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Record W4407630519 · doi:10.1186/s12934-025-02661-9

Cell-free expression system: a promising platform for bacteriophage production and engineering

2025· review· en· W4407630519 on OpenAlexaff
Hanzada T. Nour El‐Din, Maryam Kettal, Serena Lam, Danielle L. Peters, Wangxue Chen

Bibliographic record

VenueMicrobial Cell Factories · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsBrock UniversityNational Research Council Canada
Fundersnot available
KeywordsSynthetic biologyCell-free protein synthesisBacteriophageProtein engineeringBiologyComputational biologyMetabolic engineeringProtein biosynthesisRibosomeProtein expressionCellEnzymeCell biologyBiochemistryEscherichia coliRNAGene

Abstract

fetched live from OpenAlex

Cell-free expression is a technique used to synthesize proteins without utilising living cells. This technique relies mainly on the cellular machinery -ribosomes, enzymes, and other components - extracted from cells to produce proteins in vitro. Thus far, cell-free expression systems have been used for an array of biologically important purposes, such as studying protein functions and interactions, designing synthetic pathways, and producing novel proteins and enzymes. In this review article, we aim to provide bacteriophage (phage) researchers with an understanding of the cell-free expression process and the potential it holds to accelerate phage production and engineering for phage therapy and other applications. Throughout the review, we summarize the system's main steps and components, both generally and particularly for the self-assembly and engineering of phages and discuss their potential optimization for better protein and phage production. Cell-free expression systems have the potential to serve as a platform for the biosynthetic production of personalized phage therapeutics. This is an area of in vitro biosynthesis that is becoming increasingly attractive, given the current high interest in phages and their promising potential role in the fight against antimicrobial resistant infections.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2025
Admission routes1
Has abstractyes

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