DNA barcoding in diet assessment

DNA barcoding in diet assessment is the use of DNA barcoding to analyse the diet of organisms.[1][2] and further detect and describe their trophic interactions.[3][4] This approach is based on the identification of consumed species by characterization of DNA present in dietary samples,[5] e.g. individual food remains, regurgitates, gut and fecal samples, homogenized body of the host organism, target of the diet study (for example with whole body of insects[6]).

The DNA sequencing approach to be adopted depends on the diet breadth of the target consumer. For organisms feeding on one or only few species, traditional Sanger sequencing techniques can be used. For polyphagous species with diet items more difficult to identify, it is conceivable to determine all consumed species using NGS methodology.[7]

The barcode markers utilized for amplification will differ depending on the diet of the target organism. For herbivore diets, the standard DNA barcode loci will differ significantly depending on the plant taxonomic level.[8] Therefore, for identifying plant tissue at the taxonomic family or genus level, the markers rbcL and trn-L-intron are used, which differ from the loci ITS2, matK, trnH-psbA (noncoding intergenic spacer) used to identify diet items to genus and species level.[9] For animal prey, the most broadly used DNA barcode markers to identify diets are the mitochondrial cytocrome C oxydase (COI) and cytochrome b (cytb).[10] When the diet is broad and diverse, DNA metabarcoding is used to identify most of the consumed items.[11]

Advantages

A major benefit of using DNA barcoding in diet assessment is the ability to provide high taxonomic resolution of consumed species.[12] Indeed, when compared to traditional morphological analysis, DNA barcoding enables a more reliable separation of closely related taxa reducing the observed bias.[13][14] Moreover, DNA barcoding enables to detect soft and highly digested items, not recognisable through morphological identification.[15] For example, Arachnids feed on pre-digested bodies of insects or other small animals and their stomach content is too decomposed and morphologically unrecognizable using traditional methods such as microscopy.[16]

When investigating herbivores diet, DNA metabarcoding enables detection of highly digested plant items with a higher number of taxa identified compared to microhistology and macroscopic analysis.[17][18] For instance, Nichols et al. (2016) highlighted the taxonomic precision of metabarcoding on rumen contents, with on average 90% of DNA-sequences being identified to genus or species level in comparison to 75% of plant fragments recognised with macroscopy. Morevoer, another empirically tested advantage of metabarcoding compared to traditional time-consuming methods, involves higher cost efficiency.[19] Finally, with its fine resolution, DNA barcoding represents a crucial tool in wildlife management to identify the feeding habits of endangered species and animals that can cause feeding damages to the environment.[20]

Challenges

With DNA barcoding it is not possible to retrieve information about sex or age of prey species, which can be crucial. This limitation can anyway be overcome with an additional step in the analysis by using microsatellite polymorphism and Y-chromosome amplification.[21][22] Moreover, DNA provides detailed information of the most recent events (e.g. 24–48 hr) but it is not able to provide a longer dietary prospect unless a continuous sampling is conducted.[23] Additionally, when using generic primers that amplify ‘barcode’ regions from a broad range of food species, the amplifiable host DNA may largely outnumber the presence of prey DNA, complicating prey detection. However, a strategy to prevent the host DNA amplification can be the addition of a predator-specific blocking primer.[24][25] [26] Indeed, blocking primers for suppressing amplification of predator DNA allows the amplification of the other vertebrate groups and produces amplicon mixes that are predominately food DNA.[27][28]

Despite the improvement of diet assessment via DNA barcoding, secondary consumption (prey of the prey, parasites, etc.) still represents a confounding factor. In fact, some secondary prey may result in the analysis as primary prey items, introducing a bias. However, due to a much lower total biomass and to a higher level of degradation, DNA of secondary prey might represent only a minor part of sequences recovered compared to primary prey.[29]

The quantitative interpretation of DNA barcoding results is not straightforward.[30] There have been attempts to use the number of sequences recovered to estimate the abundance of prey species in diet contents (e.g. gut, faeces). For example, if the wolf ate more moose than wild boar, there should be more moose DNA in their gut, and thus, more moose sequences are recovered. Despite the evidence for general correlations between the sequence number and the biomass, actual evaluations of this method have been unsuccessful.[31][32] This can be explained by the fact that tissues originally contain different densities of DNA and can be digested differently.[33]

Examples

Mammals

Mammals diet is widely studied using DNA barcoding and metabarcoding. Some differences in the methodology can be observed depending on the feeding strategy of the target mammal species, i.e. whether it is herbivore, carnivore, or omnivore.

For herbivore mammal species, DNA is usually extracted from faeces samples[34][35][36][37] or rumen contents collected from road kills or animals killed during regular hunting.[38] Within DNA barcoding, the trnL approach can be used to identify plant species by using a very short but informative fragment of chloroplast DNA (P6 loop of the chloroplast trnL (UAA) intron).[39] Potentially, this application is applicable to all herbivorous species feeding on angiosperms and gymnosperms[39] Alternatively to the trnL approach, the markers rbcL, ITS2, matK, trnH-psbA can be used to amplify plant species.

When studying small herbivores with a cryptic life style, such as voles and lemmings, DNA barcoding of ingested plants can be a crucial tool giving an accurate picture of food utilization.[40] Additionally, the fine resolution in plant identification obtained with DNA barcoding allows researchers to understand change in diet composition over time and variability among individuals, as observed in the alpine chamois (Rupicapra rupicapra).[41] Between October and November, by analyzing the faeces composition via DNA barcoding, the alpine chamois showed a shift in diet preferences. Also, different diet categories were observed amongst individuals within each month.[42]

Faeces of wolf (Canis lupus) collected in Sweden

For carnivores, the use of non-invasive approaches is crucial especially when dealing with elusive and endangered species. Diet assessment through DNA barcoding of faeces can have a greater efficiency in prey species detection compared to traditional diet analysis, which mostly rely upon the morphological identification of undigested hard remains in the faeces.[43] Estimating the vertebrate diet diversity of the leopard cat (Prionailurus bengalensis) in Pakistan, Shehzad et al. (2012) identified a total of 18 prey taxa using DNA barcoding on faeces. Eight distinct bird taxa were reported, while previous studies based on conventional methods did not identify any bird species in the leopard cat diet.[44] Another example is the use of DNA barcoding to identify soft remains of prey in the stomach contents of predators e.g. grey seals (Halichoerus grypus) and harbour porpoises (Phocoena phocoena).[45]

DNA metabarcoding is a game changer for the study of complex diets, such as for omnivores predators, feeding on many different species with both plants and animal origin.[46][47] This methodology does not require knowledge about the food consumed by animals in the habitat they occupy.[48] In a study on brown bear (Ursus arctos) diet, DNA metabarcoding allowed accurate reconstruction of a wide range of taxonomically different items present in faecal samples collected in the field.[49]

See also

Reference
  1. King RA, Read DS, Traugott M, Symondson WO (February 2008). "Molecular analysis of predation: a review of best practice for DNA-based approaches". Molecular Ecology. 17 (4): 947–63. doi:10.1111/j.1365-294X.2007.03613.x. PMID 18208490. S2CID 44796921.
  2. Pompanon F, Deagle BE, Symondson WO, Brown DS, Jarman SN, Taberlet P (April 2012). "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology. 21 (8): 1931–50. doi:10.1111/j.1365-294X.2011.05403.x. PMID 22171763. S2CID 10013333.
  3. Sheppard SK, Harwood JD (October 2005). "Advances in molecular ecology: tracking trophic links through predator-prey food-webs". Functional Ecology. 19 (5): 751–762. doi:10.1111/j.1365-2435.2005.01041.x.
  4. Kress WJ, García-Robledo C, Uriarte M, Erickson DL (January 2015). "DNA barcodes for ecology, evolution, and conservation". Trends in Ecology & Evolution. 30 (1): 25–35. doi:10.1016/j.tree.2014.10.008. PMID 25468359.
  5. Pompanon F, Deagle BE, Symondson WO, Brown DS, Jarman SN, Taberlet P (April 2012). "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology. 21 (8): 1931–50. doi:10.1111/j.1365-294x.2011.05403.x. PMID 22171763. S2CID 10013333.
  6. Harwood JD, Desneux N, Yoo HJ, Rowley DL, Greenstone MH, Obrycki JJ, O'Neil RJ (October 2007). "Tracking the role of alternative prey in soybean aphid predation by Orius insidiosus: a molecular approach". Molecular Ecology. 16 (20): 4390–400. doi:10.1111/j.1365-294x.2007.03482.x. PMID 17784913. S2CID 21211301.
  7. Pompanon F, Deagle BE, Symondson WO, Brown DS, Jarman SN, Taberlet P (April 2012). "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology. 21 (8): 1931–50. doi:10.1111/j.1365-294x.2011.05403.x. PMID 22171763. S2CID 10013333.
  8. Kress WJ, García-Robledo C, Uriarte M, Erickson DL (January 2015). "DNA barcodes for ecology, evolution, and conservation". Trends in Ecology & Evolution. 30 (1): 25–35. doi:10.1016/j.tree.2014.10.008. PMID 25468359.
  9. Kress WJ, García-Robledo C, Uriarte M, Erickson DL (January 2015). "DNA barcodes for ecology, evolution, and conservation". Trends in Ecology & Evolution. 30 (1): 25–35. doi:10.1016/j.tree.2014.10.008. PMID 25468359.
  10. Tobe SS, Kitchener A, Linacre A (December 2009). "Cytochrome b or cytochrome c oxidase subunit I for mammalian species identification—An answer to the debate". Forensic Science International: Genetics Supplement Series. 2 (1): 306–307. doi:10.1016/j.fsigss.2009.08.053. ISSN 1875-1768.
  11. Jakubavičiūtė E, Bergström U, Eklöf JS, Haenel Q, Bourlat SJ (October 2017). "DNA metabarcoding reveals diverse diet of the three-spined stickleback in a coastal ecosystem". PLOS ONE. 12 (10): e0186929. Bibcode:2017PLoSO..1286929J. doi:10.1371/journal.pone.0186929. PMC 5653352. PMID 29059215.
  12. Garnick S, Barboza PS, Walker JW (July 2018). "Assessment of Animal-Based Methods Used for Estimating and Monitoring Rangeland Herbivore Diet Composition". Rangeland Ecology & Management. 71 (4): 449–457. doi:10.1016/j.rama.2018.03.003.
  13. Santos T, Fonseca C, Barros T, Godinho R, Bastos-Silveira C, Bandeira V, Rocha RG (2015-05-20). "Using stomach contents for diet analysis of carnivores through DNA barcoding". Wildlife Biology in Practice. 11 (1). doi:10.2461/wbp.2015.11.4.
  14. Valentini A, Pompanon F, Taberlet P (February 2009). "DNA barcoding for ecologists". Trends in Ecology & Evolution. 24 (2): 110–7. doi:10.1016/j.tree.2008.09.011. PMID 19100655.
  15. Piñol J, San Andrés V, Clare EL, Mir G, Symondson WO (January 2014). "A pragmatic approach to the analysis of diets of generalist predators: the use of next-generation sequencing with no blocking probes" (PDF). Molecular Ecology Resources. 14 (1): 18–26. doi:10.1111/1755-0998.12156. PMID 23957910. S2CID 206946302.
  16. Agustí N, Shayler SP, Harwood JD, Vaughan IP, Sunderland KD, Symondson WO (2003). "Collembola as alternative prey sustaining spiders in arable ecosystems: prey detection within predators using molecular markers". Molecular Ecology. 12 (12): 3467–3475. doi:10.1046/j.1365-294X.2003.02014.x. PMID 14629361. S2CID 7985256.
  17. Nichols RV, Åkesson M, Kjellander P (June 2016). "Diet Assessment Based on Rumen Contents: A Comparison between DNA Metabarcoding and Macroscopy". PLOS ONE. 11 (6): e0157977. Bibcode:2016PLoSO..1157977N. doi:10.1371/journal.pone.0157977. PMC 4913902. PMID 27322387.
  18. Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P (August 2009). "Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures". Frontiers in Zoology. 6 (1): 16. doi:10.1186/1742-9994-6-16. PMC 2736939. PMID 19695081.
  19. Stein ED, Martinez MC, Stiles S, Miller PE, Zakharov EV (April 2014). Casiraghi M (ed.). "Is DNA barcoding actually cheaper and faster than traditional morphological methods: results from a survey of freshwater bioassessment efforts in the United States?". PLOS ONE. 9 (4): e95525. Bibcode:2014PLoSO...995525S. doi:10.1371/journal.pone.0095525. PMC 3995707. PMID 24755838.
  20. Ando H, Fujii C, Kawanabe M, Ao Y, Inoue T, Takenaka A (October 2018). "Evaluation of plant contamination in metabarcoding diet analysis of a herbivore". Scientific Reports. 8 (1): 15563. Bibcode:2018NatSR...815563A. doi:10.1038/s41598-018-32845-w. PMC 6197254. PMID 30349088.
  21. Griffiths R, Tiwari B (December 1993). "Primers for the differential amplification of the sex-determining region Y gene in a range of mammal species". Molecular Ecology. 2 (6): 405–6. doi:10.1111/j.1365-294x.1993.tb00034.x. PMID 8162230. S2CID 43323282.
  22. Taberlet P, Luikart G (September 1999). "Non-invasive genetic sampling and individual identification". Biological Journal of the Linnean Society. 68 (1–2): 41–55. doi:10.1111/j.1095-8312.1999.tb01157.x. ISSN 0024-4066.
  23. Thomsen PF, Kielgast J, Iversen LL, Møller PR, Rasmussen M, Willerslev E (August 2012). "Detection of a diverse marine fish fauna using environmental DNA from seawater samples". PLOS ONE. 7 (8): e41732. Bibcode:2012PLoSO...741732T. doi:10.1371/journal.pone.0041732. PMC 3430657. PMID 22952584.
  24. Vestheim H, Jarman SN (July 2008). "Blocking primers to enhance PCR amplification of rare sequences in mixed samples - a case study on prey DNA in Antarctic krill stomachs". Frontiers in Zoology. 5 (1): 12. doi:10.1186/1742-9994-5-12. PMC 2517594. PMID 18638418.
  25. Shehzad W, Riaz T, Nawaz MA, Miquel C, Poillot C, Shah SA, Pompanon F, Coissac E, Taberlet P (April 2012). "Carnivore diet analysis based on next-generation sequencing: application to the leopard cat (Prionailurus bengalensis) in Pakistan". Molecular Ecology. 21 (8): 1951–65. doi:10.1111/j.1365-294x.2011.05424.x. PMID 22250784. S2CID 205364612.
  26. Jarman SN, McInnes JC, Faux C, Polanowski AM, Marthick J, Deagle BE, Southwell C, Emmerson L (December 2013). "Adélie penguin population diet monitoring by analysis of food DNA in scats". PLOS ONE. 8 (12): e82227. Bibcode:2013PLoSO...882227J. doi:10.1371/journal.pone.0082227. PMC 3864945. PMID 24358158.
  27. Vestheim H, Jarman SN (July 2008). "Blocking primers to enhance PCR amplification of rare sequences in mixed samples - a case study on prey DNA in Antarctic krill stomachs". Frontiers in Zoology. 5 (1): 12. doi:10.1186/1742-9994-5-12. PMC 2517594. PMID 18638418.
  28. Vestheim H, Deagle BE, Jarman SN (October 2010). "Application of blocking oligonucleotides to improve signal-to-noise ratio in a PCR". PCR Protocols. Methods in Molecular Biology. 687. Humana Press. pp. 265–74. doi:10.1007/978-1-60761-944-4_19. ISBN 9781607619437. PMID 20967615.
  29. Jakubavičiūtė E, Bergström U, Eklöf JS, Haenel Q, Bourlat SJ (2017-10-23). "DNA metabarcoding reveals diverse diet of the three-spined stickleback in a coastal ecosystem". PLOS ONE. 12 (10): e0186929. Bibcode:2017PLoSO..1286929J. doi:10.1371/journal.pone.0186929. PMC 5653352. PMID 29059215.
  30. Valentini A, Pompanon F, Taberlet P (February 2009). "DNA barcoding for ecologists". Trends in Ecology & Evolution. 24 (2): 110–7. doi:10.1016/j.tree.2008.09.011. PMID 19100655.
  31. Pompanon F, Deagle BE, Symondson WO, Brown DS, Jarman SN, Taberlet P (April 2012). "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology. 21 (8): 1931–50. doi:10.1111/j.1365-294x.2011.05403.x. PMID 22171763. S2CID 10013333.
  32. Piñol J, San Andrés V, Clare EL, Mir G, Symondson WO (January 2014). "A pragmatic approach to the analysis of diets of generalist predators: the use of next-generation sequencing with no blocking probes" (PDF). Molecular Ecology Resources. 14 (1): 18–26. doi:10.1111/1755-0998.12156. PMID 23957910. S2CID 206946302.
  33. Deagle BE, Chiaradia A, McInnes J, Jarman SN (2010-06-17). "Pyrosequencing faecal DNA to determine diet of little penguins: is what goes in what comes out?". Conservation Genetics. 11 (5): 2039–2048. doi:10.1007/s10592-010-0096-6. ISSN 1566-0621. S2CID 19992150.
  34. Kowalczyk R, Taberlet P, Coissac E, Valentini A, Miquel C, Kamiński T, Wójcik JM (February 2011). "Influence of management practices on large herbivore diet—Case of European bison in Białowieża Primeval Forest (Poland)". Forest Ecology and Management. 261 (4): 821–828. doi:10.1016/j.foreco.2010.11.026.
  35. Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P (August 2009). "Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures". Frontiers in Zoology. 6 (1): 16. doi:10.1186/1742-9994-6-16. PMC 2736939. PMID 19695081.
  36. Ait Baamrane MA, Shehzad W, Ouhammou A, Abbad A, Naimi M, Coissac E, Taberlet P, Znari M (2012-04-27). "Assessment of the food habits of the Moroccan dorcas gazelle in M'Sabih Talaa, west central Morocco, using the trnL approach". PLOS ONE. 7 (4): e35643. Bibcode:2012PLoSO...735643A. doi:10.1371/journal.pone.0035643. PMC 3338736. PMID 22558187.
  37. Riaz T, Shehzad W, Viari A, Pompanon F, Taberlet P, Coissac E (November 2011). "ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis". Nucleic Acids Research. 39 (21): e145. doi:10.1093/nar/gkr732. PMC 3241669. PMID 21930509.
  38. Nichols RV, Åkesson M, Kjellander P (June 2016). "Diet Assessment Based on Rumen Contents: A Comparison between DNA Metabarcoding and Macroscopy". PLOS ONE. 11 (6): e0157977. Bibcode:2016PLoSO..1157977N. doi:10.1371/journal.pone.0157977. PMC 4913902. PMID 27322387.
  39. Valentini A, Miquel C, Nawaz MA, Bellemain E, Coissac E, Pompanon F, Gielly L, Cruaud C, Nascetti G, Wincker P, Swenson JE, Taberlet P (January 2009). "New perspectives in diet analysis based on DNA barcoding and parallel pyrosequencing: the trnL approach". Molecular Ecology Resources. 9 (1): 51–60. doi:10.1111/j.1755-0998.2008.02352.x. PMID 21564566. S2CID 5308081.
  40. Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P (August 2009). "Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures". Frontiers in Zoology. 6 (1): 16. doi:10.1186/1742-9994-6-16. PMC 2736939. PMID 19695081.
  41. Rayé G, Miquel C, Coissac E, Redjadj C, Loison A, Taberlet P (2010-11-23). "New insights on diet variability revealed by DNA barcoding and high-throughput pyrosequencing: chamois diet in autumn as a case study". Ecological Research. 26 (2): 265–276. doi:10.1007/s11284-010-0780-5. ISSN 0912-3814. S2CID 20754195.
  42. Rayé G, Miquel C, Coissac E, Redjadj C, Loison A, Taberlet P (2010-11-23). "New insights on diet variability revealed by DNA barcoding and high-throughput pyrosequencing: chamois diet in autumn as a case study". Ecological Research. 26 (2): 265–276. doi:10.1007/s11284-010-0780-5. ISSN 0912-3814. S2CID 20754195.
  43. Shehzad W, Riaz T, Nawaz MA, Miquel C, Poillot C, Shah SA, Pompanon F, Coissac E, Taberlet P (April 2012). "Carnivore diet analysis based on next-generation sequencing: application to the leopard cat (Prionailurus bengalensis) in Pakistan". Molecular Ecology. 21 (8): 1951–65. doi:10.1111/j.1365-294x.2011.05424.x. PMID 22250784. S2CID 205364612.
  44. Shehzad W, Riaz T, Nawaz MA, Miquel C, Poillot C, Shah SA, Pompanon F, Coissac E, Taberlet P (April 2012). "Carnivore diet analysis based on next-generation sequencing: application to the leopard cat (Prionailurus bengalensis) in Pakistan". Molecular Ecology. 21 (8): 1951–65. doi:10.1111/j.1365-294x.2011.05424.x. PMID 22250784. S2CID 205364612.
  45. Méheust E, Alfonsi E, Le Ménec P, Hassani S, Jung JL (2014-11-19). "DNA barcoding for the identification of soft remains of prey in the stomach contents of grey seals (Halichoerus grypus) and harbour porpoises (Phocoena phocoena)". Marine Biology Research. 11 (4): 385–395. doi:10.1080/17451000.2014.943240. ISSN 1745-1000. S2CID 83991013.
  46. De Barba M, Miquel C, Boyer F, Mercier C, Rioux D, Coissac E, Taberlet P (March 2014). "DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet". Molecular Ecology Resources. 14 (2): 306–23. doi:10.1111/1755-0998.12188. PMID 24128180. S2CID 25972059.
  47. Clare EL, Fraser EE, Braid HE, Fenton MB, Hebert PD (June 2009). "Species on the menu of a generalist predator, the eastern red bat (Lasiurus borealis): using a molecular approach to detect arthropod prey". Molecular Ecology. 18 (11): 2532–42. doi:10.1111/j.1365-294x.2009.04184.x. PMID 19457192. S2CID 3940026.
  48. De Barba M, Miquel C, Boyer F, Mercier C, Rioux D, Coissac E, Taberlet P (March 2014). "DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet". Molecular Ecology Resources. 14 (2): 306–23. doi:10.1111/1755-0998.12188. PMID 24128180. S2CID 25972059.
  49. De Barba M, Miquel C, Boyer F, Mercier C, Rioux D, Coissac E, Taberlet P (March 2014). "DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet". Molecular Ecology Resources. 14 (2): 306–23. doi:10.1111/1755-0998.12188. PMID 24128180. S2CID 25972059.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.