Evidence map›Paper›PMID 41592123›Full record

ArticlePloS one2026

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

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

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Maor KnafoDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.ORCID https://orcid.org/0000-0002-3800-4555
Shahar RezenmanDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Tal IdanDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Michael ElgartMetabolomic Discovery Unit, Metabolic Center, Sheba Medical Center, Ramat Gan, Israel.
Shlomi DaganFisher Drug Discovery Resource Center, The Rockefeller University, New York, New York, United States of America.
Vered ZavaroDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Ziv ReichDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Ruti KaponDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Dagan SadeDepartment of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Noam ShentalDepartment of Mathematics and Computer Science, The Open University of Israel, Ra'anana, Israel.ORCID https://orcid.org/0000-0001-9645-3773

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BacteriaRNA, Ribosomal, 16SHigh-Throughput Nucleotide SequencingSequence Analysis, DNARNA, Ribosomal, 16S

Identifiers

PMID41592123
PMCPMC12844514

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.