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Record W2143226881 · doi:10.1186/1475-2859-9-81

Two-stage, self-cycling process for the production of bacteriophages

2010· article· en· W2143226881 on OpenAlexafffund
Dominic Sauvageau, David G. Cooper

Bibliographic record

VenueMicrobial Cell Factories · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMultiplicity of infectionInfectivityCyclingBiologyBacteriaMicrobiologyMultiplicity (mathematics)Cell cycleFermentationChemistryFood scienceCellBiochemistryMathematicsVirologyGeneticsVirus

Abstract

fetched live from OpenAlex

BACKGROUND: A two-stage, self-cycling process for the production of bacteriophages was developed. The first stage, containing only the uninfected host bacterium, was operated under self-cycling fermentation (SCF) conditions. This automated method, using the derivative of the carbon dioxide evolution rate (CER) as the control parameter, led to the synchronization of the host bacterium. The second stage, containing both the host and the phage, was operated using self-cycling infection (SCI) with CER and CER-derived data as the control parameters. When each infection cycle was terminated, phages were harvested and a new infection cycle was initiated by adding host cells from the SCF (first stage). This was augmented with fresh medium and the small amount of phages left from the previous cycle initiated the next infection cycle. Both stages were operated independently, except for this short period of time when the SCF harvest was added to the SCI to initiate the next cycle. RESULTS: It was demonstrated that this mode of operation resulted in stable infection cycles if the growth of the host cells in the SCF was synchronized. The final phage titers obtained were reproducible among cycles and were as good as those obtained in batch productions performed under the same conditions (medium, temperature, initial multiplicity of infection, etc.). Moreover, phages obtained in different cycles showed no important difference in infectivity. Finally, it was shown that cell synchronization of the host cells in the first stage (SCF) not only maintained the volumetric productivity (phages per volume) but also led to higher specific productivity (phage per cell per hour) in the second stage (SCI). CONCLUSIONS: Production of bacteriophage T4 in the semi-continuous, automated SCF/SCI system was efficient and reproducible from cycle to cycle. Synchronization of the host in the first stage prior to infection led to improvements in the specific productivity of phages in the second stage while maintaining the volumetric productivity. These results demonstrate the significant potential of this approach for both upstream and downstream process optimization.

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)0.001
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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

Citations52
Published2010
Admission routes2
Has abstractyes

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