Biology subjects

Storm, P.

Publications and source records attributed to Storm, P..

10 recordsLinked to original sources

bioRxiv2026

A human developmental and adult brain atlas benchmarks dopaminergic stem cell models and cell therapy candidates

Parkinsons disease (PD) is characterized by the progressive loss of midbrain dopaminergic (mDA) neurons1. Stem cell-derived mDA neurons hold promise for disease modelling2,3 and are currently in clinical trials for cell replacement therapy4-6. However, systematic benchmarking has been limited by the lack of a unified high-resolution reference and methods that quantify incomplete or mixed lineage specification in vitro7. We establish a single-cell and spatial atlas of the human developing diencephalon-midbrain-hindbrain axis resolving 93 cell subtypes, including 39 lacking prior single-cell characterization and 4 entirely novel populations. Using this atlas as a reference, we integrate 19 hPSC-derived mDA datasets, both published2,8-25 and unpublished, to build the Human Dopaminergic Neural Atlas (HDNA) spanning 2D, 3D, and graft models, including those used in clinical trials. To classify cells and quantify lineage fidelity, we develop CapybaraBrain, a marker-driven non-negative decomposition framework that assigns each cell continuous identity scores across all 93 developmental programs, enabling systematic discrimination of discrete, transitioning, and cross-lineage hybrid states26. We uncover a pervasive landscape of off-target populations reflecting relaxed transcriptional boundaries in vitro, including a previously unrecognized TH-PITX2 midbrain neuronal population, and we validate atlas-predicted latent lineage plasticity through inducible genetic fate mapping in mouse models. We further define maturation-associated transcriptional programs by harmonizing adult mDA subtype atlases, revealing that dopaminergic identity and maturation are partially decoupled across protocols. Finally, projecting PD patient-derived tri-cultures onto the HDNA uncovers genotype- and cell-type-specific transcriptional dysregulation. Together, these integrated atlases and computational framework establish a unified standard for benchmarking differentiation fidelity, exposing off-target states, and guiding next-generation PD models and cell therapies.

Developmental Biology↗

bioRxiv2025

Cografting strategies uncover cell type dependent regulation of dopamine neuron specification and functional maturation in a pre clinical model of Parkinson`s Disease

Parkinsons disease (PD), the second most common neurodegenerative disorder, is characterized by the progressive loss of A9 dopaminergic neurons in the substantia nigra, leading to dopamine (DA) depletion in the striatum and subsequent motor symptoms. Transplantation of ventral midbrain-patterned DA (vmDA) progenitors derived from human pluripotent stem cells, aimed at restoring DA neurotransmission in the striatum, is being developed and currently explored in ongoing clinical trials. One factor that may improve the maturation and fate determination of DA neurons in vivo is the intercellular communication within the graft environment, ultimately affecting the therapeutic outcome. In this study, we co-transplanted vmDA progenitors with either glial, ventral forebrain or striatal progenitors into a preclinical xenograft PD model to investigate how these interactions shape the development, maturation, and function of therapeutic DA neurons. Our findings show that co-grafts with ventral forebrain progenitors increase the yield of DA neurons and also promote their functional maturation. Furthermore, we demonstrated that co-grafts with striatal neurons promote functional maturation and the acquisition of DA subtype identity. From these data, we identified EBF3 and PBX3 as candidate transcription factors directing DA neuron maturation and subtype specification, and then functionally validated their role in brain organoids. Taken together, our data highlight that the cellular microenvironment, including specific interactions with neighbouring cells, guides in vivo DA neuron specification and maturation. These findings provide a foundation for developing more refined and effective cell preparations for replacement therapy in PD, and define a conceptual framework that could inform stem cell-based strategies for other neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Nuclei Isolation Protocol for Single-Nucleus RNA Sequencing of Human Stem Cell-Derived Grafts

Single-nucleus RNA sequencing enables high-resolution transcriptomic profiling of brain tissue, facilitating detailed analysis of cell identity in models of neurodegeneration and repair. Here, we describe a protocol for isolating nuclei from long-term human stem cell-derived grafts in the rat brain, incorporating vibratome sectioning, graft dissection, nuclear extraction, and fluorescence-activated sorting. This workflow supports analysis of human neurons embedded within host tissue or sensitive to dissociation, offering a powerful approach to assess graft composition, integration, and neuronal identity in living brain. For complete details on the use and execution of this protocol, please refer to Fiorenzano et al.1 Subject areasSingle nucleus RNA sequencing, stem cell biology, neuroscience, transplantation, cell replacement therapy Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC="FIGDIR/small/672369v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1ac3b90org.highwire.dtl.DTLVardef@7aab65org.highwire.dtl.DTLVardef@18a8fd4org.highwire.dtl.DTLVardef@1e8bfae_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIStep-by-step vibratome sectioning of xenografted rat brain tissue. C_LIO_LIPrecise dissection of human stem cell-derived grafts from host brain sections. C_LIO_LIExtraction of intact nuclei from fragile, grafted neurons. C_LIO_LIIsolation of single nuclei via fluorescence-activated nuclei sorting (FANS) for snRNA-seq sample preparation. C_LI

cell biology↗

bioRxiv2023

Injectable 3D microcultures enable intracerebral transplantation of mature neurons directly reprogrammed from patient fibroblasts

Direct reprogramming of somatic cells into induced neurons (iNs) has become an attractive strategy for the generation of patient-specific neurons for disease modeling and regenerative neuroscience. To this end, adult human dermal fibroblasts (hDFs) present one of the most relevant cell sources. However, iNs generated from adult hDFs using two-dimensional (2D) cultures poorly survive transplantation into the adult brain in part due to the need for enzymatic or mechanical cellular dissociation before transplantation. Three-dimensional (3D) culturing methodologies have the potential to overcome these issues but have largely been unexplored for the purposes of direct neuronal reprogramming. Here we report a strategy for direct in vitro reprogramming of adult hDFs inside suspension 3D microculture arrays into induced DA neurospheroids (iDANoids). We show that iDANoids express neuronal and DA markers and are capable of firing mature action potentials and releasing dopamine. Importantly, they can be gently harvested and transplanted into the brain of a Parkinsons disease rat model to reproducibly generate functionally integrated neuron-rich grafts. The 3D culturing approach presented here thus eliminates a major bottleneck in direct neuronal reprogramming field and, due to its simplicity and versatility, could readily be adapted as a culturing platform used for a broad range of transplantation studies as well as disease modeling.

neuroscience↗

bioRxiv2021

Age-related pathological impairments in induced neurons derived from patients with idiopathic Parkinson's disease

Understanding the pathophysiology of Parkinsons disease has been hampered by the lack of models that recapitulate all the critical factors underlying its development. Here, we generated functional induced dopaminergic neurons (iDANs) that were directly reprogrammed from adult human dermal fibroblasts of patients with idiopathic Parkinsons disease to investigate diseaserelevant pathology. We show that iDANs derived from Parkinsons disease patients exhibit lower basal chaperone-mediated autophagy as compared to iDANs of healthy donors. Furthermore, stress-induced autophagy resulted in an accumulation of macroautophagic structures in induced neurons (iNs) derived from Parkinsons disease patients, independently of the specific neuronal subtype but dependent on the age of the donor. Finally, we found that these impairments in patient-derived iNs lead to an accumulation of phosphorylated alpha-synuclein, a hallmark of Parkinsons disease pathology. Taken together, our results demonstrate that direct neural reprogramming provides a patient-specific model to study aged neuronal features relevant to idiopathic Parkinsons disease.

neuroscience↗

bioRxiv2021

Distinct sub-cellular autophagy impairments occur independently of protein aggregation in induced neurons from patients with Huntington's disease

Huntingtons disease (HD) is a neurodegenerative disorder caused by CAG expansions in the huntingtin (HTT) gene. Modelling HD has remained challenging, as rodent and cellular models poorly recapitulate the disease. To address this, we generated induced neurons (iNs) through direct reprogramming of human skin fibroblasts, which retain age-dependent epigenetic characteristics. HD-iNs displayed profound deficits in autophagy, characterised by reduced transport of late autophagic structures from the neurites to the soma. The neurite-specific alterations in autophagy resulted in shorter, thinner and fewer neurites presented by HD-iNs. CRISPRi-mediated silencing of HTT did not rescue this phenotype but rather resulted in additional autophagy alterations in ctrl-iNs, highlighting the importance of wild type HTT in neuronal autophagy. In summary, our work identifies a distinct subcellular autophagy impairment in aged patient derived HD-neurons and provides a new rational for future development of autophagy activation therapies.

neuroscience↗

bioRxiv2020

Single cell transcriptional and functional analysis of human dopamine neurons in 3D fetal ventral midbrain organoid like cultures

Transplantation of midbrain dopamine (DA) neurons for the treatment of Parkinsons disease (PD) is a strategy that has being extensively explored and clinical trials using fetal and stem cell-derived DA neurons are ongoing. An increased understanding of the mechanisms promoting the generation of distinct subtypes of midbrain DA during normal development will be essential for guiding future efforts to precisely generate molecularly defined and subtype specific DA neurons from pluripotent stem cells. In this study, we used droplet-based scRNA-seq to transcriptionally profile a large number of fetal cells from human embryos at different stages of ventral midbrain (VM) development (6, 8, and 11 weeks post conception). This revealed that the emergence of transcriptionally distinct cellular populations was evident already at these early timepoints. To study late events of human DA differentiation and functional maturation, we established a primary fetal 3D culture system that recapitulates key molecular aspects of late human DA neurogenesis and sustains differentiation and functional maturation of DA neurons in a physiologically relevant cellular context. This approach allowed us to define the molecular identities of distinct human DA progenitors and neurons at single cell resolution and construct developmental trajectories of cell types in the developing fetal VM. Overall these findings provide a unique transcriptional profile of developing fetal VM and functionally mature human DA neurons, which can be used to quality control stem cell-derived DA neurons and guide stem cell-based therapies and disease modeling approaches in PD.

neuroscience↗

bioRxiv2018

Islet Gene View - a tool to facilitate islet research

Changes in the hormone-producing pancreatic islets are central culprits in type 2 diabetes (T2D) pathogenesis. Characterization of gene expression in islets how it is altered in T2D are therefore vital in understanding islet function and T2D pathogenesis. We leveraged RNA-sequencing and genome-wide genotyping in islets from 188 donors to create the Islet Gene View (IGW) platform to make this information easily accessible to the scientific community. The IGW combines expression data for a given gene with phenotypical data such as T2D status, BMI, HbA1c, insulin secretion, purity of islets, etc.), regulation of gene expression by genetic variants e.g., expression quantitative trait loci (eQTLs) and relationship with expression of islet hormones. In IGW, 285 differentially expressed genes (DEGs) were identified in T2D donors islets compared to controls. Forty percent of the DEGs showed cell-type enrichment and a large proportion of them were significantly co-expressed with islet hormone-encoding genes like glucagon (GCG, 56%), amylin (IAPP, 52%), insulin (INS, 44%) and somatostatin (SST, 24%). Inhibition of two DEGs, UNC5D and SERPINE2 impaired glucose-stimulated insulin secretion and impacted cell survival in a human beta-cell model. Significance StatementWe present Islet Gene View (IGW), a web resource facilitating information on gene expression in human pancreatic islets from organ donors easily accessible to the scientific community. In IGW, we explored RNA expression from 188 donor-islets and examined their relationship with islet phenotypes including insulin secretion and expression of genes encoding islet hormones. GWAS have shown 403 genetic variants associated with risk of type 2 diabetes (T2D) risk, however, the target genes and function of these variants in islets are largely unknown. By linking T2D risk variants to expression in islets from T2D and non-diabetic donors as well as islet phenotypes, use of IGW provided new insight into mechanisms by which variants in these loci may increase risk of T2D.

molecular biology↗

bioRxiv2017

Perturbed Mitochondrial Metabolism in Islets from Donors with Type-2 Diabetes

There is a preponderance for genes involved in {beta}-cell function among gene variants associated with future risk of type-2 diabetes (T2D). {beta}-cell function is controlled by metabolism of glucose, yielding signals triggering and amplifying insulin secretion. Perturbed {beta}-cell metabolism is a likely, albeit not proven, cause of T2D. We profiled metabolites in islets from T2D and non-diabetic donors, and found altered levels of mitochondrial metabolites in T2D. Analysis of genes encoding proteins localized to mitochondria (MitoCarta) by RNA-seq in an extended sample of islets revealed genes whose expression was associated with glycaemia- and/or BMI. Expression of two of these, -methylacyl-CoA racemase (AMACR) and methylmalonyl-CoA mutase (MUT), was influenced by genetic variation (cis-eQTL). Silencing of AMACR and MUT in insulin-secreting cells reduced hormone secretion by 40-50%. In conclusion, by linking the metabolome to the transcriptome, we showed that perturbed mitochondrial metabolism is a feature of {beta}-cell dysfunction in T2D.\n\n[Supplementary material is available for this article.]

cell biology↗

bioRxiv2017

Clustering of adult-onset diabetes into novel subgroups guides therapy and improves prediction of outcome

BackgroundDiabetes is presently classified into two main forms, type 1 (T1D) and type 2 diabetes (T2D), but especially T2D is highly heterogeneous. A refined classification could provide a powerful tool individualize treatment regimes and identify individuals with increased risk of complications already at diagnosis.\n\nMethodsWe applied data-driven cluster analysis (k-means and hierarchical clustering) in newly diagnosed diabetic patients (N=8,980) from the Swedish ANDIS (All New Diabetics in Scania) cohort, using five variables (GAD-antibodies, BMI, HbA1c, HOMA2-B and HOMA2-IR), and related to prospective data on development of complications and prescription of medication from patient records. Replication was performed in three independent cohorts: the Scania Diabetes Registry (SDR, N=1466), ANDIU (All New Diabetics in Uppsala, N=844) and DIREVA (Diabetes Registry Vaasa, N=3485). Cox regression and logistic regression was used to compare time to medication, time to reaching the treatment goal and risk of diabetic complications and genetic associations.\n\nFindingsWe identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease, but had been prescribed similar diabetes treatment compared to the less susceptible individuals in clusters 4 and 5. The insulin deficient cluster 2 had the highest risk of retinopathy. In support of the clustering, genetic associations to the clusters differed from those seen in traditional T2D.\n\nInterpretationWe could stratify patients into five subgroups predicting disease progression and development of diabetic complications more precisely than the current classification. This new substratificationn may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.\n\nFundingThe funders of the study had no role in study design, data collection, analysis, interpretation or writing of the report.\n\nResearch in contextEvidence before this study\n\nThe current diabetes classification into T1D and T2D relies primarily on presence (T1D) or absence (T2D) of autoantibodies against pancreatic islet beta cell autoantigens and age at diagnosis (earlier for T1D). With this approach 75-85% of patients are classified as T2D. A third subgroup, Latent Autoimmune Diabetes in Adults (LADA,<10%), is defined by presence of autoantibodies against glutamate decarboxylase (GADA) with onset in adult age. In addition, several rare monogenic forms of diabetes have been described, including Maturity Onset Diabetes of the Young (MODY) and neonatal diabetes. This information is provided by national guidelines (ADA,WHO, IDF, Diabetes UK etc) but has not been much updated during the past 20 years and very few attempts have been made to explore heterogeneity of T2D. A topological analysis of potential T2D subgroups using electronic health records was published in 2015 but this information has not been implemented in the clinic.\n\nAdded value of this study\n\nHere we applied a data-driven cluster analysis of 5 simple variables measured at diagnosis in 4 independent cohorts of newly-diagnosed diabetic patients (N=14755) and identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease.\n\nImplications of the available evidence\n\nThis new sub-stratification may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes

epidemiology↗