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An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms
Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, r...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948189/ https://www.ncbi.nlm.nih.gov/pubmed/35332182 http://dx.doi.org/10.1038/s41598-022-08740-w |
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author | Pandit, Kunal Petrescu, Joana Cuevas, Miguel Stephenson, William Smibert, Peter Phatnani, Hemali Maniatis, Silas |
author_facet | Pandit, Kunal Petrescu, Joana Cuevas, Miguel Stephenson, William Smibert, Peter Phatnani, Hemali Maniatis, Silas |
author_sort | Pandit, Kunal |
collection | PubMed |
description | Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument, comprising an epifluorescence microscope with integrated fluidics, into an open platform for programmable applications without need for specialized engineering or software development expertise. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. Given the widespread availability of HiSeq 2500 platforms and the simplicity of the modifications required to repurpose these systems, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system. |
format | Online Article Text |
id | pubmed-8948189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89481892022-03-28 An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms Pandit, Kunal Petrescu, Joana Cuevas, Miguel Stephenson, William Smibert, Peter Phatnani, Hemali Maniatis, Silas Sci Rep Article Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument, comprising an epifluorescence microscope with integrated fluidics, into an open platform for programmable applications without need for specialized engineering or software development expertise. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. Given the widespread availability of HiSeq 2500 platforms and the simplicity of the modifications required to repurpose these systems, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system. Nature Publishing Group UK 2022-03-24 /pmc/articles/PMC8948189/ /pubmed/35332182 http://dx.doi.org/10.1038/s41598-022-08740-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pandit, Kunal Petrescu, Joana Cuevas, Miguel Stephenson, William Smibert, Peter Phatnani, Hemali Maniatis, Silas An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title | An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title_full | An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title_fullStr | An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title_full_unstemmed | An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title_short | An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms |
title_sort | open source toolkit for repurposing illumina sequencing systems as versatile fluidics and imaging platforms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948189/ https://www.ncbi.nlm.nih.gov/pubmed/35332182 http://dx.doi.org/10.1038/s41598-022-08740-w |
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