High-throughput profiling of sequence recognition by tyrosine kinases and SH2 domains using bacterial peptide display

  1. Allyson Li
  2. Rashmi Voleti
  3. Minhee Lee
  4. Dejan Gagoski
  5. Neel H Shah  Is a corresponding author
  1. Columbia University, United States

Abstract

Tyrosine kinases and SH2 (phosphotyrosine recognition) domains have binding specificities that depend on the amino acid sequence surrounding the target (phospho)tyrosine residue. Although the preferred recognition motifs of many kinases and SH2 domains are known, we lack a quantitative description of sequence specificity that could guide predictions about signaling pathways or be used to design sequences for biomedical applications. Here, we present a platform that combines genetically-encoded peptide libraries and deep sequencing to profile sequence recognition by tyrosine kinases and SH2 domains. We screened several tyrosine kinases against a million-peptide random library and used the resulting profiles to design high-activity sequences. We also screened several kinases against a library containing thousands of human proteome-derived peptides and their naturally-occurring variants. These screens recapitulated independently measured phosphorylation rates and revealed hundreds of phosphosite-proximal mutations that impact phosphosite recognition by tyrosine kinases. We extended this platform to the analysis of SH2 domains and showed that screens could predict relative binding affinities. Finally, we expanded our method to assess the impact of non-canonical and post-translationally modified amino acids on sequence recognition. This specificity profiling platform will shed new light on phosphotyrosine signaling and could readily be adapted to other protein modification/recognition domains.

Data availability

All of the processed data from the high-throughput specificity screens are provided as source data files. The raw fastq and fasta sequencing files are available as a Dryad repository (DOI: 10.5061/dryad.0zpc86727). Custom code used to process/analyze screening data can be found in a GitHub repository, as specified in the manuscript.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Allyson Li

    Department of Chemistry, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2359-7703
  2. Rashmi Voleti

    Department of Chemistry, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Minhee Lee

    Department of Chemistry, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Dejan Gagoski

    Department of Chemistry, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Neel H Shah

    Department of Chemistry, Columbia University, New York, United States
    For correspondence
    neel.shah@columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1186-0626

Funding

National Institute of General Medical Sciences (R35GM138014)

  • Neel H Shah

Damon Runyon Cancer Research Foundation (DFS 31-18)

  • Neel H Shah

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Tony Hunter, Salk Institute for Biological Studies, United States

Version history

  1. Preprint posted: August 1, 2022 (view preprint)
  2. Received: August 1, 2022
  3. Accepted: March 15, 2023
  4. Accepted Manuscript published: March 16, 2023 (version 1)
  5. Version of Record published: March 31, 2023 (version 2)

Copyright

© 2023, Li et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,798
    views
  • 224
    downloads
  • 5
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Allyson Li
  2. Rashmi Voleti
  3. Minhee Lee
  4. Dejan Gagoski
  5. Neel H Shah
(2023)
High-throughput profiling of sequence recognition by tyrosine kinases and SH2 domains using bacterial peptide display
eLife 12:e82345.
https://doi.org/10.7554/eLife.82345

Share this article

https://doi.org/10.7554/eLife.82345

Further reading

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Natalia Dolgova, Eva-Maria E Uhlemann ... Oleg Y Dmitriev
    Research Article

    Mediator of ERBB2-driven Cell Motility 1 (MEMO1) is an evolutionary conserved protein implicated in many biological processes; however, its primary molecular function remains unknown. Importantly, MEMO1 is overexpressed in many types of cancer and was shown to modulate breast cancer metastasis through altered cell motility. To better understand the function of MEMO1 in cancer cells, we analyzed genetic interactions of MEMO1 using gene essentiality data from 1028 cancer cell lines and found multiple iron-related genes exhibiting genetic relationships with MEMO1. We experimentally confirmed several interactions between MEMO1 and iron-related proteins in living cells, most notably, transferrin receptor 2 (TFR2), mitoferrin-2 (SLC25A28), and the global iron response regulator IRP1 (ACO1). These interactions indicate that cells with high MEMO1 expression levels are hypersensitive to the disruptions in iron distribution. Our data also indicate that MEMO1 is involved in ferroptosis and is linked to iron supply to mitochondria. We have found that purified MEMO1 binds iron with high affinity under redox conditions mimicking intracellular environment and solved MEMO1 structures in complex with iron and copper. Our work reveals that the iron coordination mode in MEMO1 is very similar to that of iron-containing extradiol dioxygenases, which also display a similar structural fold. We conclude that MEMO1 is an iron-binding protein that modulates iron homeostasis in cancer cells.

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Isabelle Petit-Hartlein, Annelise Vermot ... Franck Fieschi
    Research Article

    NADPH oxidases (NOX) are transmembrane proteins, widely spread in eukaryotes and prokaryotes, that produce reactive oxygen species (ROS). Eukaryotes use the ROS products for innate immune defense and signaling in critical (patho)physiological processes. Despite the recent structures of human NOX isoforms, the activation of electron transfer remains incompletely understood. SpNOX, a homolog from Streptococcus pneumoniae, can serves as a robust model for exploring electron transfers in the NOX family thanks to its constitutive activity. Crystal structures of SpNOX full-length and dehydrogenase (DH) domain constructs are revealed here. The isolated DH domain acts as a flavin reductase, and both constructs use either NADPH or NADH as substrate. Our findings suggest that hydride transfer from NAD(P)H to FAD is the rate-limiting step in electron transfer. We identify significance of F397 in nicotinamide access to flavin isoalloxazine and confirm flavin binding contributions from both DH and Transmembrane (TM) domains. Comparison with related enzymes suggests that distal access to heme may influence the final electron acceptor, while the relative position of DH and TM does not necessarily correlate with activity, contrary to previous suggestions. It rather suggests requirement of an internal rearrangement, within the DH domain, to switch from a resting to an active state. Thus, SpNOX appears to be a good model of active NOX2, which allows us to propose an explanation for NOX2’s requirement for activation.