De novo design of modular and tunable allosteric biosensors

  1. Alfredo Quijano-Rubio
  2. Hsien-Wei Yeh
  3. Jooyoung Park
  4. Hansol Lee
  5. Robert A. Langan
  6. Scott E. Boyken
  7. Marc J. Lajoie
  8. Longxing Cao
  9. Cameron M. Chow
  10. Marcos C. Miranda
  11. Jimin Wi
  12. Hyo Jeong Hong
  13. Lance Stewart
  14. Byung-Ha Oh
  15. David Baker

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Abstract

Naturally occurring allosteric protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications 1 , but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of allosteric protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest 2 . Using broadly applicable design principles, we allosterically couple binding of protein analytes of interest to the reconstitution of luciferase activity and a bioluminescent readout through the association of designed lock and key proteins. Because the sensor is based purely on thermodynamic coupling of analyte binding to switch activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the hIgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-19 3 , we use the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder, has a limit of detection of 15pM with an up to seventeen fold increase in luminescence upon addition of RBD. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.18.206946: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Bioluminescence was measured with the designed lucCages (20 nM) and lucKey (20 nM) in the presence or absence of the anti-HVB antibody HzKR127-3.2 (100 nM) to select lucCageHBV.
    anti-HVB
    suggested: None
    All designs at 50nM were mixed with 50nM lucKey and experimentally screened for an increase in luminescence in the presence of rabbit anti-SARS-CoV Membrane polyclonal antibodies (ProSci, Cat. No.: 3527) at 100nM or mouse anti-SARS-CoV Nucleocapsid monoclonal antibody (clone 18F629.1, NovusBio Cat. No. NBP2-24745) at 100 nM.
    anti-SARS-CoV
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The vector was introduced into HEK 293T cells using Lipofectamine (Invitrogen), and the cells were grown in FreeStyle 293 (GIBCO) in 5% CO2 in a 37 °C humidified incubator.
    HEK 293T
    suggested: None
    Software and Algorithms
    SentencesResources
    The protein was purified using HisPurTM nickel resin (Thermo), a HiTrap Q anion exchange column (GE Healthcare) and a HiLoad 26/60 Superdex 75 gel filtration column (GE Healthcare).
    Thermo
    suggested: (Thermo Xcalibur, RRID:SCR_014593)
    The model building and structure refinement were performed by using COOT 45 and PHENIX.
    COOT
    suggested: (Coot, RRID:SCR_014222)
    PHENIX
    suggested: (Phenix, RRID:SCR_014224)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.07.18.206946v1 on bioRxiv