Biology subjects

Nehme, R.

Publications and source records attributed to Nehme, R..

At least 19 recordsLinked to original sources

bioRxiv2025

Gene editing in "cell villages" enables exploring disease-relevant mutations in many genetic backgrounds

Understanding how individual genetic backgrounds shape the effects of disease-associated mutations is central to elucidating the biology of complex psychiatric disorders. We developed a scalable village editing strategy that enables simultaneous genome editing across multiple induced pluripotent stem cell (iPSC) lines, allowing systematic assessment of how polygenic context modulates the impact of specific mutations. Using pooled CRISPR editing in 15 iPSC lines spanning a range of schizophrenia (SCZ) polygenic risk scores, we generated homozygous and heterozygous knockouts in two known SCZ-associated genes: LRP1, involved in cholesterol import, and NRXN1, a presynaptic adhesion molecule. By mixing all lines prior to editing and de-multiplexing them afterward, we efficiently produced multi-donor knockout neurons at scale. Transcriptomic profiling revealed that LRP1 and NRXN1 loss produce both shared and donor-specific effects on neuronal gene expression, with variable perturbation of neurotransmitter transport and cholesterol biosynthesis pathways across genetic backgrounds. These results demonstrate that village editing enables systematic dissection of gene-background interactions in human neurons, offering a powerful framework for studying the polygenic architecture of psychiatric disease.

cell biology↗

bioRxiv2025

Human genetic variation shapes the response of neurons to interferons

Inflammation is increasingly recognized as important to neuropathology, including more classic neuroimmune disease as well as neurodegenerative and neuropsychiatric disorders. Interferons (IFN) are important mediators of central nervous system inflammation. Individuals appear to vary in susceptibility to neuroinflammatory pathology, suggesting that identifying human genetic modifiers of the neuronal IFN response might provide insight into disease pathophysiology. To identify potential modifiers, we stimulated neuronal "cellular villages" of iPSC-derived neurons from over one hundred donors with IFN-alpha (IFNa) or IFN-gamma (IFNg). We then correlated allele states of common variable SNPs to gene expression to identify hundreds of expression quantitative trait loci (eQTLs), many of which emerged specifically upon IFN treatment. We characterized the distinct but overlapping neuronal transcriptional responses to IFNa and IFNg, and identified specific response QTLs. Functional annotation of STAT1 binding to the genome in response to IFN stimulus identified STAT1 binding sites as enriched for response-regulating human genetic variation and also enabled identification of loci with IFN-dependent allele-specific binding of STAT1. These results demonstrate how human genetic variation can influence IFN-dependent mechanisms in neurons in disease-relevant ways.

molecular biology↗

bioRxiv2025

Abnormal Lipid Metabolism and Altered Neuronal Support by Astrocytes Lacking Akap11, a Risk Gene for Schizophrenia and Bipolar Disorder

A-Kinase Anchoring Protein 11 (AKAP11) is a shared genetic risk factor for schizophrenia and bipolar disorder, yet its role in the brain remains poorly understood. Through multi-omic analysis of Akap11 mutant mouse brains and cultured astrocytes, we identified significant transcriptomic, proteomic, and metabolomic alterations. Key findings include the upregulation of cholesterol and fatty acid metabolic pathways, accumulation of lipid species such as cholesteryl esters, triacylglycerols, ceramides, and glycerophospholipids, and elevated levels of 3,5-cyclic AMP and protein kinase A (PKA) signaling. These metabolic perturbations manifested as increased lipid droplet accumulation in Akap11 mutant astrocytes, highlighting AKAP11s critical role in regulating intracellular lipid homeostasis. Mechanistically, AKAP11 functions as an autophagy receptor mediating PKA degradation and interacts with endoplasmic reticulum-resident proteins VAP-A and VAP-B through its FFAT motif, providing possible molecular insight into AKAP11s regulation of lipid metabolism. Co-culture experiments with mouse astrocytes and human induced pluripotent stem cell-derived neurons demonstrated that loss of Akap11 in astrocytes, relative to wild-type, increases excitatory neurotransmission and neuronal activity. Collectively, these findings link AKAP11-mediated lipid and synaptic dysregulation to psychiatric disease risk and highlight the potential role of astrocytes in these disorders.

cell biology↗

bioRxiv2025

CellFIE: Integrating Pathway Discovery With Pooled Profiling of Perturbations Uncovers Pathways of Huntington's Disease, Including Genetic Modifiers of Neuronal Development and Morphology

Genomic screens and GWAS are powerful tools for identifying disease-modifying genes, but it is often challenging to understand the pathways by which these genes function. Here, we take an integrated approach that combines network analysis and an imaging-based pooled genetic perturbation study to examine modifiers of Huntingtons disease (HD). The computational analysis highlighted several genes in a subnetwork enriched for modifiers of neuronal development and morphology. To test the functional roles of these genes, we developed an experimental pipeline that allows pooled CRISPRi KD of 21 genes in human iPSC-derived neurons followed by optical analysis of genotypes, neuronal arborization, multiplexed pathway activity and morphological fingerprint readout. This approach recovered known genes involved in morphology and confirmed unexpected links from the network between several genetic modifiers of HD and morphology. Our approach overcomes challenges in pooled measurement of neuronal function and health and could be adapted for other phenotypes in HD and other neurological diseases.

neuroscience↗

bioRxiv2025

Astrocytic-supplied cholesterol drives synaptic gene expression programs in developing neurons and downstream astrocytic transcriptional programs

Astrocytes participate in neuronal synaptic programs that are enriched for genetic associations in schizophrenia and autism spectrum disorders (ASD). To better understand how these co-regulated cellular programs are induced during early neuronal development, we studied astrocytes and iPSC-derived neurons in co-cultures and mono-cultures at 16 time points spanning 0.5 hours to 8 days. We found that upregulation in astrocytes of genes involved in cholesterol biosynthesis preceded the activation of synaptic gene programs in neurons and upregulation of the astrocytic Nrxn1. Neuronal knockdown of key cholesterol receptors led to downregulation of neuronal synaptic genes and induced a robust transcriptional response in the astrocytes, including further upregulation of Nrxn1. This suggests that astrocyte-supplied cholesterol drives these neuronal changes and that bi-directional signalling is occuring. The genes upregulated in neurons were enriched for deleterious variants in schizophrenia and neurodevelopmental disorders, suggesting that their pathogenic effect may be, in part, mediated by reduced buffering capacity for changes in the astrocyte cholesterol supply to neurons. These findings highlight the critical role of astrocyte-neuron interactions in psychiatric and neurodevelopmental disorders, particularly in relation to lipid metabolism and synaptic plasticity.

molecular biology↗

bioRxiv2024

Combining NeuroPainting with transcriptomics reveals cell-type-specific morphological and molecular signatures of the 22q11.2 deletion

Neuropsychiatric conditions pose substantial challenges for therapeutic development due to their complex and poorly understood underlying mechanisms. High-throughput, unbiased phenotypic assays present a promising path for advancing therapeutic discovery, especially within disease-relevant neural tissues. Here, we introduce NeuroPainting, a novel adaptation of the Cell Painting assay, optimized for high-dimensional morphological phenotyping of neural cell types, including neurons, neuronal progenitor cells, and astrocytes derived from human stem cells. Using NeuroPainting, we quantified cell structure and organelle behavior across various brain cell types, creating a public dataset of over 4,000 cellular traits. This extensive dataset not only sets a new benchmark for phenotypic screening in neuropsychiatric research but also serves as a gold standard for the research community, enabling comparisons and validation of results. We then applied NeuroPainting to identify morphological signatures associated with the 22q11.2 deletion, a major genetic risk factor for schizophrenia. We observed profound cell-type-specific effects of the 22q11.2 deletion, with significant alterations in mitochondrial structure, endoplasmic reticulum organization, and cytoskeletal dynamics, particularly in astrocytes. Transcriptomic analysis revealed reduced expression of cell adhesion genes in 22q11.2 deletion astrocytes, consistent with recent post-mortem findings. Integrating the RNA sequencing data and morphological profiles uncovered a novel biological link between altered expression of specific cell adhesion molecules and observed changes in mitochondrial morphology in 22q11.2 deletion astrocytes. These findings underscore the power of combined phenomic and transcriptomic analyses to reveal mechanistic insights associated with human genetic variants of neuropsychiatric conditions.

neuroscience↗

bioRxiv2024

Robust self-supervised denoising of voltage imaging data using CellMincer

Voltage imaging enables high-throughput investigation of neuronal activity, yet its utility is often constrained by a low signal-to-noise ratio (SNR). Conventional denoising algorithms, such as those based on matrix factorization, impose limiting assumptions about the noise process and the spatiotemporal structure of the signal. While deep learning based denoising techniques offer greater adaptability, existing approaches fail to fully exploit the fast temporal dynamics and unique short- and long-range dependencies within voltage imaging datasets. Here, we introduce CellMincer, a novel self-supervised deep learning method designed specifically for denoising voltage imaging datasets. CellMincer operates on the principle of masking and predicting sparse sets of pixels across short temporal windows and conditions the denoiser on precomputed spatiotemporal auto-correlations to effectively model long-range dependencies without the need for large temporal denoising contexts. We develop and utilize a physics-based simulation framework to generate realistic datasets for rigorous hyperparameter optimization and ablation studies, highlighting the key role of conditioning the denoiser on precomputed spatiotemporal auto-correlations to achieve 3-fold further reduction in noise. Comprehensive benchmarking on both simulated and real voltage imaging datasets, including those with paired patch-clamp electrophysiology (EP) as ground truth, demonstrates CellMincers state-of-the-art performance. It achieves substantial noise reduction across the entire frequency spectrum, enhanced detection of subthreshold events, and superior cross-correlation with ground-truth EP recordings. Finally, we demonstrate how CellMincers addition to a typical voltage imaging data analysis workflow improves neuronal segmentation, peak detection, and ultimately leads to significantly enhanced separation of functional phenotypes.

neuroscience↗

bioRxiv2024

A systems-biology approach connects aging mechanisms with Alzheimer's disease pathogenesis

Despite years of intense investigation, the mechanisms underlying neuronal death in Alzheimers disease, the most common neurodegenerative disorder, remain incompletely understood. To define relevant pathways, we integrated the results of an unbiased, genome-scale forward genetic screen for age-associated neurodegeneration in Drosophila with human and Drosophila Alzheimers disease-associated multi-omics. We measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimers disease and identified Alzheimers disease human genetic variants that modify expression in disease-vulnerable neurons. We used a network optimization approach to integrate these data with previously published Alzheimers disease multi-omic data. We computationally predicted and experimentally demonstrated how HNRNPA2B1 and MEPCE enhance tau-mediated neurotoxicity. Furthermore, we demonstrated that the screen hits CSNK2A1 and NOTCH1 regulate DNA damage in Drosophila and human iPSC-derived neural progenitor cells. Our work identifies candidate pathways that could be targeted to ameliorate neurodegeneration in Alzheimers disease.

systems biology↗

bioRxiv2023

Simultaneous CRISPR screening and spatial transcriptomics reveals intracellular, intercellular, and functional transcriptional circuits.

Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but have not yet leveraged the power of highly-plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present Perturb-FISH, which bridges these approaches by combining imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs. We show that Perturb-FISH recovers intracellular effects that are consistent with Perturb-seq results in a screen of lipopolysaccharide response in cultured monocytes, and uncover new intercellular and density-dependent regulation of the innate immune response. We further pair Perturb-FISH with a functional readout in a screen of autism spectrum disorder risk genes, showing common calcium activity phenotypes in induced pluripotent stem cell derived astrocytes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a generally applicable method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.

genomics↗

bioRxiv2023

Multi-donor human cortical Chimeroids reveal individual susceptibility to neurotoxic triggers

Inter-individual genetic variation affects the susceptibility to and progression of many diseases. Efforts to study the molecular mechanisms mediating the impact of human genetic variation on normal development and disease phenotypes are limited, however, by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple individuals. Here, we present human brain "Chimeroids", a highly reproducible, multi-donor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid, while maintaining fidelity to endogenous tissue. By reaggregating cells from multiple single-donor organoids at the neural stem or committed progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We leveraged Chimeroids to investigate inter-individual variation in susceptibility to neurotoxic stressors that exhibit high clinical phenotypic variability: ethanol and the anti-epileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results show that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of the contribution of human genetic variation to brain development and disease.

neuroscience↗

bioRxiv2023

Early Alzheimer's disease pathology in human cortex is associated with a transient phase of distinct cell states

Cellular perturbations underlying Alzheimers disease are primarily studied in human postmortem samples and model organisms. Here we generated a single-nucleus atlas from a rare cohort of cortical biopsies from living individuals with varying degrees of Alzheimers disease pathology. We next performed a systematic cross-disease and cross-species integrative analysis to identify a set of cell states that are specific to early AD pathology. These changes-which we refer to as the Early Cortical Amyloid Response--were prominent in neurons, wherein we identified a transient state of hyperactivity preceding loss of excitatory neurons, which correlated with the selective loss of layer 1 inhibitory neurons. Microglia overexpressing neuroinflammatory-related processes also expanded as AD pathological burden increased. Lastly, both oligodendrocytes and pyramidal neurons upregulated genes associated with amyloid beta production and processing during this early hyperactive phase. Our integrative analysis provides an organizing framework for targeting circuit dysfunction, neuroinflammation, and amyloid production early in AD pathogenesis.

genomics↗

bioRxiv2023

High-dimensional phenotyping to define the genetic basis of cellular morphology

The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combined genomic and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identified novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirmed their role in cell morphology. Analysis of common variants yielded one significant association and nominated over 300 variants with suggestive evidence (P<10-6) of association with one or more morphology traits. Our results showed that, similar to other molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.

genomics↗

bioRxiv2022

Robust induction of functional astrocytes using NGN2 expression in human pluripotent stem cells

Astrocytes play essential roles in normal brain function, with dysfunction implicated in diverse developmental and degenerative disease processes. Emerging evidence of profound species divergent features of astrocytes coupled with the relative inaccessibility of human brain tissue underscore the utility of human pluripotent stem cell (hPSC) technologies for the generation and study of human astrocytes. However, existing approaches for hPSC-astrocyte generation are typically lengthy, incompletely characterized, or require intermediate purification steps, limiting their utility for multi-cell line, adequately powered functional studies. Here, we establish a rapid and highly scalable method for generating functional human induced astrocytes (hiAs) based upon transient Neurogenin 2 (NGN2) induction of neural progenitor-like cells followed by maturation in astrocyte media, which demonstrate remarkable homogeneity within the population and across 11 independent cell lines in the absence of additional purification steps. These hiAs express canonical astrocyte markers, respond to pro-inflammatory stimuli, exhibit ATP-induced calcium transients and support neuronal maturation in vitro. Moreover, single-cell transcriptomic analyses reveal the generation of highly reproducible cell populations across individual donors, most closely resembling human fetal astrocytes, and highly similar to hPSC-derived astrocytes generated using more complex approaches. Finally, the hiAs capture key molecular hallmarks in a trisomy 21 disease model. Thus, hiAs provide a valuable and practical resource well-suited for study of basic human astrocyte function and dysfunction in disease.

neuroscience↗

bioRxiv2022

Efficient generation of lower induced Motor Neurons by coupling Ngn2 expression with developmental cues

Human pluripotent stem cells (hPSCs) are a powerful tool for disease modelling and drug discovery, especially when access to primary tissue is limited, such as in the brain. Current neuronal differentiation approaches use either small molecules for directed differentiation or transcription-factor-mediated programming. In this study we coupled the overexpression of the neuralising transcription factor Neurogenin2 (Ngn2) with small molecule patterning to differentiate hPSCs into lower induced Motor Neurons (liMoNes). We showed that this approach induced activation of the motor neuron (MN) specific transcription factor Hb9/MNX1, using anHb9::GFP-reporter line, with up to 95% of cells becoming Hb9::GFP+. These cells acquired and maintained expression of canonical early and mature MN markers. Molecular and functional profiling revealed that liMoNes resembled bona fide hPSC-derived MN differentiated by conventional small molecule patterning. liMoNes exhibited spontaneous electrical activity, expressed synaptic markers and formed contacts with muscle cells in vitro. Pooled, multiplex single-cell RNA sequencing on 50 cell lines revealed multiple anatomically distinct MN subtypes of cervical and brachial, limb-innervating MNs in reproducible quantities. We conclude that combining small molecule patterning with Ngn2 can facilitate the high-yield, robust and reproducible production of multiple disease-relevant MN subtypes, which is fundamental in the path to propel forward our knowledge of motoneuron biology and its disruption in disease.

neuroscience↗

bioRxiv2021

The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia

To study how the 22q11.2 deletion predisposes to psychiatric disease, we generated induced pluripotent stem cells from deletion carriers and controls, as well as utilized CRISPR/Cas9 to introduce the heterozygous deletion into a control cell line. Upon differentiation into neural progenitor cells, we found the deletion acted in trans to alter the abundance of transcripts associated with risk for neurodevelopmental disorders including Autism Spectrum Disorder. In more differentiated excitatory neurons, altered transcripts encoded presynaptic factors and were associated with genetic risk for schizophrenia, including common (per-SNP heritability p ({tau}c)= 4.2 x 10-6) and rare, loss of function variants (p = 1.29x10-12). These findings suggest a potential relationship between cellular states, developmental windows and susceptibility to psychiatric conditions with different ages of onset. To understand how the deletion contributed to these observed changes in gene expression, we developed and applied PPItools, which identifies the minimal protein-protein interaction network that best explains an observed set of gene expression alterations. We found that many of the genes in the 22q11.2 interval interact in presynaptic, proteasome, and JUN/FOS transcriptional pathways that underlie the broader alterations in psychiatric risk gene expression we identified. Our findings suggest that the 22q11.2 deletion impacts genes and pathways that may converge with risk loci implicated by psychiatric genetic studies to influence disease manifestation in each deletion carrier.

neuroscience↗

bioRxiv2021

Astrocytic cell adhesion genes linked to schizophrenia promote synaptic programs in neurons

The maturation of neurons and the development of synapses - while emblematic of neurons - also rely on interactions with astrocytes and other glia. To study the role of glia-neuron interactions, we analyzed the transcriptomes of human pluripotent stem cell (hPSC)-derived neurons, from a total of 80 human donors, that were cultured with or without contact with glial cells. We found that the presence of astrocytes enhanced synaptic gene-expression programs in neurons. These changes in neuronal synaptic gene expression correlated with increased expression in the co-cultured glia of genes that encode synaptic cell adhesion molecules, and they were greatly enhanced in the glia in coculture. Both the neuronal and astrocyte gene-expression programs were enriched for genes that are linked to schizophrenia risk. Physical contact between the two cell types was required for the induction of synaptic programs in neurons. Our results suggest that astrocyte-expressed genes with synaptic functions are associated with stronger expression of synaptic genetic programs in neurons and suggest a potential role for astrocyte-neuron interactions in schizophrenia.

molecular biology↗

bioRxiv2021

waveRAPID(R) - a robust assay for high-throughput kinetic screens with the Creoptix(R) WAVEsystem

Surface-based biophysical methods for measuring binding kinetics of molecular interactions, such as Surface Plasmon Resonance (SPR) or Grating-Coupled Interferometry (GCI), are now well established and widely used in drug discovery. Increasing throughput is an often-cited need in the drug discovery process, and this has been achieved with new instrument generations where multiple interactions are measured in parallel, shortening the total measurement times and enabling new application areas within the field. Here, we present the development of a novel technology called waveRAPID for a further - up to ten-fold - increase in throughput, consisting of an injection method using a single sample. Instead of sequentially injecting increasing analyte concentrations for constant durations, the analyte is injected at a single concentration in short pulses of increasing durations. A major advantage of the new method is its ability to determine kinetics from a single well of a micro-titer plate, making it uniquely suitable for kinetic screening. We present the fundamentals of this approach using a small molecule model system for experimental validation and comparing kinetic parameters to traditional methods. By varying experimental conditions, we furthermore assess the robustness of this new technique. Finally, we discuss its potential for improving hit quality and shortening cycle times in the areas of fragment screening, low molecule weight compound screening, and hit-to-lead optimization.

biophysics↗

bioRxiv2020

Mapping genetic effects on cellular phenotypes with "cell villages"

Tens of thousands of genetic variants shape human phenotypes, mostly by unknown cellular mechanisms. Here we describe Census-seq, a way to measure cellular phenotypes in cells from many people simultaneously. Analogous to pooled CRISPR screens but for natural variation, Census-seq associates cellular phenotypes to donors genotypes by quantifying the presence of each donors DNA in cell "villages" before and after sorting or selection for cellular traits of interest. Census-seq enables population-scale cell-biological phenotyping with low cost and high internal control. We demonstrate Census-seq through investigation of genetic effects on the SMN protein whose deficiency underlies spinal muscular atrophy (SMA). Census-seq quantified and mapped effects of many common alleles on SMN protein levels and response to SMN-targeted therapeutics, including a common, cryptic non-responder allele. We provide tools enabling population-scale cell experiments and explain how Census-seq can be used to map genetic effects on diverse cell phenotypes. O_FIG O_LINKSMALLFIG WIDTH=185 HEIGHT=200 SRC="FIGDIR/small/174383v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@169bf4borg.highwire.dtl.DTLVardef@18dd9c0org.highwire.dtl.DTLVardef@1d30ca5org.highwire.dtl.DTLVardef@e35bf0_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LICensus-seq reveals how inherited genetic variation affects cell phenotypes C_LIO_LIGenetic analysis of cellular traits in cell villages of >100 donors C_LIO_LICharacterizing human alleles that shape SMN protein expression and drug responses C_LIO_LIDevelopment of protocols and software to enable cellular population genetics C_LI

genetics↗