Biology subjects

Domanska, D.

Publications and source records attributed to Domanska, D..

13 recordsLinked to original sources

bioRxiv2026

The Human Gut Cell Atlas v1.0: A Unified, Community-BuiltReference of Cellular Diversity Across the Gut

Single-cell RNA-sequencing (scRNA-seq) studies have transformed our understanding of cellular diversity in the human intestine, but differences in anatomical sampling, experimental processing and cell-type nomenclature limit comparison across datasets. Here, we present the Human Gut Cell Atlas (HGCA) V1, a community-curated reference of 944,390 healthy and disease-adjacent intestinal cells from 502 samples, 265 donors and 24 landmark studies, linked to detailed anatomical, clinical, and technical metadata. As this metadata is of critical importance to human biology, we developed MetaManager, an open source data management framework for standardized metadata collection and tracking. A five-level consensus taxonomy resolves 94 homeostatic cell identities and enables transferrable, high-resolution annotation of new gut datasets. By assembling cell identity, sampling metadata, and independent spatial validation, intestinal segment and radial tissue depth were revealed to systematically shape cellular composition and transcriptional state, enabling inference of the presence of sampling-dependent tissue niches, including lymphoid follicles. Reference mapping accurately and rapidly recovered cohort-level Crohn's disease and treatment signatures without de novo annotation, while mapping human intestinal organoids quantified cell-type-specific identity, regional specification, maturation, and transcriptional fidelity to native tissue. The HGCA V1 provides a standardized cellular, anatomical coordinate, and metadata system for reproducible, high-quality analysis of intestinal biology across healthy tissue, disease-associated remodelling, and experimental models, providing a continuously evolving community reference for cumulative discovery in human intestinal biology.

systems biology↗

bioRxiv2025

The glutamine transporter Slc38a1 is widely expressed in the embryonic neurogenic niches and impacts neuronal volume, survival, and morphology

The amino acid glutamine, and its derivatives glutamate and GABA, are pivotal for neurogenesis. However, how glutamine is mechanistically supplied to the cells in the neurogenic niches and its broader impact on neurodevelopment, remain poorly characterized. The Solute carrier family 38 member 1 (Slc38a1) exhibits high affinity for glutamine and accumulates glutamine in select cells. We investigated whether Slc38a1 is essential for neurogenesis and whether it has an impact on brain structure and function. Slc38a1 mRNA transcript and protein are widely expressed in the embryonic brain, including in the dorsal pallium and sub-pallium. At embryonic day 15.5, Slc38a1 localizes in neuronal stem cells in the ventricular zone in the forebrain, while it localizes in mature neurons in the sub-ventricular zone of the hindbrain. In the adult brain, Slc38a1 is not detected in neuronal stem cells in the sub-granular zone, however, it is highly enriched in mature local parvalbumin+ and somatostatin+ interneurons and ependyma. Analyses of single-cell RNA sequencing data further reveal that both the number of Slc38a1-expressing cells and the average transcript level of Slc38a1 are significantly higher in embryo brain cells compared to adults. In the embryo, Slc38a1 transcripts are particularly enriched in immature neuronal lineages and embryonic oligodendrocyte precursor populations, whereas in the adult, expression is more prominent in neural progenitor cells and radial glia. Disruption of Slc38a1 in mice impacts body weight, brain size and glutamatergic neuronal volume, while dendritic arborization is diminished and cellular life span is shortened. Altogether, Slc38a1 is essential for normal neurodevelopment, indirectly regulates adult neurogenesis in the sub-granular zone and influence neuronal morphology and cell viability.

neuroscience↗

bioRxiv2025

Easydecon: A Lightweight Workflow for Cell Type Analysis in High-Definition Spatial Transcriptomics Assays

The emergence of high-resolution spatial transcriptomics platforms, such as VisiumHD, has enabled transcriptome-wide spatial profiling at near-single-cell resolution. However, existing analysis tools often lack scalability or compatibility with this new resolution, limiting their utility for multimodal cell type analysis. We present Easydecon, a lightweight and modular computational framework for spatial transcriptomics analysis using marker genes from single-cell RNA sequencing datasets. Easydecon uses a two-phase strategy, which firstly detects expression hotspots and then refines cell type assignments with similarity-based methods. We demonstrate its efficacy by resolving cell type subsets with high accuracy. Easydecon supports integration with segmentation tools and outperforms established methods in speed, usability and cell type recovery.

bioinformatics↗

bioRxiv2025

Single cell spatial transcriptomics identifies coordinated cellular programs that are associated with good prognosis in microsatellite stable colorectal cancer

It has been reported that microsatellite instable (MSI) tumors in colorectal cancer (CRC) exhibit stronger anti-tumor responses than microsatellite stable (MSS) tumors. Analyzing scRNA-seq data from 185 CRC patients we found that immune, structural, and cancer cells in MSS tumors with high numbers of tumor-infiltrating CD8 T cells and macrophages (TAMs; CD8hiTAMhi) and CD8lowTAMhi tumors were enriched for pathways associated with anti- and pro-tumor responses, respectively. In CD8hiTAMhi tumors, TAMs expressed an IFN-induced phenotype (e.g. GBP1, CXCL9, IFITM3) and high infiltration of GBP1+ TAMs was associated with better overall survival (n=941). High-resolution spatial transcriptomics (Visium HD) revealed that GBP1+ TAMs clustered with CXCL13+IFNG+PDCD1+ CD8 T cells in tumoral niches, suggesting that GBP1+ TAMs were involved in recruitment and activation of tumor-reactive CD8 T cells. Together, we uncovered coordinated cellular programs across cell types in the microenvironment of MSS tumors, based on simple classification variables, that were strongly associated with prognosis.

cancer biology↗

bioRxiv2025

Ultra long-lived plasma cells in the human small intestine produce microbiota-reactive IgA antibodies

A large fraction of the intestinal microbiota is highly coated with secretory IgA, and bacteria-specific IgA is believed to shape the composition of the microbiota. A hallmark of the adaptive immune system is immunological memory to specific antigens. However, whether there is strong and persistent memory of secretory antibodies to bacterial antigens has not been determined. Here we show that ultra long-lived CD19- CD45- (age>20 years) plasma cells (PCs) residing in the human small intestine produce IgA that binds to most taxa of a diverse anaerobic microbiota culture. Long-lived CD19-CD45+ (age>10 years) and short-lived CD19+CD45+ (age<2 years) PCs also produced IgA with broad bacterial reactivity. A clear correlation between high-binding and low-binding taxa was observed across the PC subsets. We also found that host PCs were depleted in acute intestinal graft versus host disease, a condition strongly associated with loss of microbiota diversity. Together, we show that bacterial antigens in the intestine induce an extremely stable, long-lasting humoral immune memory that may be important for the long-term stability and resilience of the intestinal microbiome.

immunology↗

bioRxiv2023

cellsnake: a user-friendly tool for single cell RNA sequencing analysis

BackgroundSingle-cell RNA sequencing (scRNA-seq) provides high-resolution transcriptome data to understand the heterogeneity of cell populations at the single-cell level. The analysis of scRNA-seq data requires the utilization of numerous computational tools. However, non-expert users usually experience installation issues, a lack of critical functionality or batch analysis modes, and the steep learning curves of existing pipelines. ResultsWe have developed cellsnake, a comprehensive, reproducible, and accessible single-cell data analysis workflow, to overcome these problems. Cellsnake offers advanced features for standard users and facilitates downstream analyses in both R and Python environments. It is also designed for easy integration into existing workflows, allowing for rapid analyses of multiple samples. ConclusionAs an open-source tool, cellsnake is accessible through Bioconda, PyPi, Docker, and GitHub, making it a cost-effective and user-friendly option for researchers. By using cellsnake, researchers can streamline the analysis of scRNA-seq data and gain insights into the complex biology of single cells.

bioinformatics↗

bioRxiv2021

Spatiotemporal single cell transcriptomic analyzis of human gut macrophages revealsmultiple functional and niche-specific subsets

Macrophages are a heterogeneous population of cells involved in tissue homeostasis, inflammation and cancer. Although macrophages are densely distributed throughout the human intestine, our understanding of how gut macrophages maintain tissue homeostasis is limited. Here we show that colonic lamina propria (LpM) and muscularis macrophages (MM) consist of monocyte-like cells that differentiate into multiple transcriptionally distinct subsets. LpM comprise subsets with proinflammatory properties and subsets high antigen presenting and phagocytic capacity. The latter are strategically positioned close to the surface epithelium. Most MM differentiate along two trajectories; one that upregulates genes associated with immune activation and angiogenesis, whereas the other upregulates genes associated with neuronal homeostasis. Importantly, MM are located adjacent to neurons and vessels. Cell-cell interaction and gene network analysis indicated that survival, migration, transcriptional reprogramming, and niche-specific localization of LpM and MM are controlled by an extensive interaction with tissue-resident cells and a few key transcription factors.

immunology↗

bioRxiv2021

The epigenetic landscape in purified myonuclei from fast and slow muscles

Muscle cells have different phenotypes adapted to different usage and can be grossly divided into fast/glycolytic and slow/oxidative types. While most muscles contain a mixture of such fiber types, we aimed at providing a genome-wide analysis of chromatin environment by ChIP-Seq in two muscle extremes, the almost completely fast/glycolytic extensor digitorum longus (EDL) and slow/oxidative soleus muscles. Muscle is a heterogeneous tissue where less than 60% of the nuclei are inside muscle fibers. Since cellular homogeneity is critical in epigenome-wide association studies we devised a new method for purifying skeletal muscle nuclei from whole tissue based on the nuclear envelope protein Pericentriolar material 1 (PCM1) being a specific marker for myonuclei. Using antibody labeling and a magnetic-assisted sorting approach we were able to sort out myonuclei with 95% purity. The sorting eliminated influence from other cell types in the tissue and improved the myo-specific signal. A genome-wide comparison of the epigenetic landscape in EDL and soleus reflected the functional properties of the two muscles each with a distinct regulatory program involving distal enhancers, including a glycolytic super-enhancer in the EDL. The two muscles are also regulated by different sets of transcription factors; e.g. in soleus binding sites for MEF2C, NFATC2 and PPARA were enriched, while in EDL MYOD1 and SOX1 binding sites were found to be overrepresented. In addition, novel factors for muscle regulation such as MAF, ZFX and ZBTB14 were identified.

physiology↗

bioRxiv2020

Towards a consensus microRNA signature of primary and metastatic colorectal cancer

Although microRNAs (miRNA) are involved in all hallmarks of cancer, miRNA dysregulation in metastasis remains poorly understood and contradictory results have been published. The aim of this work was to identify miRNAs associated with metastatic progression of colorectal cancer (CRC). Novel and previously published next generation sequencing (NGS) datasets generated from 268 samples with primary (pCRC) and metastatic CRC (mCRC; liver, lung and peritoneal metastases) and tumor adjacent tissues were analyzed. Differential expression analysis was performed using a meticulous bioinformatics pipeline, including only bona fide miRNAs, utilizing miRNA-tailored quality control and processing, and applying a physiologically meaningful cut-off value (100 reads per million). The results were adjusted for host tissue background expression and samples from the different metastatic sites were independently analyzed. A metastatic signature containing five miRNAs up-regulated at multiple metastatic sites was identified (Mir-210_3p, Mir-191_5p, Mir-8-P1b_3p (mir-141-3p), Mir-1307_5p, and Mir-155_5p) along with a number of miRNAs that were differentially expressed at individual metastatic sites. Several of these have previously been implicated in metastasis through involvement in epithelial-to-mesenchymal transition and hypoxia, while other identified miRNAs represent novel findings. The identified differentially expressed miRNAs confirm known associations and contribute novel insights into miRNA involvement in the metastatic process. The use of open science practices facilitates reproducibility, and new datasets may easily be added to the publicly available pipeline to continuously improve the knowledge in the field. The identified set of miRNAs provides a reliable starting-point for further research into the role of miRNAs in metastatic progression.

cancer biology↗

bioRxiv2020

Genome-Wide Search for Candidate Drivers of Adaptation Reveals Genes Enriched for Shifts in Purifying Selection (SPurS)

An open question in comparative evolutionary genomics is whether or not certain loci are the primary drivers of divergence between taxonomic lineages or species groups. Alternatively, genetic drivers of species divergence may be evenly distributed across the genome. The increasing availability of genome sequences from diverse taxa has enabled the development of novel methods to address this question. Genomes of many highly diverged species may now be compared in order to tease apart genetic differences that drive adaptive or functional divergence, and genetic differences that are observed by chance and are not causally linked to traits that differ between species or lineages. In order to test the hypothesis that a particular subset of loci or genes is responsible for driving adaptive changes between mammals and non-mammals, we developed a novel comparative approach to identify sites that are highly conserved within lineages or species groups and diverge between them. Loci with a high concentration of these sites may be called Shifts in Purifying Selection (SPurS) because a change has occurred between two groups of species at some point in the past, and the shift is conserved (via purifying selection) over a long period of time. Evaluating 7484 orthologous gene copies from 76 vertebrate species, we developed an empirical distribution of SPurS across the genome between Synapsida (placental and non-placental mammals) and Sauropsida (birds, crocodilians, squamates, and turtles), and compared this distribution to the expected null distribution of SPurS using matched simulated data. We then identified a subset of genes that is enriched for SPurS, relative to the full set of genes and to their matched simulated alignments. These SPurS-enriched genes are thus likely candidate drivers of functional divergence or adaptation between the mammalian and non-mammalian species groups in our analysis. Investigators seeking to identify genetic drivers of inter-species evolution may find this method useful, and we provide a web-based software interface to facilitate its use.

evolutionary biology↗

bioRxiv2018

MirGeneDB2.0: the curated microRNA Gene Database

Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are unique because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this separation is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database MirGeneDB to 45 organisms that represent the full taxonomic breadth of Metazoa. By consistently annotating and naming more than 10,900 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked more than 2,100 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct Metazoan evolution. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs but also biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.

genomics↗

bioRxiv2018

Mind your gaps: Overlooking assembly gaps confounds statistical testing in genome analysis

BackgroundThe difficulties associated with sequencing and assembling some regions of the DNA sequence result in gaps in the reference genomes that are typically represented as stretches of Ns. Although the presence of assembly gaps causes a slight reduction in the mapping rate in many experimental settings, that does not invalidate the typical statistical testing comparing read count distributions across experimental conditions. However, we hypothesize that not handling assembly gaps in the null model may confound statistical testing of co-localization of genomic features.\n\nResultsFirst, we performed a series of explorative analyses to understand whether and how the public genomic tracks intersect the assembly gaps track (hg19). The findings rightly confirm that the genomic regions in public genomic tracks intersect very little with assembly gaps and the intersection was observed only at the beginning and end regions of the assembly gaps rather than covering the whole gap sizes. Further, we simulated a set of query and reference genomic tracks in a way that nullified any dependence between them to test our hypothesis that not avoiding assembly gaps in the null model would result in spurious inflation of statistical significance. We then contrasted the distributions of test statistics and p-values of Monte Carlo simulation-based permutation tests that either avoided or not avoided assembly gaps in the null model when testing for significant co-localization between a pair of query and reference tracks. We observed that the statistical tests that did not account for the assembly gaps in the null model resulted in a distribution of the test statistic that is shifted to the right and a distribu tion of p-values that is shifted to the left (leading to inflated significance).\n\nConclusionOur results shows that not accounting for assembly gaps in statistical testing of co-localization analysis may lead to false positives and over-optimistic findings.

bioinformatics↗

bioRxiv2017

Genome Build Information Is An Essential Part Of Genomic Track Files

Genomic locations are represented as coordinates on a specific genome build version, but the build information is frequently missing when coordinates are provided. It is essential to correctly interpret and analyse the genomic intervals contained in genomic track files. Here, we demonstrate that this crucial metadatum (or rather datum) is often isolated from the genomic track files in public repositories and journal articles, which could be a major time thief. We propose best practices to ensure that genome build version is always carried along with genomic track files. Although not a substitute to the best practices, we also provide a tool to predict the genome build version of genomic track files.

bioinformatics↗