Severe Dysbiosis and Specific Haemophilus and Neisseria Signatures as Hallmarks of the Oropharyngeal Microbiome in Critically Ill Coronavirus Disease 2019 (COVID-19) Patients.

BACKGROUND: At the entry site of respiratory virus infections, the oropharyngeal microbiome has been proposed as a major hub integrating viral and host immune signals. Early studies suggested that infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are associated with changes of the upper and lower airway microbiome, and that specific microbial signatures may predict coronavirus disease 2019 (COVID-19) illness. However, the results are not conclusive, as critical illness can drastically alter a patient's microbiome through multiple confounders. METHODS: To study oropharyngeal microbiome profiles in SARS-CoV-2 infection, clinical confounders, and prediction models in COVID-19, we performed a multicenter, cross-sectional clinical study analyzing oropharyngeal microbial metagenomes in healthy adults, patients with non-SARS-CoV-2 infections, or with mild, moderate, and severe COVID-19 (n = 322 participants). RESULTS: In contrast to mild infections, patients admitted to a hospital with moderate or severe COVID-19 showed dysbiotic microbial configurations, which were significantly pronounced in patients treated with broad-spectrum antibiotics, receiving invasive mechanical ventilation, or when sampling was performed during prolonged hospitalization. In contrast, specimens collected early after admission allowed us to segregate microbiome features predictive of hospital COVID-19 mortality utilizing machine learning models. Taxonomic signatures were found to perform better than models utilizing clinical variables with Neisseria and Haemophilus species abundances as most important features. CONCLUSIONS: In addition to the infection per se, several factors shape the oropharyngeal microbiome of severely affected COVID-19 patients and deserve consideration in the interpretation of the role of the microbiome in severe COVID-19. Nevertheless, we were able to extract microbial features that can help to predict clinical outcomes.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage.

Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

IL-17A and IFN-γ synergistically induce RNase 7 expression via STAT3 in primary keratinocytes.

Human keratinocytes produce several antimicrobial peptides and proteins (AMP) which contribute to the protection of human skin against infection. RNase 7 is a major AMP involved in cutaneous defense with a high expression in keratinocytes and a broad spectrum of antimicrobial activity. The cytokine IL-17A has been recently identified as a potent inducer of several AMP in keratinocytes. Since the role of IL-17A to induce RNase 7 expression is unknown we analyzed IL-17A alone and in combination with other cytokines to induce RNase 7 expression in keratinocytes. Whereas IL-17A alone only weakly induced RNase 7 expression, the synergistic combination of IL-17A and IFN-γ (IL-17A/IFN-γ) was identified as a potent inducer of RNase 7 expression. This combination was more effective in inducing RNase 7 than the combination of IL-17A/TNF-α, a combination previously identified as a strong inducer of psoriasis-related immune response genes including several AMP. IFN-γ and IL-17A both have been reported to activate the transcription factor STAT3 (Signal transducer and activator of transcription 3). Therefore we investigated the influence of STAT3 on the IL-17A/IFN-γ -mediated RNase 7 induction. The use of a STAT3 inhibitor as well as siRNA-mediated downregulation of STAT3 resulted in a diminished IL-17A/IFN-γ -mediated RNase 7 induction in keratinocytes indicating that STAT3 is involved in this process. Similarly as seen with RNase 7, treatment of keratinocytes with IL-17A/IFN-γ revealed also a synergistic induction of gene expression of the AMP human beta-defensin (hBD)-2 and -3 as well as the S100 protein psoriasin (S100A7) indicating that the combination of IL-17A/IFN-γ is a potent inducer of various AMP classes in general. This was also reflected by an increase of the Staphylococcus aureus-killing activity of IL-17A/IFN-γ -treated keratinocytes.