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Record W3035259135 · doi:10.1101/2020.06.15.151498

Mobile element warfare via CRISPR and anti-CRISPR in <i>Pseudomonas aeruginosa</i>

2020· preprint· en· W3035259135 on OpenAlexfundno aff
Lina M León, Allyson E. Park, Adair L. Borges, Jenny Y. Zhang, Joseph Bondy‐Denomy

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersNational Institutes of HealthUniversity of California, San FranciscoUniversity of TorontoMontana State UniversitySandler FoundationInnovative Genomics InstituteVallee FoundationHoward Hughes Medical Institute
KeywordsCRISPRMobile genetic elementsTrans-activating crRNAPseudomonas aeruginosaBiologyMutagenesisTransposable elementGeneticsDNAComputational biologyGenomeCas9BacteriaGeneMutation

Abstract

fetched live from OpenAlex

SUMMARY Bacteria deploy multiple defense mechanisms to prevent the invasion of mobile genetic elements (MGEs). CRISPR-Cas systems use RNA-guided nucleases to target MGEs, which in turn produce anti-CRISPR (Acr) proteins that inactivate Cas protein effectors. The minimal component Type I-C CRISPR-Cas subtype is highly prevalent in bacteria, and yet a lack of a tractable in vivo model system has slowed its study, the identification of cognate Acr proteins, and thus our understanding of its true role in nature. Here, we describe MGE-MGE conflict between a mobile Pseudomonas aeruginosa Type I-C CRISPR-Cas system always encoded on pKLC102-like conjugative elements, which are large mobile islands, and seven new Type I-C anti-CRISPRs (AcrIF2*, AcrIC3-IC8) encoded by phages, other mobile islands, and transposons. The P. aeruginosa Type I-C system possesses a total of 300 non-redundant spacers (from 980 spacers total) across the 42 genomes analyzed, predominantly targeting P. aeruginosa phages. Of the seven new Type I-C anti-CRISPRs, all but one are highly acidic, and four have surprisingly broad inhibition activity, blocking multiple distantly related P. aeruginosa Type I CRISPR system subtypes (e.g. I-C and I-F, or I-C and I-E), including AcrIF2 (now, AcrIF2*), a previously described DNA mimic. Anti-type I-C activity of AcrIF2* was far more sensitive to mutagenesis of acidic residues in AcrIF2* than anti-type I-F activity, suggesting distinct binding mechanisms for this highly negatively charged protein. Five of the seven Acr proteins block DNA-binding, while the other two act downstream of DNA-binding, likely by preventing Cas3 recruitment or activity. For one such Cas3 inhibitor (AcrIC3), we identify a novel anti-CRISPR evasion strategy: a cas3-cas8 gene fusion, which also occurs in nature. Collectively, the Type I-C CRISPR spacer diversity and corresponding anti-CRISPR response, all occurring on Pseudomonas MGEs, demonstrates an active co-evolutionary battle between parasitic elements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.247
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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