Faculty Bibliography

Neuronal replacement therapies rely on the in vitro differentiation of specific cell types from embryonic or induced pluripotent stem cells, or on the direct reprogramming of differentiated adult cells via the expression of transcription factors or signaling molecules. The factors used to induce differentiation or reprogramming are often identified by informed guesses based on differential gene expression or known roles for these factors during development. Moreover, differentiation protocols usually result in partly differentiated cells or the production of a mix of cell types. In this Hypothesis article, we suggest that, to overcome these inefficiencies and improve neuronal differentiation protocols, we need to take into account the developmental history of the desired cell types. Specifically, we present a strategy that uses single-cell sequencing techniques combined with machine learning as a principled method to select a sequence of programming factors that are important not only in adult neurons but also during differentiation.

Pathogenic muscle-specific tyrosine kinase (MuSK)-specific IgG4 autoantibodies in autoimmune myasthenia gravis (MG) are functionally monovalent as a result of Fab-arm exchange. The development of these unique autoantibodies is not well understood. We examined MG patient-derived monoclonal autoantibodies (mAbs), their corresponding germline-encoded unmutated common ancestors (UCAs), and monovalent antigen-binding fragments (Fabs) to investigate how affinity maturation contributes to binding and immunopathology. Mature mAbs, UCA mAbs, and mature monovalent Fabs bound to MuSK and demonstrated pathogenic capacity. However, monovalent UCA Fabs bound to MuSK but did not have measurable pathogenic capacity. Affinity of the UCA Fabs for MuSK was 100-fold lower than the subnanomolar affinity of the mature Fabs. Crystal structures of two Fabs revealed how mutations acquired during affinity maturation may contribute to increased MuSK-binding affinity. These findings indicate that the autoantigen drives autoimmunity in MuSK MG through the accumulation of somatic mutations such that monovalent IgG4 Fab-arm-exchanged autoantibodies reach a high-affinity threshold required for pathogenic capacity.

Rationale: Fibroblast growth factor homologous factors (FHFs) are key regulators of sodium channel inactivation. Mutations in these critical proteins have been implicated in human diseases including Brugada syndrome, idiopathic ventricular arrhythmias, and epileptic encephalopathy. The underlying ionic mechanisms by which reduced sodium channel availability in Fhf2 knockout mice predisposes to abnormal excitability at the tissue level are not well defined. Objective: Using animal models and theoretical multicellular linear strands, we examined how FHF2 orchestrates the interdependency of sodium, calcium, and gap junctional conductances to safeguard cardiac conduction. Methods and Results:Fhf2^KO mice were challenged by reducing calcium conductance using verapamil or by reducing gap junctional conductance using carbenoxolone or by backcrossing into a connexin 43 heterozygous (Cx43^+/-) background. All conditions produced conduction block in Fhf2^KO mice, with Fhf2^WT showing normal impulse propagation. To explore the ionic mechanisms of block in Fhf2^KO hearts, multicellular linear strand models incorporating FHF2-deficient sodium channel inactivation properties were constructed and faithfully recapitulated conduction abnormalities seen in mutant hearts. The mechanisms of conduction block in mutant strands with reduced calcium conductance or gap junction uncoupling are very different. Enhanced sodium channel inactivation due to FHF2 deficiency shifts dependence onto calcium current to sustain electrotonic driving force, axial current flow, and action potential generation from cell-to-cell. In the setting of gap junction uncoupling, slower charging time from upstream cells conspires with accelerated sodium channel inactivation in mutant strands to prevent sufficient downstream cell charging for action potential propagation. Conclusions: FHF2-dependent effects on sodium channel inactivation ensure adequate sodium current reserve to safeguard against numerous threats to reliable cardiac impulse propagation.

A 10-year-old girl presented with ileus, urinary retention, dry mouth, lack of tears, fixed dilated pupils, and diffuse anhidrosis 7-days after a febrile illness. We hypothesized that her syndrome was due to autoimmunity against muscarinic acetylcholine receptors, blocking their activation. Using an indirect enzyme-linked immunosorbent assay for all five muscarinic receptors (M₁ -M₅ ) we identified in the patient's serum antibodies that selectively bound to M₃ receptors. In-vitro functional studies confirmed that these autoantibodies selectively blocked M₃ receptor activation. Thus, autoantibodies against M₃ acetylcholine receptors can cause acute postganglionic cholinergic dysautonomia. This article is protected by copyright. All rights reserved.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Aberrant aggregation of RNA binding protein TDP-43 in neurons is a hallmark of frontotemporal lobar degeneration caused by progranulin haploinsufficiency^1,2. However, the mechanism leading to TDP-43 proteinopathy remains unclear. Here we use single-nucleus RNA-sequencing (snRNA-seq) to show that progranulin deficiency promotes microglial transition from a homeostatic to disease-specific state that causes endolysosomal dysfunction and neurodegeneration. These defects persist even when Grn^-/- microglia are cultured ex vivo. In addition, snRNA-seq reveals selective loss of excitatory neurons at disease end-stage, characterized by prominent nuclear and cytoplasmic TDP-43 granules and nuclear pore defects. Remarkably, conditioned media from Grn^-/- microglia is sufficient to promote TDP-43 granule formation, nuclear pore defects and cell death in excitatory neurons via the complement activation pathway. Consistent with these results, deleting C1qa and C3 mitigates microglial toxicity, and rescues TDP-43 proteinopathy and neurodegeneration. These results uncover previously unappreciated contributions of chronic microglial toxicity to TDP-43 proteinopathy during neurodegeneration.

Recent success in identifying gene-regulatory elements in the context of recombinant adeno-associated virus vectors has enabled cell-type-restricted gene expression. However, within the cerebral cortex these tools are largely limited to broad classes of neurons. To overcome this limitation, we developed a strategy that led to the identification of multiple new enhancers to target functionally distinct neuronal subtypes. By investigating the regulatory landscape of the disease gene Scn1a, we discovered enhancers selective for parvalbumin (PV) and vasoactive intestinal peptide-expressing interneurons. Demonstrating the functional utility of these elements, we show that the PV-specific enhancer allowed for the selective targeting and manipulation of these neurons across vertebrate species, including humans. Finally, we demonstrate that our selection method is generalizable and characterizes additional PV-specific enhancers with exquisite specificity within distinct brain regions. Altogether, these viral tools can be used for cell-type-specific circuit manipulation and hold considerable promise for use in therapeutic interventions.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

PURPOSE/OBJECTIVE:To advance research in the field of machine learning for MR image reconstruction with an open challenge. METHODS:We provided participants with a dataset of raw k-space data from 1,594 consecutive clinical exams of the knee. The goal of the challenge was to reconstruct images from these data. In order to strike a balance between realistic data and a shallow learning curve for those not already familiar with MR image reconstruction, we ran multiple tracks for multi-coil and single-coil data. We performed a two-stage evaluation based on quantitative image metrics followed by evaluation by a panel of radiologists. The challenge ran from June to December of 2019. RESULTS:We received a total of 33 challenge submissions. All participants chose to submit results from supervised machine learning approaches. CONCLUSIONS:The challenge led to new developments in machine learning for image reconstruction, provided insight into the current state of the art in the field, and highlighted remaining hurdles for clinical adoption.

In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (v_e, v_p, PS, F_p, K^trans), DWI (ADC) and PET (K_i, K₁, k₂, k₃) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median v_p, F_p, PS, and K^trans values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. v_e and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k₃ (p value = 8.8 × 10^-8) and K_i (p value = 5.3 × 10^-8) than normal nodes. K₁ and k₂ did not show any statistically significant difference. K_i had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of K_i = 5.3 × 10^-3 mL/cm³/min, while k₃ and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with K_i < 5.3 × 10^-3 mL/cm³/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET.