Biology subjects

Pennitz, P.

Publications and source records attributed to Pennitz, P..

6 recordsLinked to original sources

bioRxiv2024

Neutrophil-chemoattractant CXCL5 induces lung barrier permeability in acute lung injury

RationaleAcute lung injury is frequently caused by pneumonia, and severity correlates with inflammatory cell recruitment and lung barrier failure. Deciphering drug-targetable pathways is of clinical importance. ObjectivesInvestigation of paracrine and autocrine effects of epithelial-derived chemokine CXCL5 in acute lung injury. MethodsWe assessed the role of CXCL5 and related chemokines in patients with severe pneumonia and primary cells or cell lines challenged with Streptococcus pneumoniae or exposed to mechanical stretch. Furthermore, we evaluated the role of CXCL5 in in vivo models of acute lung injury through use of Cxcl5-deficient mice and in vitro human lung barrier models. ResultsPneumococcal infection and mechanical ventilation were associated with CXCL5 production in human subjects and in mice. CXCL5 was produced by bronchial and alveolar epithelial cells. The alveolar-epithelial barrier was protected in acute lung injury models in Cxcl5-deficient mice, independent of alveolar neutrophil recruitment. Single-cell transcriptomics revealed enhanced cell junctional transcripts in epithelial, but not endothelial cells in Cxcl5-deficient mice. Accordingly, CXCL5 exposure disrupted the barrier function of TNF-primed human primary alveolar epithelial cells, but not pulmonary microvascular endothelial cells. ConclusionsWe describe a novel function of CXCL5 in acute lung injury. Besides its recognized role in recruiting highly inflammatory cells such as neutrophils, CXCL5 increases alveolar-epithelial barrier permeability. Thus, in severe bacterial pneumonia, targeting of CXCL5 as adjunctive therapy to antibiotics may aid in reducing overshooting inflammation as well as stabilizing lung barrier function.

immunology↗

bioRxiv2024

Neural Network-Assisted Humanization of COVID-19 Hamster scRNAseq Data Reveals Matching Severity States in Human Disease

Translating findings from animal models to human disease is essential for dissecting disease mechanisms, developing and testing precise therapeutic strategies. The coronavirus disease 2019 (COVID-19) pandemic has highlighted this need, particularly for models showing disease severity-dependent immune responses. Single-cell transcriptomics (scRNAseq) is well poised to reveal similarities and differences between species at the molecular and cellular level with unprecedented resolution. However, computational methods enabling detailed matching are still scarce. Here, we provide a structured scRNAseq-based approach that we applied to scRNAseq from blood leukocytes originating from humans and hamsters affected with moderate or severe COVID-19. Integration of COVID-19 patient data with two hamster models that develop moderate (Syrian hamster, Mesocricetus auratus) or severe (Roborovski hamster, Phodopus roborovskii) disease revealed that most cellular states are shared across species. A neural network-based analysis using variational autoencoders quantified the overall transcriptomic similarity across species and severity levels, showing highest similarity between neutrophils of Roborovski hamsters and severe COVID-19 patients, while Syrian hamsters better matched patients with moderate disease, particularly in classical monocytes. We further used transcriptome-wide differential expression analysis to identify which disease stages and cell types display strongest transcriptional changes. Consistently, hamsters response to COVID-19 was most similar to humans in monocytes and neutrophils. Disease-linked pathways found in all species specifically related to interferon response or inhibition of viral replication. Analysis of candidate genes and signatures supported the results. Our structured neural network-supported workflow could be applied to other diseases, allowing better identification of suitable animal models with similar pathomechanisms across species. Key PointsO_LINeural networks can successfully match disease states between animal models and humans using single-cell data as shown for COVID-19 C_LIO_LIModerately diseased patients best matched Syrian hamster cells; severely diseased patients best matched Roborovski hamster neutrophils C_LI

immunology↗

bioRxiv2023

Single-cell-resolved interspecies comparison identifies a shared inflammatory axis and a dominant neutrophil-endothelial program in severe COVID-19

Key issues for research of COVID-19 pathogenesis are the lack of biopsies from patients and of samples at the onset of infection. To overcome these hurdles, hamsters were shown to be useful models for studying this disease. Here, we further leveraged the model to molecularly survey the disease progression from time-resolved single-cell RNA-sequencing data collected from healthy and SARS-CoV-2-infected Syrian and Roborovski hamster lungs. We compared our data to human COVID-19 studies, including BALF, nasal swab, and post-mortem lung tissue, and identified a shared axis of inflammation dominated by macrophages, neutrophils, and endothelial cells, which we show to be transient in Syrian and terminal in Roborovski hamsters. Our data suggest that, following SARS-CoV-2 infection, commitment to a type 1 or type 3-biased immunity determines moderate versus severe COVID-19 outcomes, respectively. One-Sentence SummaryActivation of different immunological programs upon SARS-CoV-2 infection determines COVID-19 severity.

immunology↗

bioRxiv2022

A live attenuated vaccine confers superior mucosal and systemic immunity to SARS-CoV-2 variants

Vaccines are a cornerstone in COVID-19 pandemic management. Here, we compare immune responses to and preclinical efficacy of the mRNA vaccine BNT162b2, an adenovirus-vectored spike vaccine, and the live-attenuated-virus vaccine candidate sCPD9 after single and double vaccination in Syrian hamsters. All regimens containing sCPD9 showed superior efficacy. The robust immunity elicited by sCPD9 was evident in a wide range of immune parameters after challenge with heterologous SARS-CoV-2 including rapid viral clearance, reduced tissue damage, fast differentiation of pre-plasmablasts, strong systemic and mucosal humoral responses, and rapid recall of memory T cells from lung tissue. Our results demonstrate that use of live-attenuated vaccines may offer advantages over available COVID-19 vaccines, specifically when applied as booster, and may provide a solution for containment of the COVID-19 pandemic.

immunology↗

bioRxiv2021

Insights into standards of care: dexamethasone and antibodies against COVID-19 in hamster models

RationaleIn face of the ongoing SARS-CoV-2 pandemic, effective and well-understood treatment options are still scarce. While vaccines have proven instrumental in fighting SARS-CoV-2, their efficacy is challenged by vaccine hesitancy, novel variants and short-lasting immunity. Therefore, understanding and optimization of therapeutic options remains essential. ObjectivesWe aimed at generating a deeper understanding on how currently used drugs, specifically dexamethasone and anti-SARS-CoV-2 antibodies, affect SARS-CoV-2 infection and host responses. Possible synergistic effects of both substances are investigated to evaluate combinatorial treatments. MethodsBy using two COVID-19 hamster models, pulmonary immune responses were analyzed to characterize effects of treatment with either dexamethasone, anti-SARS-CoV-2 spike monoclonal antibody or a combination of both. scRNA sequencing was employed to reveal transcriptional response to treatment on a single cell level. Measurements and main resultsDexamethasone treatment resulted in similar or increased viral loads compared to controls. Anti-SARS-CoV-2 antibody treatment alone or combined with dexamethasone successfully reduced pulmonary viral burden. Dexamethasone exhibited strong anti-inflammatory effects and prevented fulminant disease in a severe COVID-19-like disease model. Combination therapy showed additive benefits with both anti-viral and anti-inflammatory potency. Bulk and single-cell transcriptomic analyses confirmed dampened inflammatory cell recruitment into lungs upon dexamethasone treatment and identified a candidate subpopulation of neutrophils specifically responsive to dexamethasone. ConclusionsOur analyses i) confirm the anti-inflammatory properties and indicate possible modes of action for dexamethasone, ii) validate anti-viral effects of anti-SARS-CoV-2 antibody treatment, and iii) reveal synergistic effects of a combination therapy and can thus inform more effective COVID-19 therapies.

molecular biology↗

bioRxiv2020

Longitudinal omics in Syrian hamsters integrated with human data unravel complexity of moderate immune responses to SARS-CoV-2

In COVID-19, the immune response largely determines disease severity and is key to therapeutic strategies. Cellular mechanisms contributing to inflammatory lung injury and tissue repair in SARS-CoV-2 infection, particularly endothelial cell involvement, remain ill-defined. We performed detailed spatiotemporal analyses of cellular and molecular processes in SARS-CoV-2 infected Syrian hamsters. Comparison of hamster single-cell sequencing and proteomics with data sets from COVID-19 patients demonstrated inter-species concordance of cellular and molecular host-pathogen interactions. In depth vascular and pulmonary compartment analyses (i) supported the hypothesis that monocyte-derived macrophages dominate inflammation, (ii) revealed endothelial inflammation status and T-cell attraction, and (iii) showed that CD4+ and CD8+ cytotoxic T-cell responses precede viral elimination. Using the Syrian hamster model of self-limited moderate COVID-19, we defined the specific roles of endothelial and epithelial cells, among other myeloid and non-myeloid lung cell subtypes, for determining the disease course.

immunology↗