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BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment

Raman microspectroscopy is a rapidly developing technique, which has an unparalleled potential for in situ proteomics, lipidomics, and metabolomics, due to its remarkable capability to analyze the molecular composition of live cells and single cellular organelles. However, the scope of Raman spectro...

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Autores principales: Kuzmin, Andrey N., Pliss, Artem, Rzhevskii, Alex, Lita, Adrian, Larion, Mioara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316203/
https://www.ncbi.nlm.nih.gov/pubmed/30423849
http://dx.doi.org/10.3390/bios8040106
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author Kuzmin, Andrey N.
Pliss, Artem
Rzhevskii, Alex
Lita, Adrian
Larion, Mioara
author_facet Kuzmin, Andrey N.
Pliss, Artem
Rzhevskii, Alex
Lita, Adrian
Larion, Mioara
author_sort Kuzmin, Andrey N.
collection PubMed
description Raman microspectroscopy is a rapidly developing technique, which has an unparalleled potential for in situ proteomics, lipidomics, and metabolomics, due to its remarkable capability to analyze the molecular composition of live cells and single cellular organelles. However, the scope of Raman spectroscopy for bio-applications is limited by a lack of software tools for express-analysis of biomolecular composition based on Raman spectra. In this study, we have developed the first software toolbox for immediate analysis of intracellular Raman spectra using a powerful biomolecular component analysis (BCA) algorithm. Our software could be easily integrated with commercial Raman spectroscopy instrumentation, and serve for precise analysis of molecular content in major cellular organelles, including nucleoli, endoplasmic reticulum, Golgi apparatus, and mitochondria of either live or fixed cells. The proposed software may be applied in broad directions of cell science, and serve for further advancement and standardization of Raman spectroscopy.
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spelling pubmed-63162032019-01-09 BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment Kuzmin, Andrey N. Pliss, Artem Rzhevskii, Alex Lita, Adrian Larion, Mioara Biosensors (Basel) Article Raman microspectroscopy is a rapidly developing technique, which has an unparalleled potential for in situ proteomics, lipidomics, and metabolomics, due to its remarkable capability to analyze the molecular composition of live cells and single cellular organelles. However, the scope of Raman spectroscopy for bio-applications is limited by a lack of software tools for express-analysis of biomolecular composition based on Raman spectra. In this study, we have developed the first software toolbox for immediate analysis of intracellular Raman spectra using a powerful biomolecular component analysis (BCA) algorithm. Our software could be easily integrated with commercial Raman spectroscopy instrumentation, and serve for precise analysis of molecular content in major cellular organelles, including nucleoli, endoplasmic reticulum, Golgi apparatus, and mitochondria of either live or fixed cells. The proposed software may be applied in broad directions of cell science, and serve for further advancement and standardization of Raman spectroscopy. MDPI 2018-11-10 /pmc/articles/PMC6316203/ /pubmed/30423849 http://dx.doi.org/10.3390/bios8040106 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kuzmin, Andrey N.
Pliss, Artem
Rzhevskii, Alex
Lita, Adrian
Larion, Mioara
BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title_full BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title_fullStr BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title_full_unstemmed BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title_short BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment
title_sort bcabox algorithm expands capabilities of raman microscope for single organelles assessment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316203/
https://www.ncbi.nlm.nih.gov/pubmed/30423849
http://dx.doi.org/10.3390/bios8040106
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