Experimental design and quantitative analysis of microbial community multiomics

Area of Science:

• Microbiome Molecular Epidemiology
• Human Health Research

Background:

• Microbiome studies have advanced with sophisticated molecular and culture-based profiling methods.
• Linking host and microbial data to human health requires addressing experimental design, data analysis, and statistical epidemiology.

Purpose of the Study:

• To survey best practices in microbiome molecular epidemiology.
• To highlight technologies for generating, analyzing, and integrating multiomics microbiome data.
• To suggest steps for scaling translational microbiome research for high-throughput target discovery.

Main Methods:

• Review of current best practices in experimental design for microbiome molecular epidemiology.
• Survey of technologies for microbiome multiomics data generation, analysis, and integration.
• Identification of studies linking molecular bioactives to human health.

Main Results:

• Identified key considerations for experimental design in microbiome molecular epidemiology.
• Highlighted technologies for comprehensive microbiome data analysis and integration.
• Showcased examples of molecular bioactives influencing human health.

Conclusions:

• Best practices are crucial for robust microbiome molecular epidemiology.
• Advanced multiomics integration is key to understanding host-microbiome interactions.
• Scaling research is essential for high-throughput discovery of microbiome-derived health targets.