4.6 Review

Key Technologies for Progressing Discovery of Microbiome-Based Medicines

Journal

FRONTIERS IN MICROBIOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2021.685935

Keywords

microbiome; faecal transplant; gastrointestinal disorder; 16S rRNA sequencing; metagenomic sequencing; microbial genomics; bacteriotherapy; live biotherapeutics

Categories

Funding

  1. Australian National Health and Medical Research Council [1159239, 1141564, 1181105, 1186371]
  2. Victorian Government's Operational Infrastructure Support Program
  3. Australian Government Research Training Program (RTP) scholarship
  4. National Health and Medical Research Council of Australia [1186371, 1181105, 1159239, 1141564] Funding Source: NHMRC

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The human microbiome presents great potential as therapeutic target for various diseases, with causal links between microbiome and diseases being essential for more efficacious treatments. Generating hypotheses using multi-omic functional analyses and validating them in relevant experimental models are crucial for determining causation and advancing microbiome research. Future progress in this field relies on effective integration of state-of-the-art sequencing approaches, computational analyses, and experimental assays.
A growing number of experimental and computational approaches are illuminating the microbial dark matter and uncovering the integral role of commensal microbes in human health. Through this work, it is now clear that the human microbiome presents great potential as a therapeutic target for a plethora of diseases, including inflammatory bowel disease, diabetes and obesity. The development of more efficacious and targeted treatments relies on identification of causal links between the microbiome and disease; with future progress dependent on effective links between state-of-the-art sequencing approaches, computational analyses and experimental assays. We argue determining causation is essential, which can be attained by generating hypotheses using multi-omic functional analyses and validating these hypotheses in complex, biologically relevant experimental models. In this review we discuss existing analysis and validation methods, and propose best-practice approaches required to enable the next phase of microbiome research.

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