Cargando…
PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data
As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microscopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationall...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327484/ https://www.ncbi.nlm.nih.gov/pubmed/34377369 http://dx.doi.org/10.1016/j.csbj.2021.07.004 |
_version_ | 1783732086988865536 |
---|---|
author | Shepherd, Jack W. Higgins, Ed J. Wollman, Adam J.M. Leake, Mark C. |
author_facet | Shepherd, Jack W. Higgins, Ed J. Wollman, Adam J.M. Leake, Mark C. |
author_sort | Shepherd, Jack W. |
collection | PubMed |
description | As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microscopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized. |
format | Online Article Text |
id | pubmed-8327484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-83274842021-08-09 PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data Shepherd, Jack W. Higgins, Ed J. Wollman, Adam J.M. Leake, Mark C. Comput Struct Biotechnol J Research Article As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microscopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized. Research Network of Computational and Structural Biotechnology 2021-07-10 /pmc/articles/PMC8327484/ /pubmed/34377369 http://dx.doi.org/10.1016/j.csbj.2021.07.004 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Shepherd, Jack W. Higgins, Ed J. Wollman, Adam J.M. Leake, Mark C. PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title_full | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title_fullStr | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title_full_unstemmed | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title_short | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
title_sort | pystachio: python single-molecule tracking stoichiometry intensity and simulation, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327484/ https://www.ncbi.nlm.nih.gov/pubmed/34377369 http://dx.doi.org/10.1016/j.csbj.2021.07.004 |
work_keys_str_mv | AT shepherdjackw pystachiopythonsinglemoleculetrackingstoichiometryintensityandsimulationaflexibleextensiblebeginnerfriendlyandoptimizedprogramforanalysisofsinglemoleculemicroscopydata AT higginsedj pystachiopythonsinglemoleculetrackingstoichiometryintensityandsimulationaflexibleextensiblebeginnerfriendlyandoptimizedprogramforanalysisofsinglemoleculemicroscopydata AT wollmanadamjm pystachiopythonsinglemoleculetrackingstoichiometryintensityandsimulationaflexibleextensiblebeginnerfriendlyandoptimizedprogramforanalysisofsinglemoleculemicroscopydata AT leakemarkc pystachiopythonsinglemoleculetrackingstoichiometryintensityandsimulationaflexibleextensiblebeginnerfriendlyandoptimizedprogramforanalysisofsinglemoleculemicroscopydata |