Expression of ALS-PFN1 impairs vesicular degradation in iPSC-derived microglia.

Microglia play a pivotal role in neurodegenerative disease pathogenesis, but the mechanisms underlying microglia dysfunction and toxicity remain to be elucidated. To investigate the effect of neurodegenerative disease-linked genes on the intrinsic properties of microglia, we studied microglia-like cells derived from human induced pluripotent stem cells (iPSCs), termed iMGs, harboring mutations in profilin-1 (PFN1) that are causative for amyotrophic lateral sclerosis (ALS). ALS-PFN1 iMGs exhibited evidence of lipid dysmetabolism, autophagy dysregulation and deficient phagocytosis, a canonical microglia function. Mutant PFN1 also displayed enhanced binding affinity for PI3P, a critical signaling molecule involved in autophagic and endocytic processing. Our cumulative data implicate a gain-of-toxic function for mutant PFN1 within the autophagic and endo-lysosomal pathways, as administration of rapamycin rescued phagocytic dysfunction in ALS-PFN1 iMGs. These outcomes demonstrate the utility of iMGs for neurodegenerative disease research and implicate microglial vesicular degradation pathways in the pathogenesis of these disorders.

Reliable multiplex generation of pooled induced pluripotent stem cells.

Reprogramming somatic cells into pluripotent stem cells (iPSCs) enables the study of systems in vitro. To increase the throughput of reprogramming, we present induction of pluripotency from pooled cells (iPPC)-an efficient, scalable, and reliable reprogramming procedure. Using our deconvolution algorithm that employs pooled sequencing of single-nucleotide polymorphisms (SNPs), we accurately estimated individual donor proportions of the pooled iPSCs. With iPPC, we concurrently reprogrammed over one hundred donor lymphoblastoid cell lines (LCLs) into iPSCs and found strong correlations of individual donors' reprogramming ability across multiple experiments. Individual donors' reprogramming ability remains consistent across both same-day replicates and multiple experimental runs, and the expression of certain immunoglobulin precursor genes may impact reprogramming ability. The pooled iPSCs were also able to differentiate into cerebral organoids. Our procedure enables a multiplex framework of using pooled libraries of donor iPSCs for downstream research and investigation of in vitro phenotypes.

Expression of ALS-PFN1 impairs vesicular degradation in iPSC-derived microglia.

Microglia play a pivotal role in neurodegenerative disease pathogenesis, but the mechanisms underlying microglia dysfunction and toxicity remain to be fully elucidated. To investigate the effect of neurodegenerative disease-linked genes on the intrinsic properties of microglia, we studied microglia-like cells derived from human induced pluripotent stem cells (iPSCs), termed iMGs, harboring mutations in profilin-1 (PFN1) that are causative for amyotrophic lateral sclerosis (ALS). ALS-PFN1 iMGs exhibited lipid dysmetabolism and deficits in phagocytosis, a critical microglia function. Our cumulative data implicate an effect of ALS-linked PFN1 on the autophagy pathway, including enhanced binding of mutant PFN1 to the autophagy signaling molecule PI3P, as an underlying cause of defective phagocytosis in ALS-PFN1 iMGs. Indeed, phagocytic processing was restored in ALS-PFN1 iMGs with Rapamycin, an inducer of autophagic flux. These outcomes demonstrate the utility of iMGs for neurodegenerative disease research and highlight microglia vesicular degradation pathways as potential therapeutic targets for these disorders.

Modeling of mitochondrial genetic polymorphisms reveals induction of heteroplasmy by pleiotropic disease locus 10398A>G.

Mitochondrial (MT) dysfunction has been associated with several neurodegenerative diseases including Alzheimer's disease (AD). While MT-copy number differences have been implicated in AD, the effect of MT heteroplasmy on AD has not been well characterized. Here, we analyzed over 1800 whole genome sequencing data from four AD cohorts in seven different tissue types to determine the extent of MT heteroplasmy present. While MT heteroplasmy was present throughout the entire MT genome for blood samples, we detected MT heteroplasmy only within the MT control region for brain samples. We observed that an MT variant 10398A>G (rs2853826) was significantly associated with overall MT heteroplasmy in brain tissue while also being linked with the largest number of distinct disease phenotypes of all annotated MT variants in MitoMap. Using gene-expression data from our brain samples, our modeling discovered several gene networks involved in mitochondrial respiratory chain and Complex I function associated with 10398A>G. The variant was also found to be an expression quantitative trait loci (eQTL) for the gene MT-ND3. We further characterized the effect of 10398A>G by phenotyping a population of lymphoblastoid cell-lines (LCLs) with and without the variant allele. Examination of RNA sequence data from these LCLs reveal that 10398A>G was an eQTL for MT-ND4. We also observed in LCLs that 10398A>G was significantly associated with overall MT heteroplasmy within the MT control region, confirming the initial findings observed in post-mortem brain tissue. These results provide novel evidence linking MT SNPs with MT heteroplasmy and open novel avenues for the investigation of pathomechanisms that are driven by this pleiotropic disease associated loci.

FACS-Based Sequencing Approach to Evaluate Cell Type to Genotype Associations Using Cerebral Organoids.

Recent technological developments have led to widespread applications of large-scale transcriptomics-based sequencing methods to identify genotype-to-cell type associations. Here we describe a fluorescence-activated cell sorting (FACS)-based sequencing method to utilize CRISPR/Cas9 edited mosaic cerebral organoids to identify or validate genotype-to-cell type associations. Our approach is high-throughput and quantitative and uses internal controls to enable comparisons of the results across different antibody markers and experiments.

oFlowSeq: a quantitative approach to identify protein coding mutations affecting cell type enrichment using mosaic CRISPR-Cas9 edited cerebral organoids.

Cerebral organoids are comprised of diverse cell types found in the developing human brain, and can be leveraged in the identification of critical cell types perturbed by genetic risk variants in common, neuropsychiatric disorders. There is great interest in developing high-throughput technologies to associate genetic variants with cell types. Here, we describe a high-throughput, quantitative approach (oFlowSeq) by utilizing CRISPR-Cas9, FACS sorting, and next-generation sequencing. Using oFlowSeq, we found that deleterious mutations in autism-associated gene KCTD13 resulted in increased proportions of Nestin+ cells and decreased proportions of TRA-1-60+ cells within mosaic cerebral organoids. We further identified that a locus-wide CRISPR-Cas9 survey of another 18 genes in the 16p11.2 locus resulted in most genes with > 2% maximum editing efficiencies for short and long indels, suggesting a high feasibility for an unbiased, locus-wide experiment using oFlowSeq. Our approach presents a novel method to identify genotype-to-cell type imbalances in an unbiased, high-throughput, quantitative manner.

Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder.

Cerebral organoids can be used to gain insights into cell type specific processes perturbed by genetic variants associated with neuropsychiatric disorders. However, robust and scalable phenotyping of organoids remains challenging. Here, we perform RNA sequencing on 71 samples comprising 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to integrate bulk RNA and single-cell RNA sequence data. We apply Orgo-Seq to 16p11.2 deletions and 15q11-13 duplications, two loci associated with autism spectrum disorder, to identify immature neurons and intermediate progenitor cells as critical cell types for 16p11.2 deletions. We further applied Orgo-Seq to identify cell type-specific driver genes. Our work presents a quantitative phenotyping framework to integrate multi-transcriptomic datasets for the identification of cell types and cell type-specific co-expressed driver genes associated with neuropsychiatric disorders.