Biology subjects

Boland, M. J.

Publications and source records attributed to Boland, M. J..

8 recordsLinked to original sources

bioRxiv2024

Generation of humanized mouse models to support therapeutic development for SYNGAP1 and STXBP1 disorders

Heterozygous variants in SYNGAP1 and STXBP1 cause distinct neurodevelopmental disorders due to haploinsufficiency of essential synaptic proteins. As gene targeted approaches to correct these disorders often target non-conserved genomic regions, thus limiting their clinical translation, we generated humanized mouse models wherein the entire Syngap1 or Stxbp1 loci were replaced with their human counterparts. Stxbp1 humanized mice exhibited impaired viability, while Stxbp1 hybrid mice (Stxbp1Hu/+) were viable and suitable for evaluating target engagement of human-specific therapeutics. Syngap1 humanized mice were viable and successfully crossed with Syngap1 heterozygous mice to produce a Syngap1 humanized-haploinsufficient model (Syngap1Hu/-). Syngap1Hu/- mice displayed haploinsufficient levels of human SYNGAP1, disease-relevant behaviors, and EEG abnormalities including epileptiform activity and generalized slowing. Importantly, parallel analysis in a cohort of patients with SYNGAP1-disorder revealed similar electrophysiological signatures. Finally, we showed that human gene-targeted antisense oligonucleotides modulate human SYNGAP1 expression in Syngap1Hu/- neurons. Together, we describe new models to support pre-clinical therapeutic development for SYNGAP1 and STXBP1 disorders and identify translational biomarkers of SYNGAP1-disorder in mice and humans to benchmark therapeutic testing.

neuroscience↗

bioRxiv2023

Aberrant Local Synchrony in Distinct Mouse Models of Epileptic Encephalopathy

Identifying and quantifying synchronous activity of primary neuronal networks using multielectrode arrays (MEAs) can potentially provide a medium-throughput platform to screen potential therapeutics for genetic epileptic encephalopathies (EEs). However, successfully identifying screenable synchrony phenotypes in vitro poses significant experimental and analytical challenges. Primary neuronal cultures quickly become highly synchronous and certain measures of synchrony tend to peak and plateau, while other network activity features remain dynamic. High levels of synchrony may confound the ability to identify reproducible phenotypes in vitro for a subset of EEs. Reducing, or delaying the onset of, high levels of synchrony in vitro may increase the dynamic range of global synchrony measures to identify disease-relevant phenotypes in vitro, but such measures have not been established. We hypothesized that an emphasis on local (nearby) connectivity could elucidate reproducible disease-relevant synchrony phenotypes in cortical cultures not identified by current approaches. We show clear evidence of enriched local synchrony in 48-well MEAs that varies in amplitude during development of neuronal networks. Then, we show new topological-based measures are capable of identifying novel phenotypes of aberrant synchrony in distinct mouse models of EEs. Such topological synchrony measures may provide screenable phenotypes for certain brain diseases and may be further enhanced by experimental innovation reducing global levels of synchrony in primary neuronal networks. SignificanceIn vitro synchrony phenotypes may provide disease-relevant features that can be used for screening potential therapeutic candidates for epileptic encephalopathies. Here, we incorporate inter-electrode distance to generate tools capable of identifying novel synchrony phenotypes in distinct neurodevelopmental disorders. We additionally report robust topological and global in vitro synchrony phenotypes, alongside in vivo synchrony phenotypes in Stxbp1+/- mice. While singular features of disease in an in vitro model are unlikely to effectively test therapeutic candidates, compounds that reverse a larger subset of distinct features may translate to human patients, suggesting such a model may be ideally suited for therapeutic development using MEAs. Across multiple disease models, the topological tools developed here are complimentary to and expand upon those within meaRtools (Gelfman 2018), which is a suite of computational tools to identify network phenotypes using MEAs.

neuroscience↗

bioRxiv2022

Single Cell transcriptional analysis of ex vivo models of cortical and hippocampal development identifies unique longitudinal trends

Postnatal cortical and hippocampal mouse primary neuronal cultures are powerful and widely-used models of neuronal activity and neurological disease. While this model is frequently used to recapitulate what is seen in vivo, how the transcriptomic profiles of neuronal networks change over development is not fully understood. We use single-cell transcriptomics to provide a view of neuronal network establishment and maturation. Our data highlight region-specific differences and suggest how cell populations program the transcriptome in these brain regions. We demonstrate that patterns of expression markedly differ between and within neurological diseases, and explore why these differences are found and how well they compare to other models. In particular, we show significant expression differences between genes associated with epilepsy, autism spectrum disorder, and other neurological disorders. Collectively, our study provides novel insights on this popular model of development and disease that will better inform design for drug discovery and therapeutic intervention. O_FIG O_LINKSMALLFIG WIDTH=153 HEIGHT=200 SRC="FIGDIR/small/519959v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1be59a3org.highwire.dtl.DTLVardef@1ef18b9org.highwire.dtl.DTLVardef@402c1dorg.highwire.dtl.DTLVardef@1103789_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO (A) Schematic representing select gene expression progression through neuronal network maturation from human cortical organoids (3- and 6-Month Organoid), newborn mice (P0 Mouse), immature ex vivo cortex derived cultures (DIV 3 ex vivo), functionally mature ex vivo cortex derived cultures (DIV15-31 ex vivo), and adult mice (P56 Mouse). Color represents proportion of excitatory neurons with detectable expression for selected representative genes Mapk10, Igfbp2, which increase and decrease through network maturation, respectively. (B) Schematic representing divergent expression patterns between genes associated with epilepsy and ASD through network maturation between the organoids and ex vivo cultures shown in (A). Color scales represent the change in the percentile, in respect to all genes, of the proportion of excitatory neurons with detectable expression. C_FIG

genetics↗

bioRxiv2020

Precision genetic cellular models identify therapies protective against endoplasmic reticulum stress

Congenital disorders of glycosylation (CDG) and deglycosylation (CDDG) are a collection of rare pediatric disorders with symptoms that range from mild to life threatening. They typically affect multiple organ systems and usually present with neurological abnormalities including hypotonia, cognitive impairment, and intractable seizures. Several genes have been implicated in the thirty-six types of CDG, but currently NGLY1 is the only known CDDG gene. A common biological mechanism among CDG types and in CDDG is endoplasmic reticulum (ER) stress. Here, we develop two isogenic human cellular models of CDG (PMM2, the most prevalent type of CDG, and DPAGT1) and of the only CDDG (NGLY1) in an effort to identify drugs that can alleviate ER stress. Systematic phenotyping identified elevated ER stress and autophagy levels among other cellular and morphological phenotypes in each of the cellular models. We screened a complex drug library for compounds able to correct aberrant morphological phenotypes in each of the models using an agnostic phenotypic cell painting assay based on >300 cellular features. The image-based screen identified multiple candidate compounds able to correct aberrant morphology, and we show a subset of these are able to correct cellular and molecular defects in each of the models. These results provide new directions for the treatment of rare diseases of glycosylation and deglycosylation and a framework for new drug screening paradigms for more common neurodegenerative diseases characterized by ER stress. Summary sentenceNovel drug screening modality identifies compounds that correct aberrant molecular phenotypes in precision cellular models of glycosylation defects.

neuroscience↗

bioRxiv2020

The paradoxical effects of K+ channel gain-of-function are mediated by GABAergic neuron hypoexcitability and hyperconnectivity.

Gain-of-function (GOF) variants in K+ channels cause severe childhood epilepsies, but there are no mechanisms to explain how increased K+ currents lead to network hyperexcitability. Here, we introduced a human Na+-activated K+ (KNa) channel variant (KCNT1-Y796H) into mice and, using a multiplatform approach, found motor cortex hyperexcitability and early-onset seizures, phenotypes strikingly similar to those of human patients. Although the variant increased KNa currents in cortical excitatory and inhibitory neurons, there was a selective increase in the KNa current across subthreshold voltages in inhibitory neurons, particularly in those with non-fast spiking properties, resulting in impaired excitability and AP generation. We further observed evidence of synaptic rewiring associated with hyperexcitable networks, including increases in homotypic synaptic connectivity and the ratio of excitatory-to-inhibitory synaptic input. These findings support inhibitory neuron-specific mechanisms in mediating the epileptogenic effects of K+ channel GOF, offering cell-type-specific currents and effects as promising targets for therapeutic intervention. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/978841v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@110d6e1org.highwire.dtl.DTLVardef@8b63ddorg.highwire.dtl.DTLVardef@14972a9org.highwire.dtl.DTLVardef@106be1c_HPS_FORMAT_FIGEXP M_FIG GRAPHICAL ABSTRACT C_FIG

neuroscience↗

bioRxiv2019

Modeling and treating GRIN2A developmental and epileptic encephalopathy in mice

NMDA receptors (NMDAR) play crucial roles in excitatory synaptic transmission. Rare variants of GRIN2A, which encodes the GluN2A NMDAR subunit, are associated with several intractable neurodevelopmental disorders, including developmental and epileptic encephalopathy (DEE). A de novo missense variant, p.Ser644Gly (c.1930A>G), was identified in a child with DEE, and Grin2a knockin mice were generated to model and extend understanding of this intractable childhood disease. Homozygous and heterozygous mutant mice exhibit altered hippocampal morphology at two weeks of age, and homozygotes exhibit lethal tonic-clonic seizures in the third week. Heterozygous adult mice display a variety of distinct features, including resistance to electrically induced partial seizures, as well as hyperactivity and repetitive and reduced anxiety behaviors. Multielectrode recordings of mutant neuronal networks reveal hyperexcitability and altered bursting and synchronicity. When expressed in heterologous cells, mutant receptors exhibit enhanced NMDAR agonist potency and slow deactivation following rapid removal of glutamate, as occurs at synapses. Consistent with these observations, NMDAR-mediated synaptic currents in hippocampal slices from mutant mice show a prolonged deactivation time course. Standard antiepileptic drug monotherapy was ineffective in the patient, but combined treatment of NMDAR antagonists with antiepileptic drugs substantially reduced the seizure burden albeit without appreciable developmental improvement. Chronic treatment of homozygous mutant mouse pups with NMDAR antagonists delayed the onset of lethal seizures but did not prevent them. These studies illustrate the power of modeling severe neurodevelopmental seizure disorders using multiple experimental modalities and suggest their extended utility in identifying and evaluating new therapies.

neuroscience↗

bioRxiv2019

G protein-coupled potassium channels implicated in mouse and cellular models of GNB1 Encephalopathy

De novo mutations in GNB1, encoding the G{beta}1 subunit of G proteins, cause a neurodevelopmental disorder with global developmental delay and epilepsy. Mice carrying a pathogenic mutation, K78R, recapitulate aspects of the disorder, including developmental delay and frequent spike-wave discharges (SWD). Cultured mutant cortical neurons display aberrant bursting activity on multi-electrode arrays. Strikingly, the antiepileptic drug ethosuximide (ETX) restores normal neuronal network behavior in vitro and suppresses SWD in vivo. In contrast, while valproic acid suppresses SWD, it does not restore normal network behavior, suggesting that ETX has mechanistic specificity for the effects of aberrant G{beta}1 signaling. Consistent with this, we show that K78R is a gain-of-function of G protein-coupled potassium channel (GIRK) activation that is potently inhibited by ETX. This work suggests that altered G{beta}1 signaling causes disease in part through effects on GIRK channels, illustrates the utility of cultured neuronal networks in pharmacological screening, and establishes effective pre-clinical models for GNB1 Encephalopathy.

neuroscience↗

bioRxiv2018

meaRtools: an R package for the Comprehensive Analysis of Neuronal Networks Recorded on Multi-Electrode Arrays

Here we present an open-source R package meaRtools that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL>=3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.\n\nAuthor summaryCultured neuronal networks are widely used to study and characterize neuronal network activity. Among the many uses of neuronal cultures are the capabilities to evaluate neurotoxicity and the effects of pharmacological compounds on cellular physiology. Multi-well microelectrode arrays (MEAs) can collect high-throughput data from multiple neuronal cultures simultaneously, and thereby make possible hypotheses-driven inquiries into neurobiology and neuropharmacology. The analysis of MEA-derived information presents many computational challenges. High frequency data recorded simultaneously from hundreds of electrodes can be difficult to handle. The need to compare network activity across various drug treatments or genotypes recorded on the same plate from experiments lasting several weeks presents another challenge. These challenges inspired us to develop meaRtools; an MEA data analysis package that contains new methods to characterize network activity patterns, which are illustrated here using examples from a genetic mouse model of epilepsy. Among the highlights of meaRtools are novel algorithms designed to characterize neuronal activity dynamics and network properties such as bursting and synchronization, options to combine multiple recordings and use a robust statistical framework to draw appropriate statistical inferences, and finally data visualizations and plots. In summary, meaRtools provides a platform for the analyses of singular and longitudinal MEA experiments.

neuroscience↗