Biology subjects

Veraszto, C.

Publications and source records attributed to Veraszto, C..

10 recordsLinked to original sources

bioRxiv2024

A quantitative spatial atlas of transcriptomic, morphological, and electrophysiological cell type densities in the mouse brain

Brain cells can be classified into transcriptomic, morphological, and electrophysiological types. We derived a quantitative spatial atlas of the distributions of these classes within the mouse brain. To do so, we first generated a 3D atlas of transcriptomic cell type densities, by scaling regional estimates of densities from brain slices using cell counts and slice dimensions. Adjustments for regions with high cell density, such as the cerebellum, were made using the average Nissl intensities as a density modifier on a voxel-by-voxel basis. To connect the transcriptomic-type signatures to cellular function (morphological-electrophysiological types), we leveraged patch-sequencing datasets, which integrate mRNA counts, morphology reconstructions, and electrophysiological recordings from single cortical neurons. We aligned mRNA counts with the established classifications of transcriptomic types, classified neuron morphologies according to morphological types, and derived electrophysiological types using K-means clustering. The resulting 3D atlas and computational framework can be used to probe neuronal cell-type diversity and its functional implications, setting the stage for further explorations into the cellular basis of brain function.

neuroscience↗

bioRxiv2024

An extended and improved CCFv3 annotation and Nissl atlas of the entire mouse brain

Brain atlases are essential for quantifying cellular composition in mouse brain regions. The Allen Institutes Common Coordinate Framework version 3 (CCFv3) is widely used, delineating over 600 anatomical regions, but it lacks coverage for the most rostral and caudal brain parts, including the main olfactory bulb, cerebellum, and medulla. Additionally, the CCFv3 omits key cerebellar layers, and its corresponding Nissl-stained reference volume is not precisely aligned, limiting its utilisability. To address these issues, we developed an extended atlas, the Blue Brain Project CCFv3 augmented (CCFv3aBBP), which includes a fully annotated mouse brain and an improved Nissl reference aligned in the CCFv3. This enhanced atlas also features the central nervous system annotation (CCFv3cBBP). Using this resource, we aligned 734 Nissl-stained brains to produce an average Nissl template, enabling an updated distribution of neuronal soma positions. These data are available as an open-source resource, broadening applications such as improved alignment precision, cell type mapping, and multimodal data integration.

bioinformatics↗

bioRxiv2021

Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons

Knowledge of the cell-type-specific composition of the brain is useful in order to understand the role of each cell type as part of the network. Here, we estimated the composition of the whole cortex in terms of well characterised morphological and electrophysiological inhibitory neuron types (me-types). We derived probabilistic me-type densities from an existing atlas of molecularly defined cell-type densities in the mouse cortex. We used a well-established me-type classification from rat somatosensory cortex to populate the cortex. These me-types were well characterized morphologically and electrophysiologically but they lacked molecular marker identity labels. To extrapolate this missing information, we employed an additional dataset from the Allen Institute for Brain Science containing molecular identity as well as morphological and electrophysiological data for mouse cortical neurons. We first built a latent space based on a number of comparable morphological and electrical features common to both data sources. We then identified 13 morpho-electrical clusters that merged neurons from both datasets while being molecularly homogeneous. The resulting clusters best mirror the molecular identity classification solely using available morpho-electrical features. Finally, we stochastically assigned a molecular identity to a me-type neuron based on the latent space cluster it was assigned to. The resulting mapping was used to derive inhibitory me-types densities in the cortex. Author SummaryThe computational abilities of the brain arise from its organisation principles at the cellular level. One of these principles is the neuronal type composition over different regions. Since computational functions of neurons are best described by their morphological and electrophysiological properties, it is logical to use morpho-electrically defined cell types to describe brain composition. However, characterizing morpho-electrical properties of cells involve low-throughput techniques not very well suited to scan the whole brain. Thanks to recent progress on transcriptomic and immuno-staining techniques we are now able to get a more accurate snapshot of the mouse brain composition for molecularly defined cell types.How to link molecularly defined cell types with morpho-electrical cell types remains an open question. Several studies have explored this problem providing valuable three-modal datasets combining electrical, morphological and molecular properties of cortical neurons. The long-term goal of the Blue Brain Project (BBP) is to accurately model the mouses whole brain, which requires detailed biophysical models of neurons. Instead of going through the time-consuming process of producing detailed models from the three-modal datasets, we explored a time-saving method. We mapped the already available detailed morpho-electrical models from the BBP rat dataset to cells from a three-modal mouse dataset. We thus assigned a molecular identity to the neuron models allowing us to populate the whole mouse cortex with detailed neuron models.

neuroscience↗

bioRxiv2021

Atlas of Inhibitory Neurons in the Mouse Brain

The mouse brain contains a rich diversity of inhibitory neuron types that have been characterized by their patterns of gene expression. However, it is still unclear how these cell types are distributed across the mouse brain. We developed a computational method to estimate the densities of different inhibitory neuron types across the mouse brain. Our method allows the unbiased integration of diverse and disparate datasets into one framework to predict inhibitory neuron densities for uncharted brain regions. We constrained our estimates based on previously computed brain-wide neuron densities, gene expression data from in situ hybridization image stacks together with a wide range of values reported in the literature. Using constrained optimization, we derived coherent estimates of cell densities for the different inhibitory neuron types. We estimate that 20.3% of all neurons in the mouse brain are inhibitory. Among all inhibitory neurons, 18% predominantly express parvalbumin (PV), 16% express somatostatin (SST), 3% express vasoactive intestinal peptide (VIP), and the remainder 63% belong to the residual GABAergic population. We find that our density estimations improve as more literature values are integrated. Our pipeline is extensible, allowing new cell types or data to be integrated as they become available. The data, algorithms, software, and results of our pipeline are publicly available and update the Blue Brain Cell Atlas. This work therefore leverages the research community to collectively converge on the numbers of each cell type in each brain region. Author summaryObtaining a global understanding of the cellular composition of the brain is a very complex task, not only because of the great variability that exists between reports of similar counts but also because of the numerous brain regions and cell types that make up the brain. Previously, we presented a model of a cell atlas, which provided an estimate of the densities of neurons, glia and their subtypes for each region in the mouse brain. Here, we describe an extension of this model to include more inhibitory neuron types. We collected estimates of inhibitory neuron counts from literature and built a framework to combine them into a consistent cell atlas. Using brain slice images, we also estimated inhibitory neuron density in regions where no literature data are available. We estimated that in the mouse brain 20.3% of all neurons are inhibitory. Among all inhibitory neurons, 18% predominantly express parvalbumin (PV), 16% express somatostatin (SST), 3% express vasoactive intestinal peptide (VIP), and the remainder 63% belong to the residual GABAergic population. Our approach can be further extended to any other cell type and provides a resource to build tissue-level models of the rodent brain.

neuroscience↗

bioRxiv2021

Desmosomal connectomics of all somatic muscles in an annelid larva

Cells form networks in animal tissues through synaptic, chemical and adhesive links. Invertebrate muscle cells often connect to other cells through desmosomes, adhesive junctions anchored by intermediate filaments. To study desmosomal networks, we skeletonised 853 muscle cells and their desmosomal partners in volume electron microscopy data covering an entire larva of the annelid Platynereis. Muscle cells adhere to each other, to epithelial, glial, ciliated, and bristle-producing cells and to the basal lamina, forming a desmosomal connectome of over 2,000 cells. The aciculae - chitin rods that form an endoskeleton in the segmental appendages - are highly connected hubs in this network. This agrees with the many degrees of freedom of their movement, as revealed by video microscopy. Mapping motoneuron synapses to the desmosomal connectome allowed us to infer the extent of tissue influenced by motoneurons. Our work shows how cellular-level maps of synaptic and adherent force networks can elucidate body mechanics.

animal behavior and cognition↗

bioRxiv2020

Whole-animal connectome and cell-type complement of the three-segmented Platynereis dumerilii larva

Nervous systems coordinate effectors across the body during movements. We know little about the cellular-level structure of synaptic circuits for such body-wide control. Here we describe the whole-body synaptic connectome and cell-type complement of a three-segmented larva of the marine annelid Platynereis dumerilii. We reconstructed and annotated over 1,500 neurons and 6,500 non-neuronal cells in a whole-body serial electron microscopy dataset. The differentiated cells fall into 180 neuronal and 90 non-neuronal cell types. We analyse the modular network architecture of the entire nervous system and describe polysynaptic pathways from 428 sensory neurons to four effector systems - ciliated cells, glands, pigment cells and muscles. The complete somatic musculature and its innervation will be described in a companion paper. We also investigated intersegmental differences in cell-type complement, descending and ascending pathways, and mechanosensory and peptidergic circuits. Our work provides the basis for understanding whole-body coordination in annelids.

neuroscience↗

bioRxiv2018

Neural circuitry of a polycystin-mediated hydrodynamic startle response for predator avoidance

Startle responses triggered by aversive stimuli including predators are widespread across animals. These coordinated whole-body actions require the rapid and simultaneous activation of a large number of muscles. Here we study a startle response in a planktonic larva to understand the whole-body circuit implementation of the behavior. Upon encountering water vibrations, larvae of the annelid Platynereis close their locomotor cilia and simultaneously contract the body and raise the parapodia. The startle response is mediated by collar receptor neurons expressing the polycystins PKD1-1 and PKD2-1. CRISPR-generated PKD1-1 and PKD2-1 mutant larvae do not startle and fall prey to a copepod predator at a higher rate. Reconstruction of the whole-body connectome of the collar-receptor-cell circuitry revealed converging feedforward circuits to the ciliary bands and muscles. The wiring diagram suggests circuit mechanisms for the intersegmental and left-right coordination of the response. Our results reveal how polycystin-mediated mechanosensation can trigger a coordinated whole-body effector response involved in predator avoidance.\n\nShort SummaryThe neuronal circuitry of the Platynereis startle response links polycystin-dependent hydrodynamic sensors to muscle and ciliary effector cells

neuroscience↗

bioRxiv2018

Ciliary and rhabdomeric photoreceptor-cell circuits form a spectral depth gauge in marine zooplankton

Ciliary and rhabdomeric photoreceptor cells represent two main lines of photoreceptor evolution in animals. The two photoreceptor-cell types coexist in some animals, however how they functionally integrate is unknown. We used connectomics to map synaptic paths between ciliary and rhabdomeric photoreceptors in the planktonic larva of the annelid Platynereis and found that ciliary photoreceptors are presynaptic to the rhabdomeric circuit. The behaviors mediated by the ciliary and rhabdomeric cells also interact hierarchically. The ciliary photoreceptors are UV-sensitive and mediate downward swimming to non-directional UV light, a behavior absent in ciliary-opsin knockouts. UV avoidance antagonizes positive phototaxis mediated by the rhabdomeric eyes so that vertical swimming direction is determined by the ratio of blue/UV light. Since this ratio increases with depth, Platynereis larvae may use it as a depth gauge during planktonic migration. Our results revealed a functional integration of ciliary and rhabdomeric photoreceptors with implications for eye and photoreceptor evolution.

neuroscience↗

bioRxiv2017

Synaptic and peptidergic connectome of a neurosecretory centre in the annelid brain

Neurosecretory centres in animal brains use peptidergic signalling to influence physiology and behaviour. Understanding neurosecretory centre function requires mapping cell types, synapses, and peptidergic networks. Here we use electron microscopy and gene expression mapping to analyse the synaptic and peptidergic connectome of an entire neurosecretory centre. We mapped 78 neurosecretory neurons in the brain of larval Platynereis dumerilii, a marine annelid. These neurons form an anterior neurosecretory organ expressing many neuropeptides, including hypothalamic peptide orthologues and their receptors. Analysis of peptide-receptor pairs revealed sparsely connected networks linking specific neuronal subsets. We experimentally analysed one peptide-receptor pair and found that a neuropeptide can couple neurosecretory and synaptic brain signalling. Our study uncovered extensive non-synaptic signalling within a neurosecretory centre and its connection to the synaptic brain.

neuroscience↗

bioRxiv2017

Ciliomotor circuitry underlying whole-body coordination of ciliary activity in the Platynereis larva

Ciliated surfaces harbouring synchronously beating cilia can generate fluid flow or drive locomotion. In ciliary swimmers, ciliary beating, arrests, and changes in beat frequency are often coordinated across extended or discontinuous surfaces. To understand how such coordination is achieved, we studied the ciliated larvae of Platynereis dumerilii, a marine annelid. Platynereis larvae have segmental multiciliated cells that regularly display spontaneous coordinated ciliary arrests. We used whole-body connectomics, activity imaging, transgenesis, and neuron ablation to characterize the ciliomotor circuitry. We identified cholinergic, serotonergic, and catecholaminergic ciliomotor neurons. The synchronous rhythmic activation of cholinergic cells drives the coordinated arrests of all cilia. The serotonergic cells are active when cilia are beating. Serotonin inhibits the cholinergic rhythm, and increases ciliary beat frequency. Based on their connectivity and alternating activity, the catecholaminergic cells may generate the rhythm. The ciliomotor circuitry thus constitutes a stop-and-go pacemaker system for the whole-body coordination of ciliary locomotion.

neuroscience↗