Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo

Abstract

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design efficient remedies for diseases. Technologies enabling accurate identification and quantification of diverse types and large numbers of proteins would provide still missing information on molecular mechanisms orchestrating tissue and organism development in space and time. Here, we present a mass spectrometry-based protocol that enables the measurement of thousands of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The approach builds on reproducible cell-fate maps and established methods to identify, fluorescently label, track, and sample cells and their progeny (clones) from this model of vertebrate development. After collecting cellular contents using microsampling or isolating cells by dissection or fluorescence-activated cell sorting, proteins are extracted and processed for bottom-up proteomic analysis. Liquid chromatography and capillary electrophoresis are used to provide scalable separation for protein detection and quantification with high-resolution mass spectrometry (HRMS). Representative examples are provided for the proteomic characterization of neural-tissue fated cells. Cell-lineage-guided HRMS proteomics is adaptable to different tissues and organisms. It is sufficiently sensitive, specific, and quantitative to peer into the spatio-temporal dynamics of the proteome during vertebrate development.

Figure 1:. Spatiotemporally scalable proteomics enabling cell-lineage guided HRMS proteomics in the developing (frog) embryo.

(A) Visualization of the specimen (1) using a stereomicroscope (2) for injection of an identified cell (inset), using a micropipette (3) under control by a translation-stage (4). (B) Subcellular sampling of the identified left D₁₁ cell in a 16-cell embryo. (C) Dissection of a whole D₁₁ cell from a 16-cell embryo. (D) Fluorescent (green) tracing of the left and right D₁₁₁ progenies from a 32-cell embryo to guide dissection of the neural ectoderm (NE) in the gastrula (stage 10) and isolation of the descendent tissue from the tadpole using FACS. Scale bars: 200 μm for embryos, 1.25 mm forthe vial. Figures were adapted with permission from references^,,,.

Figure 2:. The bioanalytical workflow.

Micro-dissection and capillary aspiration, or FACS facilitated sampling of cellular and clonal protein content. Depletion of abundant yolk proteins and separation by capillary electrophoresis (CE) or nano-flow liquid chromatography (LC) enhanced detection sensitivity using electrospray ionization (ESI) high-resolution mass spectrometry (HRMS). Quantification revealed dysregulation, supplying new information for hypothesis-driven studies. Figures were adapted with permission from references.

Figure 3:. Protocol scalability from the subcellular space to clonal tissues in X. laevis embryo.

(A) Measurement of proteomic differences between identified whole D₁₁ cells, revealing cell-cell heterogeneity. Gene names shown for select proteins. (B) Reorganization of the cellular proteome in the developing D11 cell clone. Fuzzy C-means cluster analysis (GProx) of quantitative protein dynamics, grouping proteins based on similar expression patterns. Gray numbers show the number of different proteins that were quantified in each cluster. Figures were adapted with permission from references^,.

Figure 4:. Example of data analysis from spatial tissue proteomics in the X. laevis embryos.

(A) Differential labeling of the Spemann’s Organizer (SO) and the neural ectoderm (NE) tissues by injection of fluorescent protein mRNA in the predecessor D₁₁₂ and D₂₁₂ in the 32-cell embryo, respectively. (B) Top 5 overrepresented biological processes in the SO (red) and NE (green) proteome showing detectable differences. Pathway overrepresentation analysis shows biological processes using Bonferroni correction. (C) Protein domain enrichment analysis (SMART), revealing enrichment of DNA and RNA binding motif-containing proteins in the SO. (D) STRING analysis predicting canonical protein-protein interactions based on the detected SO proteome.