Evidence map›Paper›PMID 37995242›Full record

ArticleScience (New York, N.Y.)2023

Uncovering the functional diversity of rare CRISPR-Cas systems with deep terascale clustering.

Han Altae-Tran, Soumya Kannan, Anthony J Suberski, Kepler S Mears, F Esra Demircioglu, Lukas Moeller, Selin Kocalar, Rachel Oshiro, Kira S Makarova, Rhiannon K Macrae and 2 more

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing 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

99 citing papers in PubMed.

  1. Article
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  9. Structural mechanism of SAM-AMP and SAM-AMPNature communications · 2026
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  18. Review
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39 more citing papers are in PubMed but not listed here.

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

12 authors.

Han Altae-Tran *Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0003-1083-4802
Soumya Kannan *Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0002-7332-9662
Anthony J Suberski *Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Kepler S Mears *Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
F Esra DemirciogluHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0002-3866-2742
Lukas MoellerHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0002-4375-8837
Selin KocalarHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0003-4521-8647
Rachel OshiroHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0003-0948-6361
Kira S MakarovaNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.ORCID 0000-0002-8174-2844
Rhiannon K MacraeHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0002-7850-9056
Eugene V KooninNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.ORCID 0000-0003-3943-8299
Feng ZhangHoward Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.ORCID 0000-0003-0178-7995

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Microbial systems underpin many biotechnologies, including CRISPR, but the exponential growth of sequence databases makes it difficult to find previously unidentified systems. In this work, we develop the fast locality-sensitive hashing-based clustering (FLSHclust) algorithm, which performs deep clustering on massive datasets in linearithmic time. We incorporated FLSHclust into a CRISPR discovery pipeline and identified 188 previously unreported CRISPR-linked gene modules, revealing many additional biochemical functions coupled to adaptive immunity. We experimentally characterized three HNH nuclease-containing CRISPR systems, including the first type IV system with a specified interference mechanism, and engineered them for genome editing. We also identified and characterized a candidate type VII system, which we show acts on RNA. This work opens new avenues for harnessing CRISPR and for the broader exploration of the vast functional diversity of microbial proteins.

Indexed as

CRISPR-Associated ProteinsCRISPR-Cas SystemsData MiningGene EditingAlgorithmsCluster AnalysisDatasets as TopicDNA CleavageHEK293 CellsHumansRNA, Guide, CRISPR-Cas SystemsCRISPR-Associated ProteinsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID37995242
PMCPMC10910872

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.