Clinically compliant cryopreservation of differentiated retinal pigment epithelial cells

BACKGROUND AIMS

Age-related macular degeneration (AMD) is the most common cause of blindness in elderly patients within developed countries, affecting more than 190 million worldwide. In AMD, the retinal pigment epithelial (RPE) cell layer progressively degenerates, resulting in subsequent loss of photoreceptors and ultimately vision. There is currently no cure for AMD, but therapeutic strategies targeting the complement system are being developed to slow the progression of the disease.

METHODS

Replacement therapy with pluripotent stem cell-derived (hPSC) RPEs is an alternative treatment strategy. A cell therapy product must be produced in accordance with Good Manufacturing Practices at a sufficient scale to facilitate extensive pre-clinical and clinical testing. Cryopreservation of the final cell product is therefore highly beneficial, as the manufacturing, pre-clinical and clinical testing can be separated in time and location.

RESULTS

We found that mature hPSC-RPE cells do not survive conventional cryopreservation techniques. However, replating the cells 2-5 days before cryopreservation facilitates freezing. The replated and cryopreserved hPSC-RPE cells maintained their identity, purity and functionality as characteristic RPEs, shown by cobblestone morphology, pigmentation, transcriptional profile, RPE markers, transepithelial resistance and pigment epithelium-derived factor secretion. Finally, we showed that the optimal replating time window can be tracked noninvasively by following the change in cobblestone morphology.

CONCLUSIONS

The possibility of cryopreserving the hPSC-RPE product has been instrumental in our efforts in manufacturing and performing pre-clinical testing with the aim for clinical translation.

Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations

Across a range of biological processes, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. Single-cell RNA-sequencing (scRNA-seq) only measures temporal snapshots of gene expression. However, information on the underlying low-dimensional dynamics can be extracted using RNA velocity, which models unspliced and spliced RNA abundances to estimate the rate of change of gene expression. Available RNA velocity algorithms can be fragile and rely on heuristics that lack statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. Here, we develop a generative model of RNA velocity and a Bayesian inference approach that solves these problems. Our model couples velocity field and manifold estimation in a reformulated, unified framework, so as to coherently identify the parameters of an autonomous dynamical system. Focusing on the cell cycle, we implemented VeloCycle to study gene regulation dynamics on one-dimensional periodic manifolds and validated using live-imaging its ability to infer actual cell cycle periods. We benchmarked RNA velocity inference with sensitivity analyses and demonstrated one- and multiple-sample testing. We also conducted Markov chain Monte Carlo inference on the model, uncovering key relationships between gene-specific kinetics and our gene-independent velocity estimate. Finally, we applied VeloCycle to in vivo samples and in vitro genome-wide Perturb-seq, revealing regionally-defined proliferation modes in neural progenitors and the effect of gene knockdowns on cell cycle speed. Ultimately, VeloCycle expands the scRNA-seq analysis toolkit with a modular and statistically rigorous RNA velocity inference framework.

Brain matters: unveiling the distinct contributions of region, age, and sex to glia diversity and CNS function

The myelinated white matter tracts of the central nervous system (CNS) are essential for fast transmission of electrical impulses and are often differentially affected in human neurodegenerative diseases across CNS region, age and sex. We hypothesize that this selective vulnerability is underpinned by physiological variation in white matter glia. Using single nucleus RNA sequencing of human post-mortem white matter samples from the brain, cerebellum and spinal cord and subsequent tissue-based validation we found substantial glial heterogeneity with tissue region: we identified region-specific oligodendrocyte precursor cells (OPCs) that retain developmental origin markers into adulthood, distinguishing them from mouse OPCs. Region-specific OPCs give rise to similar oligodendrocyte populations, however spinal cord oligodendrocytes exhibit markers such as SKAP2 which are associated with increased myelin production and we found a spinal cord selective population particularly equipped for producing long and thick myelin sheaths based on the expression of genes/proteins such as HCN2. Spinal cord microglia exhibit a more activated phenotype compared to brain microglia, suggesting that the spinal cord is a more pro-inflammatory environment, a difference that intensifies with age. Astrocyte gene expression correlates strongly with CNS region, however, astrocytes do not show a more activated state with region or age. Across all glia, sex differences are subtle but the consistent increased expression of protein-folding genes in male donors hints at pathways that may contribute to sex differences in disease susceptibility. These findings are essential to consider for understanding selective CNS pathologies and developing tailored therapeutic strategies.

Self-organizing in vitro mouse neural tube organoids mimic embryonic development

The embryonic neural tube is the origin of the entire adult nervous system, and disturbances in its development cause life-threatening birth defects. However, the study of mammalian neural tube development is limited by the lack of physiologically realistic three-dimensional (3D) in vitro models. Here, we report a self-organizing 3D neural tube organoid model derived from single mouse embryonic stem cells that exhibits an in vivo-like tissue architecture, cell type composition and anterior-posterior (AP) patterning. Moreover, maturation of the neural tube organoids showed the emergence of multipotent neural crest cells and mature neurons. Single-cell transcriptome analyses revealed the sequence of transcriptional events in the emergence of neural crest cells and neural differentiation. Thanks to the accessibility of this model, phagocytosis of migrating neural crest cells could be observed in real time for the first time in a mammalian model. We thus introduce a tractable in vitro model to study some of the key morphogenetic and cell type derivation events during early neural development.

Molecular profiling of stem cell-derived retinal pigment epithelial cell differentiation established for clinical translation

Human embryonic stem cell-derived retinal pigment epithelial cells (hESC-RPE) are a promising cell source to treat age-related macular degeneration (AMD). Despite several ongoing clinical studies, a detailed mapping of transient cellular states during in vitro differentiation has not been performed. Here, we conduct single-cell transcriptomic profiling of an hESC-RPE differentiation protocol that has been developed for clinical use. Differentiation progressed through a culture diversification recapitulating early embryonic development, whereby cells rapidly acquired a rostral embryo patterning signature before converging toward the RPE lineage. At intermediate steps, we identified and examined the potency of an NCAM1⁺ retinal progenitor population and showed the ability of the protocol to suppress non-RPE fates. We demonstrated that the method produces a pure RPE pool capable of maturing further after subretinal transplantation in a large-eyed animal model. Our evaluation of hESC-RPE differentiation supports the development of safe and efficient pluripotent stem cell-based therapies for AMD.

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Transcriptional analysis of hESC-RPE differentiation benchmarked to in vivo cells

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NCAM1 emerges as a cell-surface marker of multipotent neuroepithelial progenitors

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hESC-RPE cells are obtained through a divergence-convergence process


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hESC-RPE further mature in vivo upon subretinal injection into the rabbit eye

Sphingolipids control dermal fibroblast heterogeneity

Human cells produce thousands of lipids that change during cell differentiation and can vary across individual cells of the same type. However, we are only starting to characterize the function of these cell-to-cell differences in lipid composition. Here, we measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging with single-cell transcriptomics. We found that the cell-to-cell variations of specific lipid metabolic pathways contribute to the establishment of cell states involved in the organization of skin architecture. Sphingolipid composition is shown to define fibroblast subpopulations, with sphingolipid metabolic rewiring driving cell-state transitions. Therefore, cell-to-cell lipid heterogeneity affects the determination of cell states, adding a new regulatory component to the self-organization of multicellular systems.

Confronting false discoveries in single-cell differential expression

Differential expression analysis in single-cell transcriptomics enables the dissection of cell-type-specific responses to perturbations such as disease, trauma, or experimental manipulations. While many statistical methods are available to identify differentially expressed genes, the principles that distinguish these methods and their performance remain unclear. Here, we show that the relative performance of these methods is contingent on their ability to account for variation between biological replicates. Methods that ignore this inevitable variation are biased and prone to false discoveries. Indeed, the most widely used methods can discover hundreds of differentially expressed genes in the absence of biological differences. To exemplify these principles, we exposed true and false discoveries of differentially expressed genes in the injured mouse spinal cord.

Spatial tissue profiling by imaging-free molecular tomography

Several techniques are currently being developed for spatially resolved omics profiling, but each new method requires the setup of specific detection strategies or specialized instrumentation. Here we describe an imaging-free framework to localize high-throughput readouts within a tissue by cutting the sample into thin strips in a way that allows subsequent image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (called STRP-seq) and validated it by profiling the spatial transcriptome of the mouse brain. We applied the technique to the brain of the Australian bearded dragon, Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. We expect that STRP-seq can be used to derive spatially resolved data from a range of other omics techniques.

Molecular architecture of the developing mouse brain

The mammalian brain develops through a complex interplay of spatial cues generated by diffusible morphogens, cell-cell interactions and intrinsic genetic programs that result in probably more than a thousand distinct cell types. A complete understanding of this process requires a systematic characterization of cell states over the entire spatiotemporal range of brain development. The ability of single-cell RNA sequencing and spatial transcriptomics to reveal the molecular heterogeneity of complex tissues has therefore been particularly powerful in the nervous system. Previous studies have explored development in specific brain regions^1-8, the whole adult brain⁹ and even entire embryos¹⁰. Here we report a comprehensive single-cell transcriptomic atlas of the embryonic mouse brain between gastrulation and birth. We identified almost eight hundred cellular states that describe a developmental program for the functional elements of the brain and its enclosing membranes, including the early neuroepithelium, region-specific secondary organizers, and both neurogenic and gliogenic progenitors. We also used in situ mRNA sequencing to map the spatial expression patterns of key developmental genes. Integrating the in situ data with our single-cell clusters revealed the precise spatial organization of neural progenitors during the patterning of the nervous system.

Myocardial micro-biopsy procedure for molecular characterization with increased precision and reduced trauma

Endomyocardial biopsy is a valuable tool in cardiac diagnostics but is limited by low diagnostic yield and significant complication risks. Meanwhile, recent developments in transcriptomic and proteomic technologies promise a wealth of biological data from minimal tissue samples. To take advantage of the minimal tissue amount needed for molecular analyses, we have developed a sub-millimeter endovascular biopsy device, considerably smaller than current clinical equipment, and devised a low-input RNA-sequencing protocol for analyzing small tissue samples. In in vivo evaluation in swine, 81% of biopsy attempts (n = 157) were successful. High quality RNA-sequencing data was generated from 91% of the sequenced cardiac micro-biopsy samples (n = 32). Gene expression signatures of samples taken with the novel device were comparable with a conventional device. No major complications were detected either during procedures or during 7 days' follow-up, despite acquiring a relatively large number of biopsies (median 30) in each animal. In conclusion, the novel device coupled with RNA-sequencing provides a feasible method to obtain molecular data from the myocardium. The method is less traumatic and has a higher flexibility compared to conventional methods, enabling safer and more targeted sampling from different parts of the myocardium.

A cell fitness selection model for neuronal survival during development

Developmental cell death plays an important role in the construction of functional neural circuits. In vertebrates, the canonical view proposes a selection of the surviving neurons through stochastic competition for target-derived neurotrophic signals, implying an equal potential for neurons to compete. Here we show an alternative cell fitness selection of neurons that is defined by a specific neuronal heterogeneity code. Proprioceptive sensory neurons that will undergo cell death and those that will survive exhibit different molecular signatures that are regulated by retinoic acid and transcription factors, and are independent of the target and neurotrophins. These molecular features are genetically encoded, representing two distinct subgroups of neurons with contrasted functional maturation states and survival outcome. Thus, in this model, a heterogeneous code of intrinsic cell fitness in neighboring neurons provides differential competitive advantage resulting in the selection of cells with higher capacity to survive and functionally integrate into neural networks.

Single-cell transcriptional logic of cell-fate specification and axon guidance in early-born retinal neurons

Retinal ganglion cells (RGCs), cone photoreceptors (cones), horizontal cells and amacrine cells are the first classes of neurons produced in the retina. However, an important question is how this diversity of cell states is transcriptionally produced. Here, we profiled 6067 single retinal cells to provide a comprehensive transcriptomic atlas showing the diversity of the early developing mouse retina. RNA velocities unveiled the dynamics of cell cycle coordination of early retinogenesis and define the transcriptional sequences at work during the hierarchical production of early cell-fate specification. We show that RGC maturation follows six waves of gene expression, with older-generated RGCs transcribing increasing amounts of guidance cues for young peripheral RGC axons that express the matching receptors. Spatial transcriptionally deduced features in subpopulations of RGCs allowed us to define novel molecular markers that are spatially restricted. Finally, the isolation of such a spatially restricted population, ipsilateral RGCs, allowed us to identify their molecular identity at the time they execute axon guidance decisions. Together, these data represent a valuable resource shedding light on transcription factor sequences and guidance cue dynamics during mouse retinal development.

Molecular Architecture of the Mouse Nervous System

The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.

RNA velocity of single cells

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

STRT-seq-2i: dual-index 5' single cell and nucleus RNA-seq on an addressable microwell array

Single-cell RNA-seq has become routine for discovering cell types and revealing cellular diversity, but archived human brain samples still pose a challenge to current high-throughput platforms. We present STRT-seq-2i, an addressable 9600-microwell array platform, combining sampling by limiting dilution or FACS, with imaging and high throughput at competitive cost. We applied the platform to fresh single mouse cortical cells and to frozen post-mortem human cortical nuclei, matching the performance of a previous lower-throughput platform while retaining a high degree of flexibility, potentially also for other high-throughput applications.

Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells

Understanding human embryonic ventral midbrain is of major interest for Parkinson's disease. However, the cell types, their gene expression dynamics, and their relationship to commonly used rodent models remain to be defined. We performed single-cell RNA sequencing to examine ventral midbrain development in human and mouse. We found 25 molecularly defined human cell types, including five subtypes of radial glia-like cells and four progenitors. In the mouse, two mature fetal dopaminergic neuron subtypes diversified into five adult classes during postnatal development. Cell types and gene expression were generally conserved across species, but with clear differences in cell proliferation, developmental timing, and dopaminergic neuron development. Additionally, we developed a method to quantitatively assess the fidelity of dopaminergic neurons derived from human pluripotent stem cells, at a single-cell level. Thus, our study provides insight into the molecular programs controlling human midbrain development and provides a foundation for the development of cell replacement therapies.

Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity

The murine epidermis with its hair follicles represents an invaluable model system for tissue regeneration and stem cell research. Here we used single-cell RNA-sequencing to reveal how cellular heterogeneity of murine telogen epidermis is tuned at the transcriptional level. Unbiased clustering of 1,422 single-cell transcriptomes revealed 25 distinct populations of interfollicular and follicular epidermal cells. Our data allowed the reconstruction of gene expression programs during epidermal differentiation and along the proximal-distal axis of the hair follicle at unprecedented resolution. Moreover, transcriptional heterogeneity of the epidermis can essentially be explained along these two axes, and we show that heterogeneity in stem cell compartments generally reflects this model: stem cell populations are segregated by spatial signatures but share a common basal-epidermal gene module. This study provides an unbiased and systematic view of transcriptional organization of adult epidermis and highlights how cellular heterogeneity can be orchestrated in vivo to assure tissue homeostasis.

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Single-cell RNA-seq analysis identifies 25 populations of epidermal cells

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Differentiation and spatial gene expression signatures can be defined

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Interplay of differentiation and spatial signatures explains most heterogeneity

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Stem cell populations are divided by spatial signatures and only share basal identity

Visceral motor neuron diversity delineates a cellular basis for nipple- and pilo-erection muscle control

Despite the variety of physiological and target-related functions, little is known regarding the cellular complexity in the sympathetic ganglion. We explored the heterogeneity of mouse stellate and thoracic ganglia and found an unexpected variety of cell types. We identified specialized populations of nipple- and pilo-erector muscle neurons. These neurons extended axonal projections and were born among other neurons during embryogenesis, but remained unspecialized until target organogenesis occurred postnatally. Target innervation and cell-type specification was coordinated by an intricate acquisition of unique combinations of growth factor receptors and the initiation of expression of concomitant ligands by the nascent erector muscles. Overall, our results provide compelling evidence for a highly sophisticated organization of the sympathetic nervous system into discrete outflow channels that project to well-defined target tissues and offer mechanistic insight into how diversity and connectivity are established during development.

Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system

Oligodendrocytes have been considered as a functionally homogeneous population in the central nervous system (CNS). We performed single-cell RNA sequencing on 5072 cells of the oligodendrocyte lineage from 10 regions of the mouse juvenile and adult CNS. Thirteen distinct populations were identified, 12 of which represent a continuum from Pdgfra(+) oligodendrocyte precursor cells (OPCs) to distinct mature oligodendrocytes. Initial stages of differentiation were similar across the juvenile CNS, whereas subsets of mature oligodendrocytes were enriched in specific regions in the adult brain. Newly formed oligodendrocytes were detected in the adult CNS and were responsive to complex motor learning. A second Pdgfra(+) population, distinct from OPCs, was found along vessels. Our study reveals the dynamics of oligodendrocyte differentiation and maturation, uncoupling them at a transcriptional level and highlighting oligodendrocyte heterogeneity in the CNS.

Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

The mammalian cerebral cortex supports cognitive functions such as sensorimotor integration, memory, and social behaviors. Normal brain function relies on a diverse set of differentiated cell types, including neurons, glia, and vasculature. Here, we have used large-scale single-cell RNA sequencing (RNA-seq) to classify cells in the mouse somatosensory cortex and hippocampal CA1 region. We found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex. We identified numerous marker genes, which allowed alignment with known cell types, morphology, and location. We found a layer I interneuron expressing Pax6 and a distinct postmitotic oligodendrocyte subclass marked by Itpr2. Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.

Quantitative single-cell RNA-seq with unique molecular identifiers

Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity, discover new cell types and characterize tumor microevolution. However, losses in cDNA synthesis and bias in cDNA amplification lead to severe quantitative errors. We show that molecular labels--random sequences that label individual molecules--can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency.