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Record W4307811795 · doi:10.1101/2022.10.26.513969

Synergistic interactions among <i>Burkholderia cepacia</i> complex (Bcc)-targeting phages reveal a novel therapeutic role for lysogenization-capable (LC) phages

2022· preprint· en· W4307811795 on OpenAlexaff
Philip Lauman, Jonathan J. Dennis

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLysogenLysogenic cycleBiologyPhage therapyLytic cycleMicrobiologyBurkholderia cepacia complexBurkholderiaBacteriophageAntibiotic resistanceVirulenceAntibioticsProphageVirologyBacteriaGeneticsGeneEscherichia coliVirus

Abstract

fetched live from OpenAlex

ABSTRACT Antimicrobial resistance is an imminent danger to global public health and threatens virtually all aspects of modern medicine. Particularly concerning are the species of the Burkholderia cepacia complex (Bcc), which cause life-threatening respiratory infections among patients who are immunocompromised or afflicted with cystic fibrosis, and are notoriously resistant to antibiotics. One promising alternative being explored to combat Bcc infections is phage therapy (PT) - the use of phages to treat bacterial infections. Unfortunately, the utility of PT against many pathogenic species, including the Bcc, is limited by the prevailing paradigm of PT: that only obligately lytic phages, which are rare, should be used therapeutically - due to the conviction that so-called ‘lysogenic’ phages do not reliably clear bacteria and instead form lysogens to which they may transfer antimicrobial resistance or virulence factors. In this study, we argue that the tendency of a lysogenization-capable (LC) phage to form stable lysogens is not predicated exclusively on its ability to do so, and that this property, along with the therapeutic suitability of the phage, must be evaluated on a case-by-case basis. Concordantly we developed several novel metrics - Efficiency of Phage Activity (EPA), Growth Reduction Coefficient (GRC), and Lysogenization Frequency ( f (lys) ) and used them to evaluate eight phages targeting members of the Bcc. We found that while these parameters vary considerably among Bcc phages, a strong inverse correlation exists between lysogen-formation and antibacterial activity, indicating that certain LC phages may be highly efficacious on their own. Moreover, we show that many LC Bcc phages interact synergistically with other phages in the first reported instance of mathematically defined polyphage synergy, and that these interactions result in the eradication of in-vitro bacterial growth. Together, these findings reveal a novel therapeutic role for LC phages, and challenge the current paradigm of PT. IMPORTANCE The spread of antimicrobial resistance is an imminent threat to public health around the world. Particularly concerning are the species of the Burkholderia cepacia complex (Bcc), which cause life-threatening respiratory infections and are notoriously resistant to antibiotics. Phage therapy (PT) is a promising alternative being explored to combat Bcc infections and antimicrobial resistance in general, but the utility of PT against many pathogenic species, including the Bcc, is restricted by the currently prevailing paradigm of exclusively using rare obligately lytic phages - due to the perception that ‘lysogenic’ phages are therapeutically unsuitable. Our findings show that many lysogenization-capable (LC) phages exhibit powerful in vitro antibacterial activity both alone and through mathematically defined synergistic interactions with other phages, demonstrating a novel therapeutic role for LC phages and therefore challenging the currently prevailing paradigm of PT.

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 score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.238
Teacher spread0.219 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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