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

Abstract

AbstractCharacterizing microbial communities at high-resolution is crucial to unravel the complexity and diversity of microbial ecosystems. Advances in bulk sequencing assays such as 16S rRNA and shotgun sequencing have enabled unparalleled qualitative and quantitative microbiota investigations. However, these methods generally do not provide accurate resolution beyond the genus or species level and lack insights into absolute microbial abundance. Here, we introduce Phylogenetically Unique Primers in python (PUPpy), a fully automated pipeline to design microbe- and group-specific primers within a given microbial community. PUPpy-designed primers detect individual microbes and quantify absolute microbial abundance in a defined community below the species level, requiring only coding sequence files of the community members as input. We experimentally evaluated the performance of PUPpy-designed primers using two bacterial communities as benchmarks. Each community was comprised of 10 members, exhibiting a range of genetic similarities that spanned from different phyla to substrains. PUPpy-designed primers also enabled the detection of groups of bacteria in an undefined community, such as the detection of a gut bacterial family in a complex stool microbiota sample. Taxon-specific primers designed with PUPpy showed 100% specificity to their intended targets, without unintended amplification, independently of community composition and complexity. Lastly, we show absolute quantification of microbial abundance using PUPpy-designed primers in droplet digital PCR (ddPCR), benchmarked against 16S rRNA and shotgun sequencing. Our data shows that PUPpy-designed microbe-specific primers can be used to quantify substrain-level absolute counts, providing more resolved and accurate quantification in defined communities than 16S rRNA and shotgun sequencing.ImportanceProfiling microbial communities at high resolution and with absolute quantification is essential to uncover hidden ecological interactions within microbial ecosystems. Nevertheless, achieving resolved and quantitative investigations has been elusive due to methodological limitations in distinguishing and quantifying highly related microbes. Here, we describe PUPpy, an automated computational pipeline to design taxon-specific primers within defined microbial communities. Taxon-specific primers can be used to selectively detect and quantify individual microbes and larger taxa within a microbial community. PUPpy achieves substrain-level specificity without the need for computationally intensive databases and prioritises user-friendliness by enabling both terminal and graphical user interface (GUI) applications. Altogether, PUPpy enables fast, inexpensive, and highly accurate perspectives into microbial ecosystems, supporting the characterization of bacterial communities in bothin vitroand complex microbiota settings.