Biology subjects

Pavan, C.

Publications and source records attributed to Pavan, C..

5 recordsLinked to original sources

bioRxiv2026

Lineage-selective suicide gene system enables post-engraftment editing of cell therapy composition

Human pluripotent stem cell (hPSC)-derived therapies are advancing rapidly toward clinical application, yet heterogeneity of transplanted cell populations remains a major barrier to safety, predictability and scalability. Existing strategies to mitigate this risk either incompletely eliminate proliferative cells or ablate the entire graft, thereby compromising therapeutic benefit. Here we present NeuroGuard, a lineage-selective suicide gene platform that decouples safety from efficacy by preserving functional neurons while enabling inducible elimination of all other cell types after transplantation. NeuroGuard integrates an inducible caspase-9 system with NEUROD1-driven Cre recombination, protecting post-mitotic neurons from apoptosis while rendering non-neuronal and proliferative populations susceptible to ablation. In vitro, activation of the system enriched neuronal content to >90% and increased dopaminergic neuron proportion >3-fold. Following transplantation of ventral midbrain progenitors, timed activation eliminated proliferative and glial populations, resulting in compact, neuron-enriched grafts without loss of dopaminergic neuron number, target innervation or behavioural recovery in Parkinsonian rodents. Single-cell transcriptomics confirmed selective removal of non-neuronal lineages while preserving neuronal identity and maturation programs. This work establishes a generalizable framework for post-engraftment editing of cell therapy composition, providing a versatile strategy to enhance the safety and functional predictability of regenerative therapies.

neuroscience↗

bioRxiv2026

Netrin-1 drives cell-type-specific plasticity of human dopaminergic neurons during circuit integration in a Parkinsonian model

The survival of transplanted ventral midbrain (vm) dopaminergic neurons (DAn) and their innervation of host striatal tissue are crucial for ameliorating motor symptoms in Parkinsons disease (PD). However, human pluripotent stem cells (hPSC) show inferior axonal plasticity compared to fetal donor tissue. While modulation of the host environment with trophic cues, such as glial cell-derived neurotrophic factor (GDNF), can improve graft outcomes, these cues lack specificity for DAn, resulting in plasticity of other neurons within the graft. Using single nuclei RNA sequencing, we identified axonal guidance pathways (Semaphorin, Netrin and Wnt) that were preferentially activated in DAn within the graft. Overexpression of Semaphorin3A/SEMA3A, Netrin1/NTN1 or WNT5A in the striatum of Parkinsonian mice following vm DA progenitor transplantation promoted A9-DA specification and selectively increased DA innervation of the host striatum, without off-target extrastriatal DA innervation observed in response to GDNF. In Parkinsonian rats, NTN1 overexpression promoted graft-induced motor recovery, selective DA plasticity and activation of postsynaptic striatal neurons without evidence of non-DAn plasticity. Further, snRNA-sequencing of NTN1 or GDNF-treated grafts confirmed the upregulation of DA-specific plasticity by NTN1, while GDNF promoted plasticity in both DA and non-DAn. These findings highlight the capacity to improve on-target integration of hPSC-derived DAn in grafts by selectively targeting DA-specific plasticity. Taken together, these results demonstrate the utility of DA-specific cues to promote functional recovery, improve graft predictability, and limit off-target innervation.

neuroscience↗

bioRxiv2026

Machine learning-based image analysis of Parkinson's disease iPS-derived neurons predicts genotype and reveals mitochondria-lysosome abnormalities

Mitochondrial and lysosomal dysfunction are central features of Parkinsons disease (PD) across major genetic forms including PRKN, SNCA, and LRRK2. We applied cell morphomics, a machine-learning-based framework combining high-content imaging with quantitative feature extraction, to analyse mitochondrial and lysosomal morphology at single-cell resolution in iPS cell-derived cortical neurons from PD patients and healthy controls (13 lines total). Supervised machine-learning models distinguished PD neurons from controls with high accuracy (AUC = 0.87) and reliably separated individual genotypes. Feature importance and attribution analysis revealed genotype-specific organelle biases, with mitochondrial features dominating classification in PRKN neurons, balanced mitochondrial and lysosomal contributions in SNCA neurons, and a greater lysosomal contribution in LRRK2 neurons. Multi-class models retained strong performance, and findings were reproduced across two independent laboratories using different dyes and imaging conditions. These results demonstrate that morphomics provides a robust and scalable framework to quantify genotype-specific organelle abnormalities in PD neurons and supports its application for cellular stratification and biomarker discovery.

neuroscience↗

bioRxiv2025

Igniting full-length isoform analysis in single-cell and spatial RNA-seq data with FLAMESv2

Long-read single-cell RNA-sequencing enables the profiling of RNA isoform expression and alternative splicing at single cell resolution. However, diverse single-cell technologies and sparse isoform data demand flexible and accurate analysis tools. We introduce FLAMESv2, a highly modular and protocol-agnostic R/Bioconductor package for long-read single-cell RNA-seq data analysis. FLAMESv2 supports a wide range of single-cell and spatial protocols, is highly configurable, scales to allow multi-sample analysis and provides versatile visualisation and analysis outputs. We demonstrate its compatibility with both droplet-based and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Benchmarking confirms FLAMESv2 achieves field-leading performance across key analysis tasks. Applying FLAMESv2 to in vitro differentiation of stem cells into neurons, we identify cell-types, differentiation trajectories, expression of annotated and novel isoforms and isoform expression diversity and heterogeneity within individual cells. FLAMESv2 provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.

bioinformatics↗

bioRxiv2024

Dopamine and cortical iPSC-derived neurons with different Parkinsonian mutations show variation in lysosomal and mitochondrial dysfunction: implications for protein deposition versus selective cell loss

BackgroundMutations causing Parkinsons disease (PD) give diverse pathological phenotypes whose cellular correlates remain to be determined. For example, those with PRKN loss of function mutations have significantly earlier selective vulnerability of dopamine neurons, those with SNCA mutations have increased alpha-synuclein deposition, while those with LRRK2 mutations have additional deposition of tau. Yet all three mutation types are implicated in mitochondrial and/or lysosomal dysfunction. Direct comparison of cell models with these mutations would clarify the relative cellular dysfunctions associated with these different pathological phenotypes. MethodsAn unbiased high-content imaging platform using orthogonal probes to assess both lysosomal and mitochondrial dysfunction, along with alpha-synuclein and tau protein deposition was established using induced pluripotent stem cell (iPSC) derived cortical and ventral midbrain neurons. Three mutation types, SNCA A53T, LRRK2 R1441G and PRKN loss of function (lof), were selected as exemplars of divergent PD pathological phenotypes and compared to each other, and to control iPSC from subjects without PD. ResultsDifferent PD mutations caused cell type specific dysfunctions, likely to impact on both selective neuronal vulnerability and the pathologies observed in PD. Comparison of dopamine neurons identified that both lysosomal and mitochondrial dysfunction were predominant with PRKN lof mutations, whereas immunofluorescent staining revealed that SNCA A53T and LRRK2 R1441G mutations had increased tau deposition. In contrast, cortical neurons with SNCA and LRRK2 mutations both had mitochondrial and autophagy impairments without protein deposition, with LRRK2 cells additionally showing decreased glucocerebrosidase activity and increased alpha-synuclein phosphorylation. ConclusionsLysosomal and mitochondrial dysfunction are predominant in dopamine neurons with PRKN lof mutations, and may drive the early selective loss of dopamine neurons in PRKN mutation carriers. More subtle cellular abnormalities in the SNCA A53T cell lines are likely to predispose to alpha-synuclein aggregation and tau protein deposition over time. The LRRK2 R1441G may also predispose to tau deposition, but despite substantial lysosomal dysfunction with increased alpha-synuclein phosphorylation, pathological alpha-synuclein accumulations were not observed. Understanding the mechanistic differences in how lysosomal and mitochondrial dysfunction impact on PD pathogenesis in different disease subtypes may be important for therapeutic development.

neuroscience↗