Biology subjects

Keogh, A.

Publications and source records attributed to Keogh, A..

5 recordsLinked to original sources

bioRxiv2024

Ribonuclease Inhibitor and Angiogenin collaboratively regulate cell-type-specific global translation

Translation of mRNAs is a fundamental process that occurs in all cell-types of multicellular organisms. Conventionally, it has been considered a default step in gene expression, lacking specific regulation. However, recent studies have documented that certain mRNAs exhibit cell-type-specific translation1-3. Despite this, it remains unclear whether global translation is controlled in a cell-type-specific manner. Here we report that a ribosome-associated protein ribonuclease inhibitor-1 (RNH1) and its binding partner Angiogenin (ANG) collaboratively regulates cell-type-specific global translation. By employing human cell-lines and mouse models, we found that deletion of RNH1 decreases global translation selectively in hematopoietic origin cells but not in the non-hematopoietic origin cells. RNH1 mediated such cell-type-specific translation is mechanistically linked to ANG. We found that ANG, which is known to regulate ribosomal biogenesis4, is predominantly expressed in non-hematopoietic origin cells and absent in hematopoietic origin cells. ANG safeguards the non-hematopoietic origin cells from RNH1-knockout-mediated translation defects by upregulating ribosomal biogenesis. Further, we discovered that RNH1 controls the translation of ribosomal protein (RP) transcripts and influences mRNA circularization. Collectively, this study unravels the existence of cell-type-specific global translation regulators and highlights the complex translation regulation in vertebrates.

biochemistry↗

bioRxiv2021

Primary infection by E. multilocularis induces distinct patterns of crosstalk between hepatic regulatory T and natural killer T cells in mice

The larval stage of the helminthic cestode Echinococcus multilocularis can inflict tumor-like hepatic lesions that cause the parasitic disease alveolar echinococcosis in humans, with high mortality in untreated patients. Recently, opportunistic properties of the disease have been proposed based on the increased incidence in immunocompromised patients and mouse models, indicating that an appropriate adaptive immune response is required for the control of the disease. However, little is known about how the local hepatic immune responses modulate the infection with E. multilocularis. In a mouse model of oral infection that mimics the normal infection route in human patients, the adaptive immune response in the liver was assessed using single-cell RNA sequencing of isolated hepatic CD3+ T cells at different infection stages. We observed an early significant increase in regulatory T and natural killer T cells in parallel with an active downregulation of CD4+ and CD8+ T cells. Early interactions between regulatory T cells and natural killer T cells indicate a promotion of the formation of hepatic lesions and later contribute to suppression of the resolution of parasite-induced pathology. The obtained data provides a fresh insight on the adaptive immune responses and local regulatory pathways at different infection stages of E. multilocularis in mice. Author summaryAlveolar echinococcosis is an endemic parasitic infection leading to slowly growing but potentially lethal liver lesions if untreated. Transmission by increasing populations of urban foxes and the raise of immunosuppressed patients in mainly industrializsed endemic zones are the main causes responsible for increased incidence of alveolar echinococcosis. Observations in humans and mice indicate that reactions of the adaptive immune system are required to control the disease and to protect from a chronic infection. Therefore, we analysed the responses of T cells in the liver at single-cell resolution in a murine model mimicking the typical route of infection in humans. This so called single-cell RNA sequencing revealed specific temporal changes of T cell subsets such as natural killer T cells and regulatory T cells, indicating that these two cell types are recruited in the early phase to try to protect from parasite proliferation and are subsequently inhibited in the late phase of infection thus indicating immune escape mechanisms of the parasite. This study shows temporal changes of the immune cell profile in the liver over the course of a natural infection with E. multilocularis at the single cell level and reveals putative targets for novel therapeutic approaches for human AE and possibly other (parasitic/helminthic) diseases.

immunology↗

bioRxiv2021

Transcriptional profiling of early differentiation of primary human mesenchymal stem cells into chondrocytes

Articular cartilage has only very limited regenerative capacities in humans. Tissue engineering techniques for cartilage damage repair are limited in the production of hyaline cartilage. Mesenchymal stem/stromal cells (MSCs) are multipotent stem cells and can be differentiated into mature cartilage cells, chondrocytes, which could be used for repairing damaged cartilage. Chondrogenesis is a highly complex, relatively inefficient process lasting over 3 weeks in vitro. In order to better understand chondrogenic differentiation, especially the commitment phase, we have performed transcriptional profiling of MSC differentiation into chondrocytes from early timepoints starting 15 minutes after induction to 16 hours and fully differentiated chondrocytes at 21 days. Transcriptional gene regulatory networks (GRN) were identified using time-course clustering and upstream-regulator predictions which revealed that cells start epigenetic reprogramming as early as 2 hours after induction and commit to differentiation within 4-6 hours. After that they adapt their gene expression to cater for differentiation specific protein production. These results suggest that interventions to improve the frequency and efficiency of differentiation should target early processes.

molecular biology↗

bioRxiv2021

Single cell chronoatlas of regenerating mouse livers reveals early Kupffer cell proliferation

The liver is exemplar to study tissue regeneration due to its inherent ability of repair and regrowth. It replaces its lost or injured tissue by the proliferation, interaction and temporal coordination of multiple residential cell types. Until now we lacked a detailed description of the specific contributions of each cell type to the regenerative process, and therefore analyzed mouse livers 0, 3, 6, and 24 hours following two-thirds partial hepatectomy (PHx) by single cell RNA-sequencing (scRNA-seq) and mass cytometry. Our resulting genome wide temporal atlas contains the time dependent transcriptional changes in hepatocytes, endothelial cells, bone marrow-derived macrophages (BMDM) and Kupffer cells. In addition, it describes the cell specific contribution of mitogenic growth factors from biliary epithelial, endothelial and stellate cells as well as chemokines and cytokines from BMDM and granulocytes. And interestingly, Kupffer cells as opposed to hepatocytes emerged as the first cell to proliferate presenting a new dynamic in the liver following PHx. Here, we provide a robust data set at cellular resolution to uncover new elements and revisit current dogmas on the mechanisms underlying liver regeneration. To facilitate access to the data, we have launched the portal www.phxatlas.ch in which the scRNA-seq data can be visualized.

developmental biology↗

bioRxiv2019

Bayesian Correlation is a robust similarity measure for single cell RNA-seq data

Assessing similarity is highly important for bioinformatics algorithms to determine correlations between biological information. A common problem is that similarity can appear by chance, particularly for low expressed entities. This is especially relevant in single cell RNA-seq (scRNA-seq) data because read counts are much lower compared to bulk RNA-seq.\n\nRecently, a Bayesian correlation scheme, that assigns low similarity to genes that have low confidence expression estimates, has been proposed to assess similarity for bulk RNA-seq. Our goal is to extend the properties of the Bayesian correlation in scRNA-seq data by considering 3 ways to compute similarity. First, we compute the similarity of pairs of genes over all cells. Second, we identify specific cell populations and compute the correlation in those populations. Third, we compute the similarity of pairs of genes over all clusters, by considering the total mRNA expression.\n\nWe demonstrate that Bayesian correlations are more reproducible than Pearson correlations. Compared to Pearson correlations, Bayesian correlations have a smaller dependence on the number of input cells. We show that the Bayesian correlation algorithm assigns high similarity values to genes with a biological relevance in a specific population.\n\nWe conclude that Bayesian correlation is a robust similarity measure in scRNA-seq data.

bioinformatics↗