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Biologists are unable to [[Microbiological culture|culture and grow]] 99% of all living [[microorganism]]s,<ref>{{cite journal |title=Single cell biotechnology to shed a light on biological 'dark matter' in nature |journal=Microbial Biotechnology |date=28 January 2015 |last=Huang |first=Wei E. |last2=Song |first2= Yizhi |last3=Xu |first3=Jian |volume=8 |issue=1 |pages=15–16 |pmc=4321360 |doi=10.1111/1751-7915.12249 |pmid=25627841}}</ref><ref>{{cite news |last=Lok |first=Corie |url=http://www.nature.com/news/mining-the-microbial-dark-matter-1.17774 |title=Mining the microbial dark matter |work=Nature News |date=16 June 2015 |accessdate=2015-09-09 }}</ref><ref>{{cite news |last=Check-Hayden |first=Erika |url=http://www.nature.com/news/researchers-glimpse-microbial-dark-matter-1.13361 |title=Researchers glimpse microbial 'dark matter' |work=Nature News |date=14 July 2013 |accessdate=2015-09-09 }}</ref><ref>{{cite news |last=Gronstal |first= Aaron L. |title=Studying Biology’s Dark Matter |work=NASA Astrobiology Institute |date=4 November 2011 |accessdate=2015-09-09 |url=https://www.astrobio.net/also-in-news/studying-biologys-dark-matter-2/ }}</ref><ref>{{cite web |url=http://microbialdarkmatter.org/index.php/11-intro/2-what-is-microbial-dark-matter-and-why-should-we-explore-it |title=What is Microbial Dark Matter and why should we explore it? |last=Rinke |first=Chris |work=Microbial Dark Matter |date=2015 |accessdate=2015-09-09 }}</ref> so few functional insights exist about the [[metabolism|metabolic potential]] of these organisms.
Biologists are unable to [[Microbiological culture|culture and grow]] 99% of all living [[microorganism]]s,<ref>{{cite journal |title=Single cell biotechnology to shed a light on biological 'dark matter' in nature |journal=Microbial Biotechnology |date=28 January 2015 |last=Huang |first=Wei E. |last2=Song |first2= Yizhi |last3=Xu |first3=Jian |volume=8 |issue=1 |pages=15–16 |pmc=4321360 |doi=10.1111/1751-7915.12249 |pmid=25627841}}</ref><ref>{{cite news |last=Lok |first=Corie |url=http://www.nature.com/news/mining-the-microbial-dark-matter-1.17774 |title=Mining the microbial dark matter |work=Nature News |date=16 June 2015 |accessdate=2015-09-09 }}</ref><ref>{{cite news |last=Check-Hayden |first=Erika |url=http://www.nature.com/news/researchers-glimpse-microbial-dark-matter-1.13361 |title=Researchers glimpse microbial 'dark matter' |work=Nature News |date=14 July 2013 |accessdate=2015-09-09 }}</ref><ref>{{cite news |last=Gronstal |first= Aaron L. |title=Studying Biology’s Dark Matter |work=NASA Astrobiology Institute |date=4 November 2011 |accessdate=2015-09-09 |url=https://www.astrobio.net/also-in-news/studying-biologys-dark-matter-2/ }}</ref><ref>{{cite web |url=http://microbialdarkmatter.org/index.php/11-intro/2-what-is-microbial-dark-matter-and-why-should-we-explore-it |title=What is Microbial Dark Matter and why should we explore it? |last=Rinke |first=Chris |work=Microbial Dark Matter |date=2015 |accessdate=2015-09-09 }}</ref> so few functional insights exist about the [[metabolism|metabolic potential]] of these organisms.

Sequences that are believed to be derived from unknown microbes are referred to as the ‘Microbial Dark Matter <ref>{{Cite journal|last=Lok|first=Corie|date=2015-06-18|title=Mining the microbial dark matter|url=https://www.ncbi.nlm.nih.gov/pubmed/26085253|journal=Nature|volume=522|issue=7556|pages=270–273|doi=10.1038/522270a|issn=1476-4687|pmid=26085253}}</ref>, the ‘Dark Virome’ <ref>{{Cite journal|last=Hannigan|first=Geoffrey D.|last2=Meisel|first2=Jacquelyn S.|last3=Tyldsley|first3=Amanda S.|last4=Zheng|first4=Qi|last5=Hodkinson|first5=Brendan P.|last6=SanMiguel|first6=Adam J.|last7=Minot|first7=Samuel|last8=Bushman|first8=Frederic D.|last9=Grice|first9=Elizabeth A.|date=2015-10-20|title=The human skin double-stranded DNA virome: topographical and temporal diversity, genetic enrichment, and dynamic associations with the host microbiome|url=https://www.ncbi.nlm.nih.gov/pubmed/26489866|journal=mBio|volume=6|issue=5|pages=e01578–01515|doi=10.1128/mBio.01578-15|issn=2150-7511|pmc=PMCPMC4620475|pmid=26489866}}</ref>, or ‘Dark Matter Fungi’ <ref>{{Cite journal|last=Ryberg|first=Martin|last2=Nilsson|first2=R. Henrik|date=2018|title=New light on names and naming of dark taxa|url=https://www.ncbi.nlm.nih.gov/pubmed/29681731|journal=MycoKeys|issue=30|pages=31–39|doi=10.3897/mycokeys.30.24376|issn=1314-4049|pmc=PMCPMC5904500|pmid=29681731}}</ref>.  Such sequences are not rare.  It has been estimated that in material from humans, between 40 and 90% of viral sequences are from Dark Matter <ref>{{Cite journal|last=Aggarwala|first=Varun|last2=Liang|first2=Guanxiang|last3=Bushman|first3=Frederic D.|date=2017|title=Viral communities of the human gut: metagenomic analysis of composition and dynamics|url=https://www.ncbi.nlm.nih.gov/pubmed/29026445|journal=Mobile DNA|volume=8|pages=12|doi=10.1186/s13100-017-0095-y|issn=1759-8753|pmc=PMCPMC5627405|pmid=29026445}}</ref> <ref>{{Cite journal|last=Kramná|first=Lenka|last2=Kolářová|first2=Kateřina|last3=Oikarinen|first3=Sami|last4=Pursiheimo|first4=Juha-Pekka|last5=Ilonen|first5=Jorma|last6=Simell|first6=Olli|last7=Knip|first7=Mikael|last8=Veijola|first8=Riitta|last9=Hyöty|first9=Heikki|date=2015-5|title=Gut virome sequencing in children with early islet autoimmunity|url=https://www.ncbi.nlm.nih.gov/pubmed/25678103|journal=Diabetes Care|volume=38|issue=5|pages=930–933|doi=10.2337/dc14-2490|issn=1935-5548|pmid=25678103}}</ref> <ref>{{Cite journal|last=Krishnamurthy|first=Siddharth R.|last2=Wang|first2=David|date=07 15, 2017|title=Origins and challenges of viral dark matter|url=https://www.ncbi.nlm.nih.gov/pubmed/28192164|journal=Virus Research|volume=239|pages=136–142|doi=10.1016/j.virusres.2017.02.002|issn=1872-7492|pmid=28192164}}</ref>.  Human blood contains over three thousand different DNA sequences which can not be identified <ref>{{Cite journal|last=Kowarsky|first=Mark|last2=Camunas-Soler|first2=Joan|last3=Kertesz|first3=Michael|last4=De Vlaminck|first4=Iwijn|last5=Koh|first5=Winston|last6=Pan|first6=Wenying|last7=Martin|first7=Lance|last8=Neff|first8=Norma F.|last9=Okamoto|first9=Jennifer|date=09 05, 2017|title=Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA|url=https://www.ncbi.nlm.nih.gov/pubmed/28830999|journal=Proceedings of the National Academy of Sciences of the United States of America|volume=114|issue=36|pages=9623–9628|doi=10.1073/pnas.1707009114|issn=1091-6490|pmc=PMCPMC5594678|pmid=28830999}}</ref>.  

The study of Biological Dark Matter requires specific software.  Algorithms have been developed that examine sequences for similarities to bacterial 16S RNA sequences <ref>{{Cite journal|last=Bowman|first=Jeff S.|date=2018|title=Identification of Microbial Dark Matter in Antarctic Environments|url=https://www.ncbi.nlm.nih.gov/pubmed/30619224|journal=Frontiers in Microbiology|volume=9|pages=3165|doi=10.3389/fmicb.2018.03165|issn=1664-302X|pmc=PMCPMC6305705|pmid=30619224}}</ref>, K-mer similarities to known viruses <ref name=":0">{{Cite journal|last=Ren|first=Jie|last2=Ahlgren|first2=Nathan A.|last3=Lu|first3=Yang Young|last4=Fuhrman|first4=Jed A.|last5=Sun|first5=Fengzhu|date=07 06, 2017|title=VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data|url=https://www.ncbi.nlm.nih.gov/pubmed/28683828|journal=Microbiome|volume=5|issue=1|pages=69|doi=10.1186/s40168-017-0283-5|issn=2049-2618|pmc=PMCPMC5501583|pmid=28683828}}</ref>,  specific features of codon usage <ref>{{Cite journal|last=Bzhalava|first=Zurab|last2=Tampuu|first2=Ardi|last3=Bała|first3=Piotr|last4=Vicente|first4=Raul|last5=Dillner|first5=Joakim|date=2018-09-24|title=Machine Learning for detection of viral sequences in human metagenomic datasets|url=https://www.ncbi.nlm.nih.gov/pubmed/30249176|journal=BMC bioinformatics|volume=19|issue=1|pages=336|doi=10.1186/s12859-018-2340-x|issn=1471-2105|pmc=PMCPMC6154907|pmid=30249176}}</ref>, or for inferring the existence of proteins <ref name=":1">{{Cite journal|last=Barrientos-Somarribas|first=Mauricio|last2=Messina|first2=David N.|last3=Pou|first3=Christian|last4=Lysholm|first4=Fredrik|last5=Bjerkner|first5=Annelie|last6=Allander|first6=Tobias|last7=Andersson|first7=Björn|last8=Sonnhammer|first8=Erik L. L.|date=01 08, 2018|title=Discovering viral genomes in human metagenomic data by predicting unknown protein families|url=https://www.ncbi.nlm.nih.gov/pubmed/29311716|journal=Scientific Reports|volume=8|issue=1|pages=28|doi=10.1038/s41598-017-18341-7|issn=2045-2322|pmc=PMCPMC5758519|pmid=29311716}}</ref>.   These approaches have suggested, for example, the existence of a novel bacteriophage of the microviridae family <ref name=":1" />, and a novel bacterioidales-like phage <ref>{{Cite journal|last=Ogilvie|first=Lesley A.|last2=Bowler|first2=Lucas D.|last3=Caplin|first3=Jonathan|last4=Dedi|first4=Cinzia|last5=Diston|first5=David|last6=Cheek|first6=Elizabeth|last7=Taylor|first7=Huw|last8=Ebdon|first8=James E.|last9=Jones|first9=Brian V.|date=2013|title=Genome signature-based dissection of human gut metagenomes to extract subliminal viral sequences|url=https://www.ncbi.nlm.nih.gov/pubmed/24036533|journal=Nature Communications|volume=4|pages=2420|doi=10.1038/ncomms3420|issn=2041-1723|pmc=PMCPMC3778543|pmid=24036533}}</ref>.  Other studies have suggested the existence of 264 new viral genera, discovered in publicly-available databases <ref>{{Cite journal|last=Roux|first=Simon|last2=Hallam|first2=Steven J.|last3=Woyke|first3=Tanja|last4=Sullivan|first4=Matthew B.|date=2015-07-22|title=Viral dark matter and virus-host interactions resolved from publicly available microbial genomes|url=https://www.ncbi.nlm.nih.gov/pubmed/26200428|journal=eLife|volume=4|doi=10.7554/eLife.08490|issn=2050-084X|pmc=PMCPMC4533152|pmid=26200428}}</ref>, and a study of human blood suggested that 42% of people have at least one previously-unknown virus each, adding up to 19 different new genera <ref>{{Cite journal|last=Moustafa|first=Ahmed|last2=Xie|first2=Chao|last3=Kirkness|first3=Ewen|last4=Biggs|first4=William|last5=Wong|first5=Emily|last6=Turpaz|first6=Yaron|last7=Bloom|first7=Kenneth|last8=Delwart|first8=Eric|last9=Nelson|first9=Karen E.|date=03 2017|title=The blood DNA virome in 8,000 humans|url=https://www.ncbi.nlm.nih.gov/pubmed/28328962|journal=PLoS pathogens|volume=13|issue=3|pages=e1006292|doi=10.1371/journal.ppat.1006292|issn=1553-7374|pmc=PMCPMC5378407|pmid=28328962}}</ref>.   A comprehensive study of DNA sequences from multiple human samples inferred the existence of 4,930 species of microbes of which 77% were previously unreported <ref>{{Cite journal|last=Pasolli|first=Edoardo|last2=Asnicar|first2=Francesco|last3=Manara|first3=Serena|last4=Zolfo|first4=Moreno|last5=Karcher|first5=Nicolai|last6=Armanini|first6=Federica|last7=Beghini|first7=Francesco|last8=Manghi|first8=Paolo|last9=Tett|first9=Adrian|date=2019-01-24|title=Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle|url=https://www.ncbi.nlm.nih.gov/pubmed/30661755|journal=Cell|volume=176|issue=3|pages=649–662.e20|doi=10.1016/j.cell.2019.01.001|issn=1097-4172|pmc=PMCPMC6349461|pmid=30661755}}</ref>.   Health-related findings include a prophage that might be associated with cirrhosis of the liver <ref name=":0" />, and seven novel sequences from children with type-1 diabetes that have characteristics of viruses <ref>{{Cite journal|last=Cinek|first=Ondrej|last2=Kramna|first2=Lenka|last3=Lin|first3=Jake|last4=Oikarinen|first4=Sami|last5=Kolarova|first5=Katerina|last6=Ilonen|first6=Jorma|last7=Simell|first7=Olli|last8=Veijola|first8=Riitta|last9=Autio|first9=Reija|date=2017-11|title=Imbalance of bacteriome profiles within the Finnish Diabetes Prediction and Prevention study: Parallel use of 16S profiling and virome sequencing in stool samples from children with islet autoimmunity and matched controls|url=https://www.ncbi.nlm.nih.gov/pubmed/27860030|journal=Pediatric Diabetes|volume=18|issue=7|pages=588–598|doi=10.1111/pedi.12468|issn=1399-5448|pmid=27860030}}</ref>.  Although they might exist, no organisms that clearly cause human disease have been discovered in the Dark Matter.

The number of life forms that remain hidden in the Biological Dark Matter is not known.  However, as discovery methods improve, so the revelation of new organisms is expected to continue and the size of the remaining Dark Matter will be reduced.  


==See also==
==See also==

Revision as of 15:05, 1 May 2019

Biological dark matter is an informal term for genetic material or microorganisms that are unclassified or poorly understood.

Biological dark matter includes non-coding DNA (junk DNA)[1][2][3] and non-coding RNA.[4][5][6] Much of the genomic dark matter is thought to originate from ancient transposable elements and from other low-complexity repetitive elements.[7][8] Uncategorized genetic material is found in humans and in several other organisms.[9][10] Their phylogenetic novelty could indicate the cellular organisms or viruses from which they evolved.[11]

Biologists are unable to culture and grow 99% of all living microorganisms,[12][13][14][15][16] so few functional insights exist about the metabolic potential of these organisms.

Sequences that are believed to be derived from unknown microbes are referred to as the ‘Microbial Dark Matter [17], the ‘Dark Virome’ [18], or ‘Dark Matter Fungi’ [19].  Such sequences are not rare.  It has been estimated that in material from humans, between 40 and 90% of viral sequences are from Dark Matter [20] [21] [22].  Human blood contains over three thousand different DNA sequences which can not be identified [23].  

The study of Biological Dark Matter requires specific software.  Algorithms have been developed that examine sequences for similarities to bacterial 16S RNA sequences [24], K-mer similarities to known viruses [25],  specific features of codon usage [26], or for inferring the existence of proteins [27].   These approaches have suggested, for example, the existence of a novel bacteriophage of the microviridae family [27], and a novel bacterioidales-like phage [28].  Other studies have suggested the existence of 264 new viral genera, discovered in publicly-available databases [29], and a study of human blood suggested that 42% of people have at least one previously-unknown virus each, adding up to 19 different new genera [30].   A comprehensive study of DNA sequences from multiple human samples inferred the existence of 4,930 species of microbes of which 77% were previously unreported [31].   Health-related findings include a prophage that might be associated with cirrhosis of the liver [25], and seven novel sequences from children with type-1 diabetes that have characteristics of viruses [32].  Although they might exist, no organisms that clearly cause human disease have been discovered in the Dark Matter.

The number of life forms that remain hidden in the Biological Dark Matter is not known.  However, as discovery methods improve, so the revelation of new organisms is expected to continue and the size of the remaining Dark Matter will be reduced.  

See also

  • Microbiological culture – Method of allowing microorganisms to multiply in a controlled medium
  • Shadow biosphere – Hypothetical biosphere of Earth
  • Shadow life – Hypothetical biosphere of Earth
  • Taxonomy – Science of naming, defining and classifying organisms

References

  1. ^ Carey, Nessa (2015). Junk DNA: A Journey Through the Dark Matter of the Genome. Columbia University Press. ISBN 9780231170840.
  2. ^ Kolata, Gina (5 September 2012). "Bits of Mystery DNA, Far From 'Junk', Play Crucial Role". The New York Times. Retrieved 2015-09-09.
  3. ^ Boyle, Rebecca (6 September 2012). "Inside the Mysterious Dark Matter of the Human Genome". Popular Science. Retrieved 2015-09-09.
  4. ^ B. F., Pugh; Voss, Katrina (13 September 2013). "Scientists Discover the Origins of Genomic "Dark Matter"". Penn State Science. Retrieved 2015-09-09.
  5. ^ "Scientists shed some light on biological "dark matter"". Ecole Polytechnique Federale de Lausanne. 20 January 2014. Retrieved 2015-09-09.
  6. ^ van Bakel H, Nislow C, Blencowe BJ, Hughes TR (2010). Eddy SR (ed.). "Most "dark matter" transcripts are associated with known genes". PLoS Biol. 8 (5): e1000371. doi:10.1371/journal.pbio.1000371. PMC 2872640. PMID 20502517.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  7. ^ de Koning AP, Gu W, Castoe TA, Batzer MA, Pollock DD (2011). "Repetitive elements may comprise over two-thirds of the human genome". PLoS Genet. 7 (12): e1002384. doi:10.1371/journal.pgen.1002384. PMC 3228813. PMID 22144907.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  8. ^ Maumus F, Quesneville H (2014). "Deep investigation of Arabidopsis thaliana junk DNA reveals a continuum between repetitive elements and genomic dark matter". PLoS ONE. 9 (4): e94101. doi:10.1371/journal.pone.0094101. PMC 3978025. PMID 24709859.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  9. ^ Wu, D.; Wu, M.; Halpern, A.; Rusch, D. B.; Yooseph, S.; Frazier, M.; Venter, J. C.; Eisen, J. A. (2011). "Stalking the Fourth Domain in Metagenomic Data: Searching for, Discovering, and Interpreting Novel, Deep Branches in Marker Gene Phylogenetic Trees". PLoS ONE. 6 (3): e18011. doi:10.1371/journal.pone.0018011. PMC 3060911. PMID 21437252.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  10. ^ Barras, Colin (March 18, 2011). "Biology's 'dark matter' hints at fourth domain of life". New Scientist. Reed Business Information Ltd. Retrieved August 23, 2015.
  11. ^ Kemsley, Tamarra (13 July 2015). "New Study on "Dark Matter" of Biology Fills in Major Holes in Tree of Life". Nature World News. Retrieved 2015-09-09.
  12. ^ Huang, Wei E.; Song, Yizhi; Xu, Jian (28 January 2015). "Single cell biotechnology to shed a light on biological 'dark matter' in nature". Microbial Biotechnology. 8 (1): 15–16. doi:10.1111/1751-7915.12249. PMC 4321360. PMID 25627841.
  13. ^ Lok, Corie (16 June 2015). "Mining the microbial dark matter". Nature News. Retrieved 2015-09-09.
  14. ^ Check-Hayden, Erika (14 July 2013). "Researchers glimpse microbial 'dark matter'". Nature News. Retrieved 2015-09-09.
  15. ^ Gronstal, Aaron L. (4 November 2011). "Studying Biology's Dark Matter". NASA Astrobiology Institute. Retrieved 2015-09-09.
  16. ^ Rinke, Chris (2015). "What is Microbial Dark Matter and why should we explore it?". Microbial Dark Matter. Retrieved 2015-09-09.
  17. ^ Lok, Corie (2015-06-18). "Mining the microbial dark matter". Nature. 522 (7556): 270–273. doi:10.1038/522270a. ISSN 1476-4687. PMID 26085253.
  18. ^ Hannigan, Geoffrey D.; Meisel, Jacquelyn S.; Tyldsley, Amanda S.; Zheng, Qi; Hodkinson, Brendan P.; SanMiguel, Adam J.; Minot, Samuel; Bushman, Frederic D.; Grice, Elizabeth A. (2015-10-20). "The human skin double-stranded DNA virome: topographical and temporal diversity, genetic enrichment, and dynamic associations with the host microbiome". mBio. 6 (5): e01578–01515. doi:10.1128/mBio.01578-15. ISSN 2150-7511. PMC PMCPMC4620475. PMID 26489866. {{cite journal}}: Check |pmc= value (help)
  19. ^ Ryberg, Martin; Nilsson, R. Henrik (2018). "New light on names and naming of dark taxa". MycoKeys (30): 31–39. doi:10.3897/mycokeys.30.24376. ISSN 1314-4049. PMC PMCPMC5904500. PMID 29681731. {{cite journal}}: Check |pmc= value (help)CS1 maint: unflagged free DOI (link)
  20. ^ Aggarwala, Varun; Liang, Guanxiang; Bushman, Frederic D. (2017). "Viral communities of the human gut: metagenomic analysis of composition and dynamics". Mobile DNA. 8: 12. doi:10.1186/s13100-017-0095-y. ISSN 1759-8753. PMC PMCPMC5627405. PMID 29026445. {{cite journal}}: Check |pmc= value (help)CS1 maint: unflagged free DOI (link)
  21. ^ Kramná, Lenka; Kolářová, Kateřina; Oikarinen, Sami; Pursiheimo, Juha-Pekka; Ilonen, Jorma; Simell, Olli; Knip, Mikael; Veijola, Riitta; Hyöty, Heikki (2015-5). "Gut virome sequencing in children with early islet autoimmunity". Diabetes Care. 38 (5): 930–933. doi:10.2337/dc14-2490. ISSN 1935-5548. PMID 25678103. {{cite journal}}: Check date values in: |date= (help)
  22. ^ Krishnamurthy, Siddharth R.; Wang, David (07 15, 2017). "Origins and challenges of viral dark matter". Virus Research. 239: 136–142. doi:10.1016/j.virusres.2017.02.002. ISSN 1872-7492. PMID 28192164. {{cite journal}}: Check date values in: |date= (help)
  23. ^ Kowarsky, Mark; Camunas-Soler, Joan; Kertesz, Michael; De Vlaminck, Iwijn; Koh, Winston; Pan, Wenying; Martin, Lance; Neff, Norma F.; Okamoto, Jennifer (09 05, 2017). "Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA". Proceedings of the National Academy of Sciences of the United States of America. 114 (36): 9623–9628. doi:10.1073/pnas.1707009114. ISSN 1091-6490. PMC PMCPMC5594678. PMID 28830999. {{cite journal}}: Check |pmc= value (help); Check date values in: |date= (help)
  24. ^ Bowman, Jeff S. (2018). "Identification of Microbial Dark Matter in Antarctic Environments". Frontiers in Microbiology. 9: 3165. doi:10.3389/fmicb.2018.03165. ISSN 1664-302X. PMC PMCPMC6305705. PMID 30619224. {{cite journal}}: Check |pmc= value (help)CS1 maint: unflagged free DOI (link)
  25. ^ a b Ren, Jie; Ahlgren, Nathan A.; Lu, Yang Young; Fuhrman, Jed A.; Sun, Fengzhu (07 06, 2017). "VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data". Microbiome. 5 (1): 69. doi:10.1186/s40168-017-0283-5. ISSN 2049-2618. PMC PMCPMC5501583. PMID 28683828. {{cite journal}}: Check |pmc= value (help); Check date values in: |date= (help)CS1 maint: unflagged free DOI (link)
  26. ^ Bzhalava, Zurab; Tampuu, Ardi; Bała, Piotr; Vicente, Raul; Dillner, Joakim (2018-09-24). "Machine Learning for detection of viral sequences in human metagenomic datasets". BMC bioinformatics. 19 (1): 336. doi:10.1186/s12859-018-2340-x. ISSN 1471-2105. PMC PMCPMC6154907. PMID 30249176. {{cite journal}}: Check |pmc= value (help)CS1 maint: unflagged free DOI (link)
  27. ^ a b Barrientos-Somarribas, Mauricio; Messina, David N.; Pou, Christian; Lysholm, Fredrik; Bjerkner, Annelie; Allander, Tobias; Andersson, Björn; Sonnhammer, Erik L. L. (01 08, 2018). "Discovering viral genomes in human metagenomic data by predicting unknown protein families". Scientific Reports. 8 (1): 28. doi:10.1038/s41598-017-18341-7. ISSN 2045-2322. PMC PMCPMC5758519. PMID 29311716. {{cite journal}}: Check |pmc= value (help); Check date values in: |date= (help)
  28. ^ Ogilvie, Lesley A.; Bowler, Lucas D.; Caplin, Jonathan; Dedi, Cinzia; Diston, David; Cheek, Elizabeth; Taylor, Huw; Ebdon, James E.; Jones, Brian V. (2013). "Genome signature-based dissection of human gut metagenomes to extract subliminal viral sequences". Nature Communications. 4: 2420. doi:10.1038/ncomms3420. ISSN 2041-1723. PMC PMCPMC3778543. PMID 24036533. {{cite journal}}: Check |pmc= value (help)
  29. ^ Roux, Simon; Hallam, Steven J.; Woyke, Tanja; Sullivan, Matthew B. (2015-07-22). "Viral dark matter and virus-host interactions resolved from publicly available microbial genomes". eLife. 4. doi:10.7554/eLife.08490. ISSN 2050-084X. PMC PMCPMC4533152. PMID 26200428. {{cite journal}}: Check |pmc= value (help)CS1 maint: unflagged free DOI (link)
  30. ^ Moustafa, Ahmed; Xie, Chao; Kirkness, Ewen; Biggs, William; Wong, Emily; Turpaz, Yaron; Bloom, Kenneth; Delwart, Eric; Nelson, Karen E. (03 2017). "The blood DNA virome in 8,000 humans". PLoS pathogens. 13 (3): e1006292. doi:10.1371/journal.ppat.1006292. ISSN 1553-7374. PMC PMCPMC5378407. PMID 28328962. {{cite journal}}: Check |pmc= value (help); Check date values in: |date= (help)CS1 maint: unflagged free DOI (link)
  31. ^ Pasolli, Edoardo; Asnicar, Francesco; Manara, Serena; Zolfo, Moreno; Karcher, Nicolai; Armanini, Federica; Beghini, Francesco; Manghi, Paolo; Tett, Adrian (2019-01-24). "Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle". Cell. 176 (3): 649–662.e20. doi:10.1016/j.cell.2019.01.001. ISSN 1097-4172. PMC PMCPMC6349461. PMID 30661755. {{cite journal}}: Check |pmc= value (help)
  32. ^ Cinek, Ondrej; Kramna, Lenka; Lin, Jake; Oikarinen, Sami; Kolarova, Katerina; Ilonen, Jorma; Simell, Olli; Veijola, Riitta; Autio, Reija (2017-11). "Imbalance of bacteriome profiles within the Finnish Diabetes Prediction and Prevention study: Parallel use of 16S profiling and virome sequencing in stool samples from children with islet autoimmunity and matched controls". Pediatric Diabetes. 18 (7): 588–598. doi:10.1111/pedi.12468. ISSN 1399-5448. PMID 27860030. {{cite journal}}: Check date values in: |date= (help)
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