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Krawitzky, M.

Publications and source records attributed to Krawitzky, M..

2 recordsLinked to original sources

Expanded Proteome Coverage Powered by Advanced Ion Processing Enables Deep Single-Cell Drug Response Subtyping in Human Stem Cell Derived Cardiomyocytes

Single-cell proteomics (SCP) enables the study of cellular heterogeneity at the functional level but remains limited by incomplete proteome coverage and high data missingness. Here, we present an enhanced label-free SCP workflow that leverages the timsUltra AIP mass spectrometry platform equipped with the Athena Ion Processor (AIP). Across a controlled dilution series of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), AIP-enabled acquisition consistently increased proteome depth and detection consistency across cells at all input levels. In single iPSC-CMs, the timsUltra AIP quantified up to 3,858 protein groups, averaging [~]1,300 proteins per cell, enabling robust proteome-level classification of cardiomyocyte subtypes. Using a reference-based protein classifier, cells were stratified into mature cardiomyocytes and less differentiated cell states, revealing substantial baseline heterogeneity. Importantly, increased single-cell sensitivity translated directly into biological insight, as approximately 30% of differentially expressed proteins associated with subtype-specific drug responses were detected exclusively by timsUltra AIP. Application of this workflow to PR-364 (a mitophagy boosting drug) dose-response experiment uncovered distinct, subtype-dependent pathway adaptations. Mature cardiomyocytes exhibited dose-dependent increases in mitochondrial and metabolic pathway activity, while immature cells showed enrichment of cytoskeletal and developmental programs. These effects were partially obscured in simulated bulk analyses, highlighting the value of single-cell resolution. Together, these results demonstrate that improved fragment ion transmission and utilization translate directly into enhanced biological insight, enabling more comprehensive and functionally relevant single-cell proteomics.

molecular biology↗

Metabolic STAMP for deciphering GPCR-regulated insulin secretion by pancreatic β cells

Pancreatic islet {beta} cells integrate glucose and hormonal cues to control insulin secretion through spatially and temporally organized phosphorylation networks in health and diabetes. Here, using Metabolic STAMP (Synchronized Temporal-Spatial Analysis via Microscopy and Phosphoproteomics), we combine time-resolved phosphoproteomics, imaging, and kinase inhibition in mouse {beta} cells and human islets to map stimulus-specific GPCR signaling pathways. Metabolic STAMP reveals that GLP1-R and FFAR4 engage distinct, compartmentalized kinase programs, including GLP1-R-biased ERK activation, receptor-specific cAMP-PKA domains, and a phospho-ATAT1/HDAC6 node that differentially modulates microtubule acetylation and insulin secretion during GSIS based on stimulation conditions. These GPCR-responsive phospho-signatures and microtubule remodeling patterns are substantially conserved in human islets. Together, our data define an integrated, compartmentalized signaling architecture linking metabolic GPCR inputs, organelle remodeling, and insulin secretion, and provide a {beta}-cell phosphoproteomic resource that connects dynamic signaling nodes to human genetic risk and potential therapeutic targets.

physiology↗