Comparison of bacterial suppression by phage cocktails, dual-receptor generalists, and coevolutionarily trained phages

More evolvable bacteriophages better suppress their host

The number of multidrug-resistant strains of bacteria is increasing rapidly, while the number of new antibiotic discoveries has stagnated. This trend has caused a surge in interest in bacteriophages as anti-bacterial therapeutics, in part because there is near limitless diversity of phages to harness. While this diversity provides an opportunity, it also creates the dilemma of having to decide which criteria to use to select phages. Here we test whether a phage's ability to coevolve with its host (evolvability) should be considered and how this property compares to two previously proposed criteria: fast reproduction and thermostability. To do this, we compared the suppressiveness of three phages that vary by a single amino acid yet differ in these traits such that each strain maximized two of three characteristics. Our studies revealed that both evolvability and reproductive rate are independently important. The phage most able to suppress bacterial populations was the strain with high evolvability and reproductive rate, yet this phage was unstable. Phages varied due to differences in the types of resistance evolved against them and their ability to counteract resistance. When conditions were shifted to exaggerate the importance of thermostability, one of the stable phages was most suppressive in the short-term, but not over the long-term. Our results demonstrate the utility of biological therapeutics' capacities to evolve and adjust in action to resolve complications like resistance evolution. Furthermore, evolvability is a property that can be engineered into phage therapeutics to enhance their effectiveness.

Phage treatment of Pseudomonas aeruginosa yields a phage-resistant population with different susceptibility to innate immune responses and mild effects on metabolic profiles

In this study, we have investigated innate immune activation capacity and metabolic features of a population of P. aeruginosa PAO1 phage-resistant mutants with diverse genetic modification (large genomic deletions and point mutations) arising after exposure to phages targetting lipopolysaccharide (LPS) or Type-4 pili (T4P). Deletions led to the loss of genes involved in LPS synthesis, cell envelope permeability, efflux systems, biofilm production, oxidative stress tolerance, and DNA repair. Loss of LPS O antigen resulted in bacterial sensitivity to serum complement and stimulation of inflammatory cascades but did not cause increased phagocytosis, while T4P phage-resistant mutants were more effectively phagocytized than LPS-defective mutants. Changes in the utilization of different carbon, nitrogen, sulphur, and phosphorus sources were identified, especially in mutants where the two phage DNA persisted in the bacterial population (pseudolysogeny). However, the metabolic changes did not directly correlate with single-gene mutations or the large gene deletions, suggesting they reflect adaptive changes to the gene modifications that arise during the selection of resistant mutants. In contrast, phage-resistant mutants were susceptible to humoral innate immune responses, suggesting that phage resistance may be a beneficial outcome of phage therapy.

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary -and largely uncharacterized- genetics of adsorption, injection, and cell take-over. Here we present a machine learning (ML) approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. The most effective ML approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, predicting phage host range with 86% mean classification accuracy while reducing the relative error in the estimated strength of the infection phenotype by 40%. Further, transparent feature selection in the predictive model revealed 18 of 176 phage λ and 6 of 18 E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage λ infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. While the genetic variation studied was limited to a focal, coevolved phage-bacteria system, the method's success at recapitulating strain-level infection outcomes provides a path forward towards developing strategies for inferring interactions in non-model systems, including those of therapeutic significance.

Phage therapy: Targeting intestinal bacterial microbiota for the treatment of liver diseases

Phage therapy has been overshadowed by antibiotics for decades. However, it is being revisited as a powerful approach against antimicrobial-resistant bacteria. As bacterial microbiota have been mechanistically linked to gastrointestinal and liver diseases, precise editing of the gut microbiota via the selective bactericidal action of phages has prompted renewed interest in phage therapy. In this review, we summarise the basic virological properties of phages and the latest findings on the composition of the intestinal phageome and the changes associated with liver diseases. We also review preclinical and clinical studies assessing phage therapy for the treatment of gastrointestinal and liver diseases, as well as future prospects and challenges.

Fitness Trade-Offs between Phage and Antibiotic Sensitivity in Phage-Resistant Variants: Molecular Action and Insights into Clinical Applications for Phage Therapy

In recent decades, phage therapy has been overshadowed by the widespread use of antibiotics in Western countries. However, it has been revitalized as a powerful approach due to the increasing prevalence of antimicrobial-resistant bacteria. Although bacterial resistance to phages has been reported in clinical cases, recent studies on the fitness trade-offs between phage and antibiotic resistance have revealed new avenues in the field of phage therapy. This strategy aims to restore the antibiotic susceptibility of antimicrobial-resistant bacteria, even if phage-resistant variants develop. Here, we summarize the basic virological properties of phages and their applications within the context of antimicrobial resistance. In addition, we review the occurrence of phage resistance in clinical cases, and examine fitness trade-offs between phage and antibiotic sensitivity, exploring the potential of an evolutionary fitness cost as a countermeasure against phage resistance in therapy. Finally, we discuss future strategies and directions for phage-based therapy from the aspect of fitness trade-offs. This approach is expected to provide robust options when combined with antibiotics in this era of phage 're'-discovery.