Extended Data Fig. 3: Assessing the impact of valence on condensate formation. | Nature Methods

Extended Data Fig. 3: Assessing the impact of valence on condensate formation.

From: Characterizing protein sequence determinants of nuclear condensates by high-throughput pooled imaging with CondenSeq

Extended Data Fig. 3: Assessing the impact of valence on condensate formation.The alt text for this image may have been generated using AI.

(A) Schematic of the experiment to test the effect of protein valence on condensate formation. The small sequence library is fused to GFP and four different oligomerization domains resulting in valence 1, 4, 6, or 24, then cells are imaged and barcodes are read out. (B) Fraction of cells that contain condensates for the small sequence library fused to GFP and each of the four different oligomerization domains. Each point represents one protein sequence. Black lines show the means. The increases in fcondensates as valence is increased are all statistically significant (valence = 1 vs 4: p = 0.002; 4 vs 6: p = 2×10−6; 6 vs 24: p = 6×10−10, two-sided paired t-test, after Bonferroni correction, medium test protein concentration bin). (C) Example images of cells (masked nuclei) expressing protein sequences (rows) fused to GFP and each oligomerization domain (columns). These example images are representative of the following numbers of cells for which we collected data in our defined concentration bins: 1933 (AAGCG, valence=1), 1629 (AAGCG, valence=4), 1040 (AAGCG, valence=6), 760 (AAGCG, valence=24), 1360 (TCGCC, valence=1), 1730 (TCGCC, valence=4), 1492 (TCGCC, valence=6), 1348 (TCGCC, valence=24), 2775 (AACCT, valence=1), 3722 (AACCT, valence=4), 3445 (AACCT, valence=6), 2238 (AACCT, valence=24), 629 (AAAGA, valence=1), 761 (AAAGA, valence=4), 736 (AAAGA, valence=6), 487 (AAAGA, valence=24). Scale bars denote 5 µm.

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