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MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
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.
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.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
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.
Acute kidney injury is associated with mortality in COVID-19 patients. However, host cell changes underlying infection of renal cells with SARS-CoV-2 remain unknown and prevent understanding of the molecular mechanisms that may contribute to renal pathology. Here, we carried out quantitative translatome and whole-cell proteomics analyses of primary renal proximal and distal tubular epithelial cells derived from human donors infected with SARS-CoV-2 or MERS-CoV to disseminate virus and cell type–specific changes over time. Our findings revealed shared pathways modified upon infection with both viruses, as well as SARS-CoV-2-specific host cell modulation driving key changes in innate immune activation and cellular protein quality control. Notably, MERS-CoV infection–induced specific changes in mitochondrial biology that were not observed in response to SARS-CoV-2 infection. Furthermore, we identified extensive modulation in pathways associated with kidney failure that changed in a virus- and cell type–specific manner. In summary, we provide an overview of the effects of SARS-CoV-2 or MERS-CoV infection on primary renal epithelial cells revealing key pathways that may be essential for viral replication.
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.
The measurement of protein dynamics by proteomics to study cell remodeling has seen increased attention over the last years. This development is largely driven by a number of technological advances in proteomics methods. Pulsed stable isotope labeling in cell culture (SILAC) combined with tandem mass tag (TMT) labeling has evolved as a gold standard for profiling protein synthesis and degradation. While the experimental setup is similar to typical proteomics experiments, the data analysis proves more difficult: After peptide identification through search engines, data extraction requires either custom scripted pipelines or tedious manual table manipulations to extract the TMT-labeled heavy and light peaks of interest. To overcome this limitation, which deters researchers from using protein dynamic proteomics, we developed a user-friendly, browser-based application that allows easy and reproducible data analysis without the need for scripting experience. In addition, we provide a python package that can be implemented in established data analysis pipelines. We anticipate that this tool will ease data analysis and spark further research aimed at monitoring protein translation and degradation by proteomics.
Cell-free therapy using extracellular vesicles (EVs) from adipose-derived mesenchymal stromal/stem cells (ASCs) seems to be a safe and effective therapeutic option to support tissue and organ regeneration. The application of EVs requires particles with a maximum regenerative capability and hypoxic culture conditions as an in vitro preconditioning regimen has been shown to alter the molecular composition of released EVs. Nevertheless, the EV cargo after hypoxic preconditioning has not yet been comprehensively examined. The aim of the present study was the characterization of EVs from hypoxic preconditioned ASCs. We investigated the EV proteome and their effects on renal tubular epithelial cells in vitro. While no effect of hypoxia was observed on the number of released EVs and their protein content, the cargo of the proteins was altered. Proteomic analysis showed 41 increased or decreased proteins, 11 in a statistically significant manner. Furthermore, the uptake of EVs in epithelial cells and a positive effect on oxidative stress in vitro were observed. In conclusion, culture of ASCs under hypoxic conditions was demonstrated to be a promising in vitro preconditioning regimen, which alters the protein cargo and increases the anti-oxidative potential of EVs. These properties may provide new potential therapeutic options for regenerative medicine.
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.