Biology subjects

Sharif, R.

Publications and source records attributed to Sharif, R..

3 recordsLinked to original sources

bioRxiv2026

Multimodal transcriptomics and calcium imaging reveal a novel subset of polymodal nociceptors expressing the interleukin 1 receptor in mice

We previously established that sensory neurons in the mouse dorsal root ganglia (DRG) express a functional receptor for the proinflammatory cytokine interleukin (IL)-1. We also demonstrated that deletion of the IL-1 receptor type 1 gene, Il1r1, in TRPV1-expressing (+) neurons prevented pain in models of chronic inflammatory diseases such as multiple sclerosis, rheumatoid arthritis and osteoarthritis. Here, we found a marked sex difference in the abundance of IL-1R1+ neurons, which represented approximately 10% of all DRG neurons in females but only 5% in males. However, male mice exhibited stronger, longer-lasting mechanical hypersensitivity than females after IL-1{beta} injection into the cerebrospinal fluid. In vivo calcium imaging revealed that IL-1{beta}- responsive DRG neurons responded to cutaneous mechanical and capsaicin stimulation. By integrating spatial transcriptomics with single-cell RNA sequencing (scRNA-Seq), we identified a gene signature uniquely marking IL-1R1+ neurons, including genes such as Ada, Cysltr2, Gpr139, Htr1a, Htr1f, Il31ra, Nppb, Npy2r, Nts, P2rx2, Pde4c, and Sst, with Ada and Sst validated at the protein level. Omics analysis revealed that IL-1R1+ DRG neurons form a subset of non-peptidergic type 3 (NP3) sensory neurons, which are linked to inflammatory pain and itch. However, Il1r1 deletion did not affect itch responses to serotonin, histamine, or chloroquine, and these mediators failed to induce calcium activity in IL-1{beta}-responsive DRG neurons. Finally, scRNA-seq identified several genes upregulated in NP3 neurons after IL-1{beta} injection, including Alkal2, Bdnf, and Lcn2, associated with chronic inflammatory pain. Thus, our study unveils novel markers for IL-1R1+ nociceptors and reaffirms their selective role in inflammatory pain.

neuroscience↗

bioRxiv2025

Visual field specializations in mouse dLGN

Neural circuits throughout the visual system process features differently depending on where they appear in the visual field. While such location-specific processing exists in retina and in superior colliculus, the dorsal lateral geniculate nucleus (dLGN) is thought to lack this specialization. Here, we show systematic visual field biases in dLGNs representation of spatial frequency, orientation, direction, and temporal frequency. Using axon-localized calcium indicators and widefield imaging, we discovered that dLGN boutons show systematic gradients in feature selectivity across the visual cortex (V1), while its retinal inputs lack such gradients for these features. Selective disruption of V1 feedback to dLGN perturbed gradient structure and magnitude. These results suggest that dLGN circuits transform uniformly distributed retinal feature inputs into spatially-biased representations along with cortical feedback. dLGN feature biases would allow a functional stream to detect ethologically salient visual inputs.

neuroscience↗

bioRxiv2023

ElecFeX: A user-friendly toolkit for efficient feature extraction from single-cell electrophysiological recordings

MotivationProfiling neurons by their electrophysiological phenotype is essential for understanding their roles in information coding within and beyond the nervous systems. Technological development has unleashed our power to record neurons more than ever before, yet the booming size of the dataset poses new challenges for data analysis. Current software tools require users to have either significant programming knowledge or to devote great time and effort, which impedes their prevalence and adoption among experimentalists. To address this problem, here we present ElecFeX, a MATLAB-based graphical user interface designed for a more accessible and efficient analysis of single-cell electrophysiological recordings. ElecFeX has a simple and succinct graphical layout to enable effortless handling of large datasets. This tool includes a set of customizable methods for most common electrophysiological features, and these methods can process multiple files all at once in a reliable and reproducible manner. The output is assembled in a properly formatted file which is exportable for further analysis such as statistical comparison and clustering. By providing such a streamlined and user-friendly open-sourced interface, we hope ElecFeX can benefit broader users for their studies associated with neural activity. SummaryCharacterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Recent developments in electrode technologies have enabled the collection of hundreds of neural recordings; that necessitated the development of new toolkits capable of performing feature extraction efficiently. To address this urgent need for a powerful and accessible tool, we present ElecFeX, an open-source MATLAB-based toolbox that (1) has a succinct and intuitive graphical user interface, (2) provides generalized methods for wide-ranging electrophysiological features, (3) processes large-size dataset effortlessly, and (4) yields formatted output for further analysis such as neuronal characterization and classification. We implemented the toolbox on a diverse set of neural recordings and demonstrated its functionality, efficiency, and versatility in capturing features that can well-distinguish neuronal subgroups across brain regions and species. ElecFeX is thus presented as a powerful tool to significantly promote future studies on neuronal electrical activity.

neuroscience↗