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gene editing

461 papers

#gene editing Open access Aug 2026

Comparative chloroplast genomics of six Bupleurum (Apiaceae) accessions: candidate barcodes, phylogeny based on available plastomes, and candidate RNA-editing sites

The whole-plastome phylogeny recovered Bupleurum as monophyletic relative to Chamaesium, and only one of seven multi-accession operational binomial groups was monophyletic, and only one showed a positive local barcode gap.

Yujie He, Mingxuan Wu, Aohan Wang et al. · 0 citations

An Explicit Interaction-Prompted Diffusion Framework for High-Fidelity 3D Molecular Generation.

Current structure-based drug design generative models often struggle to faithfully recapitulate genuine ligand-protein binding interactions. Instead, under the coupling of implicit learning architectures and biased training data, they tend to learn spurious statistical correlations. To address this, we propose EIP-Diff (Explicit Interaction-Prompted Diffusion), an architecture featuring a novel explicit interaction-prompt embedding mechanism that is better suited for real-world target-specific drug design. This architecture replaces biased implicit learning with explicit, residue-level biological guidance, thereby promoting more fine-grained geometric fidelity and more precise interaction-aware conditioning. To fully realize the capabilities of EIP-Diff and provide a reliable basis for performance evaluation, we further constructed CrystalData set, which provides higher-fidelity and less-biased structural supervision than existing data sets. This explicit architecture markedly improves distribution consistency: even when trained on the crossdocked data set, EIP-Diff achieves the highest alignment with authentic pharmacological distributions among evaluated models. Training on CrystalData set further enhances this alignment and improves 3D geometric accuracy, while retaining strong controllability, high chemical space coverage, and near-perfect uniqueness. In addition, target-based validation on KAT6A and YTHDC1 confirmed that EIP-Diff accurately recapitulates native-like binding modes. Furthermore, in a real-world drug design task against IDO1, we successfully designed a novel lead compound with nanomolar potency (IC50 = 0.31 nM). These results demonstrate that the EIP-Diff architecture can explicitly leverage experimentally derived structural data and biologically meaningful interaction information for target-specific molecular generation, thereby enabling its effective application to real-world structure-based drug design.

Huabin Du, Mingyang Wang, M. Luo et al. · 0 citations
#gene editing Review Aug 2026

Universal CAR-T cell therapy: mechanisms and evasion strategies of bidirectional immune rejection.

This review systematically delineates the mechanisms underlying bidirectional immune rejection and comprehensively summarizes state-of-the-art mitigation strategies and highlights the development of alternative, inherently hypoimmunogenic cell sources as a fundamental approach to circumventing these immunological barriers.

Lu Ding, Lianfeng Zhao, Mengting Zhang et al. · 0 citations
#gene editing Open access Aug 2026

Analysing long-read CRISPR experiments with CRISPRLungo.

This work presents CRISPRLungo, a computational pipeline specifically designed for long-read amplicon sequencing of gene edited samples that incorporates unique molecular identifier-based error correction and statistical filtering to distinguish true editing events from background noise, enabling robust detection of small indels and structural variants.

Gue-Ho Hwang, Benjamin Vyshedskiy, Timothy M. Barry et al. · 0 citations
#gene editing Aug 2026

Identification of root system architecture associated genes, regulatory network, and expression analysis under abiotic stress in maize.

expression modules suggest that Zm00001eb403030 (RTCL1) and auxin-associated regulators modulate post-embryonic root initiation and branching, and the current investigation outlines a stress-responsive maize RSA network and identifies targets for functional validation, genome editing, and breeding climate-resilient cultivars.

G. M. Keerthi, M. Mallikarjuna, H. C. Lohithaswa et al. · 0 citations
#gene editing Review Aug 2026

Gene-edited hypoimmune islets as a cure for type 1 diabetes: a review of the immunological challenges.

Current preclinical and clinical evidence from 2019 to 2026 for gene-edited hypoimmune islets is critically evaluated, highlighting key immunological vulnerabilities that may emerge over time and whether these long-term challenges can be overcome.

Ahmed Hassanein, F. Cyprian, Saghir Akhtar · 0 citations
#gene editing Open access Aug 2026

Expansion and optimization of the auxin-inducible degron 2 (AID2) system in Candida pathogens

ABSTRACT The auxin-inducible degron (AID) technology is a convenient and powerful tool for protein functional characterization in a broad array of eukaryotic species. We recently demonstrated that the original AID and improved AID2 systems are very effective at rapid protein depletion in Candida albicans, and described a limited set of reagents for their use in certain auxotrophic lab strains. With an eye toward broader applicability with improved flexibility, we report here a new series of template vectors suitable for employing AID2 technology in prototrophic C. albicans strains, such as clinical isolates and the reference strain SC5314. We adapted a common recyclable antibiotic marker system for the required genome editing steps, and developed a strategy for simultaneous CRISPR/Cas9-mediated tagging of both target alleles. We also developed a composite all-in-one tagging cassette that combines the degron tag and the OsTIR1F74A gene for single-step strain engineering. We added a fluorescent protein tag option and designed and validated an approach for N-terminal tagging that retains natural promoter control. We also compared the effectiveness of the two commonly used synthetic auxins, 5-phenyl-indole-3-acetic acid and 5-adamantyl-indole-3-acetic acid, and the two common OsTIR1 variants, F74A and F74G, and provide guidelines for using the new AID2 system. Finally, using the novel all-in-one cassette, we demonstrate that the AID2 system also works in Candida auris, albeit less effectively under some conditions. The new reagents should enhance the convenience and accessibility of the AID2 system for the Candida research community. IMPORTANCE Invasive fungal infections, including those caused by Candida species, are a persistent global health problem, and their treatment is hindered by limited antifungal options and the emergence of drug resistance. There is an urgent need for tools and methods to accelerate the discovery of novel therapeutic targets. The expanded and optimized auxin-inducible degron system described herein provides a versatile platform for characterizing protein function and dissecting pathways governing important traits like virulence, stress tolerance, and antifungal resistance. The new reagents make AID technology applicable to any strain. Ultimately, this enhanced toolkit has the potential to help identify and validate new high‑value drug targets and deepen our understanding of molecular mechanisms that drive pathogenicity of Candida and other fungal pathogen species. Invasive fungal infections, including those caused by Candida species, are a persistent global health problem, and their treatment is hindered by limited antifungal options and the emergence of drug resistance. There is an urgent need for tools and methods to accelerate the discovery of novel therapeutic targets. The expanded and optimized auxin-inducible degron system described herein provides a versatile platform for characterizing protein function and dissecting pathways governing important traits like virulence, stress tolerance, and antifungal resistance. The new reagents make AID technology applicable to any strain. Ultimately, this enhanced toolkit has the potential to help identify and validate new high‑value drug targets and deepen our understanding of molecular mechanisms that drive pathogenicity of Candida and other fungal pathogen species.

E. Danzeisen, Michelle V. Lihon, Kedric L. Milholland et al. · 0 citations

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