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Ecological Research

, Volume 29, Issue 6, pp 1105–1113 | Cite as

Intra-population variation and geographic correlation in Canthon humectus hidalgoensis using FTIR-ATR spectroscopy

  • José R. VerdúEmail author
  • Belén Gallego
  • Jorge M. Lobo
  • Antonio J. Ortiz
  • Vieyle Cortez
  • Gonzalo Halffter
Original Article
  • 302 Downloads

Abstract

In some cases external morphology is not sufficient to discern between populations of a species, as occurs in the dung beetle Canthon humectus hidalgoensis Bates; and much less to determine phenotypic distances between them. FTIR-ATR spectroscopy show several advantages over other identification techniques (e.g. morphological, genetic, and cuticular hydrocarbons analysis) due to the non-invasive manner of the sample preparation, the relative speed of sample analysis and the low-cost of this technology. The infrared spectrum obtained is recognized to give a unique ‘fingerprint’ because vibrational spectra are specific and unique to the molecular nature of the sample. In our study, results showed that proteins, amino acids and aromatic ethers of insect exocuticle have promising discriminative power to discern between different populations of C. h. hidalgoensis. Furthermore, the correlation between geographic distances between populations and the chemical distances obtained by proteins + amino acids + aromatic ethers was statistically significant, showing that the spectral and spatial information available of the taxa together with appropriated chemometric methods may help to a better understanding of the identity, structure, dynamics and diversity of insect populations.

Keywords

Chemical differentiation Dung beetles Multivariate statistical methods Population differentiation Scarabaeidae 

Notes

Acknowledgments

We thank Dr J. Juan and Dr T. Soler for the introduction and technical assistance of FTIR-ATR spectrophotometer. Financial support was provided by the Projects CGL2008/03878/BOS and CGL2011-25544 of the Secretaría de Estado de Investigación-Ministerio de Educación, Ciencia e Innovación, OAPN 762/2012, Ministerio de Agricultura, Alimentación y Medio Ambiente and CONACYT México (49472-Q).

References

  1. Adt I, Toubas D, Pinon JM, Manfait M, Sockalingum GD (2006) FTIR spectroscopy as a potential tool to analyse structural modifications during morphogenesis of Candida albicans. Arch Microbiol 185:277–285PubMedCrossRefGoogle Scholar
  2. Ammar E-D, Alessandro R, Shatters RG Jr, Hall DG (2013) Behavioral, ultrastructural and chemical studies on the honeydew and waxy secretions by nymphs and adults of the Asian citrus psyllid Diaphorina citri (Hemiptera: Psyllidae). PLoS One 8:e64938PubMedCentralCrossRefGoogle Scholar
  3. Andersen SO (1979) Biochemistry of insect cuticle. Ann Rev Entomol 24:29–61CrossRefGoogle Scholar
  4. Anderson MJ, Gorley RN, Clarke KR (2008) PERMANOVA+ for PRIMER: guide to software and statistical methods. PRIMER-E, PlymouthGoogle Scholar
  5. Barth A (2000) The infrared absorption of amino acid side chains. Prog Biophys Mol Biol 74:141–173PubMedCrossRefGoogle Scholar
  6. Barth A, Zscherp C (2002) What vibrations tell us about proteins. Q Rev Biophys 35:369–430PubMedCrossRefGoogle Scholar
  7. Blomquist GJ (2010) Structure and analysis of insect hydrocarbons. In: Blomquist GJ, Bagnères AG (eds) Insect hydrocarbons. Cambridge University Press, Cambridge, pp 19–34CrossRefGoogle Scholar
  8. Carlson DA, Mayer MS, Silhacek DL, James JD, Beroza M, Bierl BA (1971) Sex attractant pheromone of the house fly: isolation, identification and synthesis. Science 174:76–78PubMedCrossRefGoogle Scholar
  9. Charles JP (2010) The regulation of expression of insect cuticle protein genes. Insect Biochem Mol Biol 40:205–213PubMedCrossRefGoogle Scholar
  10. Chen B, Peng X, Wang W, Zhang J, Zhang R (2002) Research on the microstructure of insect cuticle and the strength of a biomimetic preformed hole composite. Micron 33:571–574PubMedCrossRefGoogle Scholar
  11. Clarke KR, Gorley RM (2006) Change in marine communities: an approach to statistical analysis and interpretation. Primer-E Ltd, PlymouthGoogle Scholar
  12. Coates J (2000) Interpretation of infrared spectra, a practical approach. In: Meyers RA (ed) Encyclopedia of analytical chemistry. John Wiley, Chichester, pp 10815–10837Google Scholar
  13. Cole TJ, Ram MS, Dowell FE, Omwega CO, Overholt WA, Ramaswamy SB (2003) Near-infrared spectroscopic method to identify Cotesia flavipes and Cotesia sesamiae (Hymenoptera: Braconidae). Ann Entomol Soc Am 96:865–869CrossRefGoogle Scholar
  14. Cornman RS (2009) Molecular evolution of Drosophila cuticular protein genes. PLoS ONE 4:e8345PubMedCentralPubMedCrossRefGoogle Scholar
  15. Darbro JM, Millar JG, McElfresh S, Mullens BA (2005) Survey of muscalure [(Z)-9-tricosene] on house flies (Diptera: Muscidae) from field populations in California. Environ Entomol 34:1418–1425CrossRefGoogle Scholar
  16. Davies GJG, Knight DP, Vollrath F (2013) Chitin in the silk gland ducts of the spider Nephila edulis and the silkworm Bombyx mori. PLoS ONE 8:e73225PubMedCentralPubMedCrossRefGoogle Scholar
  17. Davis R, Mauer LJ (2010) Fourier transform infrared (FT-IR) spectroscopy: a rapid tool for detection and analysis of foodborne pathogenic bacteria. Appl Microbiol 1:1582–1594Google Scholar
  18. Dronnet S, Lohou C, Christides J-Ph, Bagnères A-G (2006) Cuticular hydrocarbon composition reflects genetic relationship among colonies of the introduced termite Reticulitermes santonensis Feytaud. J Chem Ecol 32:1027–1042PubMedCrossRefGoogle Scholar
  19. Dziuba D (2013) Identification of Propionibacteria to the species level using Fourier transform infrared spectroscopy and artificial neural networks. Pol J Vet Sci 16:351–357PubMedGoogle Scholar
  20. Futahashi R, Okamoto S, Kawasaki H, Zhong YS, Iwanaga M, Mita K, Fujiwara H (2008) Genome-wide identification of cuticular protein genes in the silkworm, Bombyx mori. Insect Biochem Mol Biol 38:1138–1146PubMedCrossRefGoogle Scholar
  21. Gibbs AG (1998) Waterproofing properties of cuticular lipids. Am Zool 38:471–482Google Scholar
  22. Gibbs AG (2002) Lipid melting and cuticular permeability: new insights into an old problem. J Insect Physiol 48:391–400PubMedCrossRefGoogle Scholar
  23. Gibbs AG, Crowe JH (1991) Intra-individual variation in cuticular lipids studied using Fourier transform infrared spectroscopy. J Insect Physiol 37:743–748CrossRefGoogle Scholar
  24. Gibbs AG, Rajpurohit S (2009) Cuticular lipids and water balance. In: Blomquist GJ, Bagnères AG (eds) Insect Hydrocarbons. Cambridge University Press, Cambridge, pp 100–120Google Scholar
  25. Google Inc. (2013) https://www.google.com/earth/
  26. Hadley NF (1994) Water relations of terrestrial arthropods. Academic Press, San DiegoGoogle Scholar
  27. Halffter G (1961) Monografía de las especies norteamericanas del género Canthon Hoffsg. Ciencia (Mex.) 20:225–320Google Scholar
  28. Halffter G, Halffter V, Martínez-Sánchez KM, Moreno CE, Sánchez-Rojas G (2011) Hybridization between subspecies of Canton humectus (say) (Coleoptera: Scarabaeidae). Col Bull 65:425–431CrossRefGoogle Scholar
  29. Hammer Ø, Harper DAT, Ryan PD (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron 4:1–9Google Scholar
  30. Hamodrakas SJ, Willis JH, Iconomidou VA (2002) A structural model of the chitin-binding domain of cuticle proteins. Insect Biochem Mol Biol 32:1577–1583PubMedCrossRefGoogle Scholar
  31. Hayes KD, Ozen BF, Nielsen SS, Mauer LJ (2003) FTIR determination of ligand-induced secondary and tertiary structural changes in bovine plasminogen. J Dairy Res 70:461–466PubMedCrossRefGoogle Scholar
  32. Hori R, Sugiyama J (2003) A combined FT-IR microscopy and principal component analysis on softwood cell walls. Carbohyd Polym 52:449–453CrossRefGoogle Scholar
  33. HeyWhatsThat Path Profiler (2014) http://www.heywhatsthat.com/profiler.html
  34. Iconomidou VA, Chryssikos GD, Gionis V, Willis JH, Hamodrakas SJ (2001) “Soft”-cuticle protein secondary structure as revealed by FTRaman, ATR FT-IR and CD spectroscopy. Insect Biochem Mol Biol 31:877–885PubMedCrossRefGoogle Scholar
  35. Junior WA, Suárez YR, Izida T, Andrade LHC, Lima SM (2008) Intra-and interspecific variation of cuticular hydrocarbon composition in two Ectatomma species (Hymenoptera: Formicidae) based on Fourier transform infrared photoacoustic spectroscopy. Genet Mol Res 7:559–566CrossRefGoogle Scholar
  36. Kaltenpoth K, Kroiss J, Strohm E (2007) The odor of origin: kinship and geographical distance are reflected in the marking pheromone of male beewolves (Philanthus triangulum F., Hymenoptera, Crabronidae). BMC Ecol 7:11Google Scholar
  37. Legendre P, Legendre L (1998) Numerical ecology. 2nd English edition. Elsevier, AmsterdamGoogle Scholar
  38. Malécot G (1991) The Mathematics of Heredity. Freeman, San FranciscoGoogle Scholar
  39. Martin SJ, Vitikainen E, Helanterä H, Drijfhout FP (2008) Chemical basis of nest-mate discrimination in the ant Formica exsecta. P Roy Soc B 275:1271–1278CrossRefGoogle Scholar
  40. Menges F (2013) Spekwin32-optical spectroscopy software, Version 1.71.6.1, 2013, http://www.effemm2.de/spekwin/
  41. Oberg KA, Ruysschaert JM, Goormaghtigh E (2004) The optimization of protein secondary structure determination with infrared and circular dichroism spectra. Eur J Biochem 271:2937–2948PubMedCrossRefGoogle Scholar
  42. Ribeiro da Luz B (2006) Attenuated total reflectance spectroscopy of plant leaves: a tool for ecological and botanical studies. New Phytol 172:305–318CrossRefGoogle Scholar
  43. Samuels AC, Snydera AP, St Amant D, Emge DK, Minter J, Campbell M, Tripathi A (2008) Classification of select category A and B bacteria by Fourier transform infrared spectroscopy. P SPIE 6954:695413-1Google Scholar
  44. Santos C, Fraga ME, Kozakiewicz Z, Lima N (2010) Fourier transform infrared as a powerful technique for the identification and characterization of filamentous fungi and yeasts. Res Microbiol 161:168–175PubMedCrossRefGoogle Scholar
  45. Savic D, Jokovic J, Topisirovic L (2008) Multivariate statistical methods for discrimination of lactobacilli based on their FTIR spectra. Dairy Sci Technol 88:273–290CrossRefGoogle Scholar
  46. Singer TL (1998) Roles of hydrocarbons in the recognition systems of insects. Am Zool 38:394–405Google Scholar
  47. Singh B, Gautam R, Kumar S, Kumar BNV, Nongthomba U, Nandi D, Mukherjee G, Santos V, Somasundaram K, Umapathy S (2012) Application of vibrational microspectroscopy to biology and medicine. Curr Sci India 102:232–244Google Scholar
  48. Socrates G (2001) Infrared and Raman characteristic group frequencies: tables and charts. John WileyGoogle Scholar
  49. Srivastava AK, Iconomidou VA, Chryssikos GD, Gionis V, Kumara K, Hamodrakas SJ (2011) Secondary structure of chorion proteins of the Lepidoptera Pericallia ricini and Ariadne merione by ATR FT-IR and micro-Raman spectroscopy. Int J Biol Macromol 49:317–322PubMedCrossRefGoogle Scholar
  50. Torres CW, Brandt M, Tsutsui ND (2007) The role of cuticular hydrocarbons as chemical cues for nestmate recognition in the invasive Argentine ant (Linepithema humile). Insect Soc 54:363–373CrossRefGoogle Scholar
  51. Tyndale-Biscoe M (1984) Age-grading methods in adult insects: a review. Bull Entomol Res 74:341–377CrossRefGoogle Scholar
  52. Verdú JR (2011) Chill tolerance variability within and among populations in the dung beetle Canthon humectus hidalgoensis along an altitudinal gradient in the mexican semiarid high plateau. J Arid Environ 75:119–124CrossRefGoogle Scholar
  53. Verdú JR, Moreno CE, Sánchez-Rojas G, Numa C, Galante E, Halffter G (2007) Grazing promotes dung beetle diversity in the xeric landscape of a Mexican Biosphere Reserve. Biol Conserv 140:308–317CrossRefGoogle Scholar
  54. Vincent JFV, Wegst UGK (2004) Design and mechanical properties of insect cuticle. Arthropod Struct Dev 33:187–199PubMedCrossRefGoogle Scholar
  55. Whittaker RH (1952) A study of summer foliage insect communities in the Great Smoky Mountains. Ecol Monogr 22:1–44CrossRefGoogle Scholar
  56. Willis JH (2010) Structural cuticular proteins from arthropods: annotation, nomenclature, and sequence characteristics in the genomics era. Insect Biochem Mol Biol 40:189–204PubMedCentralPubMedCrossRefGoogle Scholar
  57. Zhou G, Taylor G, Polle A (2011) FTIR-ATR-based prediction and modelling of lignin and energy contents reveals independent intra-specific variation of these traits in bioenergy poplars. Plant Method 7:9CrossRefGoogle Scholar

Copyright information

© The Ecological Society of Japan 2014

Authors and Affiliations

  • José R. Verdú
    • 1
    Email author
  • Belén Gallego
    • 1
  • Jorge M. Lobo
    • 2
  • Antonio J. Ortiz
    • 3
  • Vieyle Cortez
    • 1
  • Gonzalo Halffter
    • 4
  1. 1.I.U.I. CIBIOUniversidad de AlicanteAlicanteSpain
  2. 2.Departmento de Biodiversidad y Biología EvolutivaMuseo Nacional de Ciencias Naturales-CSICMadridSpain
  3. 3.Departmento de Química Inorgánica y Química OrgánicaUniversidad de JaénJaénSpain
  4. 4.Instituto de Ecología, A.C.XalapaMexico

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