Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

TL;DR

This paper presents TransNet, a systems biology method that integrates multi-omics data to identify causal relationships between host and microbiota, addressing computational challenges and enhancing data analysis.

Contribution

It introduces a novel transkingdom network analysis protocol for integrating diverse omics data to uncover causal host-microbiota interactions.

Findings

Successfully identified causal relationships between mammals and microbes

Demonstrated effectiveness of the TransNet protocol in multi-omics integration

Addressed computational complexity in high-throughput data analysis

Abstract

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of data.