Fig. 1: Development and benchmarking of SEC-MX. | Nature Communications

Fig. 1: Development and benchmarking of SEC-MX.

From: SEC-MX: an approach to systematically study the interplay between protein assembly states and phosphorylation

Fig. 1: Development and benchmarking of SEC-MX.The alternative text for this image may have been generated using AI.

A Overview of experimental pipeline used to establish SEC-MX and compare it to SEC-DIA. PPI stands for Protein-Protein Interactions. Created in BioRender. Jovanovic, M. (2024). [https://BioRender.com/ s07v514]77. B A full overlap mixing scheme was developed, in which each fraction is divided into two parts, and each half is measured in a different mix, keeping adjacent fractions together. Full details of the labeling and pooling scheme can be found in Supplementary Fig. 1. Created in BioRender. Jovanovic, M. (2024). [https://BioRender.com/ s07v514]77. C Table showing protein and peptide coverage and measurement time in SEC-DIA and SEC-MX. D Heatmap representation comparing signals in SEC-DIA and SEC-MX, averaged across replicates for 4749 proteins measured in both (each row represents a protein). Columns represent fractions. Signal is row-normalized from 0 to 1 so that the max elution peak per protein is represented in red. Rows in both heatmaps are arranged in the same order. E Elution traces and heatmap representation (subset from Fig. 1D) of the SEC elution of the CCT complex subunits (n = 8) in either SEC-DIA or SEC-MX. Traces are color-coded by subunit, as indicated to the right of the heatmaps. F Distribution of Pearson correlation coefficients between elution profiles in SEC-MX versus SEC-DIA per protein measured in both. 2947/4749 proteins have a correlation coefficient >0.5. G Parameters of the SECAT interaction networks based on SEC-DIA and SEC-MX data. H The overlap of interactions between SEC-DIA and SEC-MX, q-value < 0.05 in at least one condition and <0.1 in the other (see Methods section for details). The overlap is statistically significant (hypergeometric survival function, log10 (pValue) = -14,100, calculated over the background of all possible pairwise interactions of the proteins in the PPI network).

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