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Biology subjects

Taenzler, D.

Publications and source records attributed to Taenzler, D..

3 recordsLinked to original sources

Local fractal dimension as an indicator of functional reorganization in molecular interaction networks

Changes in protein abundance incompletely describe how molecular perturbations reshape cellular organization. Here we introduce DIFFRACT, a framework that integrates quantitative proteomics with protein-protein interaction networks to identify reorganization through changes in local fractal dimension. Molecular associations define effective distances between connected proteins, allowing the geometry of their surrounding network neighborhoods to be compared across conditions. Analyses across four organisms (E. coli, A. thaliana, C. elegans, and H. sapiens) and three interaction resources (STRING, BioGRID, and IntAct) establish heterogeneous local scaling, while controlled perturbations demonstrate sensitivity to regional changes and invariance to uniform distance rescaling. Applied to RAVER1-deficient A549 cells, DIFFRACT identifies components associated with established RNA-regulatory functions and candidate roles in tRNA biology, mitochondrial organization and ciliogenesis. Selected RNA-regulatory and ciliary themes are not significantly enriched by abundance-ranked gene set analysis, supporting complementary information from network geometry. Selected functional annotations also recur in HEK293T cells. Guided by the ciliary predictions, we show that RAVER1 depletion increases the proportion of ciliated A549 cells 2.57-fold and increases cilium length. DIFFRACT thus connects changes in molecular network geometry to experimentally testable biological responses, extending the interpretation of proteomic perturbations beyond differential abundance.

bioinformatics↗

First 3D-Structural Data of Full-length Rod-Outer-Segment Guanylyl Cyclase 1 in Bovine Retina by Cross-linking/Mass Spectrometry

The rod-outer-segment guanylyl cyclase 1 (ROS-GC1) is a key transmembrane protein for retinal phototransduction. Mutations of ROS-GC1 correlate with different retinal diseases that often lead to blindness. No structural data are available for ROS-GC1 so far. We performed a 3D-structural analysis of native ROS-GC1 from bovine retina by cross-linking/mass spectrometry (XL-MS) and computational modeling. Absolute quantification and activity measurements of native ROS-GC1 were performed by MS-based assays directly in bovine retina samples. Our data present the first 3D-structural analysis of active, full-length ROS-GC1 in bovine retina. We propose a novel domain organization for the intracellular domain ROS-GC1. Our XL-MS data reveal that the -helical domain connecting the kinase homology and catalytic domains can acquire different conformations. Also, the XL-MS data of native ROS-GC1 in bovine retina agree with a dimeric architecture. Our integrated approach can serve as a blueprint for conducting 3D-structural studies of membrane proteins in their native environment.

biochemistry↗

Mass Spectrometric Identification of SARS-CoV-2 Proteins from Gargle Solution Samples of COVID-19 Patients

Mass spectrometry (MS) can deliver valuable diagnostic data that complements genomic information and allows us to increase our current knowledge of the COVID-19 disease caused by the SARS-CoV-2 virus. We developed a simple, MS-based method to specifically detect SARS-CoV-2 proteins from gargle solution samples of COVID-19 patients. Our protocol consists of an acetone precipitation and tryptic digestion of proteins contained within the gargle solution, followed by a targeted MS analysis. Our methodology identifies unique peptides originating from SARS-CoV-2 nucleoprotein. Building on these promising initial results, faster MS protocols can now be developed as routine diagnostic tools for COVID-19 patients. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Image credit (left): Gerd Altmann, Pixabay License, https://pixabay.com/illustrations/corona-coronavirus-virus-covid-19-4959447 C_FIG_DISPLAY

biochemistry↗