Genome editing and human induced pluripotent stem cells hold great promise for the development of isogenic disease models and the correction of disease-associated mutations for isogenic tissue ...therapy. CRISPR-Cas9 has emerged as a versatile and simple tool for engineering human cells for such purposes. However, the current protocols to derive genome-edited lines require the screening of a great number of clones to obtain one free of random integration or on-locus non-homologous end joining (NHEJ)-containing alleles. Here, we describe an efficient method to derive biallelic genome-edited populations by the use of fluorescent markers. We call this technique FACS-assisted CRISPR-Cas9 editing (FACE). FACE allows the derivation of correctly edited polyclones carrying a positive selection fluorescent module and the exclusion of non-edited, random integrations and on-target allele NHEJ-containing cells. We derived a set of isogenic lines containing Parkinson's-disease-associated mutations in α-synuclein and present their comparative phenotypes.
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•Fluorescent protein-SNP pairs enable deterministic genotypes for genome editing•Repetitive elements modulate off-targeting random integration•Parkinson's disease NESCs present impaired mitochondrial energy performance
In this article, Arias-Fuenzalida and colleagues show a platform to achieve deterministic genotypes for genome editing. The combinatorial use of fluorescent proteins and defined SNPs facilitates the genome editing endeavor. Using neuroepithelial stem cells, they demonstrate early mitochondrial phenotypes in SNCA mutants.
Abstract
The study of complex diseases relies on large amounts of data to build models toward precision medicine. Such data acquisition is feasible in the context of high-throughput screening, in ...which the quality of the results relies on the accuracy of the image analysis. Although state-of-the-art solutions for image segmentation employ deep learning approaches, the high cost of manually generating ground truth labels for model training hampers the day-to-day application in experimental laboratories. Alternatively, traditional computer vision-based solutions do not need expensive labels for their implementation. Our work combines both approaches by training a deep learning network using weak training labels automatically generated with conventional computer vision methods. Our network surpasses the conventional segmentation quality by generalising beyond noisy labels, providing a 25% increase of mean intersection over union, and simultaneously reducing the development and inference times. Our solution was embedded into an easy-to-use graphical user interface that allows researchers to assess the predictions and correct potential inaccuracies with minimal human input. To demonstrate the feasibility of training a deep learning solution on a large dataset of noisy labels automatically generated by a conventional pipeline, we compared our solution against the common approach of training a model from a small manually curated dataset by several experts. Our work suggests that humans perform better in context interpretation, such as error assessment, while computers outperform in pixel-by-pixel fine segmentation. Such pipelines are illustrated with a case study on image segmentation for autophagy events. This work aims for better translation of new technologies to real-world settings in microscopy-image analysis.
Autophagic processes play a central role in cellular homeostasis. In pathological conditions, the flow of autophagy can be affected at multiple and distinct steps of the pathway. Current analyses ...tools do not deliver the required detail for dissecting pathway intermediates. The development of new tools to analyze autophagic processes qualitatively and quantitatively in a more straightforward manner is required. Defining all autophagy pathway intermediates in a high-throughput manner is technologically challenging and has not been addressed yet. Here, we overcome those requirements and limitations by the developed of stable autophagy and mitophagy reporter-iPSC and the establishment of a novel high-throughput phenotyping platform utilizing automated high-content image analysis to assess autophagy and mitophagy pathway intermediates.
In vitro culture systems that structurally model human myogenesis and promote PAX7+ myogenic progenitor maturation have not been established. Here we report that human skeletal muscle organoids can ...be differentiated from induced pluripotent stem cell lines to contain paraxial mesoderm and neuromesodermal progenitors and develop into organized structures reassembling neural plate border and dermomyotome. Culture conditions instigate neural lineage arrest and promote fetal hypaxial myogenesis toward limb axial anatomical identity, with generation of sustainable uncommitted PAX7 myogenic progenitors and fibroadipogenic (PDGFRa+) progenitor populations equivalent to those from the second trimester of human gestation. Single-cell comparison to human fetal and adult myogenic progenitor /satellite cells reveals distinct molecular signatures for non-dividing myogenic progenitors in activated (CD44High/CD98+/MYOD1+) and dormant (PAX7High/FBN1High/SPRY1High) states. Our approach provides a robust 3D in vitro developmental system for investigating muscle tissue morphogenesis and homeostasis.
The juvenile form of neuronal ceroid Lipofuscinosis (JNCL) is the most common form within this group of rare lysosomal storage disorders, causing pediatric neurodegeneration. The genetic disorder, ...which is caused by recessive mutations affecting the CLN3 gene, features progressive vision loss, cognitive and motor decline and other psychiatric conditions, seizure episodes, leading to premature death. Animal models have traditionally aid the understanding of the disease mechanisms and pathology and are very relevant for biomarker research and therapeutic testing. Nevertheless, there is a need for establishing reliable and predictive human cellular models to study the disease. Since patient material, particularly from children, is scarce and difficult to obtain, we generated an engineered a CLN3-mutant isogenic human induced pluripotent stem cell (hiPSC) line carrying the c.1054C → T pathologic variant, using state of the art CRISPR/Cas9 technology. To prove the suitability of the isogenic pair to model JNCL, we screened for disease-specific phenotypes in non-neuronal two-dimensional cell culture models as well as in cerebral brain organoids. Our data demonstrates that the sole introduction of the pathogenic variant gives rise to classical hallmarks of JNCL in vitro. Additionally, we discovered an alteration of the splicing caused by this particular mutation. Next, we derived cerebral organoids and used them as a neurodevelopmental model to study the particular effects of the CLN3
mutation during brain formation in the disease context. About half of the mutation -carrying cerebral organoids completely failed to develop normally. The other half, which escaped this severe defect were used for the analysis of more subtle alterations. In these escapers, whole-transcriptome analysis demonstrated early disease signatures, affecting pathways related to development, corticogenesis and synapses. Complementary metabolomics analysis confirmed decreased levels of cerebral tissue metabolites, some particularly relevant for synapse formation and neurotransmission, such as gamma-amino butyric acid (GABA). Our data suggests that a mutation in CLN3 severely affects brain development. Furthermore, before disease onset, disease -associated neurodevelopmental changes, particular concerning synapse formation and function, occur.
The vast majority of Parkinson's disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic ...and metabolic alterations consistent across different idiopathic Parkinson's disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.
In the search for biomarkers of synapse loss associated with Alzheimer's disease (AD), we used shotgun proteomics to identify a panel of 9 synaptic proteins detectable in human cerebrospinal fluid ...(CSF). Expression at the human synapse was verified using super resolution microscopy. Using SRM, we monitored the panel in CSF from 3 independent clinical cohorts. We report 6 synaptic biomarkers that demonstrate changes in preclinical AD prior to markers of neurodegeneration, which could have clinical value for assessing disease progression.
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Highlights
•Proteomic analysis of cerebrospinal fluid and identification of synaptic component.•Use of super resolution microscopy to verify synapse-specificity in human tissue.•Selective reaction monitoring MS (SRM) of synaptic panel in 3 cohorts of Alzheimer's disease cerebrospinal fluid.•Synaptic protein changes precede tau in preclinical Alzheimer's disease.
A biomarker of synapse loss, an early event in Alzheimer's disease (AD) pathophysiology that precedes neuronal death and symptom onset, would be a much-needed prognostic biomarker. With direct access to the brain interstitial fluid, the cerebrospinal fluid (CSF) is a potential source of synapse-derived proteins. In this study, we aimed to identify and validate novel CSF biomarkers of synapse loss in AD. Discovery: Combining shotgun proteomics of the CSF with an exhaustive search of the literature and public databases, we identified 251 synaptic proteins, from which we selected 22 for further study. Verification: Twelve proteins were discarded because of poor detection by Selected Reaction Monitoring (SRM). We confirmed the specific expression of 9 of the remaining proteins (Calsyntenin-1, GluR2, GluR4, Neurexin-2A, Neurexin-3A, Neuroligin-2, Syntaxin-1B, Thy-1, Vamp-2) at the human synapse using Array Tomography microscopy and biochemical fractionation methods. Exploration: Using SRM, we monitored these 9 synaptic proteins (20 peptides) in a cohort of CSF from cognitively normal controls and subjects in the pre-clinical and clinical AD stages (n = 80). Compared with controls, peptides from 8 proteins were elevated 1.3 to 1.6-fold (p < 0.04) in prodromal AD patients. Validation: Elevated levels of a GluR4 peptide at the prodromal stage were replicated (1.3-fold, p = 0.04) in an independent cohort (n = 60). Moreover, 7 proteins were reduced at preclinical stage 1 (0.6 to 0.8-fold, p < 0.04), a finding that was replicated (0.7 to 0.8-fold, p < 0.05) for 6 proteins in a third cohort (n = 38). In a cross-cohort meta-analysis, 6 synaptic proteins (Calsyntenin-1, GluR4, Neurexin-2A, Neurexin-3A, Syntaxin-1B and Thy-1) were reduced 0.8-fold (p < 0.05) in preclinical AD, changes that precede clinical symptoms and CSF markers of neurodegeneration. Therefore, these proteins could have clinical value for assessing disease progression, especially in preclinical stages of AD.
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