PUPpy: a primer design pipeline for substrain-level microbial detection and absolute quantification

Area of Science:

• Microbiology
• Bioinformatics
• Molecular Biology

Background:

• Accurate characterization of microbial communities is vital for understanding ecosystem dynamics.
• PCR assays offer selective detection and absolute quantification of microbial DNA, but primer design specificity remains a challenge.
• Distinguishing and quantifying highly related microbes in complex ecosystems is difficult with current methods.

Purpose of the Study:

• To introduce Phylogenetically Unique Primers in python (PUPpy), an automated pipeline for designing microbe- and group-specific primers.
• To enable high-resolution, absolute quantification of microbial abundance, even at the substrain level.
• To provide a user-friendly tool for designing taxon-specific primers for diverse microbial community analyses.

Main Methods:

• Developed an automated computational pipeline, PUPpy, for primer design using only coding sequence files.
• Executed PUPpy via a graphical user interface and terminal commands.
• Experimentally validated PUPpy-designed primers using bacterial communities with varying genetic similarities.

Main Results:

• PUPpy successfully designed taxon-specific primers with 100% specificity in tested communities.
• PUPpy primers enabled detection of individual microbes and groups of bacteria, including in complex microbiota samples.
• Absolute quantification using PUPpy primers in droplet digital PCR demonstrated higher resolution and accuracy than 16S rRNA and shotgun sequencing.

Conclusions:

• PUPpy provides a fast, inexpensive, and highly accurate method for microbial community profiling.
• The designed primers facilitate substrain-level absolute quantification, improving microbiome research accuracy.
• PUPpy supports the characterization of bacterial communities in both controlled and complex natural settings.