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Plasma proteomics data from hibernating and active Scandinavian brown bears
In this article, we present mass-spectrometry based plasma proteomics data from hibernating and active free-ranging Scandinavian brown bears (Ursus arctos). The brown bear hibernates for half the year. Despite obesity when entering the den and the prolonged period of inactivity, the bear shows no si...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873540/ https://www.ncbi.nlm.nih.gov/pubmed/35242939 http://dx.doi.org/10.1016/j.dib.2022.107959 |
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author | Frøbert, Anne Mette Gregersen, Simon Brohus, Malene Welinder, Karen G. Kindberg, Jonas Fröbert, Ole Overgaard, Michael T. |
author_facet | Frøbert, Anne Mette Gregersen, Simon Brohus, Malene Welinder, Karen G. Kindberg, Jonas Fröbert, Ole Overgaard, Michael T. |
author_sort | Frøbert, Anne Mette |
collection | PubMed |
description | In this article, we present mass-spectrometry based plasma proteomics data from hibernating and active free-ranging Scandinavian brown bears (Ursus arctos). The brown bear hibernates for half the year. Despite obesity when entering the den and the prolonged period of inactivity, the bear shows no signs of the harmful effects associated with these conditions in humans. Thus, the hibernating bear is a potential translational model for addressing these complications in humans. We analyzed plasma samples from fourteen 2- to 3-year-old bears (6 males and 8 females) collected both during hibernation and the active state, and for some of the bears during two seasons, resulting in a total of 38 analyzed plasma samples. In triplicates, the plasma proteins were unfolded and reduced. To increase the chance of detecting low-molecular-weight proteins and peptides, we filtered the samples using a 50 K molecular weight cut-off filter with the aim to deplete larger abundant proteins, including albumin, and thereby increase the depth of the analysis. The proteins in the permeate were then tryptically digested, desalted, and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein identification and quantification was performed with the MaxQuant software searching against an Ursus arctos horribilis protein database. Here, we provide the raw data, a list with identified proteins in the plasma samples, and the databases applied for protein identification. Based on the provided data, differentially expressed proteins in hibernation compared to active state can be identified. These proteins may be involved in the bears’ adaptions to hibernation physiology and hold potential as novel therapeutic targets. |
format | Online Article Text |
id | pubmed-8873540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88735402022-03-02 Plasma proteomics data from hibernating and active Scandinavian brown bears Frøbert, Anne Mette Gregersen, Simon Brohus, Malene Welinder, Karen G. Kindberg, Jonas Fröbert, Ole Overgaard, Michael T. Data Brief Data Article In this article, we present mass-spectrometry based plasma proteomics data from hibernating and active free-ranging Scandinavian brown bears (Ursus arctos). The brown bear hibernates for half the year. Despite obesity when entering the den and the prolonged period of inactivity, the bear shows no signs of the harmful effects associated with these conditions in humans. Thus, the hibernating bear is a potential translational model for addressing these complications in humans. We analyzed plasma samples from fourteen 2- to 3-year-old bears (6 males and 8 females) collected both during hibernation and the active state, and for some of the bears during two seasons, resulting in a total of 38 analyzed plasma samples. In triplicates, the plasma proteins were unfolded and reduced. To increase the chance of detecting low-molecular-weight proteins and peptides, we filtered the samples using a 50 K molecular weight cut-off filter with the aim to deplete larger abundant proteins, including albumin, and thereby increase the depth of the analysis. The proteins in the permeate were then tryptically digested, desalted, and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein identification and quantification was performed with the MaxQuant software searching against an Ursus arctos horribilis protein database. Here, we provide the raw data, a list with identified proteins in the plasma samples, and the databases applied for protein identification. Based on the provided data, differentially expressed proteins in hibernation compared to active state can be identified. These proteins may be involved in the bears’ adaptions to hibernation physiology and hold potential as novel therapeutic targets. Elsevier 2022-02-16 /pmc/articles/PMC8873540/ /pubmed/35242939 http://dx.doi.org/10.1016/j.dib.2022.107959 Text en © 2022 The Author(s). Published by Elsevier Inc. 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 | Data Article Frøbert, Anne Mette Gregersen, Simon Brohus, Malene Welinder, Karen G. Kindberg, Jonas Fröbert, Ole Overgaard, Michael T. Plasma proteomics data from hibernating and active Scandinavian brown bears |
title | Plasma proteomics data from hibernating and active Scandinavian brown bears |
title_full | Plasma proteomics data from hibernating and active Scandinavian brown bears |
title_fullStr | Plasma proteomics data from hibernating and active Scandinavian brown bears |
title_full_unstemmed | Plasma proteomics data from hibernating and active Scandinavian brown bears |
title_short | Plasma proteomics data from hibernating and active Scandinavian brown bears |
title_sort | plasma proteomics data from hibernating and active scandinavian brown bears |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873540/ https://www.ncbi.nlm.nih.gov/pubmed/35242939 http://dx.doi.org/10.1016/j.dib.2022.107959 |
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