Biology subjects

Shainer, I.

Publications and source records attributed to Shainer, I..

6 recordsLinked to original sources

bioRxiv2024

Voltage imaging reveals circuit computations in the raphe underlying serotonin-mediated motor vigor learning

As animals adapt to new situations, neuromodulation is a potent way to alter behavior, yet mechanisms by which neuromodulatory nuclei compute during behavior are underexplored. The serotonergic raphe supports motor learning in larval zebrafish by visually detecting distance traveled during swims, encoding action effectiveness, and modulating motor vigor. We found that swimming opens a gate for visual input to cause spiking in serotonergic neurons, enabling encoding of action outcomes and filtering out learning-irrelevant visual signals. Using light-sheet microscopy, voltage sensors, and neurotransmitter/modulator sensors, we tracked millisecond-timescale neuronal input-output computations during behavior. Swim commands initially inhibited serotonergic neurons via GABA, closing the gate to spiking. Immediately after, the gate briefly opened: voltage increased consistent with post-inhibitory rebound, allowing swim-induced visual motion to evoke firing through glutamate, triggering serotonin secretion and modulating motor vigor. Ablating GABAergic neurons impaired raphe coding and motor learning. Thus, serotonergic neuromodulation arises from action-outcome coincidence detection within the raphe, suggesting the existence of similarly fast and precise circuit computations across neuromodulatory nuclei.

neuroscience↗

bioRxiv2024

Global and compartmentalized serotonergic control of sensorimotor integration underlying motor adaptation

The vertebrate serotonergic system plays a critical role in modulating adaptive behavior. Yet, it has been challenging to unravel the downstream targets and the effects of serotonin on ongoing neural dynamics due to its widespread innervation and the complex nature of receptor signaling. Here, we show that the serotonergic system controls brain-wide neural dynamics in a spatially dualistic manner, global and compartmentalized, during motor adaptation behavior in zebrafish. Larval zebrafish adapt the vigor of tail motions depending on environmental drag force during visual pursuit behavior in a serotonin-dependent manner. Whole-brain imaging of serotonin release and systematic spatial mapping of serotonin receptors showed highly compartmentalized patterns that span multiple brain areas. Interestingly, whole-brain neural activity imaging combined with the perturbation of tph2+ raphe serotonin neurons revealed dualistic modulation of neural activity depending on behavioral encoding: global suppression of locomotor networks and the compartmentalized enhancement of midbrain sensory networks, both of which synergistically enabled motor adaptation. The compartmentalized modulation resulted from local serotonin release and receptor expression, while the global effect was due to modulation of a key network hub that broadcasts behavioral state signals. Our results reveal how the serotonergic system interacts with brain-wide neural dynamics through its parallel interactions and provide a conceptual framework for understanding the neural mechanisms of widespread serotonergic behavioral control.

neuroscience↗

bioRxiv2024

Positional information drives distinct traits in transcriptomically identified neuronal types

Neuronal phenotypic traits such as morphology, connectivity, and function are dictated, to a large extent, by a specific combination of differentially expressed genes. Clusters of neurons in transcriptomic space correspond to distinct cell types and in some cases (e. g., C. elegans neurons1 and retinal ganglion cells2-4) have been shown to share morphology and function. The zebrafish optic tectum is composed of a spatial array of neurons that transforms visual inputs into motor outputs. While the visuotopic map is continuous, subregions of the tectum are functionally specialized5,6. To uncover the cell-type architecture of the tectum, we transcriptionally profiled its neurons, revealing more than 60 cell types that are organized in distinct anatomical layers. We then measured the visual responses of thousands of tectal neurons by two-photon calcium imaging and matched them with their transcriptional profile. Furthermore, we characterized the morphologies of transcriptionally identified neurons using specific transgenic lines. Surprisingly, we found that neurons that are transcriptionally similar can diverge functionally and morphologically. Incorporating the spatial coordinates of neurons within the tectal volume revealed functionally and morphologically defined anatomical subclusters within individual transcriptomic clusters. Our findings demonstrate that extrinsic, position-dependent factors expand the phenotypic repertoire of genetically similar neurons.

neuroscience↗

bioRxiv2022

A single-cell resolution gene expression atlas of the larval zebrafish brain

The advent of multimodal brain atlases promises to accelerate discoveries in neuroscience by offering in silico queries of cell types, connectivity and gene expression in regions of interest. We employed multiplexed fluorescent in situ RNA hybridization chain reaction (HCR) to generate expression maps for an initial set of 200 marker genes across the larval zebrafish brain. The data were registered to the Max Planck Zebrafish Brain (mapzebrain) atlas, thus allowing co-visualization of gene expression patterns, single-neuron tracings, transgenic lines and anatomical segmentations. Additionally, brain activity maps of freely swimming larvae were generated at single-cell resolution using HCR labeling of the immediate-early gene cfos and integrated into the atlas. As a proof of concept, we identified a novel class of cerebellar eurydendroid cells that express calb2a, project to the hypothalamus and are activated in animals that have recently ingested food. Thus, a cellular-resolution gene expression atlas will not only help with rapid identification of marker genes for neuronal populations of interest, but also bridge the molecular and circuit levels by anchoring genetic information to functional activity maps and synaptic connectivity.

neuroscience↗

bioRxiv2021

Visual recognition of social signals by a tecto-thalamic neural circuit

Social affiliation emerges from individual-level behavioral rules that are driven by conspecific signals1-5. Long-distance attraction and short-distance repulsion, for example, are rules that jointly set a preferred inter-animal distance in swarms6-8. However, little is known about their perceptual mechanisms and executive neuronal circuits3. Here we trace the neuronal response to self-like biological motion9,10 (BM), a visual trigger for affiliation in developing zebrafish2,11. Unbiased activity mapping and targeted volumetric two-photon calcium imaging revealed 19 activity hotspots distributed throughout the brain and clustered BM-tuned neurons in a multimodal, socially activated nucleus of the dorsal thalamus (DT). Individual DT neurons encode fish-like local acceleration but are insensitive to global or continuous motion. Electron microscopic reconstruction of DT neurons revealed synaptic input from the optic tectum (TeO/superior colliculus) and projections into nodes of the conserved social behavior network12,13. Chemogenetic ablation of the TeO selectively disrupted DT responses to BM and social attraction without affecting short-distance repulsion. Together, we discovered a tecto-thalamic pathway that drives a core network for social affiliation. Our findings provide an example of visual social processing, and dissociate neuronal control of attraction from repulsion during affiliation, thus revealing neural underpinnings of collective behavior.

neuroscience↗

bioRxiv2021

Choice of alignment pipeline strongly influences clustering quality of scRNA-seq datasets

BackgroundSingle-cell RNA sequencing (scRNA-seq) has quickly become one of the most dominant techniques in modern transcriptome assessment. In particular, 10X Genomics Chromium system, with its high throughput approach, turn key and thorough user guide made this cutting-edge technique accessible to many laboratories using diverse animal models. However, standard pre-processing, including the alignment and cell filtering pipelines might not be ideal for every organism or tissue. Here we applied an alternative strategy, based on the pseudoaligner kallisto, on twenty-two publicly available single cell sequencing datasets from a wide range of tissues of eight organisms and compared the results with the standard 10X Genomics Cell Ranger pipeline. ResultsIn most of the tested samples, kallisto produced higher sequencing read alignment rates and total gene detection rates in comparison to Cell Ranger. Although datasets processed with Cell Ranger had higher cell counts, outside of human and mouse datasets, these additional cells were routinely of low quality, containing low gene detection rates. Thorough downstream analysis of one kallisto processed dataset, obtained from the zebrafish pineal gland, revealed clearer clustering, allowing the identification of an additional photoreceptor cell type that previously went undetected. The finding of the new cluster suggests that the photoreceptive pineal gland is essentially a bi-chromatic tissue containing both green and red cone-like photoreceptors and implies that the alignment and pre-processing pipeline can affect the discovery of biologically-relevant cell types. ConclusionWhile Cell Ranger favors higher cell numbers, using kallisto results in datasets with higher median gene detection per cell. We could demonstrate that cell type identification was not hampered by the lower cell count, but in fact improved as a result of the high gene detection rate and the more stringent filtering. Depending on the acquired dataset, it can be beneficial to favor high quality cells and accept a lower cell count, leading to an improved classification of cell types.

genomics↗