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Mundt, F.

Publications and source records attributed to Mundt, F..

5 recordsLinked to original sources

SARS-CoV-2 hijacks fragile X mental retardation proteins for efficient infection

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1 and FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and have delayed disease onset in vivo. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins for efficient infection and provides molecular insight to the possible underlying molecular defects in fragile X syndrome.

microbiology↗

In depth profiling of the cancer proteome from the flowthrough of standard RNA-preparation kits for precision oncology

Cancer is a highly heterogeneous disease, even within the same patient. Biopsies taken from different regions of a tumor may stand in stark molecular contrast to each other. Therefore, the ability to generate meaningful data from multiple platforms using the same biopsy is crucial for translating multi-omics characterizations into the clinic. However, it is generally a cumbersome and lengthy procedure to generate DNA, RNA and protein material from the same biopsy. The Qiagen AllPrep kit is an accessible, straightforward, and widely used kit in clinics worldwide to process biopsies and generate genomic and transcriptomic data from tumors. We aimed to determine if high-quality proteomics data could also be obtained from the remaining material. Here, we investigated procedures for generating deep and quantitatively accurate proteomic information in high throughput from Qiagen AllPrep flowthroughs. With a number of refinements, we obtain in excess of 10,000 quantified proteins, from 60 samples per day, achieving a substantial coverage of the total proteome. Additionally, we successfully characterize the tumors using phosphoproteomics. Combining a standard kit with in-depth proteomics will be an attractive approach for clinics seeking to implement multi-omics-based precision oncology.

cancer biology↗

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes and normal tissues

Defects in pancreatic islets and the progression of multi-tissue insulin resistance in combination with environmental factors are the main causes of type 2 diabetes (T2D). Mass spectrometry-based proteomics of five key-metabolic tissues on a cohort of 42 multi-organ donors provided deep coverage of the proteomes of pancreatic islets, visceral adipose tissue (VAT), liver, skeletal muscle and serum. Enrichment analysis of gene ontology (GO) terms built a tissue-specific map of the chronological order of altered biological processes across healthy controls (CTRL), pre-diabetes (PD) and T2D subjects. This unique dataset allowed us to explore alterations of entire biological pathways and individual proteins in multiple tissues. We confirmed the significant decrease of the citric acid cycle and the respiratory electron transport in VAT and muscle of T2D and we provided a thorough visual representation of the complete set of downregulated proteins. Importantly, we found widespread novel alterations in relevant biological pathways including the increase in hemostasis in pancreatic islets of PD, the increase in the complement cascade in liver and pancreatic islets of PD and the elevation in cholesterol biosynthesis in liver of T2D. Overall, our findings suggest inflammatory, immune and vascular impairments in pancreatic islets as potentially causal factors of insufficient insulin production and increased glucagon levels in the early stages of T2D. In contrast alterations in lipid metabolism and mitochondrial function in the liver and VAT/muscle, respectively, became evident later in manifest T2D. This first multi-tissue proteomic map indicates the temporal order of tissue-specific metabolic dysregulation in T2D development.

cell biology↗

Clinical Knowledge Graph Integrates Proteomics Data into Clinical Decision-Making

The promise of precision medicine is to deliver personalized treatment based on the unique physiology of each patient. This concept was fueled by the genomic revolution, but it is now evident that integrating other types of omics data, like proteomics, into the clinical decision-making process will be essential to accomplish precision medicine goals. However, quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across myriad biomedical databases and publications makes this exceptionally difficult. To address this, we developed the Clinical Knowledge Graph (CKG), an open source platform currently comprised of more than 16 million nodes and 220 million relationships to represent relevant experimental data, public databases and the literature. The CKG also incorporates the latest statistical and machine learning algorithms, drastically accelerating analysis and interpretation of typical proteomics workflows. We use several biomarker studies to illustrate how the CKG may support, enrich and accelerate clinical decision-making. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/084897v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@433689org.highwire.dtl.DTLVardef@b18068org.highwire.dtl.DTLVardef@1656084org.highwire.dtl.DTLVardef@a38201_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Mapping the unique and shared functions of oncogenic KRAS and RIT1 with proteome and transcriptome profiling

Aberrant activation of RAS oncogenes is prevalent in lung adenocarcinoma, with somatic mutation of KRAS occurring in [~]30% of tumors. Recently, we identified somatic mutation of the RAS-family GTPase RIT1 in lung adenocarcinoma, but relatively little is known about the biological pathways regulated by RIT1 and how these relate to the oncogenic KRAS network. Here we present quantitative proteomic and transcriptomic profiles from KRAS-mutant and RIT1-mutant isogenic lung epithelial cells and globally characterize the signaling networks regulated by each oncogene. We find that both mutant KRAS and mutant RIT1 promote S6 kinase, AKT, and RAF/MEK signaling, and promote epithelial-to-mesenchymal transition and immune evasion via HLA protein loss. However, KRAS and RIT1 diverge in regulation of phosphorylation sites on EGFR, USO1, and AHNAK proteins. The majority of the proteome changes are related to altered transcriptional regulation, but a small subset of proteins are differentially regulated by both oncoproteins at the post-transcriptional level, including intermediate filament proteins, metallothioneins, and MHC Class I proteins. These data provide the first global, unbiased characterization of oncogenic RIT1 network and identify the shared and divergent functions of oncogenic RIT1 and KRAS GTPases in lung cancer.

cancer biology↗