Yan Xingchi, Yu Polly Y, Srinivasan Arvind, Abdul Rehman Sohaib, Sreenivas Surabhi Kottigegollahalli, Conway Jeremy B, Prigozhin Maxim B
Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138.
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138.
Proc Natl Acad Sci U S A. 2025 May 20;122(20):e2409426122. doi: 10.1073/pnas.2409426122. Epub 2025 May 12.
Intermolecular interactions underlie all cellular functions, yet visualizing these interactions at the single-molecule level remains challenging. Single-molecule localization microscopy (SMLM) offers a potential solution. Given a nanoscale map of two putative interaction partners, it should be possible to assign molecules either to the class of coupled pairs or to the class of noncoupled bystanders. Here, we developed a probabilistic algorithm that allows accurate determination of both the absolute number and the proportion of molecules that form coupled pairs. The algorithm calculates interaction probabilities for all possible pairs of localized molecules, selects the most likely interaction set, and corrects for any spurious colocalizations. Benchmarking this approach across a set of simulated molecular localization maps with varying densities (up to ∼55 molecules μm) and localization precisions (1 to 50 nm) showed typical errors in the identification of correct pairs of only a few percent. At molecular densities of ∼5 to 10 molecules μm and localization precisions of 20 to 30 nm, which are typical parameters for SMLM imaging, the recall was ∼90%. The algorithm was effective at differentiating between noninteracting and coupled molecules both in simulations and experiments. Finally, it correctly inferred the number of coupled pairs over time in a simulated reaction-diffusion system, enabling determination of the underlying rate constants. The proposed approach promises to enable direct visualization and quantification of intermolecular interactions using SMLM.
分子间相互作用是所有细胞功能的基础,但在单分子水平上可视化这些相互作用仍然具有挑战性。单分子定位显微镜(SMLM)提供了一种潜在的解决方案。给定两个假定相互作用伙伴的纳米级图谱,应该能够将分子分为耦合对类别或非耦合旁观者类别。在这里,我们开发了一种概率算法,该算法能够准确确定形成耦合对的分子的绝对数量和比例。该算法计算所有可能的定位分子对的相互作用概率,选择最可能的相互作用集,并校正任何虚假的共定位。在一组具有不同密度(高达约55个分子/μm)和定位精度(1至50nm)的模拟分子定位图谱上对该方法进行基准测试,结果表明在识别正确对时的典型误差仅为百分之几。在约5至10个分子/μm的分子密度和20至30nm的定位精度下(这是SMLM成像的典型参数),召回率约为90%。该算法在模拟和实验中都能有效区分非相互作用分子和耦合分子。最后,它正确地推断了模拟反应扩散系统中随时间变化的耦合对数量,从而能够确定潜在的速率常数。所提出的方法有望使用SMLM直接可视化和量化分子间相互作用。