$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
With recent advancements in both instrument hardware1,2 and image processing software3,4,5, cryogenic electron microscopy (cryo-EM) has emerged as a popular and powerful tool in modern structural biology. Despite these breakthroughs, bottlenecks persist in achieving high-resolution macromolecular structures using cryo-EM. One such significant challenge is the uneven particle distribution, including the orientation preference phenomenon, which is predominantly observed at the air-water interface6,7,8,9.
During sample vitrification, some molecules exhibit a tendency to align themselves along specific axes on the grid. This leads to an uneven distribution of particle views in the final dataset. Certain orientations may be overrepresented while others are underrepresented or completely absent, resulting in incomplete sampling of the total protein architecture. Regions of the protein that are preferentially oriented towards the electron beam will appear more prominent in the density map, while regions oriented away from the beam may be poorly resolved or completely missing10,11. Consequently, uneven particle distribution introduces potential biases and artifacts into the final reconstructed three-dimensional (3D) structure. Notably, key structural elements such as alpha helices and beta sheets may become skewed, amino acid or nucleotide chains may appear fragmented, and densities of specific protein or nucleic acid segments may exhibit distortion12. Ultimately, these misrepresentations pose a major challenge to accurately unraveling the structure and function of biological molecules.
Various experimental approaches are currently used to overcome such challenges, including sample preparation optimization13,14,15, grid treatment16,17,18,19,20,21,22, and data collection strategy23. Notably, it is advised to address the challenge at the sample preparation stage whenever feasible7. Common optimizations in sample preparation include modifying buffer composition, introducing small-molecular or macromolecular binding partners, generating intramolecular crosslinks, and varying detergents. This is also true for membrane proteins24,25, although detergents must be used specifically for purification and stabilization purposes. Among these, the customizability, cost-effectiveness, and widespread accessibility of protein buffer optimization make it a preferred strategy in most laboratories. This approach allows precise and immediate adjustments of the various parameters to match the specific requirement of each protein sample. Through iterative refinement, researchers can systematically test diverse buffer conditions and adjust various parameters aimed at minimizing preferred orientations and improving the overall quality of cryo-EM data. Simply varying protein buffer components and adjusting their concentrations has demonstrated efficacy in influencing protein stability by modulating surface charge, consequently impacting protein behavior within vitreous ice25. Therefore, optimizing protein buffer composition is considered one of the most convenient and straightforward approaches for addressing common challenges in cryo-EM.
Here, a protocol is suggested for addressing a common obstacle in cryo-EM—overcoming uneven particle distribution. In this protocol, key procedures for protein preparation and buffer screening, complemented by grid preparation, are outlined using a small heat shock protein from Methanocaldococcus jannaschii (MjsHSP16.5)26 as a case study (Figure 1). This sHSP is natively stable, has a molecular mass of 16.5 kDa per monomer, and assembles into a 24-mer octahedral cage26,27, making it an attractive candidate for structural analysis by cryo-EM. However, the observation of an uneven particle distribution during cryo-EM data collection was not anticipated, and it emerged as a significant challenge during the experiments. Furthermore, potential approaches beneficial for researchers tackling similar challenges are discussed, thus facilitating the efficient elucidation of macromolecular structures using cryo-EM.