Abstract
The production of cheese and other dairy products relies on the constant monitoring of viruses, called bacteriophages, that attack the organisms responsible for the fermentation process. Bacteriophage species are characterized by a stable core genome, and a ‘genetic reservoir’ of gene variants that are exchanged through recombination. Phylogenetic analysis of phage populations are notably difficult due not only to extreme levels of horizontal exchange at the borders of functional modules, but also inside of them.
In this paper we present the first known attempt at directly modeling gene flux between phage populations. This represents an important departure from gene-based alignment and phylogenetic reconstruction, shifting focus to a genetic reservoir-based evolutionary inference. We present a combinatorial framework for the comparison of bacteriophage populations, and use it to compute recombination scenarios that generate one population from another. We apply our heuristic, based on this framework, to four populations sampled from Dutch dairy factories by Murphy [14]. We find that, far from being random, these scenarios are highly constrained. We use our method to test for factory-specific diversity, and find that there was likely a large amount of recombination in the ancestral population.
Find instructions for reproducing the results at: https://bitbucket.org/thekswenson/phage_population_comparison
The code is publicly available at: https://bitbucket.org/thekswenson/phagerecombination
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Notes
- 1.
After invading a cell, linear phage genomes are often circularized. This is due to a variety of mechanisms: a circular configuration may protect phages from degradation by the defense mechanisms of the bacteria; it may allow the phage genome to be duplicated as a plasmid, or to be integrated in the host genome; or it may be used to initiate a rolling circle replication procedure that leads to a concatenamer [16].
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Funding
AB is partially supported by Canada NSERC Grant number 05729-2014. MJM is partially supported by Canada NSERC Grant number 06487-2017. RVL acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds de recherche du Québec - Nature et technologies (FRQNT). KMS is partially supported by VIROGENESIS (EU H2020-PHC-32-2014 #634650) and the Labex NUMEV (ANR-10-LABX-20, 2017-2-46).
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Annex 1
Annex 1
Example 1
A shortest scenario is not necessarily tied to a minimum cover.
Child \(\texttt {J}\) has a minimum cover of size 5, namely \(\texttt {ABCDE}\). Thus a shortest scenario must have at least 3 recombinations. Using the minimum cover, there is a trivial scenario of length 4, but there is an alternate one of length 3 that uses the cover \(\texttt {AFGHGF}\), which is not a minimal cover.
Example 2
A recombination scenario of length 6 for the example of Fig. 6.
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Bergeron, A., Meurs, MJ., Valiquette-Labonté, R., Swenson, K.M. (2022). On the Comparison of Bacteriophage Populations. In: Jin, L., Durand, D. (eds) Comparative Genomics. RECOMB-CG 2022. Lecture Notes in Computer Science(), vol 13234. Springer, Cham. https://doi.org/10.1007/978-3-031-06220-9_1
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