Biology subjects

Zucha, D.

Publications and source records attributed to Zucha, D..

4 recordsLinked to original sources

bioRxiv2023

Characterization of regeneration initiating cells during Xenopus laevis tail regeneration

Embryos are regeneration and wound healing masters. They not only rapidly close their wounds, remodel injured tissue without a scar, but also regenerate body parts. Many animal models with variable regenerative capabilities have already been studied. Additionally, with the introduction of high throughput techniques, novel regeneration mechanisms including genes and signaling pathways, and specialized cell types required for regeneration control in spatial and temporal aspects have been identified. Until now our knowledge has been limited to primarily the late phases of regeneration (> 1 day post injury). In this paper, we reveal the critical steps for regeneration initiation. We have discovered Regeneration Initiating Cells (RICs) using single cell and spatial transcriptomic analyses during tail regeneration in Xenopus laevis. RICs are formed transiently from the basal epidermal cells and are critical for the modification of the surrounding extracellular matrix to allow for migration of other cell types such as regeneration organizing cells that further promote regeneration. Absence or deregulation of RICs leads to excessive extracellular matrix deposition and regeneration defects.

developmental biology↗

bioRxiv2023

Spatiotemporal transcriptomic map of ischemic brain injury

The role of non-neuronal cells in the resolution of cerebral ischemia remains to be fully understood. To decode key cellular processes that occur after ischemia, we performed spatial and single-cell transcriptomic profiling of mouse brain tissue during the first week of injury. Cortical gene expression was severely disrupted, being defined by inflammation and cell death in the lesion core, and glial scar formation on the periphery. For each of the three major glial populations, an inflammatory-responsive state, resembling the reactive states observed in neurodegenerative contexts, was documented. The recovered spectrum of ischemia-induced oligodendrocyte states supports the emerging hypothesis that oligodendrocytes actively respond to and modulate the neuroinflammatory stimulus. Thus, we present a landmark transcriptomic dataset that provides a comprehensive view of spatiotemporal organization of processes in the post-ischemic brain and documents the conservation of glial response in CNS pathology.

neuroscience↗

bioRxiv2019

Decoding the transcriptional response to ischemic stroke in young and aged mouse brain

Ischemic stroke is one of the leading causes of mortality and major healthcare and economic burden. It is a well-recognized disease of aging, yet it is unclear how the age-dependent vulnerability occurs and what are the underlying mechanisms. To address these issues, we performed a comprehensive RNA-Seq analysis of aging, ischemic stroke and their interaction using a model of permanent middle cerebral artery occlusion (MCAO) in 3 and 18 month old female mice. We assessed differential gene expression across injury status and age, estimated cell type proportion changes, assayed the results against a range of transcriptional signatures from the literature and performed unsupervised co-expression analysis, identifying modules of genes with varying response to injury. We uncovered selective vulnerability of neuronal populations and increased activation of type-I interferon (IFN-I) signaling and several other inflammatory pathways in aged mice. We extended these findings via targeted expression analysis in tissue as well as acutely purified cellular populations to show differential temporal dynamics of IFN-I signaling between age groups and contribution of individual cell types. Together, these results paint a picture of ischemic stroke as a complex age-related disease and provide insights into interaction of aging and stroke on cellular and molecular level.\n\nGraphical summary\n\nO_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC=\"FIGDIR/small/769331v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (46K):\norg.highwire.dtl.DTLVardef@1590c10org.highwire.dtl.DTLVardef@126fc76org.highwire.dtl.DTLVardef@88e20aorg.highwire.dtl.DTLVardef@b000d9_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2019

Performance comparison of reverse transcriptases for single-cell studies

BackgroundRecent technical advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on conversion of RNA to cDNA by reverse transcription (RT). However, RT is recognized as highly limiting step due to its inherent variability and suboptimal sensitivity, especially at minute amounts of RNA. Primary factor influencing RT outcome is reverse transcriptase (RTase). Recently, several new RTases with potential to decrease the loss of information during RT have been developed, but the thorough assessment of their performance is missing.\n\nMethodsWe have compared the performance of 11 RTases in RT-qPCR on single-cell and 100-cell bulk templates using two priming strategies: conventional mixture of random hexamers with oligo(dT)s and reduced concentration of oligo(dT)s mimicking common single-cell RNA-Seq library preparation protocols. Based on the performance, two RTases were further tested in high-throughput single-cell experiment.\n\nResultsAll RTases tested reverse transcribed low-concentration templates with high accuracy (R2 > 0.9445) but variable reproducibility (median CVRT = 40.1 %). The most pronounced differences were found in the ability to capture rare transcripts (0 - 90% reaction positivity rate) as well as in the rate of RNA conversion to cDNA (7.3 - 124.5 % absolute yield). Finally, RTase performance and reproducibility across all tested parameters were compared using Z-scores and validity of obtained results was confirmed in a single-cell model experiment. The better performing RTase provided higher positive reaction rate and expression levels and improved resolution in clustering analysis.\n\nConclusionsWe performed a comprehensive comparison of 11 RTases in low RNA concentration range and identified two best-performing enzymes (Maxima H-; SuperScript IV). We found that using better-performing enzyme (Maxima H-) over commonly-used below-average performer (SuperScript II) increases the sensitivity of single-cell experiment. Our results provide a reference for the improvement of current single-cell quantification protocols.

molecular biology↗