Treffer: A Python framework for magnetic tweezers real-time image processing and microscope control.

Title:
A Python framework for magnetic tweezers real-time image processing and microscope control.
Authors:
London JA; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA., Singh AK; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA., Teague C S; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA., Tirtom NE; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA., Root ZA; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA., Fishel R; Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.
Source:
BioRxiv : the preprint server for biology [bioRxiv] 2025 Nov 03. Date of Electronic Publication: 2025 Nov 03.
Publication Type:
Journal Article; Preprint
Language:
English
Journal Info:
Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Grant Information:
R01 AI150496 United States AI NIAID NIH HHS; R01 CA067007 United States CA NCI NIH HHS; R56 AI150496 United States AI NIAID NIH HHS
Entry Date(s):
Date Created: 20251124 Date Completed: 20251215 Latest Revision: 20251215
Update Code:
20251215
PubMed Central ID:
PMC12637577
DOI:
10.1101/2025.10.31.685671
PMID:
41279331
Database:
MEDLINE

Weitere Informationen

Magnetic tweezers are a popular biophysical instrument for manipulating and measuring single molecules. Most laboratories rely on custom-built setups tailored to specific experiments, resulting in a variety of hardware and software implementations. Typically, image acquisition and hardware control are automated via LabVIEW and specialized C/C++/CUDA libraries for real-time video processing. Live processing eliminates the need to store raw video, enabling high throughput, fast acquisition rates, and simplified experimental workflows. However, no open-source, general-purpose software framework currently unifies these capabilities for magnetic tweezers experiments. Here, we introduce MagTrack and MagScope, open-source Python-based tools designed to fill this gap. MagTrack is an image-processing library that efficiently determines bead-positions from magnetic-tweezers videos using CPU and/or GPU computation. MagScope is a comprehensive software framework offering a graphical user interface, real-time hardware control, data acquisition, and video processing. It is built on a multiprocessing architecture for responsive, high-throughput computation. Together, MagTrack and MagScope offer a flexible, modern, and fully customizable open-source alternative to proprietary or fragmented systems, enabling laboratories to adapt and extend the framework according to their experimental and programming needs.