Evidence map›Paper›PMID 36074282›Full record

ArticleBiotechnology letters2022

Genome-scale metabolic model-based engineering of Escherichia coli enhances recombinant single-chain antibody fragment production.

Aidin Behravan, Atieh Hashemi, Sayed-Amir Marashi, Hamideh Fouladiha

Abstract read
PubMed Publisher
In one paragraph

Article in Biotechnology letters, 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
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  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

4 authors at 3 institutions in 1 country.

Aidin BehravanDepartment of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, ValiAsr Avenue, Niayesh Junction, PO Box 14155-6153, Tehran, Iran.ORCID http://orcid.org/0000-0002-7218-4262
Atieh HashemiDepartment of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, ValiAsr Avenue, Niayesh Junction, PO Box 14155-6153, Tehran, Iran. At_hashemi@sbmu.ac.ir.ORCID http://orcid.org/0000-0001-7121-5306
Sayed-Amir MarashiDepartment of Biotechnology, College of Science, University of Tehran, Shafiei Str. 13, Qods Str., Enghelab Avenue, PO Box 1417614411, Tehran, Iran. marashi@ut.ac.ir.ORCID http://orcid.org/0000-0001-9801-7449
Hamideh FouladihaDepartment of Biotechnology, College of Science, University of Tehran, Shafiei Str. 13, Qods Str., Enghelab Avenue, PO Box 1417614411, Tehran, Iran.ORCID http://orcid.org/0000-0002-5522-8809
University of Tehran · IRShahid Beheshti University · IRShahid Beheshti University of Medical Sciences · IR

Funding

research deputy of Shahid Beheshti University of Medical Sciences IR.SBMU.PHARMACY.REC.1399.372
6 · The paper itself

Abstract

purposeEscherichia coli is an attractive and cost-effective cell factory for producing recombinant proteins such as single-chain variable fragments (scFvs). AntiEpEX-scFv is a small antibody fragment that has received considerable attention for its ability to target the epithelial cell adhesion molecule (EpCAM), a cancer-associated biomarker of solid tumors. Due to its metabolic burden, scFv recombinant expression causes a remarkable decrease in the maximum specific growth rate of the scFv-producing strain. In the present study, a genome-scale metabolic model (GEM)-guided engineering strategy is proposed to identify gene targets for improved antiEpEX-scFv production in E. coli.

methodsIn this study, a genome-scale metabolic model of E. coli (iJO1366) and a metabolic modeling tool (FVSEOF) were employed to find appropriate genes to be amplified in order to improve the strain for incresed production of antiEpEX-scFv. To validate the model predictions, one target gene was overexpressed in the parent strain Escherichia coli BW25113 (DE3).

resultsFor improving scFv production, we applied the FVSEOF method to identify a number of potential genetic engineering targets. These targets were found to be localized in the glucose uptake system and pentose phosphate pathway. From the predicted targets, the glk gene encoding glucokinase was chosen to be overexpressed in the parent strain Escherichia coli BW25113 (DE3). By overexpressing glk, the growth capacity of the recombinant E. coli strain was recovered. Moreover, the engineered strain with glk overexpression successfully led to increased scFv production.

conclusionThe genome-scale metabolic modeling can be considered for the improvement of the production of other recombinant proteins.

Indexed as

Escherichia coliMetabolic EngineeringSingle-Chain AntibodiesBiomarkersEpithelial Cell Adhesion MoleculeGlucokinaseGlucoseRecombinant ProteinsBiomarkersEpithelial Cell Adhesion MoleculeGlucokinaseGlucoseRecombinant ProteinsSingle-Chain AntibodiesAntiEpEX-scFvEscherichia coliFVSEOFGenome-scale metabolic modelglkGlucokinase

Identifiers

PMID36074282
OpenAlexW4294992573

What OpenQuestion holds

Textmetadata
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.