Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition

Abstract

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

Keywords: Embryo; Low-input proteomics; Maternal-to-zygotic transition; Oocyte; Single-cell proteomics.

Graphical abstract

Fig. 1

A comprehensive solution of ultrasensitive proteome technology (CS-UPT) for single-cell or low-input mouse embryo samples. The top is the deep coverage strategy, prepared in tubes without labeling. The bottom is the high-throughput strategy, prepared in 384-well plates with tandem mass tags (TMT) labeling. ABC: ammonium bicarbonate; LC-MS/MS: liquid chromatography tandem mass spectrometry.

Fig. 2

Data-independent acquisition (DIA)-based low-input proteomics improves zygote (Zyg) proteome depth while significantly reducing starting material. (A) Number of protein groups identified from mouse zygotes of various numbers. Each group had two independent replicates (10 runs); data in the plot are presented as mean ± standard deviation (SD). Curve Fitting was performed with R (V4.2.2). (B) Proportion of co-identified proteins between the two replicates in each group. (C) Correlation of protein expression among 10 mass spectrometry (MS) runs of mouse zygotes. There were five groups with different numbers of zygotes and two replicates in each group. Pearson's correlation coefficients were presented numerically and color-coded. (D) Comparison of the number of commonly identified proteins and uniquely identified proteins between different numbers of zygotes. Unique proteins were defined as being only identified in one group and not identified in all other groups. (E) Intensity distribution of 471 unique proteins identified in 20 mouse zygotes. (F) Intensity distribution of 2,273 proteins co-identified in five groups with different zygote numbers. (G) Doughnut chart displays the distribution of top 10 subcellular compartments for identified proteins in each group based on enrichment analysis of Gene Ontology (GO) cellular component terms.

Fig. 3

High-throughput proteomic profiling of mouse zygotes by single-cell proteomics. (A) Workflow for characterizing the mouse zygote proteome by high-throughput single-cell proteomics with the carrier channel. (B) Channel design for TMT6plex single-cell proteomics. Each TMT6plex experiment included one blank channel (0 zygote), one carrier channel (50 or 100 oocytes), and four single-cell channels (1 zygote for each). (C) Comparison of the number of protein groups identified by multiplexed single-cell proteomics with TMT6plex-50× carrier, TMT6plex-100× carrier, and TMT8plex. Data in the plot are presented as mean ± standard deviation. (D) Intensity distribution of all proteins in each TMT channel. Each different carrier TMT6plex experiment had two replicates. Boxplots show the median (middle bar), 25th and 75th percentiles (box), and 1.5× interquartile range (whiskers). (E) Boxplots of measuring ratios of protein groups based on tandem mass tags (TMT) intensities between different single-cell channels in each TMT6plex experiment. The denominator is the quantitative mean of 16 single-cell channels in four TMT experiments. Boxplots show the median (middle bar), 25th and 75th percentiles (box), and 1.5× interquartile range (whiskers). (F) Comparison of Pearson's correlation coefficients between each run (or single-cell channel) of data-independent acquisition (DIA) low-input proteomics, TMT6plex-50× carrier, TMT6plex-100× carrier, and TMT8plex single-cell proteomics. Boxplots show the median (middle bar), 25th and 75th percentiles (box), and 1.5× interquartile range (whiskers). (G) Venn diagram shows the overlap between DIA low-input proteomics, TMT6plex, and TMT8plex single-cell proteomics identified proteins from single mouse zygotes. LC-MS/MS: liquid chromatography tandem mass spectrometry.

Fig. 4

Proteomics analysis of very early stage of mouse maternal-to-zygotic transition by ultrasensitive proteomics. (A) Protein groups identified in each sample. (B) Data distribution after normalization for each sample. (C) Comparison of protein groups identified in this experiment and Wang et al. [35]. (D) Venn diagram of protein species in metaphase II (MII) oocytes and 1-cell embryos. (E) Heatmap and biological processes annotation of differentially expressed proteins. (F) Differentially expressed kinases and transcription factors (TFs) identified in this experiment. (G) Differentially expressed protein interaction network dominated by kinases and TFs containing major molecular complexes formed by their respective upregulated proteins; colored areas are molecular complexes detected by Molecular COmplex DEtection (MCODE); corresponding boxes are functional annotations. mRNA: messenger RNA; PI3K: phosphatidylinositol-4,5-bisphosphate 3-kinase; Akt: protein kinase B; FC: fold change.