Mutagenesis-Visualization: Analysis of Site-Saturation Mutagenesis Datasets in Python

Hidalgo, Frank; Templeton, Sage; Gallegos, Che Olavarria; Wang, Joanne

doi:10.1101/2021.10.08.463725

Cited by 2 publications

(2 citation statements)

References 36 publications

(34 reference statements)

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“…Data processing, statistical analysis, and visualization were conducted using "mutagenesis-visualization", an open-source Python package that can analyze saturation-mutagenesis datasets (Hidalgo et al, 2021). The documentation can be found at readthedocs, the source code on GitHub ("fhidalgor/mutagenesis_visualization"), and the software can be used without previous Python knowledge.…”

Section: Calculation Of Enrichment Scores Using Mutagenesis-visualiza...mentioning

confidence: 99%

“…The absence of correlation between the enrichment values of wild-type alleles in replicates rules out the possibility that a wild-type DNA sequences is more enriched than another wild-type sequence due to expression level differences. This topic is covered in the documentation of mutagenesis-visualization (Hidalgo et al, 2021).…”

Section: Calculation Of Enrichment Scores Using Mutagenesis-visualiza...mentioning

confidence: 99%

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A saturation-mutagenesis analysis of the interplay between stability and activation in Ras

Hidalgo

Nocka

Shah

et al. 2022

eLife

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Cancer mutations in Ras occur predominantly at three hotspots: Gly 12, Gly 13, and Gln 61. Previously, we reported that deep mutagenesis of H-Ras using a bacterial assay identified many other activating mutations (Bandaru et al., 2017). We now show that the results of saturation mutagenesis of H-Ras in mammalian Ba/F3 cells correlate well with the results of bacterial experiments in which H-Ras or K-Ras are co-expressed with a GTPase-activating protein (GAP). The prominent cancer hotspots are not dominant in the Ba/F3 data. We used the bacterial system to mutagenize Ras constructs of different stabilities and discovered a feature that distinguishes the cancer hotspots. While mutations at the cancer hotspots activate Ras regardless of construct stability, mutations at lower-frequency sites (e.g. at Val 14 or Asp 119) can be activating or deleterious, depending on the stability of the Ras construct. We characterized the dynamics of three non-hotspot activating Ras mutants by using NMR to monitor hydrogen-deuterium exchange (HDX). These mutations result in global increases in HDX rates, consistent with destabilization of Ras. An explanation for these observations is that mutations that destabilize Ras increase nucleotide dissociation rates, enabling activation by spontaneous nucleotide exchange. A further stability decrease can lead to insufficient levels of folded Ras – and subsequent loss of function. In contrast, the cancer hotspot mutations are mechanism-based activators of Ras that interfere directly with the action of GAPs. Our results demonstrate the importance of GAP surveillance and protein stability in determining the sensitivity of Ras to mutational activation.

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Section: Calculation Of Enrichment Scores Using Mutagenesis-visualiza...mentioning

confidence: 99%

Section: Calculation Of Enrichment Scores Using Mutagenesis-visualiza...mentioning

confidence: 99%

A saturation-mutagenesis analysis of the interplay between stability and activation in Ras

Hidalgo

Nocka

Shah

et al. 2022

eLife

Self Cite

View full text Add to dashboard Cite

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A Saturation-Mutagenesis Analysis of the Interplay Between Stability and Activation in Ras

Hidalgo

Nocka

Shah

et al. 2022

Preprint

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Cancer mutations in Ras occur predominantly at three hotspots: Gly 12, Gly 13, and Gln 61. Previously, we reported that deep mutagenesis of H?Ras using a bacterial assay identified many other activating mutations (Bandaru et al., 2017). We now show that the results of saturation mutagenesis of H?Ras in mammalian Ba/F3 cells correlate well with results of bacterial experiments in which H-Ras or K-Ras are co-expressed with a GTPase?activating protein (GAP). The prominent cancer hotspots are not dominant in the Ba/F3 data. We used the bacterial system to mutagenize Ras constructs of different stabilities and discovered a feature that distinguishes the cancer hotspots. While mutations at the cancer hotspots activate Ras regardless of construct stability, mutations at lower-frequency sites (e.g., at Val 14 or Asp 119) can be activating or deleterious, depending on the stability of the Ras construct. We characterized the dynamics of three non-hotspot activating Ras mutants by using NMR to monitor hydrogen?deuterium exchange (HDX). These mutations result in global increases in HDX rates, consistent with the destabilization of Ras. An explanation for these observations is that mutations that destabilize Ras increase nucleotide dissociation rates, enabling activation by spontaneous nucleotide exchange. A further stability decrease can lead to insufficient levels of folded Ras – and subsequent loss of function. In contrast, the cancer hotspot mutations are mechanism-based activators of Ras that interfere directly with the action of GAPs. Our results demonstrate the importance of GAP surveillance and protein stability in determining the sensitivity of Ras to mutational activation.

show abstract

Mutagenesis-Visualization: Analysis of Site-Saturation Mutagenesis Datasets in Python

Cited by 2 publications

References 36 publications

A saturation-mutagenesis analysis of the interplay between stability and activation in Ras

A saturation-mutagenesis analysis of the interplay between stability and activation in Ras

A Saturation-Mutagenesis Analysis of the Interplay Between Stability and Activation in Ras

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