Biology:16S ribosomal RNA

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Short description: RNA component
Molecular structure of the 30S Subunit from Thermus thermophilus. Proteins are shown in blue and the single RNA strand in orange.[1]

16S ribosomal RNA (or 16S rRNA) is the RNA component of the 30S subunit of a prokaryotic ribosome (SSU rRNA). It binds to the Shine-Dalgarno sequence and provides most of the SSU structure.

The genes coding for it are referred to as 16S rRNA genes and are used in reconstructing phylogenies, due to the slow rates of evolution of this region of the gene.[2] Carl Woese and George E. Fox were two of the people who pioneered the use of 16S rRNA in phylogenetics in 1977.[3] Multiple sequences of the 16S rRNA gene can exist within a single bacterium.[4]

Functions

  • Like the large (23S) ribosomal RNA, it has a structural role, acting as a scaffold defining the positions of the ribosomal proteins.
  • The 3′-end contains the anti-Shine-Dalgarno sequence, which binds upstream to the AUG start codon on the mRNA. The 3′-end of 16S RNA binds to the proteins S1 and S21 which are known to be involved in initiation of protein synthesis[5]
  • Interacts with 23S, aiding in the binding of the two ribosomal subunits (50S and 30S)
  • Stabilizes correct codon-anticodon pairing in the A-site by forming a hydrogen bond between the N1 atom of adenine residues 1492 and 1493 and the 2′OH group of the mRNA backbone.

Structure

SSU Ribosomal RNA, bacteria and archaea. From Woese 1987.[6]

Universal primers

The 16S rRNA gene is used for phylogenetic studies[7] as it is highly conserved between different species of bacteria and archaea.[8] Carl Woese pioneered this use of 16S rRNA in 1977.[2] It is suggested that 16S rRNA gene can be used as a reliable molecular clock because 16S rRNA sequences from distantly related bacterial lineages are shown to have similar functionalities.[9] Some thermophilic archaea (e.g. order Thermoproteales) contain 16S rRNA gene introns that are located in highly conserved regions and can impact the annealing of "universal" primers.[10] Mitochondrial and chloroplastic rRNA are also amplified.[11]

The most common primer pair was devised by Weisburg et al. (1991)[7] and is currently referred to as 27F and 1492R; however, for some applications shorter amplicons may be necessary, for example for 454 sequencing with titanium chemistry the primer pair 27F-534R covering V1 to V3.[12] Often 8F is used rather than 27F. The two primers are almost identical, but 27F has an M instead of a C. AGAGTTTGATCMTGGCTCAG compared with 8F.[13]

Primer name Sequence (5′–3′) Ref.
8F AGA GTT TGA TCC TGG CTC AG [14][15]
27F AGA GTT TGA TCM TGG CTC AG [13]
336R ACT GCT GCS YCC CGT AGG AGT CT [16]
337F GAC TCC TAC GGG AGG CWG CAG [17]
518R GTA TTA CCG CGG CTG CTG G
533F GTG CCA GCM GCC GCG GTA A
785F GGA TTA GAT ACC CTG GTA
806R GGA CTA CVS GGG TAT CTA AT [18][19]
907R CCG TCA ATT CCT TTR AGT TT
928F TAA AAC TYA AAK GAA TTG ACG GG [16]
1100F YAA CGA GCG CAA CCC
1100R GGG TTG CGC TCG TTG
U1492R GGT TAC CTT GTT ACG ACT T [14][15]
1492R CGG TTA CCT TGT TAC GAC TT [20]

PCR and NGS applications

In addition to highly conserved primer binding sites, 16S rRNA gene sequences contain hypervariable regions that can provide species-specific signature sequences useful for identification of bacteria.[21][22] As a result, 16S rRNA gene sequencing has become prevalent in medical microbiology as a rapid and cheap alternative to phenotypic methods of bacterial identification.[23] Although it was originally used to identify bacteria, 16S sequencing was subsequently found to be capable of reclassifying bacteria into completely new species,[24] or even genera.[7][25] It has also been used to describe new species that have never been successfully cultured.[26][27] With third-generation sequencing coming to many labs, simultaneous identification of thousands of 16S rRNA sequences is possible within hours, allowing metagenomic studies, for example of gut flora.[28]

Hypervariable regions

The bacterial 16S gene contains nine hypervariable regions (V1–V9), ranging from about 30 to 100 base pairs long, that are involved in the secondary structure of the small ribosomal subunit.[29] The degree of conservation varies widely between hypervariable regions, with more conserved regions correlating to higher-level taxonomy and less conserved regions to lower levels, such as genus and species.[30] While the entire 16S sequence allows for comparison of all hypervariable regions, at approximately 1,500 base pairs long it can be prohibitively expensive for studies seeking to identify or characterize diverse bacterial communities.[30] These studies commonly utilize the Illumina platform, which produces reads at rates 50-fold and 12,000-fold less expensive than 454 pyrosequencing and Sanger sequencing, respectively.[31] While cheaper and allowing for deeper community coverage, Illumina sequencing only produces reads 75–250 base pairs long (up to 300 base pairs with Illumina MiSeq), and has no established protocol for reliably assembling the full gene in community samples.[32] Full hypervariable regions can be assembled from a single Illumina run, however, making them ideal targets for the platform.[32]

While 16S hypervariable regions can vary dramatically between bacteria, the 16S gene as a whole maintains greater length homogeneity than its eukaryotic counterpart (18S ribosomal RNA), which can make alignments easier.[33] Additionally, the 16S gene contains highly conserved sequences between hypervariable regions, enabling the design of universal primers that can reliably produce the same sections of the 16S sequence across different taxa.[34] Although no hypervariable region can accurately classify all bacteria from domain to species, some can reliably predict specific taxonomic levels.[30] Many community studies select semi-conserved hypervariable regions like the V4 for this reason, as it can provide resolution at the phylum level as accurately as the full 16S gene.[30] While lesser-conserved regions struggle to classify new species when higher order taxonomy is unknown, they are often used to detect the presence of specific pathogens. In one study by Chakravorty et al. in 2007, the authors characterized the V1–V8 regions of a variety of pathogens in order to determine which hypervariable regions would be most useful to include for disease-specific and broad assays.[35] Amongst other findings, they noted that the V3 region was best at identifying the genus for all pathogens tested, and that V6 was the most accurate at differentiating species between all CDC-watched pathogens tested, including anthrax.[35]

While 16S hypervariable region analysis is a powerful tool for bacterial taxonomic studies, it struggles to differentiate between closely related species.[34] In the families Enterobacteriaceae, Clostridiaceae, and Peptostreptococcaceae, species can share up to 99% sequence similarity across the full 16S gene.[36] As a result, the V4 sequences can differ by only a few nucleotides, leaving reference databases unable to reliably classify these bacteria at lower taxonomic levels.[36] By limiting 16S analysis to select hypervariable regions, these studies can fail to observe differences in closely related taxa and group them into single taxonomic units, therefore underestimating the total diversity of the sample.[34] Furthermore, bacterial genomes can house multiple 16S genes, with the V1, V2, and V6 regions containing the greatest intraspecies diversity.[8] While not the most precise method of classifying bacterial species, analysis of the hypervariable regions remains one of the most useful tools available to bacterial community studies.[36]

Promiscuity of 16S rRNA genes

Under the assumption that evolution is driven by vertical transmission, 16S rRNA genes have long been believed to be species-specific, and infallible as genetic markers inferring phylogenetic relationships among prokaryotes. However, a growing number of observations suggest the occurrence of horizontal transfer of these genes. In addition to observations of natural occurrence, transferability of these genes is supported experimentally using a specialized Escherichia coli genetic system. Using a null mutant of E. coli as host, growth of the mutant strain was shown to be complemented by foreign 16S rRNA genes that were phylogenetically distinct from E. coli at the phylum level.[37][38] Such functional compatibility was also seen in Thermus thermophilus.[39] Furthermore, in T. thermophilus, both complete and partial gene transfer was observed. Partial transfer resulted in spontaneous generation of apparently random chimera between host and foreign bacterial genes. Thus, 16S rRNA genes may have evolved through multiple mechanisms, including vertical inheritance and horizontal gene transfer; the frequency of the latter may be much higher than previously thought.[40]

16S ribosomal databases

The 16S rRNA gene is used as the standard for classification and identification of microbes, because it is present in most microbes and shows proper changes.[41] Type strains of 16S rRNA gene sequences for most bacteria and archaea are available on public databases, such as NCBI. However, the quality of the sequences found on these databases is often not validated. Therefore, secondary databases that collect only 16S rRNA sequences are widely used. The most frequently used databases are listed below:

MIMt

MIMt is a compact non-redundant 16S database for a rapid metagenomic samples identification. It is composed of 39.940 full 16S sequences belonging to 17,625 well classified bacteria and archaea species. All sequences were obtained from complete genomes deposited in NCBI and for each of the sequences full taxonomic hierarchy is provided. It contains no redundancy, so only one representative for each species was considered avoiding same sequences from differente strains, isolates or patovars resulting in a very fast tool for microorganisms identification, compatible with any classification software (QIIME, Mothur, DADA, etc). [42]

EzBioCloud

EzBioCloud database, formerly known as EzTaxon, consists of a complete hierarchical taxonomic system containing 62,988 bacteria and archaea species/phylotypes which includes 15,290 valid published names as of September 2018. Based on the phylogenetic relationship such as maximum-likelihood and OrthoANI, all species/subspecies are represented by at least one 16S rRNA gene sequence. The EzBioCloud database is systematically curated and updated regularly which also includes novel candidate species. Moreover, the website provides bioinformatics tools such as ANI calculator, ContEst16S and 16S rRNA DB for QIIME and Mothur pipeline.[43]

Ribosomal Database Project

The Ribosomal Database Project (RDP) is a curated database that offers ribosome data along with related programs and services. The offerings include phylogenetically ordered alignments of ribosomal RNA (rRNA) sequences, derived phylogenetic trees, rRNA secondary structure diagrams and various software packages for handling, analyzing and displaying alignments and trees. The data are available via ftp and electronic mail. Certain analytic services are also provided by the electronic mail server.[44] Due to its large size the RDP database is often used as the basis for bioinformatic tool development and creating manually curated databases.[45]

SILVA

SILVA provides comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life as well as a suite of search, primer-design and alignment tools (Bacteria, Archaea and Eukarya).[46]

GreenGenes

GreenGenes is a quality controlled, comprehensive 16S rRNA gene reference database and taxonomy based on a de novo phylogeny that provides standard operational taxonomic unit sets. Beware that it utilizes taxonomic terms proposed from phylogenetic methods applied years ago between 2012 and 2013. Since then, a variety of novel phylogenetic methods have been proposed for Archaea and Bacteria.[47][48]

References

  1. ↑ "Structure of functionally activated small ribosomal subunit at 3.3 angstroms resolution". Cell 102 (5): 615–623. September 2000. doi:10.1016/S0092-8674(00)00084-2. PMID 11007480. 
  2. ↑ 2.0 2.1 "Phylogenetic structure of the prokaryotic domain: the primary kingdoms". Proceedings of the National Academy of Sciences of the United States of America 74 (11): 5088–5090. November 1977. doi:10.1073/pnas.74.11.5088. PMID 270744. Bibcode: 1977PNAS...74.5088W. open access
  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): 4576–4579. June 1990. doi:10.1073/pnas.87.12.4576. PMID 2112744. Bibcode: 1990PNAS...87.4576W. 
  4. ↑ "Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies". Applied and Environmental Microbiology 73 (1): 278–288. January 2007. doi:10.1128/AEM.01177-06. PMID 17071787. Bibcode: 2007ApEnM..73..278C. 
  5. ↑ "30S ribosomal proteins associated with the 3'-terminus of 16S RNA". FEBS Letters 58 (1): 281–284. October 1975. doi:10.1016/0014-5793(75)80279-1. PMID 1225593. 
  6. ↑ "Bacterial evolution". Microbiological Reviews 51 (2): 221–271. June 1987. doi:10.1128/MR.51.2.221-271.1987. PMID 2439888. 
  7. ↑ 7.0 7.1 7.2 "16S ribosomal DNA amplification for phylogenetic study". Journal of Bacteriology 173 (2): 697–703. January 1991. doi:10.1128/jb.173.2.697-703.1991. PMID 1987160. 
  8. ↑ 8.0 8.1 "Intragenomic heterogeneity between multiple 16S ribosomal RNA operons in sequenced bacterial genomes". FEMS Microbiology Letters 228 (1): 45–49. November 2003. doi:10.1016/S0378-1097(03)00717-1. PMID 14612235. 
  9. ↑ "Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs" (in En). Scientific Reports 7 (1): 9993. August 2017. doi:10.1038/s41598-017-10214-3. PMID 28855596. Bibcode: 2017NatSR...7.9993T. 
  10. ↑ "The distribution, diversity, and importance of 16S rRNA gene introns in the order Thermoproteales". Biology Direct 10 (35): 35. July 2015. doi:10.1186/s13062-015-0065-6. PMID 26156036. 
  11. ↑ Walker, Sidney P.; Barrett, Maurice; Hogan, Glenn; Flores Bueso, Yensi; Claesson, Marcus J.; Tangney, Mark (2020-10-01). "Non-specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis". Scientific Reports 10 (1): 16356. doi:10.1038/s41598-020-73403-7. ISSN 2045-2322. PMID 33004967. 
  12. ↑ "Human Microbiome Project DACC - Home". http://www.hmpdacc.org/tools_protocols.php#sequencing. 
  13. ↑ 13.0 13.1 "Primers, 16S ribosomal DNA - François Lutzoni's Lab". http://www.lutzonilab.net/primers/page604.shtml. 
  14. ↑ 14.0 14.1 "Phylogenetic analysis of Aquaspirillum magnetotacticum using polymerase chain reaction-amplified 16S rRNA-specific DNA". International Journal of Systematic Bacteriology 41 (2): 324–325. April 1991. doi:10.1099/00207713-41-2-324. PMID 1854644. 
  15. ↑ 15.0 15.1 James, Greg (15 May 2018). "Universal Bacterial Identification by PCR and DNA Sequencing of 16S rRNA Gene". PCR for Clinical Microbiology. Springer, Dordrecht. pp. 209–214. doi:10.1007/978-90-481-9039-3_28. ISBN 978-90-481-9038-6. 
  16. ↑ 16.0 16.1 "Diversity of uncultured microorganisms associated with the seagrass Halophila stipulacea estimated by restriction fragment length polymorphism analysis of PCR-amplified 16S rRNA genes". Applied and Environmental Microbiology 62 (3): 766–771. March 1996. doi:10.1128/AEM.62.3.766-771.1996. PMID 8975607. PMC 167844. Bibcode: 1996ApEnM..62..766W. http://aem.asm.org/cgi/reprint/62/3/766.pdf. 
  17. ↑ Park, Changwoo; Kim, Seung Bum; Choi, Sang Ho; Kim, Seil (2021). "Comparison of 16S rRNA Gene Based Microbial Profiling Using Five Next-Generation Sequencers and Various Primers". Frontiers in Microbiology 12. doi:10.3389/fmicb.2021.715500. ISSN 1664-302X. 
  18. ↑ "Metagenomics uncovers gaps in amplicon-based detection of microbial diversity". Nature Microbiology 1 (4): 15032. February 2016. doi:10.1038/nmicrobiol.2015.32. PMID 27572438. 
  19. ↑ "The under-recognized dominance of Verrucomicrobia in soil bacterial communities". Soil Biology & Biochemistry 43 (7): 1450–1455. July 2011. doi:10.1016/j.soilbio.2011.03.012. PMID 22267877. 
  20. ↑ "Microbial diversity in water and sediment of Lake Chaka, an athalassohaline lake in northwestern China". Applied and Environmental Microbiology 72 (6): 3832–3845. June 2006. doi:10.1128/AEM.02869-05. PMID 16751487. Bibcode: 2006ApEnM..72.3832J. 
  21. ↑ "Identification of species by multiplex analysis of variable-length sequences". Nucleic Acids Research 38 (22): e203. December 2010. doi:10.1093/nar/gkq865. PMID 20923781. 
  22. ↑ "Ribosomal DNA sequencing as a tool for identification of bacterial pathogens". Current Opinion in Microbiology 2 (3): 299–305. June 1999. doi:10.1016/S1369-5274(99)80052-6. PMID 10383862. 
  23. ↑ "Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases". Clinical Microbiology Reviews 17 (4): 840–62, table of contents. October 2004. doi:10.1128/CMR.17.4.840-862.2004. PMID 15489351. 
  24. ↑ "Reverse transcription of 16S rRNA to monitor ribosome-synthesizing bacterial populations in the environment". Applied and Environmental Microbiology 75 (13): 4589–4598. July 2009. doi:10.1128/AEM.02970-08. PMID 19395563. Bibcode: 2009ApEnM..75.4589L. 
  25. ↑ "Burkholderia thailandensis sp. nov., a Burkholderia pseudomallei-like species". International Journal of Systematic Bacteriology 48 Pt 1 (1): 317–320. January 1998. doi:10.1099/00207713-48-1-317. PMID 9542103. 
  26. ↑ "Phylogenetic identification of uncultured pathogens using ribosomal RNA sequences". Bacterial Pathogenesis Part A: Identification and Regulation of Virulence Factors. Methods in Enzymology. 235. 1994. pp. 205–222. doi:10.1016/0076-6879(94)35142-2. ISBN 978-0-12-182136-4. https://archive.org/details/bacterialpathoge0000unse_f8b6/page/205. 
  27. ↑ "Phylogenetic analysis of the bacterial communities in marine sediments". Applied and Environmental Microbiology 62 (11): 4049–4059. November 1996. doi:10.1128/AEM.62.11.4049-4059.1996. PMID 8899989. Bibcode: 1996ApEnM..62.4049G. 
  28. ↑ "Next-generation sequencing of 16S ribosomal RNA gene amplicons". Journal of Visualized Experiments (90). August 2014. doi:10.3791/51709. PMID 25226019. 
  29. ↑ "On the evolutionary descent of organisms and organelles: a global phylogeny based on a highly conserved structural core in small subunit ribosomal RNA". Nucleic Acids Research 12 (14): 5837–5852. July 1984. doi:10.1093/nar/12.14.5837. PMID 6462918. 
  30. ↑ 30.0 30.1 30.2 30.3 "Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis". BMC Bioinformatics 17 (1): 135. March 2016. doi:10.1186/s12859-016-0992-y. PMID 27000765. 
  31. ↑ "Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads". Applied and Environmental Microbiology 77 (11): 3846–3852. June 2011. doi:10.1128/AEM.02772-10. PMID 21460107. Bibcode: 2011ApEnM..77.3846B. 
  32. ↑ 32.0 32.1 "A method for high precision sequencing of near full-length 16S rRNA genes on an Illumina MiSeq". PeerJ 4: e2492. 2016-09-20. doi:10.7717/peerj.2492. PMID 27688981. 
  33. ↑ "A quantitative map of nucleotide substitution rates in bacterial rRNA". Nucleic Acids Research 24 (17): 3381–3391. September 1996. doi:10.1093/nar/24.17.3381. PMID 8811093. 
  34. ↑ 34.0 34.1 34.2 "The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses". PLOS ONE 8 (2): e57923. 2013-02-27. doi:10.1371/journal.pone.0057923. PMID 23460914. Bibcode: 2013PLoSO...857923V. 
  35. ↑ 35.0 35.1 "A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria". Journal of Microbiological Methods 69 (2): 330–339. May 2007. doi:10.1016/j.mimet.2007.02.005. PMID 17391789. 
  36. ↑ 36.0 36.1 36.2 "Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics". Frontiers in Microbiology 7: 459. 2016-01-01. doi:10.3389/fmicb.2016.00459. PMID 27148170. 
  37. ↑ "Mutational robustness of 16S ribosomal RNA, shown by experimental horizontal gene transfer in Escherichia coli". Proceedings of the National Academy of Sciences of the United States of America 109 (47): 19220–19225. November 2012. doi:10.1073/pnas.1213609109. PMID 23112186. Bibcode: 2012PNAS..10919220K. 
  38. ↑ "Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs". Scientific Reports 7 (1): 9993. August 2017. doi:10.1038/s41598-017-10214-3. PMID 28855596. Bibcode: 2017NatSR...7.9993T. 
  39. ↑ "Occurrence of randomly recombined functional 16S rRNA genes in Thermus thermophilus suggests genetic interoperability and promiscuity of bacterial 16S rRNAs". Scientific Reports 9 (1): 11233. August 2019. doi:10.1038/s41598-019-47807-z. PMID 31375780. Bibcode: 2019NatSR...911233M. 
  40. ↑ Miyazaki, Kentaro; Tomariguchi, Natsuki (2019-08-02). "Occurrence of randomly recombined functional 16S rRNA genes in Thermus thermophilus suggests genetic interoperability and promiscuity of bacterial 16S rRNAs". Scientific Reports 9 (1): 11233. doi:10.1038/s41598-019-47807-z. ISSN 2045-2322. PMID 31375780. Bibcode: 2019NatSR...911233M. 
  41. ↑ "Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences". Nature Reviews. Microbiology 12 (9): 635–645. September 2014. doi:10.1038/nrmicro3330. PMID 25118885. 
  42. ↑ https://mimt.bu.biopolis.pt
  43. ↑ Yoon, S. H., Ha, S. M., Kwon, S., Lim, J., Kim, Y., Seo, H. and Chun, J. (2017). Introducing EzBioCloud: A taxonomically united database of 16S rRNA and whole genome assemblies. Int J Syst Evol Microbiol. 67:1613–1617
  44. ↑ Larsen N, Olsen GJ, Maidak BL, McCaughey MJ, Overbeek R, Macke TJ, Marsh TL, Woese CR. (1993) The ribosomal database project. Nucleic Acids Res. Jul 1;21(13):3021-3.
  45. ↑ "SPINGO: a rapid species-classifier for microbial amplicon sequences". BMC Bioinformatics 16 (1): 324. October 2015. doi:10.1186/s12859-015-0747-1. PMID 26450747. 
  46. ↑ Elmar Pruesse, Christian Quast, Katrin Knittel, Bernhard M. Fuchs, Wolfgang Ludwig, Jörg Peplies, Frank Oliver Glöckner (2007) Nucleic Acids Res. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. December; 35(21): 7188–7196.
  47. ↑ "Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB". Applied and Environmental Microbiology 72 (7): 5069–5072. July 2006. doi:10.1128/aem.03006-05. PMID 16820507. Bibcode: 2006ApEnM..72.5069D. 
  48. ↑ "An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea". The ISME Journal 6 (3): 610–618. March 2012. doi:10.1038/ismej.2011.139. PMID 22134646. Bibcode: 2012ISMEJ...6..610M. 

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