Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Pavlova, Yekaterina S.; Paez-Espino, David; Morozov, Andrew Yu.; Belalov, Ilya S.

doi:10.1371/journal.pcbi.1008841

Title: Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Journal Article · Fri Mar 26 00:00:00 EDT 2021 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1008841· OSTI ID:1904074

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Palomar College, San Marcos, CA (United States)
USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Mammoth BioSciences, San Franisco, CA (United States)
Univ. of Leicester (United Kingdom); Russian Academy of Sciences (RAS), Moscow (Russian Federation)
Russian Academy of Sciences (RAS), Moscow (Russian Federation)

Understanding CRISPR-Cas systems—the adaptive defence mechanism that about half of bacterial species and most of archaea use to neutralise viral attacks—is important for explaining the biodiversity observed in the microbial world as well as for editing animal and plant genomes effectively. The CRISPR-Cas system learns from previous viral infections and integrates small pieces from phage genomes called spacers into the microbial genome. The resulting library of spacers collected in CRISPR arrays is then compared with the DNA of potential invaders. One of the most intriguing and least well understood questions about CRISPR-Cas systems is the distribution of spacers across the microbial population. Here, using empirical data, we show that the global distribution of spacer numbers in CRISPR arrays across multiple biomes worldwide typically exhibits scale-invariant power law behaviour, and the standard deviation is greater than the sample mean. We develop a mathematical model of spacer loss and acquisition dynamics which fits observed data from almost four thousand metagenomes well. In analogy to the classical ‘rich-get-richer’ mechanism of power law emergence, the rate of spacer acquisition is proportional to the CRISPR array size, which allows a small proportion of CRISPRs within the population to possess a significant number of spacers. Our study provides an alternative explanation for the rarity of all-resistant super microbes in nature and why proliferation of phages can be highly successful despite the effectiveness of CRISPR-Cas systems.

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Research Organization:: USDOE Joint Genome Institute (JGI), Berkeley, CA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1904074

Journal Information:: PLoS Computational Biology (Online), Vol. 17, Issue 3; ISSN 1553-7358

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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59 BASIC BIOLOGICAL SCIENCES
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metagenomics
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bacterial genomics
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Title: Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

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