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Strategies for picking membrane-associated particles within subtomogram averaging workflows.

ABSTRACT: Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) has emerged as a key tool for determining macromolecular structure(s) in vitro and in situ. However, processing cryo-ET data with STA currently requires significant user expertise. Recent efforts have streamlined several steps in STA workflows; however, particle picking remains a time-consuming bottleneck for many projects and requires considerable user input. Here, we present several strategies for the time-efficient and accurate picking of membrane-associated particles using the COPII inner coat as a case study. We also discuss a range of particle cleaning solutions to remove both poor quality and false-positive particles from STA datasets. We provide a step-by-step guide and the necessary scripts for users to independently carry out the particle picking and cleaning strategies discussed.

SUBMITTER: Pyle E

PROVIDER: S-EPMC9642003 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Strategies for picking membrane-associated particles within subtomogram averaging workflows.

Pyle Euan E Hutchings Joshua J Zanetti Giulia G

Faraday discussions 20221108 0

Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) has emerged as a key tool for determining macromolecular structure(s) <i>in vitro</i> and <i>in situ</i>. However, processing cryo-ET data with STA currently requires significant user expertise. Recent efforts have streamlined several steps in STA workflows; however, particle picking remains a time-consuming bottleneck for many projects and requires considerable user input. Here, we present several strategies for the time-effici ...[more]

PMID: 35924570

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Project description:Microtubule structure is commonly investigated using single-particle analysis (SPA) or subtomogram averaging (STA), whose main objectives are to gather high-resolution information on the αβ-tubulin heterodimer and on its interactions with neighboring molecules within the microtubule lattice. The maps derived from SPA approaches usually delineate a continuous organization of the αβ-tubulin heterodimer that alternate regularly head-to-tail along protofilaments, and that share homotypic lateral interactions between monomers (α-α, β-β), except at one unique region called the seam, made of heterotypic ones (α-β, β-α). However, this textbook description of the microtubule lattice has been challenged over the years by several studies that revealed the presence of multi-seams in microtubules assembled in vitro from purified tubulin. To analyze in deeper detail their intrinsic structural heterogeneity, we have developed a segmented subtomogram averaging (SSTA) strategy on microtubules decorated with kinesin motor-domains that bind every αβ-tubulin heterodimer. Individual protofilaments and microtubule centers are modeled, and sub-volumes are extracted at every kinesin motor domain position to obtain full subtomogram averages of the microtubules. The model is divided into shorter segments, and subtomogram averages of each segment are calculated using the main parameters of the full-length microtubule settings as a template. This approach reveals changes in the number and location of seams within individual microtubules assembled in vitro from purified tubulin and in Xenopus egg cytoplasmic extracts. Key features This protocol builds upon the method developed by J.M. Heumann to perform subtomogram averages of microtubules and extends it to divide them into shorter segments. Microtubules are decorated with kinesin motor-domains to determine the underlying organization of its constituent αβ-tubulin heterodimers. The SSTA approach allows analysis of the structural heterogeneity of individual microtubules and reveals multi-seams and changes in their number and location within their shaft. Graphical overview.

Dataset Information

Strategies for picking membrane-associated particles within subtomogram averaging workflows.

Publications

Strategies for picking membrane-associated particles within subtomogram averaging workflows.

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