Fluorescence-detection size-exclusion chromatography utilizing nanobody technology for expression screening of membrane proteins

  1. Fei Jin
  2. Yao Wang
  3. Mengqi Wang
  4. Minxuan Sun
  5. Motoyuki Hattori

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Abstract

Membrane proteins play numerous physiological roles and are thus of tremendous interest in pharmacology. Nevertheless, stable and homogeneous sample preparation is one of the bottlenecks in biophysical and pharmacological studies of membrane proteins because membrane proteins are typically unstable and poorly expressed. To overcome such obstacles, GFP fusion-based Fluorescence-detection Size-Exclusion Chromatography (FSEC) has been widely employed for membrane protein expression screening for over a decade. However, fused GFP itself may occasionally affect the expression and/or stability of the targeted membrane protein, leading to both false-positive and false-negative results in expression screening. Furthermore, GFP fusion technology is not well suited for some membrane proteins depending on their membrane topology. Here, we developed an FSEC assay utilizing nanobody (Nb) technology, named FSEC-Nb, in which targeted membrane proteins are fused to a small peptide tag and recombinantly expressed. The whole-cell extracts are solubilized, mixed with anti-peptide Nb fused to GFP and applied to a size-exclusion chromatography column attached to a fluorescence detector for FSEC analysis. FSEC-Nb enables one to evaluate the expression, monodispersity and thermostability of membrane proteins without the need of purification by utilizing the benefits of the GFP fusion-based FSEC method, but does not require direct GFP fusion to targeted proteins. We applied FSEC-Nb to screen zinc-activated ion channel (ZAC) family proteins in the Cys-loop superfamily and membrane proteins from SARS-CoV-2 as examples of the practical application of FSEC-Nb. We successfully identified a ZAC ortholog with high monodispersity but moderate expression levels that could not be identified with the previously developed GFP fusion-free FSEC method. Consistent with the results of FSEC-Nb screening, the purified ZAC ortholog showed monodispersed particles by both negative staining EM and cryo-EM. Furthermore, we identified two membrane proteins from SARS-CoV-2 with high monodispersity and expression level by FSEC-Nb, which may facilitate structural and functional studies of SARS-CoV-2. Overall, our results show FSEC-Nb as a powerful tool for membrane protein expression screening that can provide further opportunity to prepare well-behaved membrane proteins for structural and functional studies.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.28.316307: (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

    Experimental Models: Cell Lines
    SentencesResources
    Thermostability assay by FSEC-Nb: ALFA peptide-tagged hP2X3 was expressed in HEK293 cells and solubilized as described above.
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Detergent screening by FSEC-Nb: HEK293S cells expressing ALFA-tagged OlZAC were prepared as described above.
    HEK293S
    suggested: RRID:CVCL_A784)
    Software and Algorithms
    SentencesResources
    The micrographs were processed in RELION 3.0 for particle picking, extraction and 2D classification70.
    RELION
    suggested: (RELION, RRID:SCR_016274)
    The plasmids shown in Fig. 9 (mEGFP-NbALFA, mCherry-NbALFA, pETNb-nALFA, pETNb-cALFA, pFBNb-cALFA, pBMNb-cALFA) have been deposited into Addgene (http://www.addgene.org/) (Addgene IDs: 159986, 159987, 159988, 159989, 159990 and 159991).
    http://www.addgene.org/
    suggested: (Addgene, RRID:SCR_002037)

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.09.28.316307 on bioRxiv