Design of an Identifiable Synthetic Community of Microbes (DISCo-microbe)

Design of an Identifiable Synthetic Community of Microbes (DISCo-microbe) generates diverse, identifiable synthetic microbial communities from input DNA sequence alignments to enable experimental and ecological studies using next-generation sequencing technologies.

Key Features:

• Custom Nucleotide Distance Algorithm (create module): Applies a custom nucleotide distance algorithm within the "create" module to generate highly diverse candidate community members from input DNA sequence alignments.
• Subsampling Capabilities (subsample module): Uses the "subsample" module to tailor community composition based on taxonomic proportions or a user-defined maximum number of members.
• Input Alignment Support: Operates directly on input DNA sequence alignments as the basis for community design.
• Taxonomic Breadth: Although developed for bacterial studies, accepts alignments from any taxonomic group.
• NGS Identifiability: Designs communities specifically to be distinguishable using next-generation sequencing technologies.

Scientific Applications:

• In vivo experimentation: Enables construction of synthetic communities with known identities for controlled in vivo studies of microbial dynamics.
• Microbiome interaction studies: Facilitates investigation of interactions within microbiomes and their effects on host organisms.
• Ecological and evolutionary studies: Supports simulation of natural taxonomic proportions to study ecological and evolutionary questions in microbial communities.
• Host-associated microbiome modeling: Allows design of communities that mimic host-associated microbiomes, including plant-associated communities.

Methodology:

DISCo-microbe processes an input DNA sequence alignment, applies a custom nucleotide distance algorithm in the "create" module to generate a diverse list of candidate members, and then uses the "subsample" module to select members according to taxonomic proportions or a user-defined maximum number of members.