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Related Experiment Video

Updated: Feb 6, 2026

Visualization and Quantitative Analysis of Embryonic Angiogenesis in Xenopus tropicalis

Visualization and Quantitative Analysis of Embryonic Angiogenesis in Xenopus tropicalis

Published on: May 25, 2017

Quantitative Proteomics for Xenopus Embryos II, Data Analysis.

Matthew Sonnett¹, Meera Gupta^1,2, Thao Nguyen^1,2

¹Department of Molecular Biology and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.

Methods in Molecular Biology (Clifton, N.J.)

|August 29, 2018

Summary

This summary is machine-generated.

This study details the proteomic analysis of Xenopus laevis development, transforming mass spectrometry data into protein expression dynamics for thousands of proteins using the MaxQuant pipeline.

Keywords:

Development False discovery rate Gene symbols Gene-set enrichment Mass spectrum MaxQuant Quantitative multiplexed proteomics TMT Xenopus laevis k-means clustering

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Last Updated: Feb 6, 2026

Visualization and Quantitative Analysis of Embryonic Angiogenesis in Xenopus tropicalis

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Optimized Analysis of Proteins from Xenopus Oocytes and Embryos by Immunoblotting

Optimized Analysis of Proteins from Xenopus Oocytes and Embryos by Immunoblotting

Published on: September 19, 2025

Area of Science:

Developmental Biology
Proteomics
Biochemistry

Background:

Xenopus laevis oocytes, embryos, and lysates are valuable models for quantitative proteomic studies.
Previous work (Chapter 13) established methods for sample preparation and data acquisition.

Purpose of the Study:

To outline the process of converting mass spectrometry data into protein expression dynamics.
To analyze a developmental time series from egg to stage 35 in Xenopus laevis.
To demonstrate data interpretation techniques for large proteomic datasets.

Main Methods:

Utilized a 10-stage developmental time series of Xenopus laevis.
Processed approximately 700,000 mass spectra using the MaxQuant proteomics pipeline.
Performed quality control, error rate control for peptide and protein identification, and quantification.

Main Results:

Successfully converted mass spectra into protein expression dynamics for approximately 9000 proteins.
Established a robust workflow for quantitative proteomic analysis in Xenopus.
Identified potential errors during sample preparation through quality control.

Conclusions:

The MaxQuant pipeline is effective for analyzing large-scale Xenopus proteomic data.
The developed methods enable the study of protein expression dynamics during development.
Clustering and gene-set enrichment analysis are useful for interpreting complex proteomic datasets.