Genetic Polymorphism Drives Susceptibility Between Bacteria and Bacteriophages

Abstract

Phage therapy has attracted much attention for the treatment of antibiotic-resistant bacteria in recent years. However, it is common for bacteria to obtain resistance capability in short time after interaction with a lytic phage, as observed in phage therapy and co-culture of host and phage in a lab. In order to understand the mechanisms behind resistance, Staphylococcus aureus AB91118 and its lytic phage LQ7 were studied as a model system. A mutant strain named R1-3-1 resistant to the ancestral phage LQ7 was isolated, and then phages experimentally evolved from LQ7 were able to kill R1-3-1. Genomes of the two bacterial strains and the three phages (LQ7, ELQ7P-10, and ELQ7P-20) were analyzed based on deep sequencing data of NGS. Analyses showed that a few mutations could be identified in R1-3-1 and the evolved phages. Instead, in all the genomes of the bacteria and the phages, there exists genetic polymorphism of minor alleles, which distributes in many functional genes. Specifically, in the AB91118-LQ7 system it was found that the unique polymorphism sites in R1-3-1 associated to metabolic pathways could be inhibited by chloramphenicol (CHL). The resistant mutant R1-3-1 could become sensitive to the phage LQ7 in the presence of CHL. Combined use of CHL and the evolved phage from 20 cycles (ELQ7P-20) could produce the least resistance when killing the bacteria AB91118. The genetic polymorphism of minor alleles would be a new mechanism to drive the co-evolution between a phage and its host, which may enable the phage and the host get ready and fast response to the selective pressure from one to the other.

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Distribution of intra‐host variations and mutations in the genomes of SARS‐CoV‐2 and their implications on detection and therapeutics

“…The identification of iSNVs was basically executed by our established pipelines and referred to Nicole's work. 9 , 48 In details, the jellyfish software (version 2.3.0) was utilized to evaluate the sequencing errors of each NGS data. 49 In order to determine the iSNVs more strictly, three requirements should be met: (a) sequencing depth greater than 100; (b) MAF should be larger than 0.02, which is significantly greater than the average sequencing errors rate (0.001); (c) the position of each iSNV was supported by the inner part of read (excluding 10 bp on each end).…”

“…The iSNVs are defined as the allele with minor frequency co‐existing with the reference allele (major frequency) at the same position within the same sample. The identification of iSNVs was basically executed by our established pipelines and referred to Nicole's work 9,48 . In details, the jellyfish software (version 2.3.0) was utilized to evaluate the sequencing errors of each NGS data 49 .…”