Effects of antibiotic resistance alleles on bacterial evolutionary responses to viral parasites

Altered human gut virome in patients undergoing antibiotics therapy for Helicobacter pylori

Transient gut microbiota alterations have been reported after antibiotic therapy for Helicobacter pylori. However, alteration in the gut virome after H. pylori eradication remains uncertain. Here, we apply metagenomic sequencing to fecal samples of 44 H. pylori-infected patients at baseline, 6-week (N = 44), and 6-month (N = 33) after treatment. Following H. pylori eradication, we discover contraction of the gut virome diversity, separation of virome community with increased community difference, and shifting towards a higher proportion of core virus. While the gut microbiota is altered at 6-week and restored at 6-month, the virome community shows contraction till 6-month after the treatment with enhanced phage-bacteria interactions at 6-week. Multiple courses of antibiotic treatments further lead to lower virus community diversity when compared with treatment naive patients. Our results demonstrate that H. pylori eradication therapies not only result in transient alteration in gut microbiota but also significantly alter the previously less known gut virome community.

Temporal encoding of bacterial identity and traits in growth dynamics

In biology, it is often critical to determine the identity of an organism and phenotypic traits of interest. Whole-genome sequencing can be useful for this but has limited power for trait prediction. However, we can take advantage of the inherent information content of phenotypes to bypass these limitations. We demonstrate, in clinical and environmental bacterial isolates, that growth dynamics in standardized conditions can differentiate between genotypes, even among strains from the same species. We find that for pairs of isolates, there is little correlation between genetic distance, according to phylogenetic analysis, and phenotypic distance, as determined by growth dynamics. This absence of correlation underscores the challenge in using genomics to infer phenotypes and vice versa. Bypassing this complexity, we show that growth dynamics alone can robustly predict antibiotic responses. These findings are a foundation for a method to identify traits not easily traced to a genetic mechanism.

Host Resistance, Genomics and Population Dynamics in a Salmonella Enteritidis and Phage System

Bacteriophages represent an alternative solution to control bacterial infections. When interacting, bacteria and phage can evolve, and this relationship is described as antagonistic coevolution, a pattern that does not fit all models. In this work, the model consisted of a microcosm of Salmonella enterica serovar Enteritidis and φSan23 phage. Samples were taken for 12 days every 48 h. Bacteria and phage samples were collected; and isolated bacteria from each time point were challenged against phages from previous, contemporary, and subsequent time points. The phage plaque tests, with the genomics analyses, showed a mutational asymmetry dynamic in favor of the bacteria instead of antagonistic coevolution. This is important for future phage-therapy applications, so we decided to explore the population dynamics of Salmonella under different conditions: pressure of one phage, a combination of phages, and phages plus an antibiotic. The data from cultures with single and multiple phages, and antibiotics, were used to create a mathematical model exploring population and resistance dynamics of Salmonella under these treatments, suggesting a nonlethal, growth-inhibiting antibiotic may decrease resistance to phage-therapy cocktails. These data provide a deep insight into bacterial dynamics under different conditions and serve as additional criteria to select phages and antibiotics for phage-therapy.