Biology:Microbial DNA barcoding

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Microbial DNA barcoding is the use of DNA metabarcoding to characterize a mixture of microorganisms. DNA metabarcoding is a method of DNA barcoding that uses universal genetic markers to identify DNA of a mixture of organisms.[1]

History

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.

Genetic markers

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.[4][5] For both bacteria and archaea the 16S rRNA/rDNA gene is used. It is a common housekeeping gene in all prokaryotic organisms and therefore is used as a standard barcode to assess prokaryotic diversity. For protists, the corresponding 18S rRNA/rDNA gene is used.[6] To distinguish different species of fungi, the ITS (Internal Transcribed Spacer) region of the ribosomal cistron is used.[7]

Advantages

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.[4] 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.[8][9] 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.[10] 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.

Applications

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[11] or comparison studies of newborn, child and adult gut bacteria composition.[12] Additionally, barcoding plays a major role in biomonitoring of e.g. rivers and streams[13] and grassland restoration.[14] Conservation parasitology, environmental parasitology and paleoparasitology rely on barcoding as a useful tool in disease investigating and management, too.[15]

Cyanobacteria

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.[16] 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.[17]

Cyanobacteria from genus Dolichospermum, as seen under a microscope.

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.[18][19] The use of cyanobacteria-specific[20] or phyto-specific 16S markers is commonly used for focusing on cyanobacteria only.[21] 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.[22][21][23][24]

Number of sequenced cyanobacterial genomes available in databases is increasing.[25] Besides 16S marker, phylogenetic studies could therefore include also more variable sequences, such as sequences of protein-coding genes (gyrB, rpoC, rpoD,[26] rbcL, hetR,[27] psbA,[28][29] rnpB,[30] nifH,[31] nifD[32]), internal transcribed spacer of ribosomal RNA genes (16S-23S rRNA-ITS)[33][25] or phycocyanin intergenic spacer (PC-IGS).[33] However, nifD and nifH can only be used for identification of nitrogen-fixing cyanobacterial strains.

DNA barcoding of cyanobacteria can be applied in various ecological, evolutionary and taxonomical studies. Some examples include assessment of cyanobacterial diversity and community structure,[34] identification of harmful cyanobacteria in ecologically and economically important waterbodies[35] and assessment of cyanobacterial symbionts in marine invertebrates.[24] 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 characteristics which are the basis for species delimitation vary in different growth conditions.[20][36] Identification under microscope 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.

Reference databases

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[37] exclusively for fungi sequences or the PR2 database solely for protist ribosomal sequences.[38] Some databases are curated, which allows a taxonomic assignment with higher accuracy than using uncurated databases as a reference.

See also

References

  1. ↑ "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. 8 July 2015. doi:10.1371/journal.pone.0130324. PMID 26154168. Bibcode: 2015PLoSO..1030324E. 
  2. ↑ "Phylogenetic measurement in procaryotes by primary structural characterization". Journal of Molecular Evolution 1 (2): 173–84. June 1972. doi:10.1007/BF01659163. PMID 24173440. Bibcode: 1972JMolE...1..173S. 
  3. ↑ "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): 4576–9. June 1990. doi:10.1073/pnas.87.12.4576. PMID 2112744. Bibcode: 1990PNAS...87.4576W. 
  4. ↑ 4.0 4.1 "DNA barcoding to map the microbial communities: current advances and future directions". Applied Microbiology and Biotechnology 98 (8): 3425–36. April 2014. doi:10.1007/s00253-014-5550-9. PMID 24522727. 
  5. ↑ "Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring". BMC Biology 5 (1): 24. June 2007. doi:10.1186/1741-7007-5-24. PMID 17567898. 
  6. ↑ Gardham, Stephanie; Hose, Grant C.; Stephenson, Sarah; Chariton, Anthony A. (2014). "DNA Metabarcoding Meets Experimental Ecotoxicology". Big Data in Ecology. Advances in Ecological Research. 51. pp. 79–104. doi:10.1016/B978-0-08-099970-8.00007-5. ISBN 978-0-08-099970-8. 
  7. ↑ "The ecologist's field guide to sequence-based identification of biodiversity". Methods in Ecology and Evolution 7 (9): 1008–1018. September 2016. doi:10.1111/2041-210X.12574. http://pure.aber.ac.uk/ws/files/27228629/Creer_et_al_2016_Methods_in_Ecology_and_Evolution.pdf. 
  8. ↑ "Cryptic species as a window on diversity and conservation". Trends in Ecology & Evolution 22 (3): 148–55. March 2007. doi:10.1016/j.tree.2006.11.004. PMID 17129636. http://ir.unimas.my/3324/1/Cryptic%20species%20as%20a%20window%20on%20diversity%20and%20conservation.pdf. 
  9. ↑ "Body doubles". Nature 433 (7022): 111. January 2005. doi:10.1038/433111a. PMID 15650721. Bibcode: 2005Natur.433..111S. 
  10. ↑ "Development and preliminary validation of a multi-trophic metabarcoding biotic index for monitoring benthic organic enrichment". Ecological Indicators 85: 1044–1057. February 2018. doi:10.1016/j.ecolind.2017.11.014. 
  11. ↑ "A core gut microbiome in obese and lean twins". Nature 457 (7228): 480–4. January 2009. doi:10.1038/nature07540. PMID 19043404. Bibcode: 2009Natur.457..480T. 
  12. ↑ "Human gut microbiome viewed across age and geography". Nature 486 (7402): 222–7. May 2012. doi:10.1038/nature11053. PMID 22699611. Bibcode: 2012Natur.486..222Y. 
  13. ↑ "Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France)". Ecological Indicators 82: 1–12. November 2017. doi:10.1016/j.ecolind.2017.06.024. 
  14. ↑ "Soil Microbial Diversity During 30 Years of Grassland Restoration on the Loess Plateau: Tight Linkages With Plant Diversity". Land Degradation & Development. 12 March 2019. doi:10.1002/ldr.3300. 
  15. ↑ "Advances and challenges in barcoding of microbes, parasites, and their vectors and reservoirs". Parasitology 145 (5): 537–542. April 2018. doi:10.1017/S0031182018000884. PMID 29900810. 
  16. ↑ "Updating prokaryotic taxonomy". Journal of Bacteriology 187 (18): 6255–7. September 2005. doi:10.1128/JB.187.18.6255-6257.2005. PMID 16159756. 
  17. ↑ "Does a barcoding gap exist in prokaryotes? Evidences from species delimitation in cyanobacteria". Life 5 (1): 50–64. December 2014. doi:10.3390/life5010050. PMID 25561355. 
  18. ↑ "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". Applied and Environmental Microbiology 64 (1): 294–303. January 1998. doi:10.1128/AEM.64.1.294-303.1998. PMID 9435081. Bibcode: 1998ApEnM..64..294R. 
  19. ↑ "Characterization of bacterial communities in four freshwater lakes differing in nutrient load and food web structure". FEMS Microbiology Ecology 53 (2): 205–20. July 2005. doi:10.1016/j.femsec.2004.12.006. PMID 16329941. 
  20. ↑ 20.0 20.1 "PCR primers to amplify 16S rRNA genes from cyanobacteria". Applied and Environmental Microbiology 63 (8): 3327–32. August 1997. doi:10.1128/AEM.63.8.3327-3332.1997. PMID 9251225. Bibcode: 1997ApEnM..63.3327N. 
  21. ↑ 21.0 21.1 "Phyto-specific 16S rDNA PCR primers for recovering algal and plant sequences from mixed samples". Molecular Ecology Notes 5 (1): 1–3. March 2005. doi:10.1111/j.1471-8286.2004.00805.x. 
  22. ↑ "Selective recovery of microalgae from diverse habitats using 'phyto-specific' 16S rDNA primers". Journal of Phycology 43 (3): 609–613. June 2007. doi:10.1111/j.1529-8817.2007.00350.x. 
  23. ↑ "Testing of primers for the study of cyanobacterial molecular diversity by DGGE". Journal of Microbiological Methods 65 (3): 542–50. June 2006. doi:10.1016/j.mimet.2005.09.017. PMID 16290299. http://orbi.ulg.ac.be/handle/2268/19902. 
  24. ↑ 24.0 24.1 "Cyanobacterial diversity and a new acaryochloris-like symbiont from Bahamian sea-squirts". PLOS ONE 6 (8): e23938. 22 August 2011. doi:10.1371/journal.pone.0023938. PMID 21915246. Bibcode: 2011PLoSO...623938L. 
  25. ↑ 25.0 25.1 "Discrimination Between Synechocystis Members (Cyanobacteria) Based on Heterogeneity of Their 16S rRNA and ITS Regions". Acta Chimica Slovenica 64 (4): 804–817. December 2017. doi:10.17344/acsi.2017.3262. PMID 29318299. 
  26. ↑ "The phylogenetic relationships of cyanobacteria inferred from 16S rRNA, gyrB, rpoC1 and rpoD1 gene sequences". The Journal of General and Applied Microbiology 49 (3): 191–203. June 2003. doi:10.2323/jgam.49.191. PMID 12949700. 
  27. ↑ "The evolutionary diversification of cyanobacteria: molecular-phylogenetic and paleontological perspectives". Proceedings of the National Academy of Sciences of the United States of America 103 (14): 5442–7. April 2006. doi:10.1073/pnas.0600999103. PMID 16569695. Bibcode: 2006PNAS..103.5442T. 
  28. ↑ "Characterization of the single psbA gene of Prochlorococcus marinus CCMP 1375 (Prochlorophyta)". Plant Molecular Biology 27 (6): 1189–96. March 1995. doi:10.1007/BF00020892. PMID 7766900. 
  29. ↑ "psbA genes indicate common ancestry of prochlorophytes and chloroplasts". Nature 337 (6205): 382–5. January 1989. doi:10.1038/337382a0. PMID 2643058. Bibcode: 1989Natur.337..382M. 
  30. ↑ "The RNase P RNA from cyanobacteria: short tandemly repeated repetitive (STRR) sequences are present within the RNase P RNA gene in heterocyst-forming cyanobacteria". Nucleic Acids Research 25 (17): 3471–7. September 1997. doi:10.1093/nar/25.17.3471. PMID 9254706. 
  31. ↑ "Phylogeny of cyanobacterial nifH genes: evolutionary implications and potential applications to natural assemblages". Microbiology 143 ( Pt 4) (4): 1443–50. April 1997. doi:10.1099/00221287-143-4-1443. PMID 9141707. 
  32. ↑ "Molecular phylogeny of the heterocystous cyanobacteria (subsections IV and V) based on nifD". International Journal of Systematic and Evolutionary Microbiology 54 (Pt 2): 493–7. March 2004. doi:10.1099/ijs.0.02821-0. PMID 15023966. 
  33. ↑ 33.0 33.1 Gabrielson, P., ed (August 2014). "Phylogenetic study of Geitlerinema and Microcystis (Cyanobacteria) using PC-IGS and 16S-23S ITS as markers: investigation of horizontal gene transfer". Journal of Phycology 50 (4): 736–43. doi:10.1111/jpy.12204. PMID 26988457. 
  34. ↑ "Cyanobacterial diversity in the hot spring, pelagic and benthic habitats of a tropical soda lake". FEMS Microbiology Ecology 85 (2): 389–401. August 2013. doi:10.1111/1574-6941.12128. PMID 23586739. 
  35. ↑ "Identification of harmful cyanobacteria in the Sacramento-San Joaquin Delta and Clear Lake, California by DNA barcoding". SpringerPlus 2 (1): 491. 2013. doi:10.1186/2193-1801-2-491. PMID 24133644. 
  36. ↑ "Phylogenetic comparison of the cyanobacterial genera Anabaena and Aphanizomenon". International Journal of Systematic and Evolutionary Microbiology 52 (Pt 5): 1867–80. September 2002. doi:10.1099/00207713-52-5-1867. PMID 12361299. 
  37. ↑ "UNITE". https://unite.ut.ee/. 
  38. ↑ "The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy". Nucleic Acids Research 41 (Database issue): D597–604. January 2013. doi:10.1093/nar/gks1160. PMID 23193267. 



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