Literature DB >> 21974592

Optics clustered to output unique solutions: a multi-laser facility for combined single molecule and ensemble microscopy.

David T Clarke1, Stanley W Botchway, Benjamin C Coles, Sarah R Needham, Selene K Roberts, Daniel J Rolfe, Christopher J Tynan, Andrew D Ward, Stephen E D Webb, Rahul Yadav, Laura Zanetti-Domingues, Marisa L Martin-Fernandez.   

Abstract

Optics clustered to output unique solutions (OCTOPUS) is a microscopy platform that combines single molecule and ensemble imaging methodologies. A novel aspect of OCTOPUS is its laser excitation system, which consists of a central core of interlocked continuous wave and pulsed laser sources, launched into optical fibres and linked via laser combiners. Fibres are plugged into wall-mounted patch panels that reach microscopy end-stations in adjacent rooms. This allows multiple tailor-made combinations of laser colours and time characteristics to be shared by different end-stations minimising the need for laser duplications. This setup brings significant benefits in terms of cost effectiveness, ease of operation, and user safety. The modular nature of OCTOPUS also facilitates the addition of new techniques as required, allowing the use of existing lasers in new microscopes while retaining the ability to run the established parts of the facility. To date, techniques interlinked are multi-photon/multicolour confocal fluorescence lifetime imaging for several modalities of fluorescence resonance energy transfer (FRET) and time-resolved anisotropy, total internal reflection fluorescence, single molecule imaging of single pair FRET, single molecule fluorescence polarisation, particle tracking, and optical tweezers. Here, we use a well-studied system, the epidermal growth factor receptor network, to illustrate how OCTOPUS can aid in the investigation of complex biological phenomena.
© 2011 American Institute of Physics

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Year:  2011        PMID: 21974592     DOI: 10.1063/1.3635536

Source DB:  PubMed          Journal:  Rev Sci Instrum        ISSN: 0034-6748            Impact factor:   1.523


  7 in total

1.  Cell wall constrains lateral diffusion of plant plasma-membrane proteins.

Authors:  Alexandre Martinière; Irene Lavagi; Gayathri Nageswaran; Daniel J Rolfe; Lilly Maneta-Peyret; Doan-Trung Luu; Stanley W Botchway; Stephen E D Webb; Sebastien Mongrand; Christophe Maurel; Marisa L Martin-Fernandez; Jürgen Kleine-Vehn; Jirí Friml; Patrick Moreau; John Runions
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-11       Impact factor: 11.205

2.  A systematic investigation of differential effects of cell culture substrates on the extent of artifacts in single-molecule tracking.

Authors:  Laura C Zanetti-Domingues; Marisa L Martin-Fernandez; Sarah R Needham; Daniel J Rolfe; David T Clarke
Journal:  PLoS One       Date:  2012-09-25       Impact factor: 3.240

3.  A stochastic model for electron multiplication charge-coupled devices--from theory to practice.

Authors:  Michael Hirsch; Richard J Wareham; Marisa L Martin-Fernandez; Michael P Hobson; Daniel J Rolfe
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

Review 4.  Single molecule fluorescence detection and tracking in mammalian cells: the state-of-the-art and future perspectives.

Authors:  Marisa L Martin-Fernandez; David T Clarke
Journal:  Int J Mol Sci       Date:  2012-11-13       Impact factor: 5.923

5.  Hydrophobic fluorescent probes introduce artifacts into single molecule tracking experiments due to non-specific binding.

Authors:  Laura C Zanetti-Domingues; Christopher J Tynan; Daniel J Rolfe; David T Clarke; Marisa Martin-Fernandez
Journal:  PLoS One       Date:  2013-09-16       Impact factor: 3.240

6.  A global sampler of single particle tracking solutions for single molecule microscopy.

Authors:  Michael Hirsch; Richard Wareham; Ji W Yoon; Daniel J Rolfe; Laura C Zanetti-Domingues; Michael P Hobson; Peter J Parker; Marisa L Martin-Fernandez; Sumeetpal S Singh
Journal:  PLoS One       Date:  2019-10-28       Impact factor: 3.240

7.  Machine learning and big scientific data.

Authors:  Tony Hey; Keith Butler; Sam Jackson; Jeyarajan Thiyagalingam
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2020-01-20       Impact factor: 4.226

  7 in total

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