Skip to main content

Analysis of Ionomic Profiles of Canine Hairs Exposed to Lipopolysaccharide (LPS)-Induced Stress

Abstract

The purpose of this study was to provide a new insight on the response of canines to stress exposure; the ionomic profiles of canine hair (2.8 ± 0.3 years, 15.17 ± 2.1 kg) (n = 10) was determined before and after lipopolysaccharide (LPS) injections. LPS was intramuscularly injected to induce inflammatory stress responses which were confirmed by observing increases in the level of serum cortisol, aldosterone, and inflammatory cytokines such as IL-6, IL-1β, and TNF-α. The hair contents of 17 elements were obtained by applying analytical procedures using the inductively coupled plasma mass spectrometry (ICP-MS). The following elements: sodium(Na) and potassium(K) among macro-elements, iron(Fe) and manganese(Mn) among micro-elements, and aluminum(Al), nickel(Ni), and lead(Pb) for toxic elements, showed significant increased levels with the immunological stress. The degree of increase in toxic elements was remarkable with the stress exposure. A forty-five-fold increase seen in Al accumulation with the stress exposure was noteworthy. Although mercury(Hg) and cadmium(Cd) showed decreased levels with the stress exposure, the degree was negligible compared to the level of increase. Correlation pattern between the elements was changed with the immunological stress. Toxic elements became more correlated with macro- or micro-elements than with toxic elements themselves after the stress exposure. Principal component analysis (PCA) showed that LPS challenge shifted the overall hair mineral profiles to a consistent direction changing Al and K up, even in animals with different hair mineral profiles before LPS treatment. In conclusion, the multivariate data processing and study of element distribution patterns provided new information about the ionomic response of the canine hairs to immunological stress, i.e., the ionomic profiles of canine hairs is strongly affected by the stress induced by LPS injections.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  1. Khalid S, Bawazeer N, Joy SS (2014) Variation in macro and trace elements in progression of type 2 diabetes. Sci World J 2014:461591, 9 pp

    Article  Google Scholar 

  2. Wilson L (2010) Nutritional balancing and hair mineral analysis. 4th ed. The Center for Development, Inc. AZ. 698pp

  3. Fleet JC, Replogle R, Salt DE (2011) Systems genetics of mineral metabolism. J Nutr 141:520–525

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Andrews NC (2008) Forging a field: the golden age of iron biology. Blood 112:219–230

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. Hill CH, Matrone G (1970) Chemical parameters in the study of in vivo and in vitro interactions of transition elements. Fed Proc 29:1474–1481

    CAS  PubMed  Google Scholar 

  6. Salt DE, Baxter I, Lahner B (2008) Ionomics and the study of the plant ionome. Annu Rev Plant Physiol Plant Mol Biol 59:709–733

    CAS  Article  Google Scholar 

  7. Baxter I (2009) Ionomics: studying the social network of mineral nutrients. Curr Opin Plant Biol 12:381–386

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. Baxter I (2015) Should we treat the ionome as a combination of individual elements, or should we be deriving novel combined traits? J Exp Bot 66:2127–2131

    CAS  Article  PubMed  Google Scholar 

  9. Ardini F, Soggia F, Abelmoschi ML, Magi E, Grotti M (2013) Ionomic profiling of Nicotiana langsdorffii wild-type and mutant genotypes exposed to abiotic stresses. Anal Bioanal Chem 405:665–677

    CAS  Article  PubMed  Google Scholar 

  10. Lahner B, Gong J, Mahmoudian M, Smith EL, Abid KB, Rogers EE, Guerinot ML, Harper JF, Ward JM, McIntyre L, Schroeder JI, Salt DE (2003) Genomic scale profiling of nutrient and trace elements in Arabidopsis thaliana. Nat Biotechnol 21:1215–1221

    CAS  Article  PubMed  Google Scholar 

  11. Danku JMC, Gumaelius L, Baxter I, Salt DE (2009) A high-throughput method for Saccharomyces cerevisiae (yeast) ionomics. J Anal At Spectrom 24:103–107

    CAS  Article  Google Scholar 

  12. Baxter IR, Vitek O, Lahner B, Muthukumar B, Borghi M, Morrissey J, Guerinot ML, Salt DE (2008) The leaf ionome as a multivariable system to detect a plant’s physiological status. Proc Natl Acad Sci U S A 105:12081–12086

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Ciavardelli D, Ammendola S, Ronci M, Consalvo A, Marzano V, Lipoma M, Sacchetta P, Federici G, Di Ilio C, Battistoni A, Urbani A (2011) Phenotypic profile linked to inhibition of the major Zn influx system in Salmonella enterica: proteomics and ionomics investigations. Mol Biosyst 7:608–619

    CAS  Article  PubMed  Google Scholar 

  14. Chen Z, Watanabe T, Shinano T, Okazaki K, Mitsuru O (2009) Rapid characterization of plant mutants with an altered ion-profile: a case study using Lotus japonicus. New Phytol 181:795–801

    CAS  Article  PubMed  Google Scholar 

  15. Chen Z, Watanabe T, Shinano T, Ezawa T, Wasaki J, Kimura K, Osaki M, Zhu Y-G (2009) Element interconnections in Lotus japonicus: a systematic study of the effects of elements additions on different natural variants. Soil Sci Plant Nutr 55:91–101

    CAS  Article  Google Scholar 

  16. Pereira R, Ribeiro R, Gonçalves F (2004) Scalp hair analysis as a tool in assessing human exposure to heavy metals (S. Domingos mine, Portugal). Sci Total Environ 327:81–92

    CAS  Article  PubMed  Google Scholar 

  17. Nadal M, Bocio A, Schuhmacher M, Domingo JL (2005) Monitoring metals in the population living in the vicinity of a hazardous waste incinerator: levels in hair of school children. Biol Trace Elem Res 104:203–213

    CAS  Article  PubMed  Google Scholar 

  18. Benderli Cihan Y, Oztürk Yıldırım S (2011) A discriminant analysis of trace elements in scalp hair of healthy controls and stage-IIIB non-small cell lung cancer (NSCLC) patients. Biol Trace Elem Res 144:272–294

    Article  PubMed  Google Scholar 

  19. Golasik M, Przybyłowicz A, Woźniak A, Herman M, Gawęcki W, Golusiński W, Walas S, Krejpcio Z, Szyfter K, Florek E, Piekoszewski W (2015) Essential metals profile of the hair and nails of patients with laryngeal cancer. J Trace Elem Med Biol 31:67–73

    CAS  Article  PubMed  Google Scholar 

  20. Anderson NB (1998) Levels of analysis in health science. A framework for integrating sociobehavioral and biomedical research. Ann N Y Acad Sci 840:563–576

    CAS  Article  PubMed  Google Scholar 

  21. Baum A, Posluszny DM (1999) Health psychology: mapping biobehavioral contributions to health and illness. Annu Rev Psychol 50:137–163

    CAS  Article  PubMed  Google Scholar 

  22. Wołowiec P, Michalak I, Chojnacka K, Mikulewicz M (2013) Hair analysis in health assessment. Clin Chim Acta 419:139–171

    Article  PubMed  Google Scholar 

  23. Webel DM, Finck BN, Baker DH, Johnson RW (1997) Time course of increased plasma cytokines, cortisol, and urea nitrogen in pigs following intraperitoneal injection of lipopolysaccharide. J Anim Sci 75:1514–1520

    CAS  PubMed  Google Scholar 

  24. Jepson MM, Pell JM, Bates PC, Millward DJ (1986) The effects of endotoxaemia on protein metabolism in skeletal muscle and liver of fed and fasted rats. Biochem J 235:329–336

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. Fong Y, Moldawer LL, Marano M, Wei H, Barber A, Manogue K, Tracey KJ, Kuo G, Fischman DA, Cerami A, Lowry SF (1989) Cachectin/TNF or IL-1 alpha induces cachexia with redistribution of body proteins. Am J Physiol 256:R659–R665

    CAS  PubMed  Google Scholar 

  26. Goodman MN (1991) Tumor necrosis factor induces skeletal muscle protein breakdown in rats. Synergism with interleukin-1. Am J Physiol 260:E727–E730

    CAS  PubMed  Google Scholar 

  27. Klasing KC, Laurin DE, Peng RK, Fry DM (1987) Immunologically mediated growth depression in chicks: Influence of feed intake, corticosterone and interleukin-1. J Nutr 117:1629–1637

    CAS  PubMed  Google Scholar 

  28. Habib A, Finn AV (2014) The role of iron metabolism as a mediator of macrophage inflammation and lipid handling in atherosclerosis. Front Pharmacol 5: article #195

  29. O’Neal SL, Zheng W (2015) Manganese toxicity upon overexposure: a decade in review. Curr Environ Health Rep 2:315–328

    Article  PubMed  PubMed Central  Google Scholar 

  30. Becaria A, Campbell A, Bondy SC (2002) Aluminum as a toxicant. Toxicol Ind Health 18:309–320

    CAS  Article  PubMed  Google Scholar 

  31. Yokel RA (2006) Blood–brain barrier flux of aluminum, manganese, iron and other metals suspected to contribute to metal-induced neurodegeneration. J Alzheimers Dis 10:223–253

    PubMed  Google Scholar 

  32. Komatsu F, Kagawa Y, Kawabata T, Kaneko Y, Kudoh H, Purvee B, Otgon J, Chimedregzen U (2012) Influence of essential trace minerals and micronutrient insufficiencies on harmful metal overload in a Mongolian patient with multiple sclerosis. Curr Aging Sci 5:112–125

    CAS  Article  PubMed  Google Scholar 

  33. Pasha Q, Malik SA, Iqbal J, Shah MH (2007) Characterization and distribution of the selected metals in the scalp hair of cancer patients in comparison with normal donors. Biol Trace Elem Res 118:207–216

    CAS  Article  PubMed  Google Scholar 

  34. Ashraf W, Jaffar M, Mohammed D, Iqbal J (1995) Utilization of scalp hair for evaluating epilepsy in male and female groups of the Pakistan population. Sci Total Environ 164:69–73

    CAS  Article  PubMed  Google Scholar 

  35. Khalique A, Ahmad S, Anjum T, Jaffar M, Shah MH, Shaheen N, Tariq SR, Manzoor S (2005) A comparative study based on gender and age dependence of selected metals in scalp hair. Environ Monit Assess 104:45–57

    CAS  Article  PubMed  Google Scholar 

  36. Watanabe T, Broadley MR, Jansen S, White PJ, Takada J, Satake K, Takamatsu T, Tuah SJ, Osaki M (2007) Evolutionary control of leaf element composition in plants. New Phytol 174:516–523

    CAS  Article  PubMed  Google Scholar 

  37. Broadley MR, Hammond JP, King GJ, Astley D, Bowen HC, Meacham MC, Mead A, Pink DA, Teakle GR, Hayden RM, Spracklen WP, White PJ (2008) Shoot calcium and magnesium concentrations differ between subtaxa, are highly heritable, and associate with potentially pleiotropic loci in Brassica oleracea. Plant Physiol 146:1707–1720

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. White PJ, Broadley MR (2005) Biofortifying crops with essential mineral elements. Trends Plant Sci 10:586–593

    Article  PubMed  Google Scholar 

  39. Vreugdenhil D, Aarts MGM, Koornneef M, Nelissen H, Ernst WHO (2004) Natural variation and QTL analysis for cationic mineral content in seeds of Arabidopsis thaliana. Plant Cell Environ 27:828–839

    CAS  Article  Google Scholar 

  40. Komatsu F, Kagawa Y, Kawabata T, Kaneko Y, Chimedregzen U, Purvee B, Otgon J (2011) A high accumulation of hair minerals in Mongolian people: 2(nd) report; influence of manganese, iron, lead, cadmium and aluminum to oxidative stress, parkinsonism and arthritis. Curr Aging Sci 4:42–56

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was carried out with the support of “Cooperative Research Program for Agriculture Science & Technology Development (Project title: Development of screening and management technique for health status of detector dogs using noninvasive tools, Project No. 00957703)” Rural Development Administration, Republic of Korea.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Myung Il Chung.

Ethics declarations

Ethical Approval

All procedures performed in studies involving animals were in accordance with an approved Institutional Animal Care and Use Committee (IACUC) protocol of the National Institute of Animal Science, Republic of Korea.

Conflict of Interest

The authors declare that they have no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

So, KM., Lee, Y., Bok, J.D. et al. Analysis of Ionomic Profiles of Canine Hairs Exposed to Lipopolysaccharide (LPS)-Induced Stress. Biol Trace Elem Res 172, 364–371 (2016). https://doi.org/10.1007/s12011-015-0611-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12011-015-0611-1

Keywords

  • Dog hair
  • Ionomic profile
  • Principle component analysis
  • LPS stress