Chaillet Marten L, Roet Sander, Veltkamp Remco C, Förster Friedrich
Structural Biochemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CG Utrecht, the Netherlands.
Department of Information and Computing Sciences, Utrecht University, 3584 CE Utrecht, the Netherlands.
J Struct Biol X. 2025 May 2;11:100125. doi: 10.1016/j.yjsbx.2025.100125. eCollection 2025 Jun.
Template matching (TM) in cryo-electron tomography (cryo-ET) enables detection and localization of known macromolecules. However, TM faces challenges of weak signal of the macromolecules and interfering features with a high signal-to-noise ratio, which are often addressed by time-consuming, subjective manual curation of results. To improve the detection performance we introduce pytom-match-pick, a GPU-accelerated, open-source command line interface for enhanced TM in cryo-ET. Using pytom-match-pick, we first quantify the effects of point spread function (PSF) weighting and show that a tilt-weighted PSF outperforms a binary wedge with a single defocus estimate. We also assess previously introduced background normalization methods for classification performance. This indicates that phase randomization is more effective than spectrum whitening in reducing false positives. Furthermore, a novel application of the tophat transform on score maps, combined with a dual-constraint thresholding strategy, reduces false positives and improves precision. We benchmarked pytom-match-pick on public datasets, demonstrating improved classification and localization of macromolecules like ribosomal subunits and proteasomes that led to fewer artifacts in subtomogram averages. This tool promises to advance visual proteomics by improving the efficiency and accuracy of macromolecule detection in cellular contexts.
冷冻电子断层扫描（cryo-ET）中的模板匹配（TM）能够检测和定位已知的大分子。然而，TM面临着大分子信号微弱以及存在高信噪比干扰特征的挑战，这些问题通常通过耗时且主观的结果人工筛选来解决。为了提高检测性能，我们引入了pytom-match-pick，这是一个用于在cryo-ET中增强TM的GPU加速开源命令行界面。使用pytom-match-pick，我们首先量化了点扩散函数（PSF）加权的效果，并表明倾斜加权PSF优于具有单一散焦估计的二元楔形。我们还评估了先前引入的背景归一化方法对分类性能的影响。这表明相位随机化在减少误报方面比频谱白化更有效。此外，一种在得分图上应用顶帽变换的新方法，结合双约束阈值策略，减少了误报并提高了精度。我们在公共数据集上对pytom-match-pick进行了基准测试，证明了其在核糖体亚基和蛋白酶体等大分子的分类和定位方面有所改进，从而减少了亚断层平均图像中的伪影。该工具有望通过提高细胞环境中大分子检测的效率和准确性来推动视觉蛋白质组学的发展。
