Biology subjects

Bergman, S.

Publications and source records attributed to Bergman, S..

3 recordsLinked to original sources

bioRxiv2026

Context-dependent determinants of CRISPR-Cas9 editing efficiency revealed through cross-species endogenous editing analysis

Accurate prediction of CRISPR-Cas9 guide RNA (gRNA) editing efficiency remains limited, particularly outside human systems, where models trained on exogenous human datasets show poor generalization. We analyzed Cas9 efficiency and repair outcomes using novel endogenous editing data from four human cell types, two tomato cell types, and cells from giant river prawn and black soldier fly. While integrating publicly available predictors via ensemble frameworks improved performance, our analysis revealed hundreds of novel features affecting activity. Crucially, dominant features related to sites competition for gRNA, and local geometric properties varied across systems, highlighting the strong context dependence of Cas9 efficiency and arguing against a universal model. Interestingly, codon usage bias-based features also emerged as informative predictors, as they are proxies for chromatin accessibility. In contrast, trends in repair outcomes remained conserved. This work provides essential resources for more generalizable CRISPR guide design.

synthetic biology↗

bioRxiv2025

AI-directed gene fusing prolongs the evolutionary half-life of synthetic gene circuits

Evolutionary instability is a persistent challenge in synthetic biology, often leading to the loss of heterologous gene expression over time. Here, we present STABLES, a novel gene fusion strategy that links a gene of interest (GOI) to an essential endogenous gene (EG), with a "leaky" stop codon in between. This ensures both selective pressure against deleterious mutations and high expression of the GOI. By leveraging a machine learning (ML) framework, we predict optimal GOI-EG pairs based on bioinformatic and biophysical features, identify linkers likely to minimize protein misfolding, and optimize DNA sequences for stability and expression. Experimental validation in Saccharomyces cerevisiae demonstrated significant improvements in stability and productivity for fluorescent proteins and human proinsulin. The results highlight a scalable, adaptable and organism-agnostic method to enhance the evolutionary stability of engineered strains, with broad implications for industrial biotechnology and synthetic biology.

synthetic biology↗

bioRxiv2024

A tool for CRISPR-Cas9 gRNA evaluation based on computational models of gene expression

CRISPR based technologies have revolutionized all biomedical fields as it enables efficient genomic editing. These technologies are often used to silence genes by inducing mutations that are expected to nullify their expression. To this end, dozens of computational tools have been developed to design gRNAs, CRISPRs gene-targeting molecular guide, with high cutting efficiency and no off-target effect. However, these tools do not consider the induced mutations effect on the genes expression, which is the actual objective that should be optimized. This fact can often lead to failures in the design, as an efficient cutting of the DNA does not ensure the desired effect in protein production. Therefore, we developed EXPosition, a computational tool for gRNA design. It is the first tool designed to improve the true objective of using CRISPR: the effect it has on gene expression. To this end, we used predictive deep-learning models for the relevant gene expression steps: transcription, splicing, and translation initiation. We validated our tool by demonstrating that it can classify sites as "silencing" or "non-silencing" better than models that consider only the cutting efficiency. We believe that this tool will significantly improve both the efficiency and accuracy of genome editing endeavors. EXPosition is available at http://www.cs.tau.ac.il/~tamirtul/EXPosition.

synthetic biology↗