DeBias

Abstract: Analysis of coupled variables is a core concept of cell biological inference, with co-localization of two molecules as a proxy for protein interaction being a ubiquitous example. However, external effectors may influence the observed co-localization independently from the local interaction of two proteins. Such global bias, although biologically meaningful, is often neglected when interpreting co-localization. Here, we describe DeBias, a computational method to quantify and decouple global bias from local interactions between variables by modeling the observed co-localization as the cumulative contribution of a global and a local component (Figure 1). We showcase five applications of DeBias in different areas of cell biology, and demonstrate that the global bias encapsulates fundamental mechanistic insight into cellular behavior. The DeBias software package is freely accessible online via a web-server.

Paper: https://elifesciences.org/articles/22323

Source code: https://github.com/assafzar/DeBias

Web-service: https://debias.biohpc.swmed.edu/

Transcript

1. Assaf Zaritsky Decoupling global biases and local interactions between cell biological variables
2. Quantifying protein-protein co-localization Dunn et al. (2011) Red Green Merge Condition B Condition A
3. What additional information is hidden in co-localization data?
4. Co-orientation of intracellular cytoskeletal networks in migrating cells
5. Vimentin provides a structural template for microtubule growth Gan, Ding and Burckhardt et al. (2016) Genome-edited Retinal Pigment Epithelial (RPE) cells
6. A relation between cell polarity and vimentin-microtubule interaction? Zhuo Gan
7. Polarity-independent interaction of vimentin and microtubules ?
8. Polarity-independent interaction of vimentin and microtubules
9. What do we want to achieve? • Simultaneous investigation of mechanisms that drive global bias and local interactions How? • By modeling the observed agreement between matched variables as the cumulative global and local components Observed colocalization = Global bias + Local interaction
10. DeBias
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15. DeBias
16. Polarity-independent interaction of vimentin and microtubules
17. Polarity-independent interaction of vimentin and microtubules Global index Local index
18. Global bias: cell polarity
19. Inferring co-localization and predicting dynamics from fixed cells during clathrin-mediated endocytosis (CME)
20. Maturation of a clathrin coated pit Marcel Mettlen
21. Cross-talk between signaling receptors (AKT) and components of the endocytic machinery Carlos Reis, H1299 cells
22. Inferring co-localization and predicting dynamics from fixed cells during clathrin-mediated endocytosis (CME) Global index Local index
23. Global bias: reduced TfnR in CCPs upon Akt inhibition
24. More CCPs containing less TfnR alter CCPs dynamics upon AKT inhibition Reduced TfnR in CCPs upon Akt inhibition increased short-lived, (most likely) abortive events  decrease in CME efficiency Live imaging Internalization Fixed imaging
25. Global bias: more CCPs with less TfnR upon Akt inhibition
26. Spatio-temporal co-localization of Rac1 and Vav1 activity in a migrating cell (With Dan Marston, UNC)
27. Resources Webserver: https://debias.biohpc.swmed.edu/ Source code: https://github.com/DanuserLab/DeBias https://elifesciences.org/content/6/e22323
28. Take home message DeBias enables identifying the gorilla Simons and Chabris (1999)
29. Uri Obolski, (Theory) Carlos Reis (Endocytosis) Zhuo Gan, (Vimentin, PKC) Yi Du (Webserver) Gaudenz Danuser Liya Ding Liqiang Wang Tamal Das Joachim Spatz Christoph Burckhardt Acknowledgments Sandy Schmid
30. Thank you! https://elifesciences.org/content/6/e22323