Uncovering Mechanistic Determinants of Host Phenotypes Using Microbial Systems Biology

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ID: 314873
2026
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Abstract
Abstract Host phenotypes are caused by a multitude of interacting factors, including but not limited to the microbiome. The advent of high throughput sequencing technology revolutionized our ability to characterize host-associated microbial communities. Early microbiome profiling studies often focused on strategies such as 16S rRNA gene amplicon sequencing to assess the relative abundance of host-associated microbiota. Waves of technological improvement and an ever-increasing knowledge base led to accessible multiomic profiling (i.e. integration of multiple different ‘omics assays). Rather than just associating phenotypes with patterns of microbial taxa, we can leverage multiple omics to advance mechanistic explanations for how microbiota cause or are affected by host phenotypes. However, it is still challenging to determine which assays (or combinations of assays) to use and how best to integrate their results. We review bioinformatic strategies for integrating diverse microbiome sequencing data and experimental approaches for validating correlative findings. We also present perspectives on how systems biology connects observational and experimental microbiology. We analyze the strengths of different ‘omics methods and how complementary combinations economically improves biological discovery. Augmenting relative abundance data with absolute quantitation (i.e. exact measurement of microbial biomass) can dramatically change the resulting insights. Functional profiling (i.e. measurement of microbial gene content or expression using high-throughput sequencing) ultimately enables linking microbial profiles with phenotypic trait expression. Finally, while many sequencing studies are observational and thus limited to correlative findings, it is critical to integrate experimental validation to mechanistically explain relationships between the microbiome and host phenotypes. Host-associated microbial ecosystems are complex. Confounded microbial and host factors make it challenging to determine the mechanisms underlying host-microbiome dynamics. Innovative experimental systems, including non-model organisms, synthetic consortia, and tissue-culture models, enable high-throughput manipulation of microbiomes to test hypotheses generated from correlative results and advance translational research.
Reference Key
openalex_W7162300761 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jack T. Sumner, Erica M. Hartmann
Journal integrative and comparative biology
Year 2026
DOI
10.1093/icb/icag052
URL
https://doi.org/10.1093/icb/icag052
Keywords Keywords not found

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