IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v133y2020icp168-179.html
   My bibliography  Save this article

Quantifying the forces that maintain prophages in bacterial genomes

Author

Listed:
  • Khan, Amjad
  • Wahl, Lindi M.

Abstract

Genome sequencing has revealed that prophages, viral sequences integrated in a bacterial chromosome, are abundant, accounting for as much as 20% of the bacterial genome. These sequences can confer fitness benefits to the bacterial host, but may also instigate cell death through induction. Several recent investigations have revealed that the distribution of prophage lengths is bimodal, with a clear distinction between small and large prophages. Here we develop a mathematical model of the evolutionary forces affecting the prophage size distribution, and fit this model to three recent data sets. This approach offers quantitative estimates for the relative rates of lysogeny, induction, mutational degradation and selection acting on a wide class of prophage sequences. The model predicts that large prophages are predominantly maintained by the introduction of new prophage sequences through lysogeny, whereas shorter prophages can be enriched when they no longer encode the genes necessary for induction, but still offer selective benefits to their hosts.

Suggested Citation

  • Khan, Amjad & Wahl, Lindi M., 2020. "Quantifying the forces that maintain prophages in bacterial genomes," Theoretical Population Biology, Elsevier, vol. 133(C), pages 168-179.
    • Handle: RePEc:eee:thpobi:v:133:y:2020:i:c:p:168-179
    DOI: 10.1016/j.tpb.2019.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580919301844
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2019.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alvaro San Millan & Macarena Toll-Riera & Qin Qi & R. Craig MacLean, 2015. "Interactions between horizontally acquired genes create a fitness cost in Pseudomonas aeruginosa," Nature Communications, Nature, vol. 6(1), pages 1-8, November.
    2. Akaike, Hirotugu, 1981. "Likelihood of a model and information criteria," Journal of Econometrics, Elsevier, vol. 16(1), pages 3-14, May.
    3. Jakob Haaber & Jørgen J. Leisner & Marianne T. Cohn & Arancha Catalan-Moreno & Jesper B. Nielsen & Henrik Westh & José R. Penadés & Hanne Ingmer, 2016. "Bacterial viruses enable their host to acquire antibiotic resistance genes from neighbouring cells," Nature Communications, Nature, vol. 7(1), pages 1-8, December.
    4. Xiaoxue Wang & Younghoon Kim & Qun Ma & Seok Hoon Hong & Karina Pokusaeva & Joseph M. Sturino & Thomas K. Wood, 2010. "Cryptic prophages help bacteria cope with adverse environments," Nature Communications, Nature, vol. 1(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. María Ayuda & Fernando Collantes & Vicente Pinilla, 2010. "From locational fundamentals to increasing returns: the spatial concentration of population in Spain, 1787–2000," Journal of Geographical Systems, Springer, vol. 12(1), pages 25-50, March.
    2. Asghar, Zahid & Abid, Irum, 2007. "Performance of lag length selection criteria in three different situations," MPRA Paper 40042, University Library of Munich, Germany.
    3. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    4. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    5. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    6. Farrell, Terence C. & Hopkins, David L., 2007. "A hedonic Model of Lamb Carcass Attributes," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 15.
    7. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    8. Morandi, Valentina & Malighetti, Paolo & Paleari, Stefano & Redondi, Renato, 2015. "Codesharing agreements by low-cost carriers: An explorative analysis," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 184-191.
    9. Simons, Andrew M. & Beltramo, Theresa & Blalock, Garrick & Levine, David I., 2017. "Using unobtrusive sensors to measure and minimize Hawthorne effects: Evidence from cookstoves," Journal of Environmental Economics and Management, Elsevier, vol. 86(C), pages 68-80.
    10. Wei Zhang & Sriram Dasu & Reza Ahmadi, 2017. "Higher Prices for Larger Quantities? Nonmonotonic Price–Quantity Relations in B2B Markets," Management Science, INFORMS, vol. 63(7), pages 2108-2126, July.
    11. Vladimir Mihajlović & Gordana Marjanović, 2020. "Asymmetries in effects of domestic inflation drivers in the Baltic States: a Phillips curve-based nonlinear ARDL approach," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 20(1), pages 94-116.
    12. Zolnik, Edmund, 2021. "Geographically weighted regression models of residential property transactions: Walkability and value uplift," Journal of Transport Geography, Elsevier, vol. 92(C).
    13. Kenneth P. Burnham & David R. Anderson, 2004. "Multimodel Inference," Sociological Methods & Research, , vol. 33(2), pages 261-304, November.
    14. Elizabeth S. Garrett & Scott L. Zeger, 2000. "Latent Class Model Diagnosis," Biometrics, The International Biometric Society, vol. 56(4), pages 1055-1067, December.
    15. Bushara, Mohammed O. A. & Abdelmahmod, Murtada Kh. A., 2016. "Efficiency of selected camel markets in Sudan: A multivariate approach (1995-2011)," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246910, African Association of Agricultural Economists (AAAE).
    16. Thi Mai Hoa Ha & Derrick Yong & Elizabeth Mei Yin Lee & Prathab Kumar & Yuan Kun Lee & Weibiao Zhou, 2017. "Activation and inactivation of Bacillus pumilus spores by kiloelectron volt X-ray irradiation," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
    17. Dimitrios Gounopoulos & Kyriaki Kosmidou & Dimitrios Kousenidis & Victoria Patsika, 2019. "The investigation of the dynamic linkages between real estate market and stock market in Greece," The European Journal of Finance, Taylor & Francis Journals, vol. 25(7), pages 647-669, May.
    18. Mati, Sagiru, 2021. "Do as your neighbours do? Assessing the impact of lockdown and reopening on the active COVID-19 cases in Nigeria," Social Science & Medicine, Elsevier, vol. 270(C).
    19. Francisco Venegas & Enrique de Alba, 1995. "An Economist´s guide to the Kalman filter," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 10(2), pages 123-145.
    20. Husmann, Kai & Möhring, Bernhard, 2017. "Modelling the economically viable wood in the crown of European beech trees," Forest Policy and Economics, Elsevier, vol. 78(C), pages 67-77.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:133:y:2020:i:c:p:168-179. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.