ArticleMolecular & cellular proteomics : MCP2026
In-Cell Proteomics Enables High-Resolution Spatial and Temporal Mapping of Early Xenopus tropicalis Embryos.
Article in Molecular & cellular proteomics : MCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Perilipin 2 drives cisplatin-induced acute kidney injury in young but not aged kidneys.American journal of physiology. Renal physiology · 2026Article
- Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy.Plant physiology · 2026Article
- Radiomics: Current Applications and Future Directions.MedComm · 2026Review
- Mapping the interactome of human tRNA methyltransferase TRMT1 using dual proximity labeling.bioRxiv : the preprint server for biology · 2026Article
- In-Cell Proteomics Enables High-Resolution Temporal Profiling of Cell Cycle Progression and DNA Damage Response in Saccharomyces cerevisiae.Proteomics · 2026Article
- Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
- Update of
Authors and funding
4 authors.
Funding
Abstract
Early embryonic development requires tightly regulated molecular programs to coordinate cell division, fate specification, and spatial patterning. While transcriptomic profiling has been widely performed, proteomic analyses of early vertebrate embryos remain limited owing to technical challenges in embryonic sample preparation. Here, we present an "in-cell proteomics" strategy, which bypasses cell lysis and yolk depletion, processes individual embryos directly in functionalized filter devices, and generates mass spectrometry (MS)-friendly samples in an extremely robust and streamlined manner. This single-vessel approach minimizes sample loss and technical variation, offering a highly sensitive and accurate alternative to low-input and low-cell quantitative proteomics. Coupled with field asymmetric ion mobility spectrometry and single-shot data-independent acquisition MS workflow, this approach enabled us to consistently quantify ∼6200 proteins from a single Xenopus tropicalis embryo, representing the deepest proteomic coverage of early X. tropicalis developmental stages reported to date. Investigation of the temporal proteomes across five cleavage stages (from 1- to 16-cell stages) revealed a drastic proteomic shift between 2- and 4-cell stages, followed by more gradual transitions thereafter. Spatial analysis of dissected 8-cell blastomeres uncovered pronounced molecular asymmetry along the animal-vegetal axis, whereas dorsal-ventral differences were minimal. This study establishes a novel in-cell proteomics technology in conjunction with field asymmetric ion mobility spectrometry and data-independent acquisition MS as a robust platform for high-resolution, low-input developmental proteomics analysis and provides a comprehensive spatiotemporal protein atlas for early X. tropicalis embryos.
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.