Evidence map›Paper›PMID 41635682›Full record

ReviewFrontiers in plant science2025

Advances in promoter engineering strategies for enhanced recombinant protein expression in plants.

Shekoofeh Sadravi, June Lee, Jianfeng Xu

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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.

Shekoofeh SadraviArkansas Biosciences Institute, Arkansas State University, Jonesboro, AR, United States.
June LeeDepartment of Biological Sciences, Arkansas State University, Jonesboro, AR, United States.
Jianfeng XuArkansas Biosciences Institute, Arkansas State University, Jonesboro, AR, United States.

Funding

Engineering novel designer biologics in plant cells for oral treatment of ulcerative colitisR15DK128757 · NIDDK · ARKANSAS STATE UNIVERSITY · PI XU, JIANFENG · 2021 to 2021
$395k
NIDDK NIH HHS R15 DK128757
6 · The paper itself

Abstract

Plant-based expression systems, known as molecular farming, have emerged as sustainable and scalable platforms for producing recombinant proteins used in pharmaceuticals, industrial enzymes, and agricultural products. Among the key determinants of transgene performance, promoter elements play a central role in defining transcriptional strength, specificity, and regulation. This review highlights current advances in promoter engineering tailored for plant systems, encompassing natural, synthetic, hybrid, inducible, and tissue-specific promoters used in stable transgenic plants, transient expression systems, and plant cell cultures. The structural and functional features of promoter elements are discussed, along with strategies to mitigate challenges such as transcriptional silencing, genomic context dependency, and variability cross species and production platform. Emerging synthetic biology tools, such as CRISPR-based transcriptional control, high-throughput screening, and machine learning-assisted promoter design, are enabling the creation of tunable, orthogonal promoters suited for complex multigene expression. As promoter engineering continues to evolve, it remains foundational to advancing plant molecular farming and expanding the role of plants as versatile biofactories for high-value recombinant proteins.

Indexed as

molecular farmingpromoter engineeringrecombinant protein expressionsynthetic biologytransgene regulation

Identifiers

PMID41635682
PMCPMC12862067

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.