Single Cell Proteomics by Data-Independent Acquisition To Study Embryonic Asymmetry in Xenopus laevis

Techniques that allow single cell analysis are gaining widespread attention, and most of these studies utilize genomics-based approaches. While nanofluidic technologies have enabled mass spectrometric analysis of single cells, these measurements have been limited to metabolomics and lipidomic studie...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2019-07, Vol.91 (14), p.8891-8899
Main Authors: Saha-Shah, Anumita, Esmaeili, Melody, Sidoli, Simone, Hwang, Hyojeong, Yang, Jing, Klein, Peter S, Garcia, Benjamin A
Format: Article
Language:English
Subjects:
Animals
Asymmetry
Chemistry
Collection
Cytoplasm
Data acquisition
Developmental biology
Developmental stages
Embryo, Nonmammalian - chemistry
Embryo, Nonmammalian - cytology
Embryos
Fluidics
Germplasm
Heterogeneity
Metabolomics
Nanofluids
Proteins
Proteomics
Proteomics - methods
Sample preparation
Single-Cell Analysis - methods
Skewed distributions
Spectrometry
Studies
Tandem Mass Spectrometry - methods
Xenopus laevis
Xenopus laevis - embryology
Xenopus Proteins - analysis
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Summary:Techniques that allow single cell analysis are gaining widespread attention, and most of these studies utilize genomics-based approaches. While nanofluidic technologies have enabled mass spectrometric analysis of single cells, these measurements have been limited to metabolomics and lipidomic studies. Single cell proteomics has the potential to improve our understanding of intercellular heterogeneity. However, this approach has faced challenges including limited sample availability, as well as a requirement of highly sensitive methods for sample collection, cleanup, and detection. We present a technique to overcome these limitations by combining a micropipette (pulled glass capillary) based sample collection strategy with offline sample preparation and nanoLC-MS/MS to analyze proteins through a bottom-up proteomic strategy. This study explores two types of proteomics data acquisition strategies namely data-dependent (DDA) and data-independent acquisition (DIA). Results from the study indicate DIA to be more sensitive enabling analysis of >1600 proteins from ∼130 μm Xenopus laevis embryonic cells containing
ISSN:0003-2700
1520-6882
1520-6882
DOI:10.1021/acs.analchem.9b00327