Protocol for isolating young adult parvalbumin interneurons from the mouse brain for extraction of high-quality RNA

Joseph, Donald J.; Deimling, Markus von; Hasegawa, Yuiko; Cristancho, Ana G.; Risbud, Rashmi; McCoy, Almedia J.; Marsh, Eric D.

doi:10.1016/j.xpro.2021.100714

Cited by 9 publications

(7 citation statements)

References 11 publications

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“…5B ). Flow cytometry of enzymatically-dissociated cortex 7 confirmed equal efficiency of PV-IN targeting across all groups (Fig. 5C ).…”

Section: Resultsmentioning

confidence: 61%

“…Functional information is nonetheless limited in transcriptomic studies, due to substantial discordance between mRNA and protein levels, especially in neurons [3][4][5] . Proteomic studies relying on physical isolation of individual neuron types are also inadequate, as physical isolation of individual neurons is poorly tolerated, and of those that do survive, the vast majority of their functional surface area (i.e., dendrites and axons) is lost 6,7 . To overcome these limitations, we recently developed an in vivo strategy called cell type-specific in vivo biotinylation of proteins (CIBOP).…”

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confidence: 99%

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Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology

Kumar,

Goettemoeller,

Espinosa-Garcia

et al. 2024

Nat Commun

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Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer’s Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aβ pathology. PV-IN CIBOP in early stages of Aβ pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis.

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“…5B ). Flow cytometry of enzymatically-dissociated cortex 7 confirmed equal efficiency of PV-IN targeting across all groups (Fig. 5C ).…”

Section: Resultsmentioning

confidence: 61%

mentioning

confidence: 99%

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology

Kumar,

Goettemoeller,

Espinosa-Garcia

et al. 2024

Nat Commun

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“…Single nuclei RNA sequencing has become an important emerging tool in the generation of atlases, particularly in tissues where obtaining single cells is difficult. Cell nuclei are used in neuroscience because adult neurons are difficult to obtain, due to their high connectivity, sensitivity to dissociation enzymes and high fragility, often resulting in datasets with abundant cell death, low neuronal representation and low quality RNA [54]. Importantly, single nuclei sequencing is compatible with cryopreserved banked tissue [55].…”

Section: Resultsmentioning

confidence: 99%

“…This showcases the consistency of gene selection by SIMS and how it could be used to find clinically relevant genes overlooked by conventional methods. death, low neuronal representation and low quality RNA [54]. Importantly, single nuclei sequencing is compatible with cryopreserved banked tissue [55].…”

Section: Sims Accurately Performs Label Transfer In Highly Complex Si...mentioning

confidence: 99%

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis

Lehrer

Gonzalez-Ferrer

Haussler

et al. 2023

Preprint

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Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably higher accuracy than state-of-the-art single cell classifiers. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities in previously unclassified cells and to uncover genetic variations in the developmental trajectories of organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

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“…To assess transcriptional changes specifically in PV interneurons after removing CP-AMPARs with RNA-seq, we sorted dissociated cortical PV interneurons by their GFP fluorescence with FACS. Dissociation of adult mouse brain neurons leads to a rapid decimation of viable PV interneurons [95][96][97] , potentially biasing downstream analyses to a select subpopulation of PV interneurons. Various proposed methods to mitigate PV interneuron loss failed to recover them at native cell frequencies in adult mice 98 .…”

Section: Facs-assisted Rna-seq Of Pv Interneuronsmentioning

confidence: 99%

Calcium-permeable AMPA receptors govern PV neuron feature selectivity

Hong

Kim

Hainmueller

et al. 2023

Preprint

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The brain helps us survive by forming internal representations of the external world1,2. Excitatory cortical neurons are often precisely tuned to specific external stimuli3,4. However, inhibitory neurons, such as parvalbumin-positive (PV) interneurons, are generally less selective5. PV interneurons differ from excitatory cells in their neurotransmitter receptor subtypes, including AMPA receptors6,7. While excitatory neurons express calcium-impermeable AMPA receptors containing the GluA2 subunit, PV interneurons express receptors that lack the GluA2 subunit and are calcium-permeable (CP-AMPARs). Here we demonstrate a causal relationship between CP-AMPAR expression and the low feature selectivity of PV interneurons. We find a low expression stoichiometry of GluA2 mRNA relative to other subunits in PV interneurons which is conserved across ferrets, rodents, marmosets, and humans, causing abundant CP-AMPAR expression. Replacing CP-AMPARs in PV interneurons with calcium-impermeable AMPARs increased their orientation selectivity in the visual cortex. Sparse CP-AMPAR manipulations demonstrated that this increase was cell-autonomous and could occur well beyond development. Interestingly, excitatory-PV interneuron connectivity rates and unitary synaptic strength were unaltered by CP-AMPAR removal, suggesting that the selectivity of PV interneurons can be altered without drastically changing connectivity. In GluA2 knockout mice, where all AMPARs are calcium-permeable, excitatory neurons showed significantly reduced orientation selectivity, suggesting that CP-AMPARs are sufficient to drive lower selectivity regardless of cell type. Remarkably, hippocampal PV interneurons, which usually exhibit low spatial tuning, became more spatially selective after removing CP-AMPARs, indicating that CP-AMPARs suppress the feature selectivity of PV interneurons independent of modality. These results reveal a novel role of CP-AMPARs in maintaining a low-selectivity sensory representation in PV interneurons and suggest a conserved molecular mechanism that distinguishes the unique synaptic computations of inhibitory and excitatory neurons.

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Protocol for isolating young adult parvalbumin interneurons from the mouse brain for extraction of high-quality RNA

Cited by 9 publications

References 11 publications

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis

Calcium-permeable AMPA receptors govern PV neuron feature selectivity

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