Evidence map›Paper›PMID 40920712›Full record

ArticlePloS one2025

Optimizing recombinant mini proinsulin production via response surface method and microbioreactor screening.

Esra Ayan, Ali Özhan Aytekin, Ahmet Kati, Hasan Demirci

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Esra AyanDepartment of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye.ORCID https://orcid.org/0000-0001-7906-4426
Ali Özhan AytekinGenetics and Bioengineering Department, Engineering Faculty, Yeditepe University, Istanbul, Türkiye.
Ahmet KatiCenter for Targeted Therapy Technologies, Bogazici University, Istanbul, Türkiye.ORCID https://orcid.org/0000-0002-9903-634X
Hasan DemirciDepartment of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing demand for efficient recombinant insulin production necessitates the development of scalable, high-yield, and cost-effective bioprocesses. In this study, we engineered a novel mini-proinsulin (nMPI) with enhanced expression properties by shortening the C-peptide and incorporating specific residue substitutions to eliminate the need for enzymatic cleavage. To optimize its production, we applied a hybrid approach combining microscale high-throughput cultivation using the BioLector microbioreactor and statistical modeling via response surface methodology (RSM). Critical medium components were first screened using Plackett-Burman Design (PBD) and refined through Central Composite Design (CDD), identifying glycerol as the most influential factor for yield. Among the four statistically derived formulations, Scenario III demonstrated the highest productivity in the microscale platform (13.00 g/L) and maintained strong performance upon scale-up to a 3-L bioreactor (11.5 g/L). The optimized medium balanced carbon and nitrogen sources to enhance cell viability and maximize protein expression. This study not only confirms the predictive accuracy and scalability of the hybrid optimization system but also introduces a robust production platform for nMPI that can be translated into industrial settings. The workflow presented here can serve as a model for the development of efficient expression systems for complex recombinant proteins in E. coli.

Indexed as

BioreactorsProinsulinRecombinant ProteinsCulture MediaEscherichia coliGlycerolCulture MediaGlycerolProinsulinRecombinant Proteins

Identifiers

PMID40920712
PMCPMC12416663

What OpenQuestion holds

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Registered trials

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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.