Aquatic macroinvertebrate DNA barcoding explained

DNA barcoding is an alternative method to the traditional morphological taxonomic classification, and has frequently been used to identify species of aquatic macroinvertebrates (generally considered those large enough to be seen without magnification). Many are crucial indicator organisms in the bioassessment of freshwater (e.g.: Ephemeroptera, Plecoptera, Trichoptera) and marine (e.g. Annelida, Echinoderms, Molluscs) ecosystems.

Since its introduction, the field of DNA barcoding has matured to bridge the gap between traditional taxonomy and molecular systematics. This technique has the ability to provide more detailed taxonomic information, particularly for cryptic, small, or rare species. DNA barcoding involves specific targeting of gene regions that are found and conserved in most animal species, but have high variation between members of different species. Accurate diagnosis depends on low intraspecific variation compared with that between species, a short DNA sequence such as Cytochrome Subunit Oxidase I gene (COI), would allow precise allocation of an individual to a taxon.

Methodology

While the concept of using DNA sequence divergence for species discrimination has been reported earlier, Hebert et al. (2003) were pioneers in proposing standardization of DNA barcoding as a method of molecularly distinguishing species.^[1]

Specimens collection for DNA barcoding does not differ from the traditional methods, apart from the fact that the samples should be preserved in high concentration (>70%) ethanol.^[2] It has been indicated that the typical protocol of storing benthic samples in formalin has an adverse effect on DNA integrity.^[3]

The key concept for barcoding macroinvertebrates, is proper selection of DNA markers (DNA barcode region) to amplify appropriate gene regions, using PCR techniques. The DNA barcode region needs to be ideally conserved within a species, but variable among different (even closely related) species and therefore, its sequence should serve as a species-specific genetic tag. Therefore, the selection of the marker plays an important role.^[4] Cytochrome Subunit Oxidase I gene (COI) is one of the most widely used markers in barcoding of macroinvertebrates. Other markers that can be used are ribosomal RNA genes 16S and 18S.

Moreover, sorting invertebrates into different size categories is useful, since specimens in a sample can vary widely in biomass, depending on species and life stage.^[5]

For further details on methods see DNA barcoding.

DNA metabarcoding

See main article: Metabarcoding.

Due to the significant number of taxa that compose aquatic macroinvertebrate communities, DNA metabarcoding method is generally used to assess distinct taxa within bulk or water samples. DNA metabarcoding is a method that consists of the same workflow as DNA barcoding, distinguished by the use of high-throughput sequencing (HTS) technologies. The potential of DNA metabarcoding in the assessment and monitoring of various taxonomic groups, has been successfully demonstrated in several studies.^{[6] [7]} Numerous researchers have used metabarcoding methods to classify benthic macroinvertebrates from tissue samples,^[8] indicating its feasibility and higher sensitivity from classical taxonomy methods. Others, validate the use of next-generation sequencing (NGS) technologies in environmental samples to evaluate water quality in marine ecosystems^[9] and in freshwater biodiversity studies,^[10] including macroinvertebrate species assessment. Applications of these technologies in environmental samples is constantly increasing.^[11] Most of the recent studies are based on advancing eDNA approaches' implementation, field validation, platform and barcode choice or database limitations.^[12]

Application and challenges

Macroinvertebrates (meta)barcoding methods are often used in:

• Biodiversity assessment. Because of the large number of macroinvertebrate species, sample processing (sorting and identification) is laborious and often difficult task that can lead to errors during the assessment.^[13]
• Environmental monitoring programs. Macroinvertebrates within the same system may be residents from several months to multiple years, depending on the lifespan of each organism. Consequently, macroinvertebrate communities inhabit aquatic ecosystems long enough to reflect the chronic effects of pollutants and yet short enough to respond to relatively acute changes in water quality. Because of the limited mobility of macroinvertebrates and their relative inability to move away from adverse conditions, the location of chronic sources of pollution often can be pinpointed by comparing communities of these organisms.
• Detection of alien species. Application of eDNA and (meta) barcoding techniques are constantly increasing in the studies of invasion processes.^[14]
• Species identification. ‘Species’ level identification requires a high level of taxonomic expertise. Different developmental stages of macroinvertebrates are often difficult to identify morphologically, even for experts, especially because of the lack of appropriate identification keys for aquatic macroinvertebrates ^[15] . For some aquatic invertebrates taxa for example, taxonomic identification is only possible for males and some late instars, but the coupling of barcoding with traditional taxonomy provides a robust framework for biological identification.^[16] Often, species cannot be identified as they are morphologically cryptic, similar or represent less known groups.^[17] It has been suggested that a combined analysis of morphological and molecular data could provide the best solution into what is called “integrative taxonomy”.^[18] Number of studies have used barcoding or metabarcoding approaches on different groups, for example Odonates, specifically dragonflies (Anisoptera) and the damselflies (Zygoptera), with recommendation to use combination of markers.^[19]
• Stress response. Individual freshwater invertebrate species, often merged to a higher taxonomic level for biomonitoring purposes, can differ substantially in their tolerance to stressors and respond in more complex ways than observed at genus level.^[20] Identifications based on DNA barcoding have the potential to improve detection of small changes in stream conditions. Recent results showed that DNA barcoding can increase taxonomic resolution and thereby, increase the sensitivity of bioassessment metrics.^[21]

There are also many challenges when it comes to genetic barcoding of aquatic macroinvertebrates:

• Reference libraries. Availability of reference libraries of DNA barcodes is very important in species' identification.^[22]
• Missing species in databases. Information about existing species are usually not complete or correlated with ecological parameters such as depth, sampling technique, salinity etc.
• Validation of data quality. Databases' records are often not curated.
• Outdated taxonomy. Species in databases can be sometimes named with outdated taxonomy (e.g. synonyms).
• Quantitative measurement of species diversity (estimation of biomass and abundance of species).
• Lacking DNA information. Species in earlier literature are identified only by taxonomic features of which no DNA samples exist to confirm.
• Technical challenges must be taken into consideration, such as the need to apply different protocols when working with different organisms, selection of an appropriate DNA barcoding markers, primer design (identification of conserved regions suitable as primer-binding sites, evaluation of the taxonomic coverage and the ability of the amplified regions to resolve taxa at the family level, etc.).
• Costs related with sequencing.

See also

• DNA barcoding
• Fish DNA barcoding
• Algae DNA barcoding
• PCR
• Sequencing

Notes and References

1. Hebert. Paul D. N.. Cywinska. Alina. Ball. Shelley L.. deWaard. Jeremy R.. 2003-02-07. Biological identifications through DNA barcodes. Proceedings of the Royal Society of London. Series B: Biological Sciences. 270. 1512. 313–321. 10.1098/rspb.2002.2218. 1471-2954. 1691236. 12614582.
2. Evaluating Ethanol-based Sample Preservation to Facilitate Use of DNA Barcoding in Routine Freshwater Biomonitoring Programs Using Benthic Macroinvertebrates. PLOS ONE. 8. 1. e51273. 10.1371/journal.pone.0051273. 23308097. 3537618. 2013. Stein. Eric D.. White. Bryan P.. Mazor. Raphael D.. Miller. Peter E.. Pilgrim. Erik M.. 2013PLoSO...851273S . free .
3. Baird. Donald J.. Pascoe. Timothy J.. Zhou. Xin. Hajibabaei. Mehrdad. March 2011. Building freshwater macroinvertebrate DNA-barcode libraries from reference collection material: formalin preservation vs specimen age. Journal of the North American Benthological Society. 30. 1. 125–130. 10.1899/10-013.1. 3940136 . 0887-3593.
4. Andújar. Carmelo. Arribas. Paula. Gray. Clare. Bruce. Catherine. Woodward. Guy. Yu. Douglas W.. Vogler. Alfried P.. January 2018. Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill. Molecular Ecology. 27. 1. 146–166. 10.1111/mec.14410. 29113023. 2018MolEc..27..146A . 10044/1/58144. 7697860 . free.
5. Elbrecht. Vasco. Peinert. Bianca. Leese. Florian. September 2017. Sorting things out: Assessing effects of unequal specimen biomass on DNA metabarcoding. Ecology and Evolution. 7. 17. 6918–6926. 10.1002/ece3.3192. 5587478. 28904771. 2017EcoEv...7.6918E .
6. Lejzerowicz. Franck. Esling. Philippe. Pillet. Loïc. Wilding. Thomas A.. Black. Kenneth D.. Pawlowski. Jan. November 2015. High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Scientific Reports. 5. 1. 13932. 10.1038/srep13932. 2045-2322. 4564730. 26355099. 2015NatSR...513932L .
7. Elbrecht. Vasco. Vamos. Ecaterina Edith. Meissner. Kristian. Aroviita. Jukka. Leese. Florian. October 2017. Yu. Douglas. Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring. Methods in Ecology and Evolution. 8. 10. 1265–1275. 10.1111/2041-210X.12789. free.
8. Carew. Melissa E. Pettigrove. Vincent J. Metzeling. Leon. Hoffmann. Ary A. 2013. Environmental monitoring using next generation sequencing: rapid identification of macroinvertebrate bioindicator species. Frontiers in Zoology. 10. 1. 45. 10.1186/1742-9994-10-45. 1742-9994. 3750358. 23919569 . free .
9. Lejzerowicz. Franck. Esling. Philippe. Pillet. Loïc. Wilding. Thomas A.. Black. Kenneth D.. Pawlowski. Jan. November 2015. High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Scientific Reports. 5. 1. 13932. 10.1038/srep13932. 2045-2322. 4564730. 26355099. 2015NatSR...513932L .
10. Deiner. Kristy. Fronhofer. Emanuel A.. Mächler. Elvira. Walser. Jean-Claude. Altermatt. Florian. December 2016. Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nature Communications. 7. 1. 12544. 10.1038/ncomms12544. 2041-1723. 5013555. 27572523. 2016NatCo...712544D .
11. Zaiko. Anastasija. Martinez. Jose L.. Ardura. Alba. Clusa. Laura. Borrell. Yaisel J.. Samuiloviene. Aurelija. Roca. Agustín. Garcia-Vazquez. Eva. December 2015. Detecting nuisance species using NGST: Methodology shortcomings and possible application in ballast water monitoring. Marine Environmental Research. 112. Pt B. 64–72. 10.1016/j.marenvres.2015.07.002. 26174116. 2015MarER.112...64Z . 9579967 .
12. Fernández. Sara. Rodríguez. Saúl. Martínez. Jose L.. Borrell. Yaisel J.. Ardura. Alba. García-Vázquez. Eva. 2018-08-08. Melcher. Ulrich. Evaluating freshwater macroinvertebrates from eDNA metabarcoding: A river Nalón case study. PLOS ONE. 13. 8. e0201741. 10.1371/journal.pone.0201741. 1932-6203. 6082553. 30089147. 2018PLoSO..1301741F . free .
13. Haase. Peter. Pauls. Steffen U.. Schindehütte. Karin. Sundermann. Andrea. December 2010. First audit of macroinvertebrate samples from an EU Water Framework Directive monitoring program: human error greatly lowers precision of assessment results. Journal of the North American Benthological Society. 29. 4. 1279–1291. 10.1899/09-183.1. 86777562 . 0887-3593.
14. REABIC - Journals - BioInvasions Records - Issue 1 (2018). www.reabic.net. 10.3391/bir.2018.7.1.08. 2019-04-19. free.
15. Venter. Hermoine J.. Unit for Environmental Sciences and Management, North-West University, Potchefstroom, South Africa. Bezuidenhout. Cornelius C.. Unit for Environmental Sciences and Management, North-West University, Potchefstroom, South Africa. 2016-05-26. DNA-based identification of aquatic invertebrates useful in the South African context?. South African Journal of Science. 112. 5/6. 4 . 10.17159/sajs.2016/20150444. 0038-2353. free.
16. DeWalt. R. Edward. 2011-03-01. DNA barcoding: a taxonomic point of view. Journal of the North American Benthological Society. 30. 1. 174–181. 10.1899/10-021.1. 84203382 . 0887-3593.
17. Carew. Melissa E. Pettigrove. Vincent J. Metzeling. Leon. Hoffmann. Ary A. 2013. Environmental monitoring using next generation sequencing: rapid identification of macroinvertebrate bioindicator species. Frontiers in Zoology. 10. 1. 45. 10.1186/1742-9994-10-45. 1742-9994. 3750358. 23919569 . free .
18. Teletchea. Fabrice. 2010-12-01. After 7 years and 1000 citations: Comparative assessment of the DNA barcoding and the DNA taxonomy proposals for taxonomists and non-taxonomists. Mitochondrial DNA. 21. 6. 206–226. 10.3109/19401736.2010.532212. 1940-1736. 21171865. 10486130 .
19. Rach. Jessica. Bergmann. Tjard. Paknia. Omid. DeSalle. Rob. Schierwater. Bernd. Hadrys. Heike. 2017-04-13. Yue. Bi-Song. The marker choice: Unexpected resolving power of an unexplored CO1 region for layered DNA barcoding approaches. PLOS ONE. 12. 4. e0174842. 10.1371/journal.pone.0174842. 1932-6203. 5390999. 28406914. 2017PLoSO..1274842R . free .
20. Macher. Jan N.. Salis. Romana K.. Blakemore. Katie S.. Tollrian. Ralph. Matthaei. Christoph D.. Leese. Florian. February 2016. Multiple-stressor effects on stream invertebrates: DNA barcoding reveals contrasting responses of cryptic mayfly species. Ecological Indicators. 61. 159–169. 10.1016/j.ecolind.2015.08.024.
21. Stein. Eric D.. White. Bryan P.. Mazor. Raphael D.. Jackson. John K.. Battle. Juliann M.. Miller. Peter E.. Pilgrim. Erik M.. Sweeney. Bernard W.. 2014-03-01. Does DNA barcoding improve performance of traditional stream bioassessment metrics?. Freshwater Science. 33. 1. 302–311. 10.1086/674782. 67753537 . 2161-9549. free.
22. Webb. Jeffrey M.. Jacobus. Luke M.. Funk. David H.. Zhou. Xin. Kondratieff. Boris. Geraci. Christy J.. DeWalt. R. Edward. Baird. Donald J.. Richard. Barton. 2012-05-30. Fenton. Brock. A DNA Barcode Library for North American Ephemeroptera: Progress and Prospects. PLOS ONE. 7. 5. e38063. 10.1371/journal.pone.0038063. 1932-6203. 3364165. 22666447. 2012PLoSO...738063W . free .