Biology subjects

Schughart, K.

Publications and source records attributed to Schughart, K..

6 recordsLinked to original sources

bioRxiv2022

Hamsters are a model for COVID-19 alveolar regeneration mechanisms: an opportunity to understand post-acute sequelae of SARS-CoV-2

A relevant number of coronavirus disease 2019 (COVID-19) survivors suffers from post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (PASC). Current evidence suggests a dysregulated alveolar regeneration in COVID-19 as a possible explanation for respiratory PASC symptoms, a phenomenon which deserves further investigation in a suitable animal model. This study investigates morphological, phenotypical and transcriptomic features of alveolar regeneration in SARS-CoV-2 infected Syrian golden hamsters. We demonstrate that CK8+ alveolar differentiation intermediate (ADI) cells occur following SARS-CoV-2-induced diffuse alveolar damage. A subset of ADI cells shows nuclear accumulation of TP53 at 6- and 14-days post infection (dpi), indicating a prolonged arrest in the ADI state. Transcriptome data show the expression of gene signatures driving ADI cell senescence, epithelial-mesenchymal transition, and angiogenesis. Moreover, we show that multipotent CK14+ airway basal cell progenitors migrate out of terminal bronchioles, aiding alveolar regeneration. At 14 dpi, presence of ADI cells, peribronchiolar proliferates, M2-type macrophages, and sub-pleural fibrosis is observed, indicating incomplete alveolar restoration. The results demonstrate that the hamster model reliably phenocopies indicators of a dysregulated alveolar regeneration of COVID-19 patients. The results provide important information on a translational COVID-19 model, which is crucial for its application in future research addressing pathomechanisms of PASC and in testing of prophylactic and therapeutic approaches for this syndrome.

pathology↗

bioRxiv2022

Tracking influenza a virus infection in the lung from hematological data with machine learning

The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-{gamma} and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.

microbiology↗

bioRxiv2021

Itaconate and derivatives reduce interferon responses and inflammation in influenza A infection

Itaconate has recently emerged as a metabolite with immunomodulatory properties. We evaluated effects of endogenous itaconate and exogenous itaconate, dimethyl-, and 4-octyl-itaconate on host responses to influenza A virus infection. Infection induced ACOD1 (the enzyme catalyzing itaconate synthesis) mRNA in monocytes and macrophages, which correlated with viral replication and was abrogated by itaconate treatment. Pulmonary inflammation and weight loss were greater in Acod1-/- than wild-type mice, and ectopic synthesis of itaconate in human epithelial cells reduced infection-induced inflammation. The compounds induced different recruitment programs in infected human macrophages, and transcriptome profiling revealed that they reversed infection-triggered interferon responses and modulated inflammation in cell lines, PBMC, and lung tissue. Single-cell RNA sequencing of PBMC revealed that infection induced ACOD1 exclusively in monocytes, whereas treatment silenced IFN-responses in monocytes, lymphocytes, and NK cells. Viral replication did not increase under treatment despite the dramatically repressed IFN responses, but 4-octyl itaconate inhibited viral transcription in PBMC. The results reveal dramatic reprogramming of host responses by itaconate and derivatives and their potential as adjunct treatments for hyperinflammation in viral infection.

immunology↗

bioRxiv2020

Strain- and age-dependent features of the nigro-striatal circuit in three common laboratory mouse strains, C57BL/6J, A/J, and DBA/2J - Implications for Parkinson's disease modeling

Mouse models have been instrumental in understanding genetic determinants of aging and its crucial role in neurodegenerative diseases. However, few studies have analyzed the evolution of the mouse brain over time at baseline. Furthermore, mouse brain studies are commonly conducted on the C57BL/6 strain, limiting the analysis to a specific genetic background. In Parkinsons disease, the gradual demise of nigral dopaminergic neurons mainly contributes to the motor symptoms. Interestingly, a decline of the dopaminergic neuron function and integrity is also a characteristic of physiological aging in some species. Age-related nigro-striatal features have never been studied in mice of different genetic backgrounds. In this study, we analyze the morphological features in the striatum of three common mouse strains, C57BL/6J, A/J, and DBA/2J at 3-, 9- and 15 months of age. By measuring dopaminergic markers, we uncover age-related changes that differ between strains and evolve dynamically over time. Overall, our results highlight the importance of considering background strain and age when studying the murine nigro-striatal circuit in health and disease. HighlightsO_LIStudy of the integrity of the nigro-striatal circuit in C57BL/6J, A/J, and DBA/2J at different ages C_LIO_LIAge related evolution of essential features of nigral dopaminergic neurons differ between strains C_LIO_LIConsider background strain and age is crutial to study the nigrostriatal circuit in health and disease C_LI

neuroscience↗

bioRxiv2020

Quantitative trait locus mapping identifies Col4a6 as a novel regulator of striatal dopamine level and axonal branching in mice.

The features of dopaminergic neurons (DAns) of nigrostriatal circuitry are orchestrated by a multitude of yet unknown factors, many of them genetic. Genetic variation between individuals at baseline can lead to differential susceptibility to and severity of diseases. As decline of DAns, a characteristic of Parkinsons disease, heralds a significant decrease in dopamine level, measuring dopamine can reflect the integrity of DAns. To identify novel genetic regulators of the integrity of DAns, we used the Collaborative Cross (CC) mouse strains as model system to search for quantitative trait loci (QTLs) related to dopamine levels in the dorsal striatum. The dopamine levels in dorsal striatum varied greatly in the eight CC founder strains, and the differences were inheritable in 32 derived CC strains. QTL mapping in these CC strains identified a QTL associated with dopamine level on chromosome X containing 393 genes. RNA-seq analysis of the ventral midbrain of two of the founder strains with large striatal dopamine difference (C57BL/6J and A/J) revealed 24 differentially expressed genes within the QTL. The protein-coding gene with the highest expression difference was Col4a6, which exhibited a 9-fold reduction in A/J compared to C57BL/6J, consistent with decreased dopamine levels in A/J. Publicly available single cell RNA-seq data from developing human midbrain suggests that Col4a6 is highly expressed in radial glia-like cells and neuronal progenitors, indicating possible involvement in neurogenesis. Interestingly, the lowered dopamine levels were accompanied by reduced striatal axonal branching of striatal DAns in A/J compared to C57BL/6J. Because Col4a6 is known to control axogenesis in non-mammal model organisms, we hypothesize that different dopamine levels in mouse dorsal striatum are due to differences in axogenesis induced by varying COL4A6 levels during neural development.

neuroscience↗

bioRxiv2020

Pituitary Tumor Transforming Gene 1 orchestrates gene regulatory variation in mouse ventral midbrain during aging

BackgroundDopaminergic neurons in the midbrain are of particular interest due to their role in diseases such as Parkinsons disease and schizophrenia. Genetic variation between individuals can affect the integrity and function of dopaminergic neurons but the DNA variants and molecular cascades modulating dopaminergic neurons and other cells types of ventral midbrain remain poorly defined. Three genetically diverse inbred mouse strains -- C57BL/6J, A/J, and DBA/2J -- differ significantly in their genomes (~7 million variants), motor and cognitive behavior, and susceptibility to neurotoxins. ResultsTo further dissect the underlying molecular networks responsible for these variable phenotypes, we generated RNA-seq and ChIP-seq data from ventral midbrains of the 3 mouse strains. We defined 1000-1200 transcripts that are differentially expressed among them. These widespread differences may be due to altered activity or expression of upstream transcription factors. Interestingly, transcription factors were significantly underrepresented among the differentially expressed genes, and only one TF, Pttg1, showed significant differences among all strains. The changes in Pttg1 expression were accompanied by consistent alterations in histone H3 lysine 4 trimethylation at Pttg1 transcription start site. The ventral midbrain transcriptome of three-month-old C57BL/6J congenic Pttg1-/- mutants was only modestly altered, but shifted towards that of A/J and DBA/2J in nine-month-old mice. Principle component analysis identified the genes underlying the transcriptome shift and deconvolution of these bulk RNA-seq changes using midbrain single cell RNA-seq data suggested that the changes were occurring in several different cell types, including neurons, oligodendrocytes, and astrocytes. ConclusionTaken together, our results show that Pttg1 contributes to gene regulatory variation between mouse strains and influences mouse midbrain transcriptome during aging.

genomics↗