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Beitel, L. K.

Publications and source records attributed to Beitel, L. K..

6 recordsLinked to original sources

A streamlined CRISPR workflow to introduce mutations and generate isogenic iPSCs for modeling amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) represents a complex neurodegenerative disorder with significant genetic heterogeneity. To date, both the genetic etiology and the underlying molecular mechanisms driving this disease remain poorly understood, although in recent years a number of studies have highlighted a number of genetic mutations causative for ALS. With these mutations pointing to potential pathways that may be affected within individuals with ALS, having the ability to generate human neurons and other disease relevant cells containing these mutations becomes even more critical if new therapies are to emerge. Recent developments with the advent of induced pluripotent stem cells (iPSCs) and clustered regularly interspaced short palindromic repeats (CRISPR) gene editing fields gave us the tools to introduce or correct a specific mutation at any site within the genome of an iPSC, and thus model the specific contribution of risk mutations. In this study we describe a rapid and efficient way to either introduce a mutation into a control line, or to correct a mutation, generating an isogenic control line from patient-derived iPSCs with a given mutation. The mutations introduced were the G93A mutation into SOD1 or H517Q into FUS, and the mutation corrected was a patient iPSC line with I114T in SOD1. A combination of small molecules and growth factors were used to guide a stepwise differentiation of the edited cells into motor neurons in order to demonstrate that disease-relevant cells could be generated for downstream applications. Through a combination of iPSCs and CRISPR editing, the cells generated here will provide fundamental insights into the molecular mechanisms underlying neuron degeneration in ALS.

neuroscience

Microfabricated disk technology: rapid scale up in midbrain organoid generation

By providing a three-dimensional in vitro culture system with key features of the substantia nigra region in the brain, 3D neuronal organoids derived from human induced pluripotent stem cells (iPSCs) provide living neuronal tissue resembling the midbrain region of the brain. However, a major limitation of conventional brain organoid culture is that it is often labor-intensive, requiring highly specialized personnel for moderate throughput. Additionally, the methods published for long-term cultures require time-consuming maintenance to generate brain organoids in large numbers. With the increasing need for human midbrain organoids (hMOs) to better understand and model Parkinsons disease (PD) in a dish, there is a need to implement new workflows and methods to both generate and maintain hMOs, while minimizing batch to batch variation. In this study, we developed a method with microfabricated disks to scale up the generation of hMOs. This opens up the possibility to generate larger numbers of hMOs, in a manner that minimizes the amount of labor required, while decreasing variability and maintaining the viability of these hMOs over time. Taken together, producing hMOs in this manner opens up the potential for these to be used to further PD studies.

neuroscience

Midbrain organoids with an SNCA gene triplication model key features of synucleinopathy

SNCA, the first gene associated with Parkinsons disease, encodes the -synuclein (-syn) protein, the predominant component within pathological inclusions termed Lewy bodies (LBs). The presence of LBs is one of the classical hallmarks found in the brain of patients with Parkinsons disease, and LBs have also been observed in patients with other synucleinopathies. However, the study of -syn pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use 3D midbrain organoids (hMOs), differentiated from human induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These hMOs recapitulate key features of -syn pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication hMOs express elevated levels of -syn and exhibit an age-dependent increase in -syn aggregation, manifested by the presence of both oligomeric and phosphorylated forms of -syn. These phosphorylated -syn aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, hMOs from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinsons disease and provide a powerful system to study the pathogenesis of synucleinopathies.

neuroscience

Auto-qPCR: A Python based web app for automated and reproducible analysis of qPCR data

Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app (https://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

molecular biology

Standardized quality control workflow to evaluate the reproducibility and differentiation potential of human iPSCs into neurons

Induced pluripotent stem cells (iPSCs) derived from human somatic cells have created new opportunities to generate disease-relevant cells. Thus, as the use of patient-derived stem cells has become more widespread, having a workflow to monitor each line is critical. This ensures iPSCs pass a suite of quality control measures, promoting reproducibility across experiments and between labs. With this in mind, we established a multistep workflow to assess our newly generated iPSCs for variations and reproducibility relative to each other and iPSCs obtained from external sources. Our benchmarks for evaluating iPSCs include examining iPSC morphology and proliferation in two different media conditions and evaluating their ability to differentiate into each of the three germ layers, with a particular focus on neurons. Genomic integrity in the human iPSCs was analyzed by G-band karyotyping and a qPCR-based test for the detection of hotspot mutations test. Cell-line identity was authenticated by Short Tandem Repeat (STR) analysis. Using standardized dual SMAD inhibition methods, all iPSC lines gave rise to neural progenitors that could subsequently be differentiated into cortical neurons. Neural differentiation was analyzed qualitatively by immunocytochemistry and quantitatively by qPCR for progenitor, neuronal, cortical, and glial markers. Taken together, we present a multistep quality control workflow to evaluate variability and reproducibility across and between iPSCs.

cell biology

Defining the Neural Kinome: Strategies and Opportunities for Small Molecule Drug Discovery to Target Neurodegenerative Diseases

Kinases are highly tractable drug targets that have reached unparalleled success in fields such as cancer but whose potential has not yet been realized in neuroscience. There are currently 55 approved small molecule kinase-targeting drugs, 48 of which have an anti-cancer indication. The intrinsic complexity linked to central nervous system (CNS) drug development and a lack of validated targets has hindered progress in developing kinase inhibitors for CNS disorders when compared to other therapeutic areas such as oncology. Identification and/or characterization of new kinases as potential drug targets for neurodegenerative diseases will create opportunities for development of CNS drugs in the future. The track record of kinase inhibitors in other disease indications supports the idea that with the best targets identified small molecule kinase modulators will become impactful therapeutics for neurodegenerative diseases. KEY CONCEPTSChemical probe: a high-quality small molecule that is potent, selective, and cell-active that meets the following criteria: (1) in vitro biochemical IC50 < 50 nM, (2) [&ge;] 30-fold selectivity relative to other kinases in a large assay panel such as DiscoverX scanMAX, and (3) cellular activity or target engagement with an IC50 < 1 M Narrow spectrum: a selectivity threshold that can be defined as potently inhibiting [~]10% or less of all kinases screened Kinome: all human kinases Kinase chemogenomic set (KCGS): publicly-available curated physical library of narrow spectrum and potent kinase inhibitors for which the SGC-UNC has received permission to share the compounds; subsequent releases will increase kinome-wide coverage Illuminating the Druggable Genome (IDG) program: several interconnected projects currently funded by the National Institutes of Health to provide information on historically understudied members within protein families that have provided drug targets; the three main focus areas are kinases, G-protein coupled receptors, and ion channels IDG kinase: a kinase that was nominated as dark (understudied) by the National Institutes of Health IDG program (curated list found here: https://druggablegenome.net/IDGProteinList); IDG consortium members generate data and resources to aid in the illumination of the function of these kinases DK tool: a narrow spectrum inhibitor that exhibits a defined selectivity score (S10(1 M) < 0.05) and cellular target engagement with an IC50 < 1 M; S10(1 M) is a measure of selectivity equal to the percentage of screened kinases biochemically inhibited by >90% at 1 M

neuroscience