Cryo-electron microscopy (cryo-EM) tomography is a powerful tool for in situ structure determination. However, this method requires the acquisition of tilt series, and its time consuming throughput of acquiring tilt series severely slows determination of in situ structures. By treating the electron densities of non-target protein as non-Gaussian distributed noise, we developed a new target function that greatly improves the efficiency of the recognition of the target protein in a single cryo-EM image without acquiring tilt series. Moreover, we developed a sorting function that effectively eliminates the model dependence and improved the resolution during the subsequent structure refinement procedure. By eliminating model bias, our method allows using homolog proteins as models to recognize the target protein. Together, we developed an in situ single particle analysis (isSPA) method. Our isSPA method was successfully applied to solve structures of glycoproteins on the surface of a non-icosahedral virus and Rubisco inside the carboxysome. The cryo-EM data from both samples were collected within 24 hours, thus allowing fast and simple structural determination in situ.

中文翻译：

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使用单粒子低温电子显微镜图像确定原位结构

低温电子显微镜（cryo-EM）断层扫描是用于原位结构确定的强大工具。但是，该方法需要获取倾斜序列，并且获取倾斜序列的耗时的吞吐量严重减慢了原位结构的确定。通过将非目标蛋白质的电子密度视为非高斯分布噪声，我们开发了一种新的目标功能，该功能极大地提高了单个冷冻EM图像中目标蛋白质的识别效率，而无需获取倾斜序列。此外，我们开发了一种排序功能，可以有效消除模型依赖性，并在后续的结构优化过程中提高分辨率。通过消除模型偏差，我们的方法允许使用同源蛋白作为模型来识别目标蛋白。一起，我们开发了一种原位单颗粒分析（isSPA）方法。我们的isSPA方法已成功应用于解决非二十面体病毒表面的糖蛋白结构和羧基体内部的Rubisco。来自两个样品的cryo-EM数据均在24小时内收集，因此可以在现场进行快速简单的结构测定。