Roee Amit

This paper introduces AntiCoV decoy particles, synthetic RNA-protein nanoparticles that inhibit SARS-CoV-2 infection by acting as stable decoy receptors, outperforming soluble ACE2 in neutralization.

The paper develops sialogranules that sense lectins and inhibit influenza infection by using sialylated RNA-protein nanoparticles.

The paper shows that synthetic RNA with hairpin binding sites and disordered coat proteins form programmable polyphasic RNP granules with tunable phase behavior.

This paper develops antiviral decoy particles using phase-separation scaffolds to inhibit coronavirus and influenza infections.

GelMetrics quantifies dynamics of gel-like phase-separated condensates by tracking fluorescence over time, revealing biophysical properties and the impact of intrinsically disordered regions.

The paper describes a cell-free assay using fluorescent particles and labeled hACE2 to screen inhibitors of SARS-CoV-2 Spike-hACE2 binding, demonstrating its effectiveness with known inhibitors and RNA-based trapping.

The paper uses high-throughput oligo libraries and machine learning to design non-repetitive RNA binding cassettes for gene editing and RNA tracking, demonstrating their functionality in mammalian cells.

The paper develops a deep-sequencing platform to refine DNA triplex binding rules and creates a synthetic regulatory tool for in vivo applications.

The paper shows that synthetic 5 UTRs can be up- or down-regulated by RBP binding, revealing RNA-RBP interactions that control translation.

The paper develops an in vivo method to quantify RNA-binding protein-RNA interactions using a reporter gene repression assay and SHAPE-seq in bacteria.

This paper introduces composite DNA alphabets to improve DNA storage capacity and fidelity by leveraging synthesis redundancy, achieving a 25% increase in storage capacity.

The paper identifies an insulation mechanism in bacterial σ54 promoters using a synthetic oligo library and sequencing, showing CT-rich motifs reduce downstream gene expression.

The paper demonstrates a synthetic chemoreceptor in E. coli for histamine using computational design and a novel quantitative assay to characterize chemotaxis.