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Biology subjects

Perrotta, R. M.

Publications and source records attributed to Perrotta, R. M..

4 recordsLinked to original sources

Short single-stranded DNA oligonucleotides enable intracellular transcription of functional RNAs in mammalian cells

Programmable intracellular production of short functional RNAs underlies diverse applications ranging from gene regulation to genome engineering, but is often constrained by cloning workflows, RNA synthesis, or viral-vector delivery. Here, we introduce a single-stranded DNA (ssDNA)-driven intracellular transcription strategy in which short ssDNA templates function as transcriptional substrates when paired with orthogonal bacteriophage RNA polymerases (RNAPs). By embedding phage promoters within short hairpin structures to create a locally double-stranded recognition site, we enable robust RNAP-dependent transcription from ssDNA in mammalian cells. We demonstrate that ssDNA templates can drive production of functional CRISPR guides, supporting adenine base editing at reporter and endogenous loci and enabling CRISPR-based transcriptional activation across distinct human cell lines. These results establish ssDNA templates as compact, synthetically accessible inputs for RNA production in mammalian cells, with broad utility in synthetic biology and genome engineering.

bioengineering↗

A Developmental Lectin-Glycan Program Enables Early Breast Cancer Dissemination and Metastatic Onset

Early dissemination of breast cancer cells can precede clinically detectable tumor progression, yet the programs enabling this process, remain poorly understood. Here, we identify a developmental glycocheckpoint governed by the galectin-1 (GAL1)-glycan axis that is hijacked during early breast cancer dissemination. In the mammary gland, regulated GAL1 expression and glycan accessibility directed epithelial lineage specification and progesterone-induced branching morphogenesis. This program was aberrantly reactivated in early breast cancer lesions to promote epithelial plasticity, stem-like traits and metastatic competence. Mechanistically, GAL1 was enriched in mammary stem cell compartments and sustained progesterone receptor expression and activity. Genetic ablation or therapeutic inhibition of GAL1 across breast cancer models restrained early lesion progression, reduced circulating tumor cell frequency, and limited lung metastasis. Consistent with these findings, high GAL1 expression combined with low expression of the GAL1-restricting sialyltransferase ST6GAL1 was associated with poor clinical outcomes in patients. Thus, breast cancer co-opts a developmental GAL1-glycan program to disseminate early, revealing an unexpected link between mammary morphogenesis and metastatic progression and identifying GAL1 as a therapeutic vulnerability in early-stage disease.

cancer biology↗

Preventing escape and malfunction of recoded cells due to tRNA base changes

Engineering the genetic code restricts DNA transfer (cellular bioisolation) and enables new chemistries via non-standard amino acid incorporation. These distinct properties make recoded cells state-of-the-art safe technologies. However, evolutionary pressures may endanger the longevity of the recoding. Here, we reveal that recoded Escherichia coli lacking 18,214 serine codons and two tRNASer can express wild-type antibiotic resistance genes and escape up to seven orders of magnitude faster than expected. We show a two-step escape process whereby recoded cells mistranslate antibiotic resistance genes to survive until modified or mutated tRNAs reintroduce serine into unassigned codons. We developed genetic-code-sensitive kill switches that sense serine incorporation and prevent cellular escape while preserving encoding of three distinct non-standard amino acids. This work lays the foundation for the long-term controlled function of cells that incorporate new chemistries, with implications for the design, use, and biosafety of synthetic genomes in clinical and environmental applications where physical containment is insufficient.

synthetic biology↗

Machine Learning and Directed Evolution of Base Editing Enzymes

As we enter the era of CRISPR medicines, base editors (BEs) emerged as one of the most promising tools to treat genetic associated diseases. However, unintended bystander editing beyond the target nucleotide poses a challenge to their translation into effective therapies. While many efforts have been made in the design of a universal enzyme with minimal bystander editing, the context dependent activity represents a major challenge for base editing-based therapies. In this work, we designed a sequence-specific guide RNA library with 3-extensions and detected guides that were able to reduce bystander and increase editing efficiency in a context dependent manner. The best candidate was later used for phage assisted non-continuous evolution to find a new generation of precise base editors. Simultaneously, we use protein language models trained on massive protein sequence datasets to find the evolutionarily plausible mutational patterns that can improve deaminase activity and precision. Both strategies provide a collection of precise TadA variants that not only drastically reduced bystander edits, but also was not in detriment of on-target activity. Our findings introduce a guide/enzyme parallel engineering pipeline, which lays the foundation for the development of new personalized genome editing strategies, ultimately enhancing the safety and precision of this groundbreaking technology.

synthetic biology↗