Biology subjects

Rohlova, E.

Publications and source records attributed to Rohlova, E..

3 recordsLinked to original sources

bioRxiv2025

PU.1-driven enrichment enables microglia profiling from frozen brain tissue using the high-throughput Smart-seq3xpress method

Single-cell transcriptomics has revealed the central role of microglia in brain development, homeostasis, and disease, particularly in the context of neuroinflammation. While single-cell RNA-sequencing enables targeted microglial analysis from fresh tissue, studying these cells in cryopreserved or archival samples remains challenging due to the lack of protocols for their specific enrichment. We introduce a method for the selective isolation of microglial nuclei from fresh-frozen brain tissue using the transcription factor PU.1 as a nuclear marker. To stabilize PU.1 for reliable detection, a brief formaldehyde fixation step is applied. The protocol is fully compatible with Smart-seq3xpress, a high-sensitivity, full-length transcriptomic method offering isoform- and allele-level resolution, making the workflow scalable and cost-efficient. We benchmarked the method in a mouse model of ischemic stroke, evaluating both technical performance and its ability to capture biologically meaningful microglial states. Compared to standard single-nucleus protocols, our approach yielded higher gene and UMI counts and a greater proportion of coding reads. Transcriptomic profiles closely matched those from whole-cell RNA-sequencing including the detection of activation markers and diverse microglial subpopulations. This approach addresses key limitations of single-nucleus RNA - sequencing and opens new possibilities for studying microglial states in cryopreserved and archival brain tissue, broadening access to cellular insights in both basic and translational research.

neuroscience↗

bioRxiv2021

Small RNA-sequencing for Analysis of Circulating miRNAs: Benchmark Study

Small RNA-sequencing (RNA-Seq) is being increasingly used for profiling of circulating microRNAs (miRNAs), a new group of promising biomarkers. Unfortunately, small RNA-Seq protocols are prone to biases limiting quantification accuracy, which motivated development of several novel methods. Here, we present comparison of all small RNA-Seq library preparation approaches that are commercially available for quantification of miRNAs in biofluids. Using synthetic and human plasma samples, we compared performance of traditional two-adaptor ligation protocols (Lexogen, Norgen) as well as methods using randomized adaptors (NEXTflex), polyadenylation (SMARTer), circularization (RealSeq), capture probes (EdgeSeq) or unique molecular identifiers, UMIs (QIAseq). Globally, there was no single protocol outperforming others across all metrics. We documented limited overlap of measured miRNA profiles between methods largely owing to protocol-specific biases. We found that methods designed to minimize bias largely differ in their performance and we identified contributing factors. We found that usage of UMIs has rather negligible effect and if designed incorrectly can even introduce spurious results. Together, these results identify strengths and weaknesses of current methods and provide guidelines for applications of small RNA-Seq in biomarker research.

genomics↗

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↗