Evidence map›Paper›PMID 34347108›Full record

ReviewJournal of industrial microbiology & biotechnology2021

Effective use of biosensors for high-throughput library screening for metabolite production.

Jennifer A Kaczmarek, Kristala L J Prather

Open access · goldAbstract readReview
In one paragraph

Review in Journal of industrial microbiology & biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
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

29 citing papers in PubMed, 62 citations in OpenAlex.

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  20. OptimizingFrontiers in microbiology · 2024
    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

2 authors at 1 institution in 1 country.

Jennifer A KaczmarekDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge 02142, USA.
Kristala L J PratherDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge 02142, USA.
NOAA Chemical Sciences Laboratory · US

Funding

MITNational Science Foundation
6 · The paper itself

Abstract

The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.

Indexed as

Biosensing TechniquesHigh-Throughput Screening AssaysGene LibraryMetabolic EngineeringPromoter Regions, GeneticTranscription FactorsTranscription FactorsBiosensorsDirected evolutionHigh-throughput screeningMetabolic engineeringTranscription factor

Identifiers

PMID34347108
PMCPMC8788864
OpenAlexW3187776647

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.