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Kelley, K. W.

Publications and source records attributed to Kelley, K. W..

5 recordsLinked to original sources

Assembloid model to study loop circuits of the human nervous system

Neural circuits connecting the cerebral cortex, the basal ganglia and the thalamus are fundamental networks for sensorimotor processing and their dysfunction has been consistently implicated in neuropsychiatric disorders1-9. These recursive, loop circuits have been investigated in animal models and by clinical neuroimaging, however, direct functional access to developing human neurons forming these networks has been limited. Here, we use human pluripotent stem cells to reconstruct an in vitro cortico-striatal-thalamic-cortical circuit by creating a four-part loop assembloid. More specifically, we generate regionalized neural organoids that resemble the key elements of the cortico-striatal-thalamic-cortical circuit, and functionally integrate them into loop assembloids using custom 3D-printed biocompatible wells. Volumetric and mesoscale calcium imaging, as well as extracellular recordings from individual parts of these assembloids reveal the emergence of synchronized patterns of neuronal activity. In addition, a multi-step rabies retrograde tracing approach demonstrate the formation of neuronal connectivity across the network in loop assembloids. Lastly, we apply this system to study heterozygous loss of ASH1L gene associated with autism spectrum disorder and Tourette syndrome and discover aberrant synchronized activity in disease model assembloids. Taken together, this human multi-cellular platform will facilitate functional investigations of the cortico-striatal-thalamic-cortical circuit in the context of early human development and in disease conditions.

neuroscience↗

Clarifying the Transcriptional Profiles of Malignant Clones through Multiscale and Multiomic Analysis of Individual Tumors

Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

cancer biology↗

Generating human neural diversity with a multiplexed morphogen screen in organoids

Morphogens choreograph the generation of remarkable cellular diversity in the developing nervous system. Differentiation of stem cells toward particular neural cell fates in vitro often relies upon combinatorial modulation of these signaling pathways. However, the lack of a systematic approach to understand morphogen-directed differentiation has precluded the generation of many neural cell populations, and knowledge of the general principles of regional specification remain in-complete. Here, we developed an arrayed screen of 14 morphogen modulators in human neural organoids cultured for over 70 days. Leveraging advances in multiplexed RNA sequencing technology and annotated single cell references of the human fetal brain we discovered that this screening approach generated considerable regional and cell type diversity across the neural axis. By deconvoluting morphogen-cell type relationships, we extracted design principles of brain region specification, including critical morphogen timing windows and combinatorics yielding an array of neurons with distinct neuro-transmitter identities. Tuning GABAergic neural subtype diversity unexpectedly led to the derivation of primate-specific interneurons. Taken together, this serves as a platform towards an in vitro morphogen atlas of human neural cell differentiation that will bring insights into human development, evolution, and disease.

neuroscience↗

CRISPR screens in 3D assembloids reveal disease genes associated with human interneuron development

The assembly of cortical circuits involves the generation and migration of cortical interneurons from the ventral to the dorsal forebrain, which has been challenging to study in humans as these processes take place at inaccessible stages of late gestation and early postnatal development. Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs) have been associated with abnormal cortical interneuron development, but which of the hundreds of NDD genes impact interneuron generation and migration into circuits and how they mediate these effects remain unknown. We previously developed a stem cell-based platform to study human cortical interneurons in self-organizing organoids resembling the ventral forebrain and their migration using forebrain assembloids. Here, we integrate assembloid technology with CRISPR screening to systematically investigate the involvement of 425 NDD genes in human interneuron development. The first screen aimed at interneuron generation revealed 13 candidate genes, including the RNA-binding protein CSDE1 and the canonical TGF{beta} signaling activator SMAD4. Then, we ran an interneuron migration screen in [~]1,000 forebrain assembloids that identified 33 candidate genes, including cytoskeleton-related genes and, notably, the endoplasmic reticulum (ER)-related gene LNPK. Interestingly, we discovered that, during interneuron migration, the ER is displaced along the leading neuronal branch prior to nuclear translocation. Deletion of LNPK interfered with this ER displacement and resulted in reduced interneuron saltation length, indicating a critical role for the ER in this migratory process. Taken together, these results highlight how this versatile CRISPR-assembloid platform can be used to systematically map disease genes onto early stages of human neural development and to reveal novel mechanisms regulating interneuron development.

neuroscience↗

Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes

It is widely assumed that cells must be physically isolated to study their molecular profiles. However, intact tissue samples naturally exhibit variation in cellular composition, which drives covariation of cell-class-specific molecular features. By analyzing transcriptional covariation in 7221 intact CNS samples from 840 individuals representing billions of cells, we reveal the core transcriptional identities of major CNS cell classes in humans. By modeling intact CNS transcriptomes as a function of variation in cellular composition, we identify cell-class-specific transcriptional differences in Alzheimers disease, among brain regions, and between species. Among these, we show that PMP2 is expressed by human but not mouse astrocytes and significantly increases mouse astrocyte size upon ectopic expression in vivo, causing them to more closely resemble their human counterparts. Our work is available as an online resource (http://oldhamlab.ctec.ucsf.edu) and provides a generalizable strategy for determining the core molecular features of cellular identity in intact biological systems.

neuroscience↗