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Biosensors 2018, 8(4), 106; https://doi.org/10.3390/bios8040106

BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment

1
Advanced Cytometry Instrumentation Systems, LLC, Buffalo, NY 14203, USA
2
Institute for Lasers, Photonics and Biophotonics, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
3
Thermo Fisher Scientific, Waltham, MA 02451, USA
4
Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
*
Author to whom correspondence should be addressed.
Received: 24 September 2018 / Revised: 2 November 2018 / Accepted: 8 November 2018 / Published: 10 November 2018
(This article belongs to the Special Issue Applications of Raman Techniques in Biosensing)
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Abstract

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. View Full-Text
Keywords: Raman spectrometry; microscopy; biomolecular analysis; single cell assay Raman spectrometry; microscopy; biomolecular analysis; single cell assay
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Kuzmin, A.N.; Pliss, A.; Rzhevskii, A.; Lita, A.; Larion, M. BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment. Biosensors 2018, 8, 106.

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