Nowrouzi, A. | Search bioRxiv

bioRxiv2025

Spatial Transcriptomics and Single-Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

The liver is a primary target for recombinant adeno-associated viral (rAAV) vectors, yet the influence of serotype, sex, and liver zonation on transduction and transcriptomic changes remain incompletely understood. This proof-of-concept study employs spatial transcriptomics alongside single-nucleus RNA sequencing to map the spatial distribution and impacts of rAAV2- and rAAV9-CMV-EGFP vectors in male and female mouse livers. Spatial transcriptomics provided precise transgene mapping and highlighted that rAAV vectors deregulate hepatocellular lipid metabolism, the circadian clock, and the immune/stress response with sex specific differences. Lipid metabolism genes (Elovl3, Chka, Irs2, Ppard), were deregulated independent of zonation, serotype, and sex, while Srebf1, Tlcd4, Cpt2, and Acot1 exhibited sex-specific patterns. Circadian clock modulators (Dbp, Tef, Arntl, Nfil3, Nr1d1/Nr1d2) were altered independent of zonation. The study found sex-specific downregulation of immune and stress-response genes and pathways, including Gadd45g and hypoxia pathways. TGF-{beta} and EGFR pathways were upregulated sex-independently. Spatial transcriptomics further enabled examination of transgene and rAAV entry factor co-expression, identifying known and novel factors like Rpsa, Dpp4, Sdc1, and solute carrier proteins highlighting its role in supporting targeted screening. Our findings demonstrate spatial transcriptomics as a powerful tool in gene therapy research and reveal novel rAAV vector effects on liver biology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/643011v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@af87b9org.highwire.dtl.DTLVardef@1f79165org.highwire.dtl.DTLVardef@6aa2ccorg.highwire.dtl.DTLVardef@e6274c_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

High complexity cellular barcoding and clonal tracing reveals stochastic and deterministic parameters of radiation resistance

The impact of functional heterogeneity in response to radiation therapy is poorly understood to the present. It remains elusive whether clonal selection of tumor cells in response to ionizing radiation (IR) is a deterministic or stochastic process. We applied high-resolution lentiviral cellular barcoding for quantitative clonal tracking and deconvolution of clonal dynamics in response to IR. Clonal tracking of over 400.000 HNSCC patient-derived tumor cells and the analyses of over 1500 million sequencing reads in clonogenic survival assays reveals that fractionated IR induced a strong selective pressure for clonal reduction. This significantly exceeded uniform clonal survival probabilities indicative for a strong clone-to clone difference within tumor cell lines. IR induced clonal reduction affected the majority of tumor cells ranging between 96-75% and correlated to the degree of radiation sensitivity. Survival and clonogenicity is characterized by an intensive clonal distortion and dominance of individual tumor cells. Survival to IR is driven by a deterministic clonal selection of a smaller population which commonly survives radiation, while increased clonogenic capacity is a result of clonal competition of cells which have been selected stochastically. A 2-fold increase in radiation resistance results in a 4-fold (p<0.05) higher deterministic clonal selection showing that the ratio of these parameters is amenable to radiation sensitivity which correlates to prognostic biomarkers of HNSCC. Evidence for the existence of a rare subpopulation with an intrinsically radiation resistant phenotype commonly surviving IR was found at a frequency of 0.6-3.3% (p<0.001, FDR 3%). With cellular barcoding we introduce a novel functional heterogeneity associated qualitative readout for tracking dynamics of clonogenic survival in response to radiation. This enables the quantification of intrinsically radiation resistant tumor cells from patient samples and reveals the contribution of stochastic and deterministic clonal selection processes in response to IR.

systems biology↗