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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.
Die Hochschulen des landesweiten Verbundprojekts “Eine gemeinsame Strategie: Hessische Forschungsdateninfrastrukturen” (HeFDI)] streben an, den Forschenden ihrer Institution eine Möglichkeit zur Sicherung und Publikation ihrer Forschungsdaten anzubieten. Die lokalen Servicestellen zu Forschungsdaten beraten Forschende im Hinblick auf den Veröffentlichungs- oder Sicherungsort ihrer Daten zunächst stets zu fachspezifischen Angeboten. Gleichwohl sind die Anfragen zur sicheren Ablage und Publikation der Forschungsdaten vielfältig und betreffen oftmals solche Forschungsdaten, die nicht oder noch nicht in einem fachspezifischen Angebot abgelegt werden können. Nachgefragt wird deshalb ein vertrauenswürdiges institutionelles Repositorium, das ‘vor Ort’ genutzt werden kann.
Für den Betrieb einer solchen vertrauenswürdigen Repositoriumslösung, die zugleich effizient angelegt ist, bestanden zunächst folgende Optionen:
* Betrieb durch einen kommerziellen Anbieter; * eine gemeinschaftlich betriebene kooperative Repositoriumslösung, bei der Ressourcen gemeinsam genutzt werden (gemeinsam-kooperativ); * ein verteiltes, aber abgestimmtes System von Repositorien an den jeweiligen Standorten, die in wesentlichen technischen und organisatorischen Aspekten koordiniert betrieben werden (verteilt-koordiniert).
Aufgrund der Ergebnisse des Verifikationsreports kam die Nutzung eines kommerziellen Angebotes (vgl. Rodriguez 2018d) nicht mehr in Betracht, insbesondere deshalb, weil über die Ergebnisse des Reports hinaus die anzunehmenden Kosten den Eigenbetrieb überstiegen hätten. Außerdem wären weder Anpassbarkeit noch lokales Entwicklungspotential für fachliche Angebote ausreichend gegeben. Deshalb hat HeFDI in 2018 eine Erprobungsphase für die beiden Betriebsformen “gemeinsam-kooperativ” sowie “verteilt-koordiniert” gestartet, stets unter Berücksichtigung, dass sich durch die Erfahrungen auch weitere Varianten ergeben könnten.
Das vorliegende Papier verfolgt das Ziel, darzulegen, wie und zu welchen Bedingungen ein jeweils abgestimmter Betrieb einer möglichst geringen Anzahl an technischen Repositoriumslösungen an den HeFDI-Hochschulen erfolgen kann, so dass einerseits ein möglichst hoher Grad an Effizienz erreicht wird und andererseits lokale Anliegen berücksichtigt werden können. Dabei soll einerseits ein Betriebskonzept dafür dargelegt werden, wie ein Hochschulstandort für andere Hochschulstandorte eine institutionelle Repositoriumslösung für Forschungsdaten anbieten kann; das Konzept wird exemplarisch als Betriebsmodell für den gemeinsam-kooperativen Betrieb ausgearbeitet (Kap. 3). Ebenso wird ein Konzept dafür dargelegt, wie im Rahmen eines verteilt-koordinierten Betriebs von Repositorien die Abstimmung und Zusammenarbeit erfolgt (Kap. 4).
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.
Regulation of translation is essential during stress. However, the precise sets of proteins regulated by the key translational stress responses—the integrated stress response (ISR) and mTORC1—remain elusive. We developed multiplexed enhanced protein dynamics (mePROD) proteomics, adding signal amplification to dynamic-SILAC and multiplexing, to enable measuring acute changes in protein synthesis. Treating cells with ISR/mTORC1-modulating stressors, we showed extensive translatome modulation with ∼20% of proteins synthesized at highly reduced rates. Comparing translation-deficient sub-proteomes revealed an extensive overlap demonstrating that target specificity is achieved on protein level and not by pathway activation. Titrating cap-dependent translation inhibition confirmed that synthesis of individual proteins is controlled by intrinsic properties responding to global translation attenuation. This study reports a highly sensitive method to measure relative translation at the nascent chain level and provides insight into how the ISR and mTORC1, two key cellular pathways, regulate the translatome to guide cellular survival upon stress.
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.
Human RNF213, which encodes the protein mysterin, is a known susceptibility gene for moyamoya disease (MMD), a cerebrovascular condition with occlusive lesions and compensatory angiogenesis. Mysterin mutations, together with exposure to environmental trigger factors, lead to an elevated stroke risk since childhood. Mysterin is induced during cell stress, to function as cytosolic AAA+ ATPase and ubiquitylation enzyme. Little knowledge exists, in which context mysterin is needed. Here, we found that genetic ablation of several mitochondrial matrix factors, such as the peptidase ClpP, the transcription factor Tfam, as well as the peptidase and AAA+ ATPase Lonp1, potently induces Rnf213 transcript expression in various organs, in parallel with other components of the innate immune system. Mostly in mouse fibroblasts and human endothelial cells, the Rnf213 levels showed prominent upregulation upon Poly(I:C)-triggered TLR3-mediated responses to dsRNA toxicity, as well as upon interferon gamma treatment. Only partial suppression of Rnf213 induction was achieved by C16 as an antagonist of PKR (dsRNA-dependent protein kinase). Since dysfunctional mitochondria were recently reported to release immune-stimulatory dsRNA into the cytosol, our results suggest that mysterin becomes relevant when mitochondrial dysfunction or infections have triggered RNA-dependent inflammation. Thus, MMD has similarities with vasculopathies that involve altered nucleotide processing, such as Aicardi-Goutières syndrome or systemic lupus erythematosus. Furthermore, in MMD, the low penetrance of RNF213 mutations might be modified by dysfunctions in mitochondria or the TLR3 pathway.
The transcription factor ∆Np63 is a master regulator of epithelial cell identity and essential for the survival of squamous cell carcinoma (SCC) of lung, head and neck, oesophagus, cervix and skin. Here, we report that the deubiquitylase USP28 stabilizes ∆Np63 and maintains elevated ∆NP63 levels in SCC by counteracting its proteasome‐mediated degradation. Impaired USP28 activity, either genetically or pharmacologically, abrogates the transcriptional identity and suppresses growth and survival of human SCC cells. CRISPR/Cas9‐engineered in vivo mouse models establish that endogenous USP28 is strictly required for both induction and maintenance of lung SCC. Our data strongly suggest that targeting ∆Np63 abundance via inhibition of USP28 is a promising strategy for the treatment of SCC tumours.
Oncogenic transformation of lung epithelial cells is a multi-step process, frequently starting with the inactivation of tumor suppressors and subsequent activating mutations in proto-oncogenes, such as members of the PI3K or MAPK family. Cells undergoing transformation have to adjust to changes, such as metabolic requirements. This is achieved, in part, by modulating the protein abundance of transcription factors, which manifest these adjustments. Here, we report that the deubiquitylase USP28 enables oncogenic reprogramming by regulating the protein abundance of proto-oncogenes, such as c-JUN, c-MYC, NOTCH and ΔNP63, at early stages of malignant transformation. USP28 is increased in cancer compared to normal cells due to a feed-forward loop, driven by increased amounts of oncogenic transcription factors, such as c-MYC and c-JUN. Irrespective of oncogenic driver, interference with USP28 abundance or activity suppresses growth and survival of transformed lung cells. Furthermore, inhibition of USP28 via a small molecule inhibitor reset the proteome of transformed cells towards a ‘pre-malignant’ state, and its inhibition cooperated with clinically established compounds used to target EGFRL858R, BRAFV600E or PI3KH1047R driven tumor cells. Targeting USP28 protein abundance already at an early stage via inhibition of its activity therefore is a feasible strategy for the treatment of early stage lung tumours and the observed synergism with current standard of care inhibitors holds the potential for improved targeting of established tumors.
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.