16S ribosomal RNA

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Molecular structure of the 30S Subunit from Thermus thermophilus. Proteins are shown in blue and the single RNA strand in a pale orange-brown colour. 010 small subunit-1FKA.gif
Molecular structure of the 30S Subunit from Thermus thermophilus . Proteins are shown in blue and the single RNA strand in a pale orange-brown colour.

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.

Contents

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

Structure

SSU Ribosomal RNA, bacteria and archaea. From Woese 1987. 16S.svg
SSU Ribosomal RNA, bacteria and archaea. From Woese 1987.

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 nameSequence (5–3)Ref.
8FAGA GTT TGA TCC TGG CTC AG [14] [15]
27FAGA GTT TGA TCM TGG CTC AG [13]
336RACT GCT GCS YCC CGT AGG AGT CT [16]
337FGAC TCC TAC GGG AGG CWG CAG [17]
518RGTA TTA CCG CGG CTG CTG G
533FGTG CCA GCM GCC GCG GTA A
785FGGA TTA GAT ACC CTG GTA
806RGGA CTA CVS GGG TAT CTA AT [18] [19]
907RCCG TCA ATT CCT TTR AGT TT
928FTAA AAC TYA AAK GAA TTG ACG GG [16]
1100FYAA CGA GCG CAA CCC
1100RGGG TTG CGC TCG TTG
U1492RGGT TAC CTT GTT ACG ACT T [14] [15]
1492RCGG 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] In samples collected from patients with confirmed infections, 16S rRNA next-generation sequencing (NGS) demonstrated enhanced detection in 40% of cases compared to traditional culture methods; moreover, pre-sampling antibiotic consumption did not significantly affect the sensitivity of 16S NGS. [29]

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. [30] 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. [31] 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. [31] 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. [32] 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. [33] Full hypervariable regions can be assembled from a single Illumina run, however, making them ideal targets for the platform. [33]

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. [34] 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. [35] Although no hypervariable region can accurately classify all bacteria from domain to species, some can reliably predict specific taxonomic levels. [31] 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. [31] 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. [36] 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. [36]

While 16S hypervariable region analysis is a powerful tool for bacterial taxonomic studies, it struggles to differentiate between closely related species. [35] In the families Enterobacteriaceae , Clostridiaceae , and Peptostreptococcaceae , species can share up to 99% sequence similarity across the full 16S gene. [37] 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. [37] 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. [35] 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. [37]

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. [38] [39] Such functional compatibility was also seen in Thermus thermophilus . [40] 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. [41]

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. [42] 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.

MIMt

MIMt is a compact non-redundant 16S database for a rapid metagenomic samples identification. It is composed of 48.749 full 16S sequences belonging to 24,626 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). [43]

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. [44] ^^

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. [45] Due to its large size the RDP database is often used as the basis for bioinformatic tool development and creating manually curated databases. [46]

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). [47]

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. [48] [49]

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<span class="mw-page-title-main">Carl Woese</span> American microbiologist (1928–2012)

Carl Richard Woese was an American microbiologist and biophysicist. Woese is famous for defining the Archaea in 1977 through a pioneering phylogenetic taxonomy of 16S ribosomal RNA, a technique that has revolutionized microbiology. He also originated the RNA world hypothesis in 1967, although not by that name. Woese held the Stanley O. Ikenberry Chair and was professor of microbiology at the University of Illinois Urbana–Champaign.

<span class="mw-page-title-main">Domain (biology)</span> Taxonomic rank

In biological taxonomy, a domain, also dominion, superkingdom, realm, or empire, is the highest taxonomic rank of all organisms taken together. It was introduced in the three-domain system of taxonomy devised by Carl Woese, Otto Kandler and Mark Wheelis in 1990.

<span class="mw-page-title-main">Three-domain system</span> Hypothesis for classification of life

The three-domain system is a taxonomic classification system that groups all cellular life into three domains, namely Archaea, Bacteria and Eukarya, introduced by Carl Woese, Otto Kandler and Mark Wheelis in 1990. The key difference from earlier classifications such as the two-empire system and the five-kingdom classification is the splitting of Archaea from Bacteria as completely different organisms. It has been challenged by the two-domain system that divides organisms into Bacteria and Archaea only, as Eukaryotes are considered a clade of Archaea.

<span class="mw-page-title-main">Nanoarchaeota</span> Phylum of archaea

Nanoarchaeota is a proposed phylum in the domain Archaea that currently has only one representative, Nanoarchaeum equitans, which was discovered in a submarine hydrothermal vent and first described in 2002.

<span class="mw-page-title-main">Thermoproteota</span> Phylum of archaea

The Thermoproteota are prokaryotes that have been classified as a phylum of the domain Archaea. Initially, the Thermoproteota were thought to be sulfur-dependent extremophiles but recent studies have identified characteristic Thermoproteota environmental rRNA indicating the organisms may be the most abundant archaea in the marine environment. Originally, they were separated from the other archaea based on rRNA sequences; other physiological features, such as lack of histones, have supported this division, although some crenarchaea were found to have histones. Until 2005 all cultured Thermoproteota had been thermophilic or hyperthermophilic organisms, some of which have the ability to grow at up to 113 °C. These organisms stain Gram negative and are morphologically diverse, having rod, cocci, filamentous and oddly-shaped cells. Recent evidence shows that some members of the Thermoproteota are methanogens.

<span class="mw-page-title-main">Korarchaeota</span> Proposed phylum within the Archaea

The Korarchaeota is a proposed phylum within the Archaea. The name is derived from the Greek noun koros or kore, meaning young man or young woman, and the Greek adjective archaios which means ancient. They are also known as Xenarchaeota. The name is equivalent to Candidatus Korarchaeota, and they go by the name Xenarchaeota or Xenarchaea as well.

The ribosomal DNA consists of a group of ribosomal RNA encoding genes and related regulatory elements, and is widespread in similar configuration in all domains of life. The ribosomal DNA encodes the non-coding ribosomal RNA, integral structural elements in the assembly of ribosomes, its importance making it the most abundant section of RNA found in cells of eukaryotes. Additionally, these segments includes regulatory sections, such as a promotor specific to the RNA polymerase I, as well as both transcribed and non-transcribed spacer segments.

Internal transcribed spacer (ITS) is the spacer DNA situated between the small-subunit ribosomal RNA (rRNA) and large-subunit rRNA genes in the chromosome or the corresponding transcribed region in the polycistronic rRNA precursor transcript.

<span class="mw-page-title-main">George E. Fox</span> American astrobiologist

George Edward Fox is an astrobiologist, a Professor Emeritus and researcher at the University of Houston. He is an elected fellow of the American Academy of Microbiology, the American Association for the Advancement of Science, American Institute for Medical and Biological Engineering and the International Astrobiology Society. Fox received his B.A. degree in 1967, and completed his Ph.D. degree in 1974; both in chemical engineering at Syracuse University.

<span class="mw-page-title-main">Archaea</span> Domain of organisms

Archaea is a domain of organisms. Traditionally, Archaea only included its prokaryotic members, but this sense has been found to be paraphyletic, as eukaryotes are now known to have evolved from archaea. Even though the domain Archaea includes eukaryotes, the term "archaea" in English still generally refers specifically to prokaryotic members of Archaea. Archaea were initially classified as bacteria, receiving the name archaebacteria, but this term has fallen out of use.

<span class="mw-page-title-main">Bacterial phyla</span> Phyla or divisions of the domain Bacteria

Bacterial phyla constitute the major lineages of the domain Bacteria. While the exact definition of a bacterial phylum is debated, a popular definition is that a bacterial phylum is a monophyletic lineage of bacteria whose 16S rRNA genes share a pairwise sequence identity of ~75% or less with those of the members of other bacterial phyla.

<span class="mw-page-title-main">Bacterial taxonomy</span> Rank based classification of bacteria

Bacterial taxonomy is subfield of taxonomy devoted to the classification of bacteria specimens into taxonomic ranks.

There are several models of the Branching order of bacterial phyla, one of these was proposed in 1987 paper by Carl Woese.

<span class="mw-page-title-main">'The All-Species Living Tree' Project</span>

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<span class="mw-page-title-main">Eocyte hypothesis</span> Hypothesis in evolutionary biology

The eocyte hypothesis in evolutionary biology proposes that the eukaryotes originated from a group of prokaryotes called eocytes. After his team at the University of California, Los Angeles discovered eocytes in 1984, James A. Lake formulated the hypothesis as "eocyte tree" that proposed eukaryotes as part of archaea. Lake hypothesised the tree of life as having only two primary branches: prokaryotes, which include Bacteria and Archaea, and karyotes, that comprise Eukaryotes and eocytes. Parts of this early hypothesis were revived in a newer two-domain system of biological classification which named the primary domains as Archaea and Bacteria.

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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.

<i>Thermodesulfobacterium hveragerdense</i> Species of bacterium

Thermodesulfobacterium hveragerdense is a bacterial species belonging to genus Thermodesulfobacterium, which are thermophilic sulfate-reducing bacteria. This species is found in aquatic areas of high temperature, and lives in freshwater like most, but not all Thermodesulfobacterium species It was first isolated from hotsprings in Iceland.

Peptidiphaga gingivicola is a Gram-positive, non-spore forming, coccus shaped bacterium. Coccus are spherical and generally round in shape. Coccus are differentiated by their groupings that can range from chains, groups, or grape-like clusters. Peptidiphaga gingivicola was observed to grow in groups of 2-5 cocci between 0.2-0.9 mm in diameter. Growth was observed when cultured under anaerobic conditions between 33 and 40 degrees celsius on Blood Brucella agar for 4 days. Peptidiphaga gingivicola has been cultured from patients with periodontal disease, primarily caused by bacterial plaque formation on the gum and teeth of the oral cavity. The microbe is known to break down peptides of the gum causing tissue damage and tooth decay, leading to serious implications for oral health.

References

  1. Schluenzen F, Tocilj A, Zarivach R, Harms J, Gluehmann M, Janell D, et al. (September 2000). "Structure of functionally activated small ribosomal subunit at 3.3 angstroms resolution". Cell. 102 (5): 615–623. doi: 10.1016/S0092-8674(00)00084-2 . PMID   11007480. S2CID   1024446.
  2. 1 2 Woese CR, Fox GE (November 1977). "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. Bibcode:1977PNAS...74.5088W. doi: 10.1073/pnas.74.11.5088 . PMC   432104 . PMID   270744. Open Access logo PLoS transparent.svg
  3. Woese CR, Kandler O, Wheelis ML (June 1990). "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. Bibcode:1990PNAS...87.4576W. doi: 10.1073/pnas.87.12.4576 . PMC   54159 . PMID   2112744.
  4. Case RJ, Boucher Y, Dahllöf I, Holmström C, Doolittle WF, Kjelleberg S (January 2007). "Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies". Applied and Environmental Microbiology. 73 (1): 278–288. Bibcode:2007ApEnM..73..278C. doi:10.1128/AEM.01177-06. PMC   1797146 . PMID   17071787.
  5. Czernilofsky AP, Kurland CG, Stöffler G (October 1975). "30S ribosomal proteins associated with the 3'-terminus of 16S RNA". FEBS Letters. 58 (1): 281–284. Bibcode:1975FEBSL..58..281C. doi: 10.1016/0014-5793(75)80279-1 . PMID   1225593. S2CID   22941368.
  6. Woese CR (June 1987). "Bacterial evolution". Microbiological Reviews. 51 (2): 221–271. doi:10.1128/MR.51.2.221-271.1987. PMC   373105 . PMID   2439888.
  7. 1 2 3 Weisburg WG, Barns SM, Pelletier DA, Lane DJ (January 1991). "16S ribosomal DNA amplification for phylogenetic study". Journal of Bacteriology. 173 (2): 697–703. doi:10.1128/jb.173.2.697-703.1991. PMC   207061 . PMID   1987160.
  8. 1 2 Coenye T, Vandamme P (November 2003). "Intragenomic heterogeneity between multiple 16S ribosomal RNA operons in sequenced bacterial genomes". FEMS Microbiology Letters. 228 (1): 45–49. doi: 10.1016/S0378-1097(03)00717-1 . PMID   14612235.
  9. Tsukuda M, Kitahara K, Miyazaki K (August 2017). "Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs". Scientific Reports. 7 (1): 9993. Bibcode:2017NatSR...7.9993T. doi:10.1038/s41598-017-10214-3. PMC   5577257 . PMID   28855596.
  10. Jay ZJ, Inskeep WP (July 2015). "The distribution, diversity, and importance of 16S rRNA gene introns in the order Thermoproteales". Biology Direct. 10 (35): 35. doi: 10.1186/s13062-015-0065-6 . PMC   4496867 . 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. PMC   7529756 . PMID   33004967.
  12. "Human Microbiome Project DACC - Home". www.hmpdacc.org. Archived from the original on 2010-10-30.
  13. 1 2 "Primers, 16S ribosomal DNA - François Lutzoni's Lab". lutzonilab.net. Archived from the original on 2012-12-27.
  14. 1 2 Eden PA, Schmidt TM, Blakemore RP, Pace NR (April 1991). "Phylogenetic analysis of Aquaspirillum magnetotacticum using polymerase chain reaction-amplified 16S rRNA-specific DNA". International Journal of Systematic Bacteriology. 41 (2): 324–325. doi: 10.1099/00207713-41-2-324 . PMID   1854644.
  15. 1 2 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. 1 2 Weidner S, Arnold W, Puhler A (March 1996). "Diversity of uncultured microorganisms associated with the seagrass Halophila stipulacea estimated by restriction fragment length polymorphism analysis of PCR-amplified 16S rRNA genes" (PDF). Applied and Environmental Microbiology. 62 (3): 766–771. Bibcode:1996ApEnM..62..766W. doi:10.1128/AEM.62.3.766-771.1996. PMC   167844 . PMID   8975607. Archived (PDF) from the original on 2011-07-15.
  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. PMC   8552068 . PMID   34721319.
  18. Eloe-Fadrosh EA, Ivanova NN, Woyke T, Kyrpides NC (February 2016). "Metagenomics uncovers gaps in amplicon-based detection of microbial diversity". Nature Microbiology. 1 (4): 15032. doi:10.1038/nmicrobiol.2015.32. OSTI   1379258. PMID   27572438. S2CID   27232975.
  19. Bergmann GT, Bates ST, Eilers KG, Lauber CL, Caporaso JG, Walters WA, et al. (July 2011). "The under-recognized dominance of Verrucomicrobia in soil bacterial communities". Soil Biology & Biochemistry. 43 (7): 1450–1455. Bibcode:2011SBiBi..43.1450B. doi:10.1016/j.soilbio.2011.03.012. PMC   3260529 . PMID   22267877.
  20. Jiang H, Dong H, Zhang G, Yu B, Chapman LR, Fields MW (June 2006). "Microbial diversity in water and sediment of Lake Chaka, an athalassohaline lake in northwestern China". Applied and Environmental Microbiology. 72 (6): 3832–3845. Bibcode:2006ApEnM..72.3832J. doi:10.1128/AEM.02869-05. PMC   1489620 . PMID   16751487.
  21. Pereira F, Carneiro J, Matthiesen R, van Asch B, Pinto N, Gusmão L, Amorim A (December 2010). "Identification of species by multiplex analysis of variable-length sequences". Nucleic Acids Research. 38 (22): e203. doi:10.1093/nar/gkq865. PMC   3001097 . PMID   20923781.
  22. Kolbert CP, Persing DH (June 1999). "Ribosomal DNA sequencing as a tool for identification of bacterial pathogens". Current Opinion in Microbiology. 2 (3): 299–305. doi:10.1016/S1369-5274(99)80052-6. PMID   10383862.
  23. Clarridge JE (October 2004). "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. doi:10.1128/CMR.17.4.840-862.2004. PMC   523561 . PMID   15489351.
  24. Lu T, Stroot PG, Oerther DB (July 2009). "Reverse transcription of 16S rRNA to monitor ribosome-synthesizing bacterial populations in the environment". Applied and Environmental Microbiology. 75 (13): 4589–4598. Bibcode:2009ApEnM..75.4589L. doi:10.1128/AEM.02970-08. PMC   2704851 . PMID   19395563.
  25. Brett PJ, DeShazer D, Woods DE (January 1998). "Burkholderia thailandensis sp. nov., a Burkholderia pseudomallei-like species". International Journal of Systematic Bacteriology. 48 Pt 1 (1): 317–320. doi: 10.1099/00207713-48-1-317 . PMID   9542103.
  26. Schmidt TM, Relman DA (1994). "Phylogenetic identification of uncultured pathogens using ribosomal RNA sequences" . Bacterial Pathogenesis Part A: Identification and Regulation of Virulence Factors. Methods in Enzymology. Vol. 235. pp.  205–222. doi:10.1016/0076-6879(94)35142-2. ISBN   978-0-12-182136-4. PMID   7520119.
  27. Gray JP, Herwig RP (November 1996). "Phylogenetic analysis of the bacterial communities in marine sediments". Applied and Environmental Microbiology. 62 (11): 4049–4059. Bibcode:1996ApEnM..62.4049G. doi:10.1128/AEM.62.11.4049-4059.1996. PMC   168226 . PMID   8899989.
  28. Sanschagrin S, Yergeau E (August 2014). "Next-generation sequencing of 16S ribosomal RNA gene amplicons". Journal of Visualized Experiments (90). doi:10.3791/51709. PMC   4828026 . PMID   25226019.
  29. Botan, Alexandru; Campisciano, Giuseppina; Zerbato, Verena; Di Bella, Stefano; Simonetti, Omar; Busetti, Marina; Toc, Dan Alexandru; Luzzati, Roberto; Comar, Manola (2024-06-21). "Performance of 16S rRNA Gene Next-Generation Sequencing and the Culture Method in the Detection of Bacteria in Clinical Specimens". Diagnostics. 14 (13): 1318. doi: 10.3390/diagnostics14131318 . ISSN   2075-4418. PMC   11240331 . PMID   39001210.
  30. Gray MW, Sankoff D, Cedergren RJ (July 1984). "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. doi:10.1093/nar/12.14.5837. PMC   320035 . PMID   6462918.
  31. 1 2 3 4 Yang B, Wang Y, Qian PY (March 2016). "Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis". BMC Bioinformatics. 17 (1): 135. doi: 10.1186/s12859-016-0992-y . PMC   4802574 . PMID   27000765.
  32. Bartram AK, Lynch MD, Stearns JC, Moreno-Hagelsieb G, Neufeld JD (June 2011). "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. Bibcode:2011ApEnM..77.3846B. doi:10.1128/AEM.02772-10. PMC   3127616 . PMID   21460107.
  33. 1 2 Burke CM, Darling AE (2016-09-20). "A method for high precision sequencing of near full-length 16S rRNA genes on an Illumina MiSeq". PeerJ. 4: e2492. doi: 10.7717/peerj.2492 . PMC   5036073 . PMID   27688981.
  34. Van de Peer Y, Chapelle S, De Wachter R (September 1996). "A quantitative map of nucleotide substitution rates in bacterial rRNA". Nucleic Acids Research. 24 (17): 3381–3391. doi:10.1093/nar/24.17.3381. PMC   146102 . PMID   8811093.
  35. 1 2 3 Větrovský T, Baldrian P (2013-02-27). "The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses". PLOS ONE. 8 (2): e57923. Bibcode:2013PLoSO...857923V. doi: 10.1371/journal.pone.0057923 . PMC   3583900 . PMID   23460914.
  36. 1 2 Chakravorty S, Helb D, Burday M, Connell N, Alland D (May 2007). "A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria". Journal of Microbiological Methods. 69 (2): 330–339. doi:10.1016/j.mimet.2007.02.005. PMC   2562909 . PMID   17391789.
  37. 1 2 3 Jovel J, Patterson J, Wang W, Hotte N, O'Keefe S, Mitchel T, et al. (2016-01-01). "Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics". Frontiers in Microbiology. 7: 459. doi: 10.3389/fmicb.2016.00459 . PMC   4837688 . PMID   27148170.
  38. Kitahara K, Yasutake Y, Miyazaki K (November 2012). "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. Bibcode:2012PNAS..10919220K. doi: 10.1073/pnas.1213609109 . PMC   3511107 . PMID   23112186.
  39. Tsukuda M, Kitahara K, Miyazaki K (August 2017). "Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs". Scientific Reports. 7 (1): 9993. Bibcode:2017NatSR...7.9993T. doi:10.1038/s41598-017-10214-3. PMC   5577257 . PMID   28855596.
  40. Miyazaki K, Tomariguchi N (August 2019). "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. Bibcode:2019NatSR...911233M. doi:10.1038/s41598-019-47807-z. PMC   6677816 . PMID   31375780.
  41. 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. Bibcode:2019NatSR...911233M. doi:10.1038/s41598-019-47807-z. ISSN   2045-2322. PMC   6677816 . PMID   31375780.
  42. Yarza P, Yilmaz P, Pruesse E, Glöckner FO, Ludwig W, Schleifer KH, et al. (September 2014). "Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences". Nature Reviews. Microbiology. 12 (9): 635–645. doi:10.1038/nrmicro3330. PMID   25118885. S2CID   21895693.
  43. "MIMt - (Mass Identification of Metagenomics tests)". mimt.bu.biopolis.pt. Retrieved 11 February 2024.
  44. 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
  45. 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.
  46. Allard G, Ryan FJ, Jeffery IB, Claesson MJ (October 2015). "SPINGO: a rapid species-classifier for microbial amplicon sequences". BMC Bioinformatics. 16 (1): 324. doi: 10.1186/s12859-015-0747-1 . PMC   4599320 . PMID   26450747.
  47. 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.
  48. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. (July 2006). "Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB". Applied and Environmental Microbiology. 72 (7): 5069–5072. Bibcode:2006ApEnM..72.5069D. doi:10.1128/aem.03006-05. PMC   1489311 . PMID   16820507.
  49. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, et al. (March 2012). "An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea". The ISME Journal. 6 (3): 610–618. Bibcode:2012ISMEJ...6..610M. doi:10.1038/ismej.2011.139. PMC   3280142 . PMID   22134646.