Search bioRxiv⌕ Search

Biology subjects

Dveirin, R. K.

Publications and source records attributed to Dveirin, R. K..

2 recordsLinked to original sources

Genomic repeats for single-cell molecular recording

Genomic recording enables transient biological signals to be indelibly captured through DNA alterations, creating a permanent record of cellular history retrievable by sequencing. However, current methods are limited by scarce writing space, typically targeting only one or a few amenable genomic sites and requiring large cell populations for signal reconstruction. Here, we establish Repeats for Genomic Recording (RGRs): sequences with up to 400 copies targetable by a single CRISPR guide RNA, readable with a common primer pair, and predicted to have minimal functional impact. We demonstrate that RGRs enable both signal deconvolution in single cells and high-resolution recording in cell populations. Individual RGR sites exhibit distinct response kinetics; thus, combining them improves recording resolution beyond what redundancy alone provides, analogous to diversity reception in wireless communication. We develop a computational pipeline for systematic RGR identification, revealing 15,000 to 25,000 candidates per species across human, mouse, and zebrafish, thereby markedly expanding recording capacity and enabling cell-type-specific applications. Finally, we validate RGRs in live mice by recording long-term immediate early gene activity across the brain following epilepsy induction. This work establishes genomic repeats as a high-capacity platform for single-cell molecular recording in vivo.

synthetic biology↗

Identifying a gene signature of metastatic potential by linking pre-metastatic state to ultimate metastatic fate

Identifying the key molecular pathways that enable metastasis by analyzing the eventual metastatic tumor is challenging because the state of the founder subclone likely changes following metastatic colonization. To address this challenge, we labeled primary mouse pancreatic ductal adenocarcinoma (PDAC) subclones with DNA barcodes to characterize their pre-metastatic state using ATAC-seq and RNA-seq and determine their relative in vivo metastatic potential prospectively. We identified a gene signature separating metastasis-high and metastasis-low subclones orthogonal to the normal-to-PDAC and classical-to-basal axes. The metastasis-high subclones feature activation of IL-1 pathway genes and high NF-{kappa}B and Zeb/Snail family activity and the metastasis-low subclones feature activation of neuroendocrine, motility, and Wnt pathway genes and high CDX2 and HOXA13 activity. In a functional screen, we validated novel mediators of PDAC metastasis in the IL-1 pathway, including the NF-{kappa}B targets Fos and Il23a, and beyond the IL-1 pathway including Myo1b and Tmem40. We scored human PDAC tumors for our signature of metastatic potential from mouse and found that metastases have higher scores than primary tumors. Moreover, primary tumors with higher scores are associated with worse prognosis. We also found that our metastatic potential signature is enriched in other human carcinomas, suggesting that it is conserved across epithelial malignancies. This work establishes a strategy for linking cancer cell state to future behavior, reveals novel functional regulators of PDAC metastasis, and establishes a method for scoring human carcinomas based on metastatic potential.

cancer biology↗