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New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease
Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473538/ https://www.ncbi.nlm.nih.gov/pubmed/32886703 http://dx.doi.org/10.1371/journal.pone.0238037 |
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author | Cozzolino, Flora Landolfi, Alfredo Iacobucci, Ilaria Monaco, Vittoria Caterino, Marianna Celentano, Simona Zuccato, Chiara Cattaneo, Elena Monti, Maria |
author_facet | Cozzolino, Flora Landolfi, Alfredo Iacobucci, Ilaria Monaco, Vittoria Caterino, Marianna Celentano, Simona Zuccato, Chiara Cattaneo, Elena Monti, Maria |
author_sort | Cozzolino, Flora |
collection | PubMed |
description | Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples. |
format | Online Article Text |
id | pubmed-7473538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74735382020-09-14 New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease Cozzolino, Flora Landolfi, Alfredo Iacobucci, Ilaria Monaco, Vittoria Caterino, Marianna Celentano, Simona Zuccato, Chiara Cattaneo, Elena Monti, Maria PLoS One Research Article Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples. Public Library of Science 2020-09-04 /pmc/articles/PMC7473538/ /pubmed/32886703 http://dx.doi.org/10.1371/journal.pone.0238037 Text en © 2020 Cozzolino et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Cozzolino, Flora Landolfi, Alfredo Iacobucci, Ilaria Monaco, Vittoria Caterino, Marianna Celentano, Simona Zuccato, Chiara Cattaneo, Elena Monti, Maria New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title | New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title_full | New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title_fullStr | New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title_full_unstemmed | New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title_short | New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease |
title_sort | new label-free methods for protein relative quantification applied to the investigation of an animal model of huntington disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473538/ https://www.ncbi.nlm.nih.gov/pubmed/32886703 http://dx.doi.org/10.1371/journal.pone.0238037 |
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