Massively parallel analysis of single-molecule dynamics on next-generation sequencing chips
Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe multiplexed single-molecule characterization at the library scale (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profiled the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding-rewinding dynamics. The ability to explore a large sequence space for Cas9 allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes.
Authors
- Martin Jínek (ORCID: https://orcid.org/0000-0002-7601-210X)
- Javier Aguirre Rivera (ORCID: https://orcid.org/0000-0002-5263-3577)
- Guanzhong Mao (ORCID: https://orcid.org/0000-0001-5841-0991)
- Sebastian Deindl (ORCID: https://orcid.org/0000-0001-6807-8654)
- Christelle Chanez (ORCID: https://orcid.org/0000-0002-3432-4375)
- Michael K. Lindell (ORCID: https://orcid.org/0000-0001-6972-5120)
- Félix Ritort (ORCID: https://orcid.org/0000-0002-4869-5003)
- Anton Sabantsev (ORCID: https://orcid.org/0000-0002-8559-8894)
- Mikhail Panfilov (ORCID: https://orcid.org/0000-0003-2875-7315)
- Qiqi Hou
Institutions
- Uppsala University (SE)
- University of Zurich (CH)
- Science for Life Laboratory (SE)
- Institut de Nanociència i Nanotecnologia de la Universitat de Barcelona
- Universitat de Barcelona (ES)
Publication Details
- Journal
- Science
- Published
- 2024-08-22
- DOI
- https://doi.org/10.1126/science.adn5371
- Citations
- 18
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 4.21