Biology:DNA barcoding in diet assessment

From HandWiki
Revision as of 15:12, 11 February 2024 by LinXED (talk | contribs) (simplify)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

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.[5]

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.[7] 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.[7] For animal prey, the most broadly used DNA barcode markers to identify diets are the mitochondrial cytochrome C oxydase (COI) and cytochrome b (cytb).[8] When the diet is broad and diverse, DNA metabarcoding is used to identify most of the consumed items.[9]

Advantages

A major benefit of using DNA barcoding in diet assessment is the ability to provide high taxonomic resolution of consumed species.[10] Indeed, when compared to traditional morphological analysis, DNA barcoding enables a more reliable separation of closely related taxa reducing the observed bias.[11][12] Moreover, DNA barcoding enables to detect soft and highly digested items, not recognisable through morphological identification.[13] 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.[14]

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.[15][16] 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.[17] 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.[18]

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.[19][20] 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.[21] 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.[22][23][24] 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.[22][25]

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.[26]

The quantitative interpretation of DNA barcoding results is not straightforward.[12] 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.[5][27] This can be explained by the fact that tissues originally contain different densities of DNA and can be digested differently.[28]

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[29][16][30][31] or rumen contents collected from road kills or animals killed during regular hunting.[15] 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).[32] Potentially, this application is applicable to all herbivorous species feeding on angiosperms and gymnosperms[32] 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.[16] 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).[33] 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.[33]

Faeces of wolf (Canis lupus) collected in Sweden
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.[23] 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.[23] 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).[34]

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.[35][36] This methodology does not require knowledge about the food consumed by animals in the habitat they occupy.[35] 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.[35]

Birds

Fish

Food web reconstruction by DNA barcodes at the coral reef of Moorea, French Polynesia. Dietary partitioning among three predatory fish species as detected using metabarcoding dietary analysis. The taxonomic resolution provided by the metabarcoding approach highlights a complex interaction web and demonstrates that levels of trophic partitioning among coral reef fishes have likely been underestimated.[37][38]

Arthropods

See also

References

  1. "Molecular analysis of predation: a review of best practice for DNA-based approaches". Molecular Ecology 17 (4): 947–63. February 2008. doi:10.1111/j.1365-294X.2007.03613.x. PMID 18208490. 
  2. "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology 21 (8): 1931–50. April 2012. doi:10.1111/j.1365-294X.2011.05403.x. PMID 22171763. 
  3. "Advances in molecular ecology: tracking trophic links through predator-prey food-webs" (in en). Functional Ecology 19 (5): 751–762. October 2005. doi:10.1111/j.1365-2435.2005.01041.x. 
  4. "DNA barcodes for ecology, evolution, and conservation" (in English). Trends in Ecology & Evolution 30 (1): 25–35. January 2015. doi:10.1016/j.tree.2014.10.008. PMID 25468359. 
  5. 5.0 5.1 5.2 "Who is eating what: diet assessment using next generation sequencing". Molecular Ecology 21 (8): 1931–50. April 2012. doi:10.1111/j.1365-294x.2011.05403.x. PMID 22171763. 
  6. "Tracking the role of alternative prey in soybean aphid predation by Orius insidiosus: a molecular approach". Molecular Ecology 16 (20): 4390–400. October 2007. doi:10.1111/j.1365-294x.2007.03482.x. PMID 17784913. 
  7. 7.0 7.1 "DNA barcodes for ecology, evolution, and conservation". Trends in Ecology & Evolution 30 (1): 25–35. January 2015. doi:10.1016/j.tree.2014.10.008. PMID 25468359. 
  8. "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. December 2009. doi:10.1016/j.fsigss.2009.08.053. ISSN 1875-1768. 
  9. "DNA metabarcoding reveals diverse diet of the three-spined stickleback in a coastal ecosystem". PLOS ONE 12 (10): e0186929. October 2017. doi:10.1371/journal.pone.0186929. PMID 29059215. Bibcode2017PLoSO..1286929J. 
  10. "Assessment of Animal-Based Methods Used for Estimating and Monitoring Rangeland Herbivore Diet Composition". Rangeland Ecology & Management 71 (4): 449–457. July 2018. doi:10.1016/j.rama.2018.03.003. 
  11. "Using stomach contents for diet analysis of carnivores through DNA barcoding". Wildlife Biology in Practice 11 (1). 2015-05-20. doi:10.2461/wbp.2015.11.4. 
  12. 12.0 12.1 "DNA barcoding for ecologists". Trends in Ecology & Evolution 24 (2): 110–7. February 2009. doi:10.1016/j.tree.2008.09.011. PMID 19100655. 
  13. "A pragmatic approach to the analysis of diets of generalist predators: the use of next-generation sequencing with no blocking probes". Molecular Ecology Resources 14 (1): 18–26. January 2014. doi:10.1111/1755-0998.12156. PMID 23957910. http://orca.cf.ac.uk/52924/1/Pinol_et_al_MER_R2.pdf. 
  14. "Collembola as alternative prey sustaining spiders in arable ecosystems: prey detection within predators using molecular markers". Molecular Ecology 12 (12): 3467–3475. 2003. doi:10.1046/j.1365-294X.2003.02014.x. PMID 14629361. 
  15. 15.0 15.1 "Diet Assessment Based on Rumen Contents: A Comparison between DNA Metabarcoding and Macroscopy". PLOS ONE 11 (6): e0157977. June 2016. doi:10.1371/journal.pone.0157977. PMID 27322387. Bibcode2016PLoSO..1157977N. 
  16. 16.0 16.1 16.2 "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. August 2009. doi:10.1186/1742-9994-6-16. PMID 19695081. 
  17. Casiraghi, Maurizio, ed (April 2014). "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. doi:10.1371/journal.pone.0095525. PMID 24755838. Bibcode2014PLoSO...995525S. 
  18. "Evaluation of plant contamination in metabarcoding diet analysis of a herbivore". Scientific Reports 8 (1): 15563. October 2018. doi:10.1038/s41598-018-32845-w. PMID 30349088. Bibcode2018NatSR...815563A. 
  19. "Primers for the differential amplification of the sex-determining region Y gene in a range of mammal species". Molecular Ecology 2 (6): 405–6. December 1993. doi:10.1111/j.1365-294x.1993.tb00034.x. PMID 8162230. 
  20. "Non-invasive genetic sampling and individual identification". Biological Journal of the Linnean Society 68 (1–2): 41–55. September 1999. doi:10.1111/j.1095-8312.1999.tb01157.x. ISSN 0024-4066. 
  21. "Detection of a diverse marine fish fauna using environmental DNA from seawater samples". PLOS ONE 7 (8): e41732. August 2012. doi:10.1371/journal.pone.0041732. PMID 22952584. Bibcode2012PLoSO...741732T. 
  22. 22.0 22.1 "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. July 2008. doi:10.1186/1742-9994-5-12. PMID 18638418. 
  23. 23.0 23.1 23.2 "Carnivore diet analysis based on next-generation sequencing: application to the leopard cat (Prionailurus bengalensis) in Pakistan". Molecular Ecology 21 (8): 1951–65. April 2012. doi:10.1111/j.1365-294x.2011.05424.x. PMID 22250784. 
  24. "Adélie penguin population diet monitoring by analysis of food DNA in scats". PLOS ONE 8 (12): e82227. December 2013. doi:10.1371/journal.pone.0082227. PMID 24358158. Bibcode2013PLoSO...882227J. 
  25. "Application of Blocking Oligonucleotides to Improve Signal-to-Noise Ratio in a PCR". PCR Protocols. Methods in Molecular Biology. 687. Humana Press. October 2010. pp. 265–74. doi:10.1007/978-1-60761-944-4_19. ISBN 9781607619437. 
  26. "DNA metabarcoding reveals diverse diet of the three-spined stickleback in a coastal ecosystem". PLOS ONE 12 (10): e0186929. 2017-10-23. doi:10.1371/journal.pone.0186929. PMID 29059215. Bibcode2017PLoSO..1286929J. 
  27. "A pragmatic approach to the analysis of diets of generalist predators: the use of next-generation sequencing with no blocking probes". Molecular Ecology Resources 14 (1): 18–26. January 2014. doi:10.1111/1755-0998.12156. PMID 23957910. http://orca.cf.ac.uk/52924/1/Pinol_et_al_MER_R2.pdf. 
  28. "Pyrosequencing faecal DNA to determine diet of little penguins: is what goes in what comes out?". Conservation Genetics 11 (5): 2039–2048. 2010-06-17. doi:10.1007/s10592-010-0096-6. ISSN 1566-0621. 
  29. "Influence of management practices on large herbivore diet—Case of European bison in Białowieża Primeval Forest (Poland)" (in en). Forest Ecology and Management 261 (4): 821–828. February 2011. doi:10.1016/j.foreco.2010.11.026. 
  30. "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. 2012-04-27. doi:10.1371/journal.pone.0035643. PMID 22558187. Bibcode2012PLoSO...735643A. 
  31. "ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis". Nucleic Acids Research 39 (21): e145. November 2011. doi:10.1093/nar/gkr732. PMID 21930509. 
  32. 32.0 32.1 "New perspectives in diet analysis based on DNA barcoding and parallel pyrosequencing: the trnL approach". Molecular Ecology Resources 9 (1): 51–60. January 2009. doi:10.1111/j.1755-0998.2008.02352.x. PMID 21564566. 
  33. 33.0 33.1 "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. 2010-11-23. doi:10.1007/s11284-010-0780-5. ISSN 0912-3814. 
  34. "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. 2014-11-19. doi:10.1080/17451000.2014.943240. ISSN 1745-1000. 
  35. 35.0 35.1 35.2 "DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet". Molecular Ecology Resources 14 (2): 306–23. March 2014. doi:10.1111/1755-0998.12188. PMID 24128180. 
  36. "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. June 2009. doi:10.1111/j.1365-294x.2009.04184.x. PMID 19457192. 
  37. Roslin, T. and Majaneva, S. (2016) "The use of DNA barcodes in food web construction—terrestrial and aquatic ecologists unite!". Genome, 59(9): 603–628. doi:10.1139/gen-2015-0229.
  38. Leray M, Meyer CP, Mills SC. (2015) "Metabarcoding dietary analysis of coral dwelling predatory fish demonstrates the minor contribution of coral mutualists to their highly partitioned, generalist diet". PeerJ, 3: e1047. doi:10.7717/peerj.1047.