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Insights from 20 years of bacterial genome sequencing
Open accessAbstract
Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.
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Cites
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
Environmental genome shotgun sequencing of the sargasso sea
Venter, J. C., Remington, K., Heidelberg, J. F., Halpern, A. L., Rusch, D., Eisen, J. A., Wu, D., Paulsen, I., Nelson, K. E., Nelson, W., et al. (2004) · Science · doi:10.1126/science.1093857 · Cited by 4,376
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903
Caspi, R., Billington, R., Ferrer, L., Foerster, H., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1164 · Cited by 3,395
Gut microbiota composition correlates with diet and health in the elderly
Claesson, M. J., Jeffery, I. B., Conde, S., Power, S. E., O’Connor, E. M., Cusack, S., Harris, H. M. B., Coakley, M., Lakshminarayanan, B., O’Sullivan, O., et al. (2012) · Nature · doi:10.1038/nature11319 · Cited by 3,314
Normal gut microbiota modulates brain development and behavior
Heijtz, R. D., Wang, S., Anuar, F., Qian, Y., Björkholm, B., Samuelsson, A., Hibberd, M. L., Forssberg, H., & Pettersson, S. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1010529108 · Cited by 3,228
Gut metagenome in European women with normal, impaired and diabetic glucose control
Karlsson, F. H., Tremaroli, V., Nookaew, I., Bergström, G., Behre, C. J., Fagerberg, B., Nielsen, J., & Bäckhed, F. (2013) · Nature · doi:10.1038/nature12198 · Cited by 3,115
Self-citationDe novo assembly of human genomes with massively parallel short read sequencing
Li, R., Zhu, H., Ruan, J., Qian, W., Fang, X., Shi, Z., Li, Y., Li, S., Shan, G., Kristiansen, K., et al. (2010) · Genome Research · doi:10.1101/gr.097261.109 · Cited by 2,926 · cited 1×
“Another approach within an alignment-free category for whole genome and proteome comparison was proposed by Jun and colleagues (Li et al. 2010).”
BackgroundISfinder: the reference centre for bacterial insertion sequences
Siguier, P. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj014 · Cited by 2,767
A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase
Sanger, F., & Coulson, A. R. (1975) · Journal of Molecular Biology · doi:10.1016/0022-2836(75)90213-2 · Cited by 2,709
A framework for human microbiome research
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11209 · Cited by 2,650
Community structure and metabolism through reconstruction of microbial genomes from the environment
Tyson, G. W., Chapman, J., Hugenholtz, P., Allen, E. E., Ram, R. J., Richardson, P. M., Solovyev, V. V., Rubin, E. M., Rokhsar, D. S., & Banfield, J. F. (2004) · Nature · doi:10.1038/nature02340 · Cited by 2,417
Alterations of the human gut microbiome in liver cirrhosis
Qin, N., Yang, F., Li, A., Prifti, E., Chen, Y., Shao, L., Guo, J., Le Chatelier, E., Yao, J., Wu, L., et al. (2014) · Nature · doi:10.1038/nature13568 · Cited by 2,177
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031
A protocol for generating a high-quality genome-scale metabolic reconstruction
Thiele, I., & Palsson, B. Ø. (2010) · Nature Protocols · doi:10.1038/nprot.2009.203 · Cited by 1,789
High-throughput generation, optimization and analysis of genome-scale metabolic models
Henry, C. S., DeJongh, M., Best, A. A., Frybarger, P. M., Linsay, B., & Stevens, R. L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1672 · Cited by 1,090
Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology
Karp, P. D., Paley, S. M., Krummenacker, M., Latendresse, M., Dale, J. M., Lee, T. J., Kaipa, P., Gilham, F., Spaulding, A., Popescu, L., et al. (2010) · Briefings in Bioinformatics · doi:10.1093/bib/bbp043 · Cited by 694
Genome update: the 1000th genome-a cautionary tale
Lagesen, K., Ussery, D. W., & Wassenaar, T. M. (2010) · Microbiology · doi:10.1099/mic.0.038257-0 · Cited by 62 · cited 2×
“As observed 10 years ago, the diversity of bacteria continues to expand and surprise (Lagesen et al. 2010).”
BackgroundSelf-citation
Cited by
Nayfach, S., Rodriguez-Mueller, B., Garud, N., & Pollard, K. S. (2016) · Genome Research · doi:10.1101/gr.201863.115 · Cited by 470
Diversity within Species: Interpreting Strains in Microbiomes
Van Rossum, T., Ferretti, P., Maistrenko, O. M., & Bork, P. (2020) · Nature Reviews Microbiology · doi:10.1038/s41579-020-0368-1 · Cited by 441
The discovery of CRISPR in archaea and bacteria
Mojica, F. J. M., & Rodriguez‐Valera, F. (2016) · The FEBS Journal · doi:10.1111/febs.13766 · Cited by 207
Linking microbiota to human diseases: a systems biology perspective
Wu, H., Tremaroli, V., & Bäckhed, F. (2015) · Trends in Endocrinology & Metabolism · doi:10.1016/j.tem.2015.09.011 · Cited by 150
Cheesomics: the future pathway to understanding cheese flavour and quality.
Afshari, R., Pillidge, C. J., Dias, D. A., Osborn, A. M., & Gill, H. (2020) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2018.1512471 · Cited by 126
Metadata
- Authors
- Land, M., Hauser, L., Jun, S.-R., Nookaew, I., Leuze, M. R., Ahn, T.-H., Karpinets, T., Lund, O., Kora, G., Wassenaar, T., Poudel, S., & Ussery, D. W.
- Venue
- Functional & Integrative Genomics
- Published
- 2015-02-27
- Volume
- 15
- Issue
- 2
- Pages
- 141-161
- ISSN
- 1438-793X (ISSN-L)
- 1438-7948
- OpenAlex
- W2143420371
- Cited by
- 727
- References
- 20
- FWCI
- 29.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
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