Nature Search

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes

Wigger, Barovic and Brunner et al. perform a multidimensional analysis of islets from metabolically characterized patients who had undergone pancreatectomy, observing remarkable heterogeneity between samples from individuals with type 2 diabetes, thus arguing against models of linear beta-cell dedifferentiation in diabetes.

Leonore Wigger
Marko Barovic
Michele Solimena
Research28 Jun 2021
Nature Metabolism

Volume: 3, P: 1017-1031
Deep learning the collisional cross sections of the peptide universe from a million experimental values

Proteomics has been advanced by algorithms that can predict different peptide features, but predicting peptide collisional cross sections (CCS) has remained challenging. Here, the authors measure over one million CCS values of tryptic peptides and develop a deep learning model for peptide CCS prediction.

Florian Meier
Niklas D. Köhler
Matthias Mann
ResearchOpen Access19 Feb 2021
Nature Communications

Volume: 12, P: 1-12
Reply to “Quality control requirements for the correct annotation of lipidomics data”

Catherine G. Vasilopoulou
Karolina Sulek
Florian Meier
ResearchOpen Access06 Aug 2021
Nature Communications

Volume: 12, P: 1-4
Site-specific ubiquitylation and SUMOylation using genetic-code expansion and sortase

A method combining genetic-code expansion, bioorthogonal Staudinger reduction and sortase-mediated transpeptidation enables site-specific and orthogonal modification of proteins with ubiquitin and SUMO in vitro and in living cells.

Maximilian Fottner
Andreas-David Brunner
Kathrin Lang
Research15 Feb 2019
Nature Chemical Biology

Volume: 15, P: 276-284
Deep Visual Proteomics defines single-cell identity and heterogeneity

Deep Visual Proteomics combines machine learning, automated image analysis and single-cell proteomics.

Andreas Mund
Fabian Coscia
Matthias Mann
ResearchOpen Access19 May 2022
Nature Biotechnology

Volume: 40, P: 1231-1240
The social and structural architecture of the yeast protein interactome

A protein interaction network constructed with data from high-throughput affinity enrichment coupled to mass spectrometry provides a highly saturated yeast interactome with 31,004 interactions, including low-abundance complexes, membrane protein complexes and non-taggable protein complexes.

André C. Michaelis
Andreas-David Brunner
Matthias Mann
ResearchOpen Access15 Nov 2023
Nature

Volume: 624, P: 192-200
Trapped ion mobility spectrometry and PASEF enable in-depth lipidomics from minimal sample amounts

Trapped ion mobility (TIMS)-mass spectrometry with parallel accumulation-serial fragmentation (PASEF) facilitates high-sensitivity proteomics experiments. Here, the authors expand TIMS and PASEF to small molecules and demonstrate fast and comprehensive lipidomics of low biological sample amounts.

Catherine G. Vasilopoulou
Karolina Sulek
Florian Meier
ResearchOpen Access16 Jan 2020
Nature Communications

Volume: 11, P: 1-11
diaPASEF: parallel accumulation–serial fragmentation combined with data-independent acquisition

diaPASEF makes use of the correlation between the ion mobility and the m/z of peptides to trap and release precursor ions in a TIMS-TOF mass spectrometer for an almost complete sampling of the precursor ion beam with data-independent acquisition.

Florian Meier
Andreas-David Brunner
Matthias Mann
Research30 Nov 2020
Nature Methods

Volume: 17, P: 1229-1236
Cardiac myocyte miR-29 promotes pathological remodeling of the heart by activating Wnt signaling

MicroRNA-29 is known to reduce collagen production in fibroblasts thereby inhibiting fibrosis in various organs. Here, Sassi et al. show that miR-29 can also enhance fibrotic signalling and pathological hypertrophy of the heart through its action in cardiomyocytes.

Yassine Sassi
Petros Avramopoulos
Stefan Engelhardt
ResearchOpen Access20 Nov 2017
Nature Communications

Volume: 8, P: 1-11

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