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Institute
Upon infection with SARS-CoV-2, a variety of changes happen inside the host cell. The virus hijacks host cell pathways for driving its own replication, while the host counteracts with response mechanisms. To gain a comprehensive understanding of COVID-19, caused by SARS-CoV-2 infection, and develop therapeutic strategies, it is crucial to observe these systematic changes in their entirety. In our recent studies, we followed the effects of SARS-CoV-2 infection on the human proteome, which led to the identification of several drugs that abolished viral proliferation in cells.
The mammalian target of rapamycin and the integrated stress response are central cellular hubs regulating translation upon stress. The precise proteins and pathway specificity of translation targets of these pathways remained largely unclear. We recently described a new method for quantitative translation proteomics and found that both pathways control translation of the same sets of proteins.
Severe acute respiratory syndrome virus 2 (SARS-CoV-2) is the cause of the current coronavirus disease 19 (COVID-19) pandemic. Protease inhibitors are under consideration as virus entry inhibitors that prevent the cleavage of the coronavirus spike (S) protein by cellular proteases. Herein, we showed that the protease inhibitor aprotinin (but not the protease inhibitor SERPINA1/alpha-1 antitrypsin) inhibited SARS-CoV-2 replication in therapeutically achievable concentrations. An analysis of proteomics and translatome data indicated that SARS-CoV-2 replication is associated with a downregulation of host cell protease inhibitors. Hence, aprotinin may compensate for downregulated host cell proteases during later virus replication cycles. Aprotinin displayed anti-SARS-CoV-2 activity in different cell types (Caco2, Calu-3, and primary bronchial epithelial cell air–liquid interface cultures) and against four virus isolates. In conclusion, therapeutic aprotinin concentrations exert anti-SARS-CoV-2 activity. An approved aprotinin aerosol may have potential for the early local control of SARS-CoV-2 replication and the prevention of COVID-19 progression to a severe, systemic disease.
SARS-CoV-2 is the causative agent of COVID-19. Severe COVID-19 disease has been associated with disseminated intravascular coagulation and thrombosis, but the mechanisms underlying COVID-19-related coagulopathy remain unknown. The risk of severe COVID-19 disease is higher in males than in females and increases with age. To identify gene products that may contribute to COVID-19-related coagulopathy, we analyzed the expression of genes associated with the Gene Ontology (GO) term “blood coagulation” in the Genotype-Tissue Expression (GTEx) database and identified four procoagulants, whose expression is higher in males and increases with age (ADAMTS13, F11, HGFAC, KLKB1), and two anticoagulants, whose expression is higher in females and decreases with age (C1QTNF1, SERPINA5). However, the expression of none of these genes was regulated in a proteomics dataset of SARS-CoV-2-infected cells and none of the proteins have been identified as a binding partner of SARS-CoV-2 proteins. Hence, they may rather generally predispose individuals to thrombosis without directly contributing to COVID-19-related coagulopathy. In contrast, the expression of the procoagulant transferrin (not associated to the GO term “blood coagulation”) was higher in males, increased with age, and was upregulated upon SARS-CoV-2 infection. Hence, transferrin warrants further examination in ongoing clinic-pathological investigations.
SARS-CoV-2 infections are rapidly spreading around the globe. The rapid development of therapies is of major importance. However, our lack of understanding of the molecular processes and host cell signaling events underlying SARS-CoV-2 infection hinder therapy development. We employed a SARS-CoV-2 infection system in permissible human cells to study signaling changes by phospho-proteomics. We identified viral protein phosphorylation and defined phosphorylation-driven host cell signaling changes upon infection. Growth factor receptor (GFR) signaling and downstream pathways were activated. Drug-protein network analyses revealed GFR signaling as key pathway targetable by approved drugs. Inhibition of GFR downstream signaling by five compounds prevented SARS-CoV-2 replication in cells, assessed by cytopathic effect, viral dsRNA production, and viral RNA release into the supernatant. This study describes host cell signaling events upon SARS-CoV-2 infection and reveals GFR signaling as central pathway essential for SARS-CoV-2 replication. It provides with novel strategies for COVID-19 treatment.
The integrated stress response (ISR) is a central cellular adaptive program that is activated by diverse stressors including ER stress, hypoxia and nutrient deprivation to orchestrate responses via activating transcription factor 4 (ATF4). We hypothesized that ATF4 is essential for the adaptation of human glioblastoma (GB) cells to the conditions of the tumor microenvironment and is contributing to therapy resistance against chemotherapy. ATF4 induction in GB cells was modulated pharmacologically and genetically and investigated in the context of temozolomide treatment as well as glucose and oxygen deprivation. The relevance of the ISR was analyzed by cell death and metabolic measurements under conditions to approximate aspects of the GB microenvironment. ATF4 protein levels were induced by temozolomide treatment. In line, ATF4 gene suppressed GB cells (ATF4sh) displayed increased cell death and decreased survival after temozolomide treatment. Similar results were observed after treatment with the ISR inhibitor ISRIB. ATF4sh and ISRIB treated GB cells were sensitized to hypoxia-induced cell death. Our experimental study provides evidence for an important role of ATF4 for the adaptation of human GB cells to conditions of the tumor microenvironment characterized by low oxygen and nutrient availability and for the development of temozolomide resistance. Inhibiting the ISR in GB cells could therefore be a promising therapeutic approach.
Leukemia cells reciprocally interact with their surrounding bone marrow microenvironment (BMM), rendering it hospitable to leukemia cell survival, for instance through the release of small extracellular vesicles (sEVs). In contrast, we show here that BMM deficiency of pleckstrin homology domain family M member 1 (PLEKHM1), which serves as a hub between fusion and secretion of intracellular vesicles and is important for vesicular secretion in osteoclasts, accelerates murine BCR-ABL1+ B-cell acute lymphoblastic leukemia (B-ALL) via regulation of the cargo of sEVs released by BMM-derived mesenchymal stromal cells (MSCs). PLEKHM1-deficient MSCs and their sEVs carry increased amounts of syntenin and syndecan-1, resulting in a more immature B-cell phenotype and an increased number/function of leukemia-initiating cells (LICs) via focal adhesion kinase and AKT signaling in B-ALL cells. Ex vivo pretreatment of LICs with sEVs derived from PLEKHM1-deficient MSCs led to a strong trend toward acceleration of murine and human BCR-ABL1+ B-ALL. In turn, inflammatory mediators such as recombinant or B-ALL cell–derived tumor necrosis factor α or interleukin-1β condition murine and human MSCs in vitro, decreasing PLEKHM1, while increasing syntenin and syndecan-1 in MSCs, thereby perpetuating the sEV-associated circuit. Consistently, human trephine biopsies of patients with B-ALL showed a reduced percentage of PLEKHM1+ MSCs. In summary, our data reveal an important role of BMM-derived sEVs for driving specifically BCR-ABL1+ B-ALL, possibly contributing to its worse prognosis compared with BCR-ABL1− B-ALL, and suggest that secretion of inflammatory cytokines by cancer cells in general may similarly modulate the tumor microenvironment.
Background: Alternative polyadenylation (APA) refers to the regulated selection of polyadenylation sites (PASs) in transcripts, which determines the length of their 3′ untranslated regions (3′UTRs). We have recently shown that SRSF3 and SRSF7, two closely related SR proteins, connect APA with mRNA export. The mechanism underlying APA regulation by SRSF3 and SRSF7 remained unknown.
Results: Here we combine iCLIP and 3′-end sequencing and find that SRSF3 and SRSF7 bind upstream of proximal PASs (pPASs), but they exert opposite effects on 3′UTR length. SRSF7 enhances pPAS usage in a concentration-dependent but splicing-independent manner by recruiting the cleavage factor FIP1, generating short 3′UTRs. Protein domains unique to SRSF7, which are absent from SRSF3, contribute to FIP1 recruitment. In contrast, SRSF3 promotes distal PAS (dPAS) usage and hence long 3′UTRs directly by counteracting SRSF7, but also indirectly by maintaining high levels of cleavage factor Im (CFIm) via alternative splicing. Upon SRSF3 depletion, CFIm levels decrease and 3′UTRs are shortened. The indirect SRSF3 targets are particularly sensitive to low CFIm levels, because here CFIm serves a dual function; it enhances dPAS and inhibits pPAS usage by binding immediately downstream and assembling unproductive cleavage complexes, which together promotes long 3′UTRs.
Conclusions; We demonstrate that SRSF3 and SRSF7 are direct modulators of pPAS usage and show how small differences in the domain architecture of SR proteins can confer opposite effects on pPAS regulation.
Here, we present a peptide-based linear mixed models tool—PBLMM, a standalone desktop application for differential expression analysis of proteomics data. We also provide a Python package that allows streamlined data analysis workflows implementing the PBLMM algorithm. PBLMM is easy to use without scripting experience and calculates differential expression by peptide-based linear mixed regression models. We show that peptide-based models outperform classical methods of statistical inference of differentially expressed proteins. In addition, PBLMM exhibits superior statistical power in situations of low effect size and/or low sample size. Taken together our tool provides an easy-to-use, high-statistical-power method to infer differentially expressed proteins from proteomics data.
The ancestral SARS-CoV-2 strain that initiated the Covid-19 pandemic at the end of 2019 has rapidly mutated into multiple variants of concern with variable pathogenicity and increasing immune escape strategies. However, differences in host cellular antiviral responses upon infection with SARS-CoV-2 variants remain elusive. Leveraging whole-cell proteomics, we determined host signaling pathways that are differentially modulated upon infection with the clinical isolates of the ancestral SARS-CoV-2 B.1 and the variants of concern Delta and Omicron BA.1. Our findings illustrate alterations in the global host proteome landscape upon infection with SARS-CoV-2 variants and the resulting host immune responses. Additionally, viral proteome kinetics reveal declining levels of viral protein expression during Omicron BA.1 infection when compared to ancestral B.1 and Delta variants, consistent with its reduced replication rates. Moreover, molecular assays reveal deferral activation of specific host antiviral signaling upon Omicron BA.1 and BA.2 infections. Our study provides an overview of host proteome profile of multiple SARS-CoV-2 variants and brings forth a better understanding of the instigation of key immune signaling pathways causative for the differential pathogenicity of SARS-CoV-2 variants.