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Diedrich, L.

Publications and source records attributed to Diedrich, L..

5 recordsLinked to original sources

Aggregate Deep Visual Proteomics reveals selective organization of α-synuclein inclusions

-Synuclein inclusions, the lesions typical of Parkinson's disease, have been interpreted as protective deposits, toxic species or failed degradation products, each predicting a different composition and correlating that enrichment with neuron dysfunction and eventual degeneration. Distinguishing them requires measuring what an inclusion concentrates relative to the cell that built it. Here we developed Aggregate Deep Visual Proteomics, which uses ultrasensitive mass spectrometry to profile laser-microdissected inclusions against the remainder of the same cell or a matched host. In HEK293 cells, iPSC-derived dopaminergic neurons and post-mortem patient brain, each inclusion concentrated a selective subset of its cell's proteome, independent of abundance and dominated by membrane, in neurons largely presynaptic. Inclusions took up whole assemblies, with subunits moving together in 421 of 438 complexes, and the V-ATPase alone was enriched in all three systems. Degradation cargo stayed with the receptors that route it, consistent with sequestration and failed degradation acting together. Neuritic and somatic inclusions differed, the former rich in UBQLN2 and the latter in intermediate filaments. In the cell line, phosphorylated -synuclein was tenfold higher in the inclusion than in the rest of the cell, with about one third of the rise already present before an inclusion was visible. Measured against its host, the composition of an inclusion becomes a readout of how it formed and a source of candidate markers and therapeutic targets.

biochemistry↗

AlphaPeptTools: scverse-native analysis of mass spectrometry-based proteomics

Mass spectrometry (MS)-based proteomics now routinely profiles proteomes at scale, but extracting biological insight and integrating complementary modalities remains challenging. Here, we present AlphaPeptTools, a Python package for the analysis of MS-proteomics data built on the AnnData data structure of the scverse. AlphaPeptTools implements scalable and modular strategies for MS-data ingestion, quality control, preprocessing, and statistical analysis while seamlessly integrating with the scverse ecosystem, unlocking multi-level, spatial, and multimodal analyses.

bioinformatics↗

In the same cell, the proteome defines cellular state and the transcriptome marks transitions

Bulk transcriptome and proteome correlate only modestly, but this has not been investigated in the same cell or across cell-state changes. Here we introduce a scalable technology that quantifies thousands of proteins and transcripts in the same cell, separating RNA from protein by tip-based C18 capture and pairing full-length RNA sequencing with latest-generation mass spectrometry. In HeLa cells, transcript and protein abundances agree on the broad ranking within a cell (r = 0.45), but do not co-vary across the population (r = 0.038). In pluripotency transitions, only a third of matched transcripts and proteins change synchronously, yet the transcription factors defining each state stay tightly co-regulated. Transcript variance is several-fold larger than protein variance, reflecting transcriptional bursting and mRNA sampling noise. The proteome is thus the stable, low-noise definition of cell state, while the transcriptome marks cellular transitions; consequently, the proteome defines cell-state from far fewer cells.

systems biology↗

A cell type-resolved proteomic atlas of the human body

Proteins define what cells do, yet their systematic quantification across human cell types has remained out of reach. Using Deep Visual Proteomics on tissue from a healthy female donor, we built an atlas of 27 cell types across 14 tissues, quantifying two-thirds of all human protein-coding genes, with up to 8,500 per population. The proteome partitions bimodally into a universal core and highly specialized programs. Integration into the Human Protein Atlas Single Cell Resource enabled comparison of RNA and protein abundance at cell type resolution, revealing that concordance depends on pathway rather than cellular identity. This resolution uncovered cancer-testis antigens in oocytes invisible to bulk profiling. Our openly accessible resource provides a foundation for cell type-resolved proteomics in health and disease.

biochemistry↗

Energetics and kinetics of membrane permeation of photoresists for bioprinting

Three-dimensional (3D) bioprinting is a promising technology which typically uses bioinks to pattern cells and their scaffolds. The selection of cytocompatible inks is critical for the printing success. In laserbased 3D bioprinting, photoresist molecules are used as bioinks. We propose that cytotoxicity can be a consequence of the interaction of photoresists with lipid membranes and their permeation into the cell. Here, molecular dynamics simulations and in vitro assays address this issue, retrieving partition coefficients, free energies, and permeabilities for eight commonly-used photoresists in model lipid bilayers. Crossing the hydrophobic center of the membrane constitutes the rate limiting step during permeation. In addition, three photoresists feature a preferential localization site at the acyl chain headgroup interface. Photoresist permeabilities range over eight orders of magnitude, with some molecules being membrane-permeable on bioprinting timescales. Moreover, permeation correlates well with the oil-water partition coefficients and is severely hampered by the lipid ordering imposed by the lipid saturation. Overall, the mechanism of interaction of photoresists with model lipid bilayers is provided here, helping to classify them according to their residence in the membrane and permeation through it. This is useful information to guide the selection of cytocompatible photoresists for 3D bioprinting.

biophysics↗