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Not to be confused with DNA barcoding. DNA metabarcoding is a method of DNA barcoding that uses universal genetic markers to identify DNA of a mixture of organisms[1]. For elementary information on DNA barcoding, see here.

Introduction

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History

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Using metabarcoding to assess microbial communities has a long history. Back in 1972, Carl Woese, Mitchell Sogin and Stephen Sogin first tried to detect several families within bacteria using the 5S rRNA gene[2]. Only a few years later, a new tree of life with three domains was proposed by again Woese and colleagues, who were the first to use the small subunit of the ribosomal RNA (SSU rRNA) gene to distinguish between bacteria, archaea and eukaryotes[3]. Out of this approach, the SSU rRNA gene made its way to be the most frequently used genetic marker for both prokaryotes (16S rRNA) and eukaryotes (18S rRNA). The tedious process of cloning those DNA fragments for sequencing got fastened up by the steady improvement of sequencing technologies. With the development of HTS (High-Throughput-Sequencing) in the early 2000s and the ability to deal with this massive data using modern bioinformatics and cluster algorithms, investigating microbial life got much easier.

Applications

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A lot of studies followed the first usage of Woese et al., and are now covering a variety of applications. Not only in biological or ecological research metabarcoding is used. Also in medicine and human biology bacterial barcodes are used, e.g. to investigate the microbiome and bacterial colonization of the human gut in normal and obese twins[4] or comparison studies of newborn, child and adult gut bacteria composition[5]. Additionally, barcoding plays a major role in biomonitoring of e.g. rivers and streams[6] and grassland restoration[7]. Conservation parasitology, environmental parasitology and paleoparasitology rely on barcoding as a useful tool in disease investigating and management, too[8].

Advantages

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The existing diversity of the microbial world is not unraveled completely yet, although we know that it is mainly composed by bacteria, fungi and unicellular eukaryotes[9]. Taxonomic identification of microbial eukaryotes requires exceedingly skillful expertise and is often difficult due to small sizes of the organisms, fragmented individuals, hidden diversity and cryptic species[10][11]. Further, prokaryotes can simply not be taxonomically assigned using traditional methods like microscopy, because they are too small and morphologically indistinguishable. Therefore, via the use of DNA metabarcoding, it is possible to identify organisms without taxonomic expertise by matching short High Throughput Sequences (HTS)-derived gene fragments to a reference sequence database, e.g. NCBI[12]. These mentioned qualities make DNA barcoding a cost-effective, reliable and less time consuming method, compared to the traditional ones, to meet the increasing need for large-scale environmental assessments.

Microbial barcodes and genetic markers

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Genetic diversity is varying from species to species. Therefore, it is possible to identify distinct species by the recovery of a short DNA sequence from a standard part of the genome. This short sequence is defined as barcode sequence. Requirements for a specific part of the genome to serve as barcode should be a high variation between two different species, but not much differences in the gene between two individuals of the same species to make differentiating individual species easier[13][14]. For both bacteria and archaea the 16S rRNA/rDNA gene is uses. It is a common housekeeping gene in all prokaryotic organisms and therefore is used as a standard barcode to asses prokaryotic diversity. For protists, the corresponding 18S rRNA/rDNA gene is used[15]. To distinguish different species of fungi, the ITS (Internal Transcribed Spacer) region of the ribosomal cistron is used[16].

Reference databases

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The reference database is a collection of DNA sequences, which are assigned to either a species or a function. It can be used to link molecular obtained sequences of an organism to pre-existing taxonomy. General databases like the NCBI platform include all kind of sequences, either whole genomes or specific marker genes of all organisms. There are also different platforms where only sequences from a distinct group of organisms are stored, e.g. UNITE database[17] exclusively for fungi sequences or the PR2 database solely for protist ribosomal sequences[18]. Some databases are curated, which allows a taxonomic assignment with higher accuracy than using uncurated databases as a reference.

Cyanobacteria

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Cyanobacteria are a group of photosynthetic prokaryotes. Similar as in other prokaryotes, taxonomy of cyanobacteria using DNA sequences is mostly based on similarity within the 16S ribosomal gene[19]. Thus, the most common barcode used for identification of cyanobacteria is 16S rDNA marker. While it is difficult to define species within prokaryotic organisms, 16S marker can be used for determining individual operational taxonomic units (OTUs). In some cases, these OTUs can also be linked to traditionally defined species and can therefore be considered a reliable representation of the evolutionary relationships[20].

However, when analyzing a taxonomic structure or biodiversity of a whole cyanobacterial community (see DNA metabarcoding), it is more informative to use markers specific for cyanobacteria. Universal 16S bacterial primers have been used successfully to isolate cyanobacterial rDNA from environmental samples, but they also recover many bacterial sequences[21][22]. The use of cyanobacteria-specific[23] or phyto-specific 16S markers is commonly used for focusing on cyanobacteria only[24]. A few sets of such primers have been tested for barcoding or metabarcoding of environmental samples and gave good results, screening out majority of non-photosynthetic or non-cyanobacterial organisms[25][26][27][28].

Applications

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DNA barcoding of cyanobacteria can be applied in various ecological, evolutionary and taxonomical studies. Some examples include assessment of cyanobacterial diversity and community structure[29], identification of harmful cyanobacteria in ecologically and economically important waterbodies[30] and assessment of cyanobacterial symbionts in marine invertebrates[31]. It has a potential to serve as a part of routine monitoring programs for occurrence of cyanobacteria, as well as early detection of potentially toxic species in waterbodies. This might help us detect harmful species before they start to form blooms and thus improve our water management strategies. Species identification based on environmental DNA could be particularly useful for cyanobacteria, as traditional identification using microscopy is challenging. Their morphological caracteristics which are the basis for species delimitation vary in different growth conditions[23][32]. Identification under mycroscope is also time-consuming and therefore relatively costly. Molecular methods can detect much lower concentration of cyanobacterial cells in the sample than traditional identification methods.

See also

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References

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  1. ^ Elbrecht, Vasco; Leese, Florian (2015-07-08). Hajibabaei, Mehrdad (ed.). "Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol". PLOS ONE. 10 (7): e0130324. doi:10.1371/journal.pone.0130324. ISSN 1932-6203. PMC 4496048. PMID 26154168.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  2. ^ Sogin, S. J.; Sogin, M. L.; Woese, C. R. (1972-06-01). "Phylogenetic measurement in procaryotes by primary structural characterization". Journal of Molecular Evolution. 1 (2): 173–184. doi:10.1007/BF01659163. ISSN 1432-1432.
  3. ^ Woese, C. R.; Kandler, O.; Wheelis, M. L. (1990-6). "Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya". Proceedings of the National Academy of Sciences of the United States of America. 87 (12): 4576–4579. ISSN 0027-8424. PMID 2112744. {{cite journal}}: Check date values in: |date= (help)
  4. ^ Turnbaugh, Peter J.; Hamady, Micah; Yatsunenko, Tanya; Cantarel, Brandi L.; Duncan, Alexis; Ley, Ruth E.; Sogin, Mitchell L.; Jones, William J.; Roe, Bruce A. (2009-01-22). "A core gut microbiome in obese and lean twins". Nature. 457 (7228): 480–484. doi:10.1038/nature07540. ISSN 1476-4687. PMC PMCPMC2677729. PMID 19043404. {{cite journal}}: Check |pmc= value (help)
  5. ^ Yatsunenko, Tanya; Rey, Federico E.; Manary, Mark J.; Trehan, Indi; Dominguez-Bello, Maria Gloria; Contreras, Monica; Magris, Magda; Hidalgo, Glida; Baldassano, Robert N. (2012-05-09). "Human gut microbiome viewed across age and geography". Nature. 486 (7402): 222–227. doi:10.1038/nature11053. ISSN 1476-4687. PMC PMCPMC3376388. PMID 22699611. {{cite journal}}: Check |pmc= value (help)
  6. ^ "ScienceDirect". www.sciencedirect.com. doi:10.1016/j.ecolind.2017.06.024. Retrieved 2019-03-28.
  7. ^ Guo, Yanqing; Hou, Lijun; Zhang, Zhiying; Zhang, Jianli; Cheng, Jimin; Wei, Gehong; Lin, Yanbing (2019-03-12). "SOIL MICROBIAL DIVERSITY DURING 30 YEARS OF GRASSLAND RESTORATION ON THE LOESS PLATEAU: TIGHT LINKAGES WITH PLANT DIVERSITY". Land Degradation & Development. doi:10.1002/ldr.3300.
  8. ^ Morand, Serge (04 2018). "Advances and challenges in barcoding of microbes, parasites, and their vectors and reservoirs". Parasitology. 145 (5): 537–542. doi:10.1017/S0031182018000884. ISSN 1469-8161. PMID 29900810. {{cite journal}}: Check date values in: |date= (help)
  9. ^ Chakraborty, Chiranjib; Doss, C. George Priya; Patra, Bidhan C.; Bandyopadhyay, Sanghamitra (2014-04-01). "DNA barcoding to map the microbial communities: current advances and future directions". Applied Microbiology and Biotechnology. 98 (8): 3425–3436. doi:10.1007/s00253-014-5550-9. ISSN 1432-0614.
  10. ^ Bickford, David; Lohman, David J.; Sodhi, Navjot S.; Ng, Peter K. L.; Meier, Rudolf; Winker, Kevin; Ingram, Krista K.; Das, Indraneil (2007-3). "Cryptic species as a window on diversity and conservation". Trends in Ecology & Evolution. 22 (3): 148–155. doi:10.1016/j.tree.2006.11.004. ISSN 0169-5347. PMID 17129636. {{cite journal}}: Check date values in: |date= (help)
  11. ^ Encarnación Lozano; Sáez, Alberto G. (2005-01). "Body doubles". Nature. 433 (7022): 111. doi:10.1038/433111a. ISSN 1476-4687. {{cite journal}}: Check date values in: |date= (help)
  12. ^ "ScienceDirect". www.sciencedirect.com. Retrieved 2019-03-27.
  13. ^ Chakraborty, Chiranjib; Doss, C. George Priya; Patra, Bidhan C.; Bandyopadhyay, Sanghamitra (2014-04-01). "DNA barcoding to map the microbial communities: current advances and future directions". Applied Microbiology and Biotechnology. 98 (8): 3425–3436. doi:10.1007/s00253-014-5550-9. ISSN 1432-0614.
  14. ^ Hajibabaei, Mehrdad; Singer, Gregory AC; Clare, Elizabeth L.; Hebert, Paul DN (2007-06-13). "Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring". BMC Biology. 5 (1): 24. doi:10.1186/1741-7007-5-24. ISSN 1741-7007. PMC 1906742. PMID 17567898.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  15. ^ Chariton, Anthony. "DNA Metabarcoding Meets Experimental Ecotoxicology: Advancing Knowledge on the Ecological Effects of Copper in Freshwater Ecosystems". {{cite journal}}: Cite journal requires |journal= (help)
  16. ^ Creer, Simon; Deiner, Kristy; Frey, Serita; Porazinska, Dorota; Taberlet, Pierre; Thomas, W. Kelley; Potter, Caitlin; Bik, Holly M. (2016). "The ecologist's field guide to sequence-based identification of biodiversity". Methods in Ecology and Evolution. 7 (9): 1008–1018. doi:10.1111/2041-210X.12574. ISSN 2041-210X.
  17. ^ "UNITE". unite.ut.ee. Retrieved 2019-03-28.
  18. ^ "Protist Ribosomal Reference database (PR2) - SSU rRNA gene database - old version". figshare. 2018-02-21. Retrieved 2019-03-28.
  19. ^ Rossello-Mora, R. (2005-09-15). "Updating Prokaryotic Taxonomy". Journal of Bacteriology. 187 (18): 6255–6257. doi:10.1128/JB.187.18.6255-6257.2005. ISSN 0021-9193. PMC 1236658. PMID 16159756.{{cite journal}}: CS1 maint: PMC format (link)
  20. ^ Eckert, Ester; Fontaneto, Diego; Coci, Manuela; Callieri, Cristiana (2014-12-31). "Does a Barcoding Gap Exist in Prokaryotes? Evidences from Species Delimitation in Cyanobacteria". Life. 5 (1): 50–64. doi:10.3390/life5010050. ISSN 2075-1729. PMC 4390840. PMID 25561355.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  21. ^ Rappé, Michael S (Jan 1998). "Phylogenetic Diversity of Ultraplankton Plastid Small-Subunit rRNA Genes Recovered in Environmental Nucleic Acid Samples from the Pacific and Atlantic Coasts of the United States". Appl Environ Microbiol. 64(1): 294–303.
  22. ^ Gucht, Katleen; Vandekerckhove, Tom; Vloemans, Nele; Cousin, Sylvie; Muylaert, Koenraad; Sabbe, Koen; Gillis, Moniek; Declerk, Steven; Meester, Luc (2005-7). "Characterization of bacterial communities in four freshwater lakes differing in nutrient load and food web structure". FEMS Microbiology Ecology. 53 (2): 205–220. doi:10.1016/j.femsec.2004.12.006. {{cite journal}}: Check date values in: |date= (help)
  23. ^ a b Nübel, U (Aug 1997). "PCR primers to amplify 16S rRNA genes from cyanobacteria". Appl Environ Microbiol. 63(8): 3327–3332.
  24. ^ Stiller, John W.; McCLANAHAN, Ana (2005-3). "Phyto-specific 16S rDNA PCR primers for recovering algal and plant sequences from mixed samples". Molecular Ecology Notes. 5 (1): 1–3. doi:10.1111/j.1471-8286.2004.00805.x. ISSN 1471-8278. {{cite journal}}: Check date values in: |date= (help)
  25. ^ Betournay, Scott; Marsh, Amanda C.; Donello, Nicholas; Stiller, John W. (2007-6). "SELECTIVE RECOVERY OF MICROALGAE FROM DIVERSE HABITATS USING "PHYTO-SPECIFIC" 16S rDNA PRIMERS". Journal of Phycology. 43 (3): 609–613. doi:10.1111/j.1529-8817.2007.00350.x. {{cite journal}}: Check date values in: |date= (help)
  26. ^ Stiller, John W.; McCLANAHAN, Ana (2005-3). "Phyto-specific 16S rDNA PCR primers for recovering algal and plant sequences from mixed samples". Molecular Ecology Notes. 5 (1): 1–3. doi:10.1111/j.1471-8286.2004.00805.x. ISSN 1471-8278. {{cite journal}}: Check date values in: |date= (help)
  27. ^ Boutte, C.; Grubisic, S.; Balthasart, P.; Wilmotte, A. (2006-6). "Testing of primers for the study of cyanobacterial molecular diversity by DGGE". Journal of Microbiological Methods. 65 (3): 542–550. doi:10.1016/j.mimet.2005.09.017. {{cite journal}}: Check date values in: |date= (help)
  28. ^ López-Legentil, Susanna; Song, Bongkeun; Bosch, Manel; Pawlik, Joseph R.; Turon, Xavier (2011-08-22). Gilbert, Jack Anthony (ed.). "Cyanobacterial Diversity and a New Acaryochloris-Like Symbiont from Bahamian Sea-Squirts". PLoS ONE. 6 (8): e23938. doi:10.1371/journal.pone.0023938. ISSN 1932-6203. PMC 3161822. PMID 21915246.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  29. ^ Dadheech, Pawan K.; Glöckner, Gernot; Casper, Peter; Kotut, Kiplagat; Mazzoni, Camila Junqueira; Mbedi, Susan; Krienitz, Lothar (2013-8). "Cyanobacterial diversity in the hot spring, pelagic and benthic habitats of a tropical soda lake". FEMS Microbiology Ecology. 85 (2): 389–401. doi:10.1111/1574-6941.12128. {{cite journal}}: Check date values in: |date= (help)
  30. ^ Kurobe, Tomofumi; Baxa, Dolores V; Mioni, Cécile E; Kudela, Raphael M; Smythe, Thomas R; Waller, Scott; Chapman, Andrew D; Teh, Swee J (2013). "Identification of harmful cyanobacteria in the Sacramento-San Joaquin Delta and Clear Lake, California by DNA barcoding". SpringerPlus. 2 (1): 491. doi:10.1186/2193-1801-2-491. ISSN 2193-1801. PMC 3797325. PMID 24133644.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  31. ^ López-Legentil, Susanna; Song, Bongkeun; Bosch, Manel; Pawlik, Joseph R.; Turon, Xavier (2011-08-22). Gilbert, Jack Anthony (ed.). "Cyanobacterial Diversity and a New Acaryochloris-Like Symbiont from Bahamian Sea-Squirts". PLoS ONE. 6 (8): e23938. doi:10.1371/journal.pone.0023938. ISSN 1932-6203. PMC 3161822. PMID 21915246.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  32. ^ Humbert, Jean-François; Lyra, Christina; Couté, Alain; Gugger, Muriel; Sivonen, Kaarina; Henriksen, Peter (2002-09-01). "Phylogenetic comparison of the cyanobacterial genera Anabaena and Aphanizomenon". International Journal of Systematic and Evolutionary Microbiology. 52 (5): 1867–1880. doi:10.1099/00207713-52-5-1867. ISSN 1466-5026.


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