Background: Thermodynamic Instability of Existing M-MLV-RT Reverse Transcription Systems and Molecular Flux Bottleneck in R&D of Difficult-to-Edit Loci

Existing CRISPR-Cas9-based and first-generation Prime Editing systems have demonstrated innovation by minimizing random insertion/deletion (Indel) errors and the risk of genetic translocation caused by double-strand breaks (DSBs). However, these systems face significant computational omics data bottlenecks due to the thermodynamic instability and limited processing activity of the core driving engine, M-MLV-RT. In particular, the reduction in reverse transcription flux within highly condensed euchromatic regions or secondary-structure-rich, difficult-to-edit loci in mammalian cells leads to a severe decrease in genome editing efficiency. Existing static analysis standard guidelines fail to control the dynamic changes in real-time, which originate from single-cell dissociation-induced structural collapse noise and the heterogeneity of the microenvironment within tissues, resulting in a significant gap between in silico computational predictions and the critical concentrations required for actual in vivo effective engraftment and permanent restoration of target gene function. These limitations have led to a lack of reproducibility and uncontrolled expression of batch effects in patient-derived cell line data, acting as a technical barrier to clinical application.

Discovery: Structure-Guided Design and Single-Cell Resolution Tensor Synchronization Demonstration of enRERV-RT Derived from Rattus norvegicus

To overcome these physicochemical limitations, the researchers performed high-throughput screening of a total of 558 reverse transcriptase candidate pools, identifying 19 high-activity candidates, among which the overwhelming catalytic activity of RERV-RT derived from Rattus norvegicus endogenous retrovirus was noteworthy. Through the fusion of structure-guided engineering based on the three-dimensional crystal structure of the protein and large-scale mutagenesis scanning (DMS), a synthetic variant, enRERV-RT, with optimized thermodynamic stability and substrate affinity was finally designed. The enRERV-RT engine precisely tunes the free energy of target DNA-RNA hybrid binding, outperforming existing M-MLV-RT-based systems by an average of 1.20-fold in mammalian and plant cells, and demonstrating a disruptive 1.88-fold improvement in editing efficiency at difficult-to-edit loci. The high-throughput functional evaluation platform, TRAP-seq-PE, synchronizes multi-dimensional genome editing tensor data, calculates reverse transcription polymerization rate constants using differential equation-based dynamic models, and computationally eliminates noise and batch effects within the system, thereby demonstrating molecular biological precision and integrity.

Establishment of a Reversible Genome Homeostasis Precision Layering Model for Coordinating Editing of Difficult-to-Edit Loci and Multiple Editing Pathways

A key strength of the enRERV-RT architecture lies in its advanced capability for programmable multi-editing, which simultaneously corrects multiple gene networks. This has enabled the construction of a computational and experimental analysis backbone that precisely layers the molecular phenotypes and family-specific genetic predispositions of individual omics matrices with multi-genic genetic backgrounds of the disease. By realizing up-clamping and down-clamping techniques that arbitrarily adjust the reaction rate constants of gene expression of enzymes involved in complex synthetic lethal gene networks or rate-limiting steps in metabolic pathways, a pathway control framework has been completed that stably maintains and restores effective in vivo homeostasis even under reversible cellular stress stimuli. This goes beyond simple single-gene knockout and involves preemptively controlling the feedback loop flux of in vivo signaling pathways at the computational screening stage, thereby preventing potential adverse effects caused by metabolic rewiring or compensatory expression changes after editing and inducing reversible functional normalization, leading to the establishment of a genome model.

Prospects: Establishment of a Standard for Programmable Genomic Precision Control and Launch of Next-Generation IND Digital Governance

This enRERV-RT-based genome editing architecture completely redefines existing static and post-hoc transcriptional analysis and clinical evaluation systems as a programmable infrastructure based on AI-powered multi-dimensional tensors, leading the way in next-generation IND digital governance. In fact, if the low-efficiency problem encountered by existing M-MLV-based platforms, such as Prime Medicine's PM359 pipeline for chronic fibromatosis, is replaced with enRERV-RT, the pipeline expansion speed of global multinational pharmaceutical companies will accelerate to an unprecedented level. By establishing a computational barrier that eliminates experimental batch-to-batch variations by linking genetic gradient correction coefficients in real-time during high-throughput screening, it meets the core requirements of companion diagnostics (CDx) technology, a key component of digital healthcare. As a result, it will act as a unique technological asset that drastically shortens the global regulatory agency's IND approval evaluation framework and safety profile passage timeline, and will solidify a dominant technological moat in the global gene editing market.