ArticleCell reports2017
A Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neurons.
Article in Cell reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
65 citing papers in PubMed, 1 synthesis or guideline pooled it, 126 citations in OpenAlex.
- Assessing sub-cellular resolution in spatial proteomics experiments.Current opinion in chemical biology · 2019Pooled it
- APEX2 and TurboID define unique subcellular proteomes.Scientific reports · 2025Article
- Proteomic aging signatures across mouse organs and life stages.The EMBO journal · 2025Article
- Article
- The role of the AP-1 adaptor complex in outgoing and incoming membrane traffic.The Journal of cell biology · 2024Article
- Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer.Aging and disease · 2024Review
- OCaR1 endows exocytic vesicles with autoregulatory competence by preventing uncontrolled Ca2+ release, exocytosis, and pancreatic tissue damage.The Journal of clinical investigation · 2024Article
- TransGCN: a semi-supervised graph convolution network-based framework to infer protein translocations in spatio-temporal proteomics.Briefings in bioinformatics · 2024Article
- SPIDER: constructing cell-type-specific protein-protein interaction networks.Bioinformatics advances · 2024Article
- Orthogonal Enzyme-Substrate Design Strategy for Discovery of Human Protein Palmitoyltransferase Substrates.Journal of the American Chemical Society · 2023Article
- Deep and fast label-free Dynamic Organellar Mapping.Nature communications · 2023Article
- Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling.Journal of proteome research · 2023Article
- Analysis of Yeast Peroxisomes via Spatial Proteomics.Methods in molecular biology (Clifton, N.J.) · 2023Article
- nuPRISM: Microfluidic Genome-Wide Phenotypic Screening Platform for Cellular Nuclei.ACS central science · 2022Article
- Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics.The annals of applied statistics · 2022Article
- Combinatorial and antagonistic effects of tubulin glutamylation and glycylation on katanin microtubule severing.Developmental cell · 2022Article
- Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE.Nature communications · 2022Article
- Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing.Proteomics · 2022Article
- Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics.Analytical chemistry · 2022Article
- SubCellBarCode: integrated workflow for robust spatial proteomics by mass spectrometry.Nature protocols · 2022Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
We previously developed a mass spectrometry-based method, dynamic organellar maps, for the determination of protein subcellular localization and identification of translocation events in comparative experiments. The use of metabolic labeling for quantification (stable isotope labeling by amino acids in cell culture [SILAC]) renders the method best suited to cells grown in culture. Here, we have adapted the workflow to both label-free quantification (LFQ) and chemical labeling/multiplexing strategies (tandem mass tagging [TMT]). Both methods are highly effective for the generation of organellar maps and capture of protein translocations. Furthermore, application of label-free organellar mapping to acutely isolated mouse primary neurons provided subcellular localization and copy-number information for over 8,000 proteins, allowing a detailed analysis of organellar organization. Our study extends the scope of dynamic organellar maps to any cell type or tissue and also to high-throughput screening.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.