State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin, China.
Department of Chemistry, University of British Columbia, Vancouver, BC, Canada.
J Microsc. 2019 Mar;273(3):178-188. doi: 10.1111/jmi.12773. Epub 2018 Nov 29.
Real-time tracking of multiple particles is key for quantitative analysis of dynamic biophysical processes and materials science via time-lapse microscopy image data, especially for single molecule biophysical techniques, such as magnetic tweezers and centrifugal force microscopy. However, real-time multiple particle tracking with high resolution is limited by the current imaging processes or tracking algorithms. Here, we demonstrate 1 nm resolution in three dimensions in real-time with a graphics-processing unit (GPU) based on a compute unified device architecture (CUDA) parallel computing framework instead of only a central processing unit (CPU). We also explore the trade-offs between processing speed and size of the utilized regions of interest and a maximum speedup of 137 is achieved with the GPU compared with the CPU. Moreover, we utilize this method with our recently self-built centrifugal force microscope (CFM) in experiments that track multiple DNA-tethered particles. Our approach paves the way for high-throughput single molecule techniques with high resolution and efficiency. LAY DESCRIPTION: Particles are widely used as probes in life sciences through their motions. In single molecule techniques such as optical tweezers and magnetic tweezers, microbeads are used to study intermolecular or intramolecular interactions via beads tracking. Also tracking multiple beads' motions could study cell-cell or cell-ECM interactions in traction force microscopy. Therefore, particle tracking is of key important during these researches. However, parallel 3D multiple particle tracking in real-time with high resolution is a challenge either due to the algorithm or the program. Here, we combine the performance of CPU and CUDA-based GPU to make a hybrid implementation for particle tracking. In this way, a speedup of 137 is obtained compared the program before only with CPU without loss of accuracy. Moreover, we improve and build a new centrifugal force microscope for multiple single molecule force spectroscopy research in parallel. Then we employed our program into centrifugal force microscope for DNA stretching study. Our results not only demonstrate the application of this program in single molecule techniques, also indicate the capability of multiple single molecule study with centrifugal force microscopy.
实时跟踪多个粒子是通过延时显微镜图像数据对动态生物物理过程和材料科学进行定量分析的关键,特别是对于磁镊和离心力显微镜等单分子生物物理技术。然而,具有高分辨率的实时多粒子跟踪受到当前成像过程或跟踪算法的限制。在这里,我们基于计算统一设备架构 (CUDA) 并行计算框架,使用图形处理单元 (GPU) 实时实现了三维 1nm 分辨率,而不仅仅是中央处理单元 (CPU)。我们还探讨了处理速度与所利用的感兴趣区域的大小之间的权衡关系,与 CPU 相比,GPU 的最大加速比达到了 137。此外,我们在最近自行构建的离心力显微镜 (CFM) 实验中利用这种方法跟踪多个 DNA 连接的粒子。我们的方法为具有高分辨率和高效率的高通量单分子技术铺平了道路。
粒子作为探针在生命科学中被广泛应用,通过它们的运动来进行研究。在单分子技术如光镊和磁镊中,微珠被用于通过珠子跟踪来研究分子间或分子内相互作用。此外,跟踪多个珠子的运动可以在牵引力显微镜中研究细胞-细胞或细胞-细胞外基质的相互作用。因此,在这些研究中,粒子跟踪至关重要。然而,由于算法或程序的原因,实时进行高分辨率的并行 3D 多粒子跟踪是一个挑战。在这里,我们结合了 CPU 和基于 CUDA 的 GPU 的性能,为粒子跟踪构建了一个混合实现。通过这种方式,与仅使用 CPU 的程序相比,速度提高了 137 倍,而精度没有损失。此外,我们改进并构建了一种新的离心力显微镜,用于并行进行多个单分子力谱研究。然后,我们将我们的程序应用于离心力显微镜来进行 DNA 拉伸研究。我们的结果不仅展示了这个程序在单分子技术中的应用,也表明了离心力显微镜在多个单分子研究中的能力。