Evidence map›Paper›PMID 35108392›Full record

ReviewJournal of industrial microbiology & biotechnology2022

Practical genetic control strategies for industrial bioprocesses.

Jonathan C Moore, Itzel Ramos, Stephen Van Dien

Abstract readReview
In one paragraph

Review in Journal of industrial microbiology & biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

3 authors.

Jonathan C MooreNo current affiliation, Encinitas, CA 92024, USA.
Itzel RamosBP Biosciences Center, San Diego, CA 92121, USA.
Stephen Van DienPersephone Biosciences, San Diego, CA 92121, USA.ORCID 0000-0002-4133-3229

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimization of metabolism to maximize production of bio-based chemicals must consistently balance cellular resources for biocatalyst growth and desired compound synthesis. This mini-review discusses synthetic biology strategies for dynamically controlling expression of genes to enable dual-phase fermentations in which growth and production are separated into dedicated phases. Emphasis is placed on practical examples which can be reliably scaled to commercial production with the current state of technology. Recent case studies are presented, and recommendations are provided for environmental signals and genetic control circuits.

Indexed as

Metabolic EngineeringSynthetic BiologyFermentationGene Expression RegulationGene Regulatory NetworksDynamic controlGenetic circuitsSynthetic biology

Identifiers

PMID35108392
PMCPMC9118995

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.