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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Plasmid vectors for gene editing and genetic engineering: Design principles, efficiency, and applications

Authors: Sokra, In; Meta, Horn; Lika, Rithy; Socheata, Chey; Somaly, Srun;

Plasmid vectors for gene editing and genetic engineering: Design principles, efficiency, and applications

Abstract

Plasmid vectors remain central to gene editing and genetic engineering, providing flexible, modular, and cost-effective platforms for genome manipulation across microbial, plant, and eukaryotic systems. Continuous advances in synthetic biology, metabolic engineering, and CRISPR–Cas technologies have driven significant evolution in plasmid design, emphasizing precision, stability, and host adaptability. Modern plasmid vectors integrate optimized origins of replication, regulatory elements, selectable markers, and programmable editing modules to support diverse applications ranging from functional genomics to industrial bioproduction. Despite their widespread adoption, plasmid-based systems face inherent challenges, including metabolic burden, structural instability, off-target activity, and regulatory constraints. This review systematically examines the design principles governing plasmid vectors, evaluates their efficiency in gene editing workflows, and highlights their applications across biological domains. Particular attention is given to CRISPR-compatible plasmids, broad-host-range vectors, and advanced architectures supporting base and prime editing. By synthesizing recent evidence from microbial, agricultural, and biotechnological studies, this review provides a comprehensive framework for rational plasmid vector selection and future optimization strategies in gene editing and genetic engineering.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green