Korarchaeum cryptofilum: Difference between revisions
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==Microbiome== | ==Microbiome== | ||
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The population of the <i>Korachaeota</i> is generally minute in its microbiome living in the biome. However in some cases they constitute 7% of all Archaea.<ref>[http://web.b.ebscohost.com.libproxy.kenyon.edu/ehost/detail/detail?vid=0&sid=644f27fc-0fae-4646-8be1-1e8ac0adc257%40pdc-v-sessmgr05&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#AN=48092345&db=eih Reigstad, Laila Johanne, et al. “Diversity and Abundance of Korarchaeota in Terrestrial Hot Springs of Iceland and Kamchatka.” ISME Journal: Multidisciplinary Journal of Microbial Ecology, vol. 4, no. 3, Mar. 2010, pp. 346–356. EBSCOhost, doi:10.1038/ismej.2009.126.]</ref> | |||
=Conclusion== | |||
Overall text length should be at least 1,000 words (before counting references), with at least 2 images. Include at least 5 references under Reference section.<br><br> | Overall text length should be at least 1,000 words (before counting references), with at least 2 images. Include at least 5 references under Reference section.<br><br> | ||
Revision as of 18:52, 2 December 2019
Introduction
Candidatus Korarchaeum cryptofilum is a species of the proposed phylum Korarchaeota, or Xenarchaeota of the Archaea. The Archean is found mainly in hydrothermal environments such as hot springs, shallow water, and deep ocean. The organism's genome has mainly been studied to open understanding of Archaean evolution.
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Genetics and Structure
The genome of Ca. K. cryptofilum is 1,590,757 base pairs long with an average G+C content of 49%. The arCOG of the archaean phyla crenarchaeota and euryarchaeota when compared with the sequenced genome of Ca. K. cryptofilum, showed that the organism shares its replication, recombination, repair, and cell division genes with that of crenarchaeota while it shares most of its transcription and translation genes with euryarcahaeota.
[1]
Ca. K. cryptofilum has three rRNA genes (16S, 23S, and 5S rRNA). The organism has shown to produce 33 23S r-proteins and 27 16S r-proteins on its rRNA operon. The species is also found to have 45 tRNA genes on its genome with one initiator and 45 elongator tRNAs.[2][3]
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Microbiome
Include some current research, with a second image.
The population of the Korachaeota is generally minute in its microbiome living in the biome. However in some cases they constitute 7% of all Archaea.[6]
Conclusion=
Overall text length should be at least 1,000 words (before counting references), with at least 2 images. Include at least 5 references under Reference section.
References
- ↑ > Miller-Coleman, Robin L et al. “Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning.” PloS one vol. 7,5 (2012): e35964. doi:10.1371/journal.pone.0035964
- ↑ > Miller-Coleman, Robin L et al. “Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning.” PloS one vol. 7,5 (2012): e35964. doi:10.1371/journal.pone.0035964
- ↑ James G et al. “A korarchaeal genome reveals insights into the evolution of the Archaea.” Proceedings of the National Academy of Sciences of the United States of America vol. 105,23 (2008): 8102-7. doi:10.1073/pnas.0801980105
- ↑ Hodgkin, J. and Partridge, F.A. "Caenorhabditis elegans meets microsporidia: the nematode killers from Paris." 2008. PLoS Biology 6:2634-2637.
- ↑ Bartlett et al.: Oncolytic viruses as therapeutic cancer vaccines. Molecular Cancer 2013 12:103.
- ↑ Reigstad, Laila Johanne, et al. “Diversity and Abundance of Korarchaeota in Terrestrial Hot Springs of Iceland and Kamchatka.” ISME Journal: Multidisciplinary Journal of Microbial Ecology, vol. 4, no. 3, Mar. 2010, pp. 346–356. EBSCOhost, doi:10.1038/ismej.2009.126.
Edited by [Charlie Stutz], student of Joan Slonczewski for BIOL 116 Information in Living Systems, 2019, Kenyon College.
Miller-Coleman, Robin L et al. “Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning.” PloS one vol. 7,5 (2012): e35964. doi:10.1371/journal.pone.0035964
