Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities

Area of Science:

• Microbiology and Bioinformatics
• Computational Biology and Genomics

Background:

• Microbial biofilms are complex communities crucial for nutrient production, colonization, and survival.
• Biofilms significantly impact plant and human health, necessitating advanced analytical methods.
• Metagenomics offers powerful insights into biofilm composition but requires specialized bioinformatics skills.

Purpose of the Study:

• To develop an accessible, dockerized, self-learning bioinformatics workflow for microbial biofilm metagenomics.
• To facilitate community adoption of metagenomic tools for analyzing biofilm microbial communities.
• To provide a comprehensive tutorial for understanding and implementing biofilm metagenomic analyses.

Main Methods:

• A cloud-based, dockerized workflow with integrated learning resources and interactive modules.
• Utilizing Nextflow pipelines for data processing and Vertex AI Jupyter notebooks for downstream analysis.
• Storing and visualizing results in Google Cloud storage to manage computational load.

Main Results:

• A user-friendly workflow that simplifies complex bioinformatics analyses for users of all skill levels.
• Enhanced accessibility to metagenomic and meta-transcriptomic investigation tools for biofilm research.
• A comprehensive tutorial integrated into the NIGMS Sandbox for Cloud-based Learning.

Conclusions:

• The developed workflow democratizes biofilm metagenomic analysis, enabling broader research participation.
• Cloud and containerization technologies significantly lower the barrier to entry for bioinformatics tool usage.
• This resource supports the validation and advancement of scientific findings in microbial ecology and health.