Matthias Mann

This study uses Aggregate Deep Visual Proteomics to show that α-synuclein inclusions selectively concentrate specific proteins in neurons, revealing their formation mechanisms and potential therapeutic targets.

The paper introduces the ZenoTOF 8600 system, which enhances proteomics by increasing ion flux and improving precursor identification and quantification in DIA mode.

FastaLake constructs compact metaproteomic databases from sequence resources to improve peptide identification without requiring matched metagenomic sequencing.

The paper develops a proteomic aging clock using longitudinal plasma proteomics data to show that biological aging is dynamically influenced by modifiable risk factors.

The paper identifies a conserved viral protein module that displaces host RNA polymerase sigma factors to control transcription in mycobacteria.

The paper introduces pSPEC, a reproducible proteomic sample preparation method for biofluids that increases protein identification by ~20% compared to in-solution plasma.

The paper identifies resilience factors in aged mice using a genome-scale ORF screen, finding NKX2-5 variants that restore vision and reduce frailty.

AlphaPeptTools provides a scverse-native Python package for analyzing MS-based proteomics data, enabling scalable analysis and integration with other modalities.

The paper quantifies proteins and transcripts in the same cell, finding that the proteome defines stable cell states while the transcriptome reflects transitions.

A >50,000-element viral smORF library screened by growth, MHC-I, ER stress, Perturb-seq and mass spectrometry yields >2,000 active microproteins and shows EBV BNLF2b inhibits PKA by mimicry.

This study uses Deep Visual Proteomics to analyze VSMC phenotypes in atherosclerotic plaques, finding spatially distinct phenotype distributions and a shift toward dedifferentiated states in unstable plaques.

The paper develops a machine learning model to detect pOXA-48-carrying Enterobacterales using MALDI-TOF MS spectra, achieving high accuracy across different cohorts.

The paper demonstrates a method to simultaneously measure genome and proteome from the same cells in archival FFPE tissue, applied to melanoma.

HIP-MS is an automated platform for high-throughput interactome profiling that improves sensitivity and throughput compared to traditional AE-MS methods.

This paper shows that loss of IFNAR1 in neurons and astrocytes disrupts brain energy metabolism and leads to Parkinsonian dementia-like features in mice.

The paper constructs a cell type-resolved proteomic atlas of the human body using Deep Visual Proteomics, revealing protein abundance patterns and uncovering cancer-testis antigens in oocytes.

This study develops a de novo insulin receptor agonist, RF-409, which effectively treats severe insulin resistance in a mouse model by activating a mutant receptor and improving glucose homeostasis.

The paper identifies LRRC58 as a cysteine-responsive E3 ligase that regulates CDO1 stability via ubiquitylation, revealing a mechanism linking cysteine availability to proteasomal turnover.

The paper systematically assesses the function of short linear motifs (SLiMs) by mutating and screening them in human cells, identifying essential SLiMs for cell proliferation and uncovering novel classes and binding partners.

The paper shows NLRP3 activators disrupt the AP2 complex and impair plasma membrane signaling, leading to inflammation and cell death.

This study uses single-cell spatial proteomics to map human liver zonation patterns and shows their disruption in fibrosis.

This study uses multi-platform plasma proteomics to identify metabolic signatures distinguishing elite athletes' acute and chronic exercise adaptations.

The paper identifies urinary protein signatures linked to LRRK2 dysfunction in Parkinson's disease using multi-cohort proteomics and machine learning, showing cross-species relevance and potential as pharmacodynamic markers.

The paper introduces QuantSelect, a deep learning method for fragment ion selection in DIA proteomics, improving quantification accuracy and differential expression sensitivity.

The paper develops an in vitro model of human subcutaneous adipocyte spheroids to study mitochondrial dysfunction and test mitochondria-activating compounds in obesity.

This study presents a spatiotemporal multi-omics analysis of aging neuromuscular junctions in mice, identifying genes with decoupled transcript and protein trajectories and highlighting post-transcriptional regulation in NMJ aging.

This study identifies the MCUR1-CCDC90B complex as a mitochondrial scaffold regulating metabolic homeostasis, showing its role in amino acid metabolism and linking its deficiency to neurometabolic disease.

This study investigates how kinase inhibitors reshape the immunopeptidome in CML by altering HLA-I peptide presentation through three molecular mechanisms.

This paper introduces a multimodal AI agent that captures and shares lab practice by integrating video, speech, and text analysis to improve reproducibility in proteomics.

This study investigates how the LRRK2-N2081D variant increases Crohn's disease risk by showing it causes more severe colitis and distinct RAB substrate phosphorylation compared to LRRK2-G2019S.