Skip to main content
SpringerLink
Log in

Metabolic Adaptation in Hibernating American Black Bears: Exploring Immobilization Protection with Mass Spectral Data and Computational Methods

  • Conference paper
  • First Online:
Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2 (FTC 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 814))

Included in the following conference series:

  • 182 Accesses

Abstract

American black bears (Ursus americanus) have adapted the ability to maintain homeostasis during a 4–6-month hibernation period and emerge from their dens without experiencing thrombosis, muscle loss, and other physiological detriments typically seen in immobile humans. Metabolomics has been shown to be a driver for other omic pathways and a reliable biomarker in observing physiological shifts occurring in critically ill patients and individuals with metabolic disease. Thus, understanding the hibernating bears’ metabolic regulation may have translational interest in clinical settings for patients whose conditions are exacerbated by immobility. Blood samples were collected from bears in the northern Minnesota region during three time periods: summer (July), early-denning (December), and late-denning (March). Biocrates MxP Quant 500 kit-based assay monitored for 630 metabolites and lipids for a targeted metabolic profiling dataset of 75 bear plasma samples. To identify metabolites influencing seasonal modulations, a sparse partial least squares discrimination analysis (sPLS-DA) model was utilized to produce sample plots in conjunction with correlation circles plots. We focused on the seasonal differences between 34 metabolites processed using liquid-chromatography (LC) methods and significances were confirmed using Kruskal-Wallis statistical tests. We identified 22 key metabolites, many of which are involved in protein synthesis and the metabolizing of lipids that could be driving homeostasis between summer and winter and between early- and late-denning. These key metabolites provide a baseline for discovering which pathways could influence the black bears’ ability to modulate their metabolisms for winter. Future works should analyze other metabolite classes, especially those of similar function or within the same pathways of the ones identified here to understand the specific dynamics of the biosynthetic pathways driving homeostasis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Billman, G.E.: Homeostasis: the underappreciated and far too often ignored central organizing principle of physiology. Front. Physiol. 11, 200 (2020). https://doi.org/10.3389/fphys.2020.00200

    Article  Google Scholar 

  2. Parry, S.M., Puthucheary, Z.A.: The impact of extended bed rest on the musculoskeletal system in the critical care environment. Extreme Physiol. Med. 4, 16 (2015). https://doi.org/10.1186/s13728-015-0036-7

    Article  Google Scholar 

  3. Fröbert, O., Frøbert, A.M., Kindberg, J., Arnemo, J.M., Overgaard, M.T.: The brown bear as a translational model for sedentary lifestyle-related diseases. J. Intern. Med. 287(3), 263–270 (2020). https://doi.org/10.1111/joim.12983

    Article  Google Scholar 

  4. Stenvinkel, P., Jani, A.H., Johnson, R.J.: Hibernating bears (Ursidae): metabolic magicians of definite interest for the nephrologist. Kidney Int. 83(2), 207–212 (2013). https://doi.org/10.1038/ki.2012.396

    Article  Google Scholar 

  5. Seebacher, F., Beaman, J.: Evolution of plasticity: metabolic compensation for fluctuating energy demands at the origin of life. J. Exp. Biol. 225(5), jeb243214 (2022). https://doi.org/10.1242/jeb.243214

  6. Booth, F.W., Roberts, C.K., Thyfault, J.P., Ruegsegger, G.N., Toedebusch, R.G.: Role of inactivity in chronic diseases: evolutionary insight and pathophysiological mechanisms. Physiol. Rev. 97(4), 1351–1402 (2017). https://doi.org/10.1152/physrev.00019.2016

    Article  Google Scholar 

  7. Cotton, C.J.: Skeletal muscle mass and composition during mammalian hibernation. J. Exp. Biol. 219(2), 226–234 (2016). https://doi.org/10.1242/jeb.125401

    Article  Google Scholar 

  8. Iles, T.: Big data analyses to identify physiologic adaptive responses in the American Black Bear (Ursus Americanus): From Basic Biological Knowledge to Clinical Applications, November 2017. http://conservancy.umn.edu/handle/11299/201695. Accessed 27 Oct 2022

  9. Iles, T.L., Laske, T.G., Garshelis, D.L., Iaizzo, P.A.: Blood clotting behavior is innately modulated in Ursus americanus during early and late denning relative to summer months. J. Exp. Biol. 220(3), 455–459 (2017). https://doi.org/10.1242/jeb.141549

    Article  Google Scholar 

  10. Wolfe, R.R.: Regulation of skeletal muscle protein metabolism in catabolic states. Curr. Opin. Clin. Nutr. Metab. Care 8(1), 61–65 (2005). https://doi.org/10.1097/00075197-200501000-00009

    Article  Google Scholar 

  11. Costa dos Santos, G., Renovato-Martins, M., de Brito, N.M.: The remodel of the ‘central dogma’: a metabolomics interaction perspective. Metabolomics 17(5), 48 (2021). https://doi.org/10.1007/s11306-021-01800-8

    Article  Google Scholar 

  12. de Lorenzo, V.: From the selfish gene to selfish metabolism: Revisiting the central dogma. BioEssays 36(3), 226–235 (2014). https://doi.org/10.1002/bies.201300153

    Article  Google Scholar 

  13. Gonzalez-Covarrubias, V., Martínez-Martínez, E., del Bosque-Plata, L.: The potential of metabolomics in biomedical applications. Metabolites 12(2), 194 (2022). https://doi.org/10.3390/metabo12020194

    Article  Google Scholar 

  14. Berg von Linde, M., Arevström, L., Fröbert, O.: Insights from the Den: how hibernating bears may help us understand and treat human disease. Clin. Transl. Sci. 8(5), 601–605 (2015). https://doi.org/10.1111/cts.12279

    Article  Google Scholar 

  15. Bertile, F., Habold, C., Le Maho, Y., Giroud, S.: Body protein sparing in hibernators: a source for biomedical innovation. Front. Physiol. 12 (2021). https://www.frontiersin.org/articles/10.3389/fphys.2021.634953. Accessed 24 Mar 2023

  16. R: The R Project for Statistical Computing. https://www.r-project.org/. Accessed 28 Mar 2023

  17. Troyanskaya, O., et al.: Missing value estimation methods for DNA microarrays. Bioinformatics 17(6), 520–525 (2001). https://doi.org/10.1093/bioinformatics/17.6.520

    Article  Google Scholar 

  18. Cao, K.-A.L., et al.: mixOmics: Omics Data Integration Project. Bioconductor version: Release (3.16) (2023). https://doi.org/10.18129/B9.bioc.mixOmics

  19. Swenson, J.E., Adamič, M., Huber, D., Stokke, S.: Brown bear body mass and growth in northern and southern Europe. Oecologia 153(1), 37–47 (2007). https://doi.org/10.1007/s00442-007-0715-1

    Article  Google Scholar 

  20. Rigano, K.S., et al.: Life in the fat lane: seasonal regulation of insulin sensitivity, food intake, and adipose biology in brown bears. J. Comp. Physiol. B 187(4), 649–676 (2017). https://doi.org/10.1007/s00360-016-1050-9

    Article  Google Scholar 

  21. Shimozuru, M., Nagashima, A., Tanaka, J., Tsubota, T.: Seasonal changes in the expression of energy metabolism-related genes in white adipose tissue and skeletal muscle in female Japanese black bears. Comp. Biochem. Physiol. B. Biochem. Mol. Biol. 196–197, 38–47 (2016). https://doi.org/10.1016/j.cbpb.2016.02.001

    Article  Google Scholar 

  22. Tapia-Rojas, C., et al.: Is L-methionine a trigger factor for Alzheimer’s-like neurodegeneration?: changes in Aβ oligomers, tau phosphorylation, synaptic proteins, Wnt signaling and behavioral impairment in wild-type mice. Mol. Neurodegener. 10(1), 62 (2015). https://doi.org/10.1186/s13024-015-0057-0

    Article  Google Scholar 

  23. Miyazaki, M., Shimozuru, M., Tsubota, T.: Skeletal muscles of hibernating black bears show minimal atrophy and phenotype shifting despite prolonged physical inactivity and starvation. PLoS ONE 14(4), e0215489 (2019). https://doi.org/10.1371/journal.pone.0215489

    Article  Google Scholar 

  24. Prescott, A.G.: Chapter Eight - Two-oxoacid-dependent dioxygenases: inefficient enzymes or evolutionary driving force? In: Romeo, J.T., Ibrahim, R., Varin, L., De Luca, V. (eds.) Recent Advances in Phytochemistry. Evolution of Metabolic Pathways, vol. 34, pp. 249–284. Elsevier (2000). https://doi.org/10.1016/S0079-9920(00)80009-X

  25. Gough, L.A., et al.: A critical review of citrulline malate supplementation and exercise performance. Eur. J. Appl. Physiol. 121(12), 3283–3295 (2021). https://doi.org/10.1007/s00421-021-04774-6

    Article  Google Scholar 

  26. Lerma, E.V.: “Approach to the patient with renal disease,” Prim. Care, vol. 35, no. 2, pp. 183–194, v, Jun. 2008, doi: https://doi.org/10.1016/j.pop.2008.02.001

  27. Karna, E., Szoka, L., Huynh, T.Y.L., Palka, J.A.: Proline-dependent regulation of collagen metabolism. Cell. Mol. Life Sci. 77(10), 1911–1918 (2020). https://doi.org/10.1007/s00018-019-03363-3

    Article  Google Scholar 

  28. Trexler, E.T., et al.: International society of sports nutrition position stand: Beta-Alanine. J. Int. Soc. Sports Nutr. 12, 30 (2015). https://doi.org/10.1186/s12970-015-0090-y

    Article  Google Scholar 

  29. Wu, G., et al.: Proline and hydroxyproline metabolism: implications for animal and human nutrition. Amino Acids 40(4), 1053–1063 (2011). https://doi.org/10.1007/s00726-010-0715-z

    Article  Google Scholar 

  30. Ostojic, S.M.: Dietary creatine and kidney function in adult population: NHANES 2017–2018. Food Sci. Nutr. 9(4), 2257–2259 (2021). https://doi.org/10.1002/fsn3.2200

    Article  Google Scholar 

  31. Malaguarnera, M.: Chapter 48 - Biomarkers of statin-induced musculoskeletal pain: Vitamin D and beyond. In: Rajendram, R., Patel, V.B., Preedy, V.R., Martin, C.R. (eds.) Features and Assessments of Pain, Anaesthesia, and Analgesia. Academic Press, pp. 539–549 (2022). https://doi.org/10.1016/B978-0-12-818988-7.00015-7

  32. Ni, Y.-Q., Liu, Y.-S.: New insights into the roles and mechanisms of spermidine in aging and age-related diseases. Aging Dis. 12(8), 1948–1963 (2021). https://doi.org/10.14336/AD.2021.0603

    Article  MathSciNet  Google Scholar 

  33. Zdrojewicz, Z., Lachowski, M.: The importance of putrescine in the human body. Postepy Hig. Med. Doswiadczalnej Online 68, 393–403 (2014). https://doi.org/10.5604/17322693.1098147

    Article  Google Scholar 

  34. Tang, Q., Tan, P., Ma, N., Ma, X.: Physiological functions of threonine in animals: beyond nutrition metabolism. Nutrients 13(8), 2592 (2021). https://doi.org/10.3390/nu13082592

    Article  Google Scholar 

  35. Ki, Y., Lim, C.: Sleep-promoting effects of threonine link amino acid metabolism in Drosophila neuron to GABAergic control of sleep drive. eLife 8, e40593. https://doi.org/10.7554/eLife.40593

  36. Shimozuru, M., Kamine, A., Tsubota, T.: Changes in expression of hepatic genes involved in energy metabolism during hibernation in captive, adult, female Japanese black bears (Ursus thibetanus japonicus). Comp. Biochem. Physiol. B. Biochem. Mol. Biol. 163(2), 254–261 (2012). https://doi.org/10.1016/j.cbpb.2012.06.007

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Surgery Medical School, University of Minnesota, Minneapolis, MN, USA

    Myana Anderson, Beth Lusczek, Kevin Murray, Sayeed Ikramuddin & Tinen L. Iles

  2. Department of Cardiology B, Odense University Hospital and, University of Southern Denmark, Odense C, Denmark

    Jens F. Lassen & Tinen L. Iles

Authors
  1. Myana Anderson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beth Lusczek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kevin Murray
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jens F. Lassen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sayeed Ikramuddin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tinen L. Iles
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tinen L. Iles .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Anderson, M., Lusczek, B., Murray, K., Lassen, J.F., Ikramuddin, S., Iles, T.L. (2023). Metabolic Adaptation in Hibernating American Black Bears: Exploring Immobilization Protection with Mass Spectral Data and Computational Methods. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2. FTC 2023. Lecture Notes in Networks and Systems, vol 814. Springer, Cham. https://doi.org/10.1007/978-3-031-47451-4_11

Download citation

Publish with us

Policies and ethics

Search

Navigation