# CoSMIC: A hybrid approach for large-scale, high-resolution microbial profiling of novel niches

**Authors:** Maor Knafo, Shahar Rezenman, Tal Idan, Michael Elgart, Shlomi Dagan, Vered Zavaro, Ziv Reich, Ruti Kapon, Dagan Sade, Noam Shental, Theodore Muth, Theodore Muth, Theodore Muth

PMC · DOI: 10.1371/journal.pone.0340349 · 2026-01-27

## TL;DR

CoSMIC is a new method for microbial profiling that combines long-read and short-read sequencing to improve accuracy and resolution in unexplored environments.

## Contribution

CoSMIC introduces a hybrid sequencing approach that enhances microbial profiling by integrating long-read and short-read data with novel primer strategies.

## Key findings

- CoSMIC outperforms standard methods in specificity and sensitivity for full-length 16S gene identification.
- The method achieves high resolution at a lower cost compared to traditional long-read sequencing.
- CoSMIC detected thousands of novel full-length 16S sequences across environmental samples.

## Abstract

Standard microbial profiling based on 16S rRNA (16S) sequencing suffers from a lack of primer universality, primer biases, and often yields low resolution. We introduce ‘Comprehensive Small Ribosomal Subunit Mapping and Identification of Communities’ (CoSMIC), addressing these challenges, especially in unexplored niches. CoSMIC begins with long-read sequencing of the full-length 16S gene, amplified by generic Locked Nucleic Acid primers over pooled samples, thus augmenting reference databases with novel niche-specific gene sequences. Subsequently, CoSMIC amplifies multiple non-consecutive variable regions along the gene, followed by short-read sequencing of each sample. Data from the different regions are integrated using the SMURF framework, alleviating primer biases and providing de facto full gene resolution. Using a mock community, CoSMIC identified full-length 16S genes with significantly higher specificity and sensitivity while dramatically increasing resolution compared to standard methods. Evaluating CoSMIC across environmental samples yielded higher accuracy and unparalleled resolution at a fraction of the cost of standard long-read sequencing per sample while allowing the detection of thousands of novel full-length 16S sequences.

## Linked entities

- **Genes:** 16S rRNA (16S ribosomal RNA) [NCBI Gene 2597965], 16S (DNA segment, 16S) [NCBI Gene 27471]

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12844514/full.md

---
Source: https://tomesphere.com/paper/PMC12844514