Biology subjects

Eichhorn, S.

Publications and source records attributed to Eichhorn, S..

3 recordsLinked to original sources

bioRxiv2023

Simple, low-cost, and well-performing method, the outgrowth technique, for the isolation of epithelial cells from nasal polyps

ObjectivesEpithelial cells are an important part of the pathomechanism in chronic rhinosinusitis with nasal polyps. It is therefore essential to establish a robust method for the isolation and culture of epithelial cells from nasal polyps to enable further research. In this study, the feasibility of the outgrowth technique for the isolation of the epithelial cells from the nasal polyps was evaluated. MethodsThe outgrowth technique was performed to isolate the epithelial cells. Proliferation was evaluated up to the 3rd passage. Epithelial cells were identified and differentiation and proliferation were evaluated using flow cytometry with anti-cytokeratin, anti-p63, and anti-Ki-67. A functionality test was assessed by determining type 2-relevant proteins using ELISA, representatively, interleukin-33 and periostin. ResultsUsing the outgrowth technique, epithelial cells could be isolated from all tissue samples. Isolated epithelial cells showed a proliferation rate of approximately 7- to 23-fold every 6 days up to the 3rd passage. Over 97% of isolated cells were shown to be cytokeratin- and p63-positive, and over 86% of them were Ki-67-positive in flow cytometry. Interleukin-33 and periostin were detectable in the supernatant. ConclusionsWe introduce a simple, low-cost, and well-performing method for isolating epithelial cells from nasal polyps with the outgrowth technique.

cell biology↗

bioRxiv2022

Three-dimensional Interrogation of Cell Types and Instinctive Behavior in the Periaqueductal Gray

The periaqueductal gray (PAG) is a critical midbrain hub that relays information from the forebrain to motor and autonomic brainstem centers to orchestrate instinctive behaviors. The current organization of the PAG into four main radial columns lacks the resolution needed to account for the vast range of PAG functions. Using spatially resolved single-cell transcriptomic measurements, we uncovered widespread transcriptional heterogeneity in the PAG with >100 excitatory and inhibitory neuronal populations, which further assemble into 19 spatial metaclusters. We explored the transcriptional and spatial logic of PAG function during instinctive behaviors and demonstrated the regional recruitment of cell types for distinct behaviors. Unexpectedly, certain behaviors trigger differential spatial activation patterns within given cell types, illustrating the complexity of PAG molecular and functional 3D organization. The newly uncovered spatial motifs and high precision cellular map of instinctive behavior in the PAG open new avenues for a mechanistic understanding of PAG function.

neuroscience↗

bioRxiv2020

Evaluating single-cell cluster stability using the Jaccard similarity index

MotivationOne major goal of single-cell RNA sequencing (scRNAseq) experiments is to identify novel cell types. With increasingly large scRNAseq datasets, unsupervised clustering methods can now produce detailed catalogues of transcriptionally distinct groups of cells in a sample. However, the interpretation of these clusters is challenging for both technical and biological reasons. Popular clustering algorithms are sensitive to parameter choices, and can produce different clustering solutions with even small changes in the number of principal components used, the k nearest neighbor, and the resolution parameters, among others. ResultsHere, we present a set of tools to evaluate cluster stability by subsampling, which can guide parameter choice and aid in biological interpretation. The R package scclusteval and the accompanying Snakemake workflow implement all steps of the pipeline: subsampling the cells, repeating the clustering with Seurat, and estimation of cluster stability using the Jaccard similarity index. The Snakemake workflow takes advantage of high-performance computing clusters and dispatches jobs in parallel to available CPUs to speed up the analysis. The scclusteval package provides functions to facilitate the analysis of the output, including a series of rich visualizations. AvailabilityR package scclusteval: https://github.com/crazyhottommy/scclusteval Snakemake workflow: https://github.com/crazyhottommy/pyflow_seuratv3_parameter Contacttsackton@g.harvard.edu, tangming2005@gmail.com Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗