers in Microbiology, 10, 1264. https://www.frontiersin.org/articles/10.3389/fmicb.2019.01264

[2] Joon-Yong Lee, et al. (2020),Prediction of Neighbor-dependent Microbial Interactions from Limited Population Data, Frontiers in Microbiology, 10, 3049. https://www.frontiersin.org/articles/10.3389/fmicb.2019.03049

Contacts

Hyun-Seob Song (hsong5@unl.edu); Joon-Yong Lee (joonyong.lee@pnnl.gov)